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Nested Case-Control Study: Hepatocellular Carcinoma Risk After Hepatitis B Surface Antigen Seroclearance

Prabhu p. gounder.

1 Arctic Investigations Program, Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Disease, Centers for Disease Control and Prevention (CDC), Anchorage, Alaska

Lisa R. Bulkow

Mary snowball.

2 Liver Disease and Hepatitis Program, Alaska Native Tribal Health Consortium, Anchorage, Alaska

Susan Negus

Philip r. spradling.

3 Division of Viral Hepatitis, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, CDC, Atlanta, Georgia

Brenna C. Simons

Brian j. mcmahon.

Hepatocellular carcinoma (HCC) risk after resolving chronic hepatitis B virus (HBV) infection is unclear.

To compare HCC risk between Alaska Native (AN) patients with and without hepatitis B surface antigen (HBsAg) seroclearance.

We selected persons with (case-patients) and without (control-patients) HBsAg seroclearance from a cohort of 1,346 chronically HBV-infected AN patients followed during 1982–2013. We attempted to match 2 control-patients/case-patient on sex, HBV genotype, and age. Person-years of follow-up for case-patients began on the date of HBsAg resolution and for control-patients began on the date equivalent to the cohort entry date plus the years of HBsAg duration for their corresponding case-patient. We compared HCC risk using a Cox proportional hazards model.

The 238 case-patients (4 with HCC) and 435 control-patients (9 with HCC) were similar in age (p-value [p]: 0.30), sex (p: 0.53) and HBV genotype (p: 0.99). Case-patients had longer person-years of follow-up than control patients (11.7 versus 10.1 years; p: 0.04). The HCC rate/100,000 persons was similar between case- (132) and control-patients (178; p: 0.65). The adjusted hazard ratio comparing case- and control-patients was similar for HCC (0.7; 95% confidence interval [CI]: 0.2–2.4), increased for each 1-year increment for age (1.1; CI: 1.0–1.1; p <0.01), and was greater if the initial HBeAg was positive (3.5; CI: 1.1–11.0; p: 0.03).

Conclusions

HBsAg seroclearance was not associated with reduced HCC risk; the HCC risk estimates are limited by wide CIs. Persons meeting HCC surveillance indications prior to HBsAg seroclearance could benefit from continued surveillance after seroclearance.

INTRODUCTION

Approximately 248 million persons worldwide have chronic hepatitis B virus (HBV) infection ( ​ (1). 1 ). Persons with chronic HBV infection are at increased risk for cirrhosis and hepatocellular carcinoma (HCC) ( 2 ). Depending on genotype, 0.5-2% of HBV infected persons will clear hepatitis B surface antigen (HBsAg) annually ( 3 - 5 ). The American Association for the Study of Liver Diseases HCC practice guidelines state that HCC surveillance is cost-effective in populations where the HCC incidence exceeds 0.2%/year. No recommendations for HCC surveillance exist for persons with spontaneous HBsAg seroclearance because of conflicting data on HCC risk in this population ( 6 ).

Demographic and Clinical Characteristics of Case-Patients (Persons With HBsAg Seroclearance) and Matched Control-Patients (Persons Without HBsAg Seroclearance) Selected from a Cohort of HBV-Infected Alaska Native Persons Followed During 1982–2013 a

Symbols and abbreviations: --, not available; +HBeAg, serology positive for hepatitis B e antigen serum; +HBsAg, serology positive for hepatitis B surface antigen; anti-HBs, antibody to HBsAg; HBV, hepatitis B virus; Max, maximum; Min, minimum; No., number

Previous studies evaluating HCC risk after HBsAg seroclearance have reached diverging conclusions ( 7 - 10 ). Reasons for the variation in reported HCC risk include differences in the predominant circulating genotype (HCC risk varies with genotype)( 11 ), study design (clinic-based versus population-based cohort), and lack of uniform follow-up after HBsAg seroclearance (since time of seroclearance is unknown for persons in some studies). In addition, those previous studies included the years of follow-up prior to HBsAg clearance when calculating the HCC incidence among persons who resolve HBsAg. Recent evidence indicates that the eventual risk for developing HCC might be substantially influenced by factors early in the course of disease such as the HBV DNA level at the time of diagnosis ( 10 , 12 ). Therefore, restricting the HCC risk analysis to the time period after HBsAg seroclearance can provide a more precise estimate of the effect of HBsAg seroclearance on the subsequent risk for HCC.

During 1982–1987, 53,000 AN persons representing 84% of the Alaska Native (AN) population in Alaska were tested for HBsAg as part of a statewide HBV vaccination campaign ( 13 ). All persons testing positive for HBsAg during/after the vaccination campaign were provided healthcare through the Alaska Tribal Health System (ATHS) and offered HCC surveillance regardless of age or risk factors ( 14 ). Previous studies of this cohort of AN HBV carriers have documented an HBsAg seroclearance rate of 0.5–0.7%/year ( 5 , 15 ). We conducted a nested case-control study among this cohort of HBV-infected AN persons to compare the risk for developing HCC after HBsAg seroclearance with the risk for HCC among persons who did not clear HBsAg. We specifically aimed to evaluate the HCC risk only during the time period after HBsAg seroclearance for case-patients or the equivalent time period of time for control-patients.

PATIENTS AND METHODS

Study population.

There were approximately 143,000 AN persons in Alaska in 2013 ( 16 ). All AN persons with chronic HBV, defined as having two positive HBsAg results >6 months apart, have been entered into an HBV clinical registry maintained by the ATHS. The clinical registry helps track when patients are due for routine screening exams and records clinical outcomes. Persons newly diagnosed with chronic HBV infection were continuously added to the clinical registry. Additionally, the names of newly diagnosed patients with HBV infection were cross-referenced with the Alaska Area Specimen Bank, which contains >266,000 biological specimen from persons who participated in research studies dating back to 1961 ( 17 ); if serum specimen from these persons were located, it was tested for HBsAg to more precisely estimate the date of infection.

Case- and control-patients

We selected case- and control-patients from among HBV registry patients who were followed during 1982–2013 and consented to participate in study ( Figure 1 ) ( 5 , 13 , 15 ). Case-patients were defined as persons with HBsAg seroclearance and control-patients as persons without HBsAg clearance. We attempted to match two control-patients for each case-patient on sex, HBV genotype, and age group at cohort entry (control age group ±2.5 years if case aged <30 years, ±7.5 years if case aged 30–50 years, and ±10 years if case aged ≥50 years). For a cohort person to be eligible for selection as a control-patient, the documented HBsAg duration must have been at least as long as their corresponding case-patient’s HBsAg duration. Because this study used data from an observational clinical cohort, rather than a prospective cohort designed specifically to study HCC in HBV-infected persons, the presence of other risk factors for HCC, such as hepatitis C virus (HCV)-coinfection, diabetes mellitus, family history of HCC, or non-alchoholic steatohepatitis ( 18 - 21 ), were not comprehensively documented for study participants not developing HCC. Therefore, we were unable to exclude HBV-infected patients with other risk factors for HCC from analysis.

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Abbreviations: AN, Alaska Native; HBsAg, hepatitis B surface antigen; HBV, hepatitis B virus; HCC, hepatocellular carcinoma

a Case-patients (persons with HBsAg seroclearance) and control-patients (persons without HBsAg seroclearance) were selected from a cohort of 1,346 chronically HBV-infected AN persons; matched two control-patients for each case-patient on sex, HBV genotype, and age group at cohort entry (control age group ±2.5 years if case aged <30 years, ±7.5 years if case aged 30–50 years, and ±10 years if case aged ≥50 years)

b Cohort patients without HBsAg seroclearance who were not followed for at least as long as corresponding case-patient’s HBsAg duration were ineligible for selection as control-patients

c Person years of follow-up for calculating HCC incidence began on case-patient’s HBsAg seroclearance date (time = 0) or the corresponding number of years after cohort entry for control-patients; years of follow-up shaded in gray were excluded for calculating HCC incidence.

Laboratory testing

All AN persons with chronic HBV infection in the clinical registry were reminded semiannually by mail to go to their clinical provider for a blood draw. The sera were sent to the Alaska Native Medical Center in Anchorage, Alaska for testing. Since 1982, sera have been tested for HBsAg and alpha-fetoprotein (AFP) semiannually, and for hepatitis B e antigen (HBeAg) and antibody to HBe (anti-HBe) annually. Beginning in 2001, sera were also tested for liver function tests semiannually, including aspartate and alanine aminotransferase (AST and ALT, respectively) levels, and to obtain a baseline HBV DNA level and HBV genotype. The HBV DNA level was repeated every 6–12 months for persons with a baseline HBV DNA level >2,000 IU/mL, a family history of HCC, or if aminotransferase levels were elevated. We tested for HBeAg, anti-HBe, antibody to HBsAg (anti-HBs), antibody to hepatitis B core antigen (anti-HBc), and HBV DNA using commercially available assays as previously described ( 5 , 22 ). Complete blood count, which includes a platelet count, was not routinely requested because of specimen instability associated with the time required to transport specimen from certain rural Alaskan villages to the Alaska Native Medical Center for testing.

Identification of persons with HCC

Most AN persons with HCC were initially detected by the ATHS HCC surveillance program. Because many AN persons live in small rural Alaskan communities that are inaccessible by road and without ultrasound capability, the ATHS has offered HCC surveillance to all AN persons with chronic HBV infection by semiannual AFP measurements. The AFP threshold for referring for liver imaging was >25 ng/mL during 1982–1992 and was reduced to >15 ng/mL beginning in 1993, and >10 ng/ml after 2000. Persons with an elevated AFP, a family history of HCC, or cirrhosis were also offered diagnostic liver imaging by ultrasound or computed tomography. All persons with radiologic findings concerning for HCC were offered further evaluation/treatment at the Alaska Native Medical Center; histologic confirmation of HCC was available for persons who received a biopsy/surgical resection of their tumor. Persons who declined biopsy/resection of their liver lesion were diagnosed with HCC based on their clinical presentation, including an elevated AFP level, and compatible findings on radiographic imaging. We likely captured all HCC cases in the study population because all patients received care at the Alaska Native Medical Center. To ensure no study patients were diagnosed/treated for HCC at another hospital in Alaska, we cross-referenced the names of study patients with the Alaska Native Tumor Registry, a National Cancer Institute Surveillance, Epidemiology and End Results Program registry in operation since 1969 ( 23 ).

Statistical analysis

Demographic and clinical characteristics between case- and control-patients were compared by using the Wilcoxon rank-sum test for ordered variables, and chi-squared or Fisher’s exact test for categorical variables. Median values are reported with 25 th and 75 th percentiles (Q 1 -Q 3 ). Person-years of follow-up for case-patients began on the date of HBsAg resolution ( Figure 1 ). The equivalent time zero to mark the start of control-patient’s person-years of follow-up began on the date equivalent to the control-patient’s cohort entry date plus the years of HBsAg duration for their corresponding case-patient. We estimated the date of HBsAg resolution as the midpoint between the last HBsAg-positive and the first HBsAg-negative test. Person-years of follow-up ended for case- and control-patients on the date of HCC diagnosis, death, or end of study period. Case-patients without at least one matching control-patient were excluded from analysis. Patients who are simultaneously positive for HBeAg and anti-HBe are considered HBeAg-positive for analysis. The initial HBeAg test was defined as the first test done after cohort entry and the final HBeAg test was defined as the last test done before end of follow-up. The duration of HBeAg positivity was defined as the difference between the first and last positive HBeAg test results.

We calculated the unadjusted HCC rate/100,000 person-years by dividing the total number of HCC tumors in case- and control-patients by their respective person-years of follow-up after time zero. We compared the HCC rate between case- and control-patients by using a Cox proportional hazards model that adjusted for exact age and initial HBeAg status (the first recorded HBeAg level after cohort entry).

Analysis was conducted with STATA 10. P-values [p] <0.05 were considered statistically significant, and all tests were two-sided.

Human subjects review

This study was approved by the Institutional Review Boards of the Alaska Area and the Centers for Disease Control and Prevention. It also received review and approval by the Alaska Native Tribal Health Consortium.

Study Cohort Characteristics

A total of 1,346 chronically HBV-infected AN persons were enrolled in the study cohort during 1982–2013. Among cohort persons, 58% (782) were male, the median age at cohort entry was 23 years (minimum–maximum years: 0–87), 35% (476/1,343) and 4% (53/1,343) had a positive HBeAg result on the initial and final tests, respectively, 19% (254) had HBsAg seroclearance, 4% (51) developed HCC, and 34% (460) died (all-causes; proportion liver-related unknown).

Characteristics of Case- and Control-Patients

We identified 435 matched control-patients, who remained HBsAg-positive throughout the follow-up period, for 238 case-patients, who had HBsAg seroclearance (41 case-patients had only one matching control-patient); we excluded from analysis 16 case-patients without any matching control-patients ( Table 1 ). There were no significant differences between case- and control-patients with respect to the matching criteria of age, sex, and HBV genotype ( Table 1 ). Case-patients were followed for a median of 28.9 years (Q 1 -Q 3 : 24.4–30.2 years) prior to HBsAg clearance and matched to control-patients who were followed for at least a median of 28.9 years (Q 1 -Q 3 : 20.7–30.3 years). Case-patients were followed for a median of 11.7 years (Q 1 -Q 3 : 6.5–18.3 years) after HBsAg clearance; the equivalent median years of follow-up for control-patients was 10.1 years (Q 1 -Q 3 : 4.8–17.9 years). Case- compared with control-patients were less likely to have an initial positive HBeAg result (22% versus 37%; p <0.01) and less likely to have received antiviral therapy for HBV infection (1% versus 7%; p <0.01). The two case-patients who received antiviral therapy were treated with lamivudine for immune active HBV infection, which possibly facilitated HBsAg seroclearance; an additional five case-patients were placed on antiviral therapy after HBsAg seroclearance ahead of planned immunosuppressive therapy. Case- and control-patients were similar in terms of the percentage that died during follow-up (28% versus 33%) and the percentage with HCV coinfection (4% versus 3%). Among the patients selected for the nested case-control study, three had HIV coinfection (one control-patient, one case-patient before HBsAg seroclearance, and one case-patient after HBsAg seroclearance), and 13 developed HCC (four case-patients and nine control-patients). An additional two cohort patients developed HCC prior to HBsAg seroclearance; these patients were not included as case-patients because person-years of follow-up for this analysis began after HBsAg seroclearance. There were no significant differences between case- and control-patients developing HCC in terms of the percentage that died (100% versus 78%), had HCV-coinfection (25% versus 11%), had cirrhosis at time of HCC diagnosis (25% versus 63%), or a family history of HCC (0% versus 50%). The specific characteristics of the 13 case- and control-patients who developed HCC are detailed in Table 2 .

Characteristics of Case-Patients (Persons With HBsAg Seroclearance) and Control-Patients (Persons Without HBsAg Seroclearance) Who Developed Hepatocellular Carcinoma (HCC)

Abbreviations: ALT, alanine aminotransferase; HBeAg, hepatitis B e antigen; HBsAg, hepatitis B surface antigen; HBV, hepatitis B virus; HCV, hepatitis C virus; N/A, not applicable; Neg, negative; Pos, positive. Note: No patients with HCC had autoimmune hepatitis

A platelet count necessary to calculate an aspartate aminotransferase–to-platelet ratio index (APRI), a non-invasive marker for liver fibrosis, was available for 131 (55%) case-patients and 258 (59%) control-patients ( 24 ). Among case-patients with an APRI, 88% had an index <0.5, 9% had an index 0.5–1.5, and 2% had an index >1.5. Among control-patients with an APRI, 81% had an index <0.5, 14% had an index 0.5–1.5, and 5% had an index >1.5. A FIB-4 index, another non-invasive liver fibrosis marker calculated using platelets, alanine aminotransferase, aspartate aminotransferase, and patient age, was available for 131 (55%) case-patients and 256 (59%) control-patients ( 25 ). Among case-patients with a FIB-4 index, 69% had an index <1.45, 24% had an index 1.45–3.25, and 7% had an index >3.25. Among control-patients with a FIB-4 index, 71% had an index <1.45, 19% had an index 1.45–3.25, and 10% had an index >3.25. There was no difference between case- and control-patients in the percentage of patients with an APRI >1.5 versus ≤1.5 (p: 0.19) or in the percentage with a Fib4 score >3.25 versus a score ≤3.25 (p: 0.34).

Hepatocellular Carcinoma Rate

The HCC rate/100,000 persons was similar between case-patients with HBsAg seroclearance (132; 95% confidence interval [CI]: 36–338) and control-patients without HBsAg seroclearance (178; CI: 81–338). The risk for HCC did not differ significantly between case- and control-patients in the multivariable Cox proportional hazards model (adjusted hazard ratio [aHR]: 0.7; CI: 0.2–2.4). The risk for HCC was associated with greater age at cohort entry (aHR for each 1-year increment: 1.1; CI: 1.0–1.1; p <0.01) and having a positive initial HBeAg result compared with a negative result (aHR: 3.5; CI: 1.1–11.0).

HBV DNA and ALT Levels

The distribution (statistical spread of values) of HBV DNA levels among case-patients was compared with control-patients at time periods before and after HBsAg seroclearance ( Table 3 ). At least one HBV DNA measurement was available for 97% of case-patients (median: 2 measurements; Q 1 -Q 3 : 1–4 measurements) and 82% of control-patients (median: 3 measurements; Q 1 -Q 3 : 1–6); the time periods for aggregating HBV DNA measurements were selected to optimize sample size for analysis. There was no difference in the distribution of the HBV DNA level between case- and control-patients ≥9 years prior to HBsAg seroclearance (p: 0.39) and <9 years prior to HBsAg seroclearance (p: 0.12). The HBV DNA level was lower among case-patients compared with control-patients <9 years after HBsAg seroclearance (median: 0 versus 212 IU/mL; % with HBV DNA >0 IU/mL: 40% versus 87%; % with HBV DNA >2,000 IU/mL: 1% versus 28%; p <0.01) and ≥9 years after HBsAg seroclearance (median: 0 versus 259 IU/mL; % with HBV DNA >0 IU/mL: 48% versus 92%; % with HBV DNA >2,000 IU/mL: 2% versus 29%; p <0.01). Among the 98 case-patients followed for ≥9 years after HBsAg seroclearance, 95% (93) were anti-HBs positive on the last serum specimen tested before end of follow-up and 51% (47) had detectable HBV DNA. The 5 case-patients who were followed for ≥9 years after HBsAg seroclearance and remained anti-HBs negative also had detectable HBV DNA on their final serum sample tested before end of follow-up.

Hepatitis B Virus (HBV) DNA Level Relative to Case-Patient Hepatitis B Surface Antigen (HBsAg) Seroclearance Date a

Abbreviations: No., number of patients contributing an HBV DNA result during the specified follow-up time period

We also compared the distribution of ALT levels among case-patients with control-patients at time periods before and after HBsAg seroclearance ( Table 4 ). The ALT level was similar between case- and control-patients ≥9 years prior to HBsAg seroclearance (p: 0.39) and <9 years prior to HBsAg seroclearance (p: 0.99). The ALT level was lower among case-patients compared with control-patients <9 years after HBsAg seroclearance (p <0.01) and ≥9 years after HBsAg seroclearance (p: 0.03).

Alanine Aminotransferase (ALT) Level Relative to Case-Patient Hepatitis B Surface Antigen (HBsAg) Seroclearance Date a

Abbreviations: IQR, interquartile range; No., number of patients contributing an ALT result during the specified follow-up time period

CONCLUSIONS

Previous studies evaluating the risk for HCC associated with HBsAg loss have included the time during which persons were seropositive for HBsAg in calculating the HCC rate ( 3 , 7 , 9 , 10 ). Our study is unique because we attempted to isolate the effect of HBsAg seroclearance on subsequent risk for developing HCC. The results indicate that HBsAg seroclearance was not associated with reduced risk for HCC. Although the small number of persons who developed HCC limits the strength of our conclusion, our case- and control-patients were sampled from one of the largest and longest followed population-based cohorts of persons with HBV infection in the world. As a result, this present study includes more persons with resolved HBsAg (including those who developed HCC) than similar previous studies that have evaluated the risk of HCC after resolving HBV infection ( 3 , 8 , 9 , 26 ). Because it is unlikely a more precise estimate of HCC risk following HBsAg seroclearance can be obtained in the near future, it would be reasonable to offer HCC surveillance after HBsAg seroclearance for persons meeting AASLD practice guidelines criteria for surveillance prior to resolving HBV infection ( 6 ).

Cirrhosis is an important risk factor for developing HCC among persons with chronic HBV infection. The presence of cirrhosis was not comprehensively known for our study participants who did not develop HCC in part because many patients lived in rural communities without ready access to liver biopsy capable facility. Therefore, we were unable to match case- and control-patients according to their cirrhosis status. For the subset of case- and control-patients with APRI and Fib4 available, we are reassured that there was no difference between the two groups in the proportion with advanced liver fibrosis as measured by these noninvasive makers. Furthermore, knowing the cirrhosis status only for case-patients who developed HCC still provides insights into the risk for HCC. Unlike previous studies where the majority of patients who developed HCC after resolving chronic HBV infection had cirrhosis at the time of HBsAg seroclearance ( 3 , 9 , 26 ), only one out of the four case-patients with HCC in our study had cirrhosis. However, the other three case-patients without cirrhosis would have met AASLD age/sex criteria for continuing HCC surveillance after HBsAg seroclearance ( 6 ).

The reasons for why HBsAg seroclearance was not associated with reduced HCC rate are unknown but likely multifactorial. It is possible that factors early in the course of HBV infection, such as the HBV DNA level or degree of hepatic necroinflammation, might have had a greater influence on HCC risk ( 10 , 12 , 27 ). We compared the distribution of HBV DNA level for the time periods before and after HBsAg seroclearance among case-patients and for the corresponding time periods among control-patients. The lack of difference in HCC rate between case- and control-patients corresponds with the similarity in HBV DNA levels among case-patients compared with control-patients before HBsAg clearance. These results support previous reports that the HBV DNA level before HBsAg seroclearance is an important predictor for developing HCC ( 10 , 12 ). It is likely for that reason that treatment with nucleos(t)ide analogues decreases both the risk for developing HCC and the risk of HCC recurrence after surgical resection ( 28 - 31 ). One mechanism by which HBV infection causes HCC could be through the integration of HBV DNA into the host hepatocyte genome and as covalently closed circular (ccc) DNA in hepatocyte nuclei ( 27 , 32 ). The integrated viral DNA and cccDNA that result from HBV viremia persist after HBsAg seroclearance and might promote the development of HCC. Furthermore, a substantial proportion of case-patients in our study had a detectable HBV DNA level after HBsAg seroclearance. Thus, it is possible that ongoing low-level HBV DNA replication with continued integration into the host hepatocyte also contributes to the persistent HCC risk after HBsAg seroclearance.

Additionally, the degree of HBV-associated hepatic inflammation, which can be assessed by measuring ALT levels, correlates with the risk for developing HCC ( 27 ). The ALT level before HBsAg seroclearance was similar among case-patients compared with control-patients. The ALT level together with the HBV DNA level indicates that the majority of case- and control-patients were in the immune-inactive phase of HBV infection prior to HBsAg seroclearance. Results from this present study confirm previous evaluations in this cohort demonstrating that most patients with chronic HBV infection are HBeAg-negative and remain in the immune-inactive phase after HBeAg clearance ( 33 , 34 ). The lack of difference in the degree of hepatic inflammation between case- and control-patients prior to HBsAg could also partly account for the lack of association between HBsAg seroclearance and reduced HCC risk.

Our adjusted analysis indicates that the initial HBeAg status and increasing age at cohort entry were associated with HCC risk. The presence of HBeAg, indicating immune-active phase of disease, is associated with high HBV DNA levels and intermittent ALT elevations ( 35 ). Therefore, HBeAg seropositivity could be associated with increased risk for HCC because it is a surrogate marker for HBV DNA level and hepatic inflammation ( 7 , 36 ). Our adjusted analysis also confirmed results from previous studies indicating that increasing age in HBV-infected persons is a risk factor for HCC ( 2 , 37 , 38 ). Although the exact date of HBV infection is unknown for patients in our study, it is likely that most patients acquired HBV infection in early childhood or at birth ( 39 ). Thus, the age at cohort entry probably correlates with the duration of infection for most study patients. Since our control-patients were matched with case-patients on age and duration of follow-up, the results additionally suggest that increasing age might be a risk factor for HCC independent of duration of HBV infection.

This study has limitations. First, our HCC risk estimates had wide confidence intervals because few case- and control-patients developed HCC. Thus, we could have failed to detect a real reduction in HCC risk associated with HBsAg seroclearance because of insufficient statistical power. It is important to note, however, that both HBsAg seroclearance and development of HCC are rare events, and our study has more persons with HBsAg seroclearance and HCC than other similar studies ( 3 , 8 - 10 , 26 ). Furthermore, it is important to note that the HCC incidence for a population cannot be calculated in a case-control study since the number of cases and controls are prespecified. The HCC rates we present allow for comparing the HCC risk between groups in this paper, but the absolute rates cannot be compared with the HCC incidence reported elsewhere. Additionally, the presence of other HCC risk factors, such as HCV-coinfection, family history of HCC, diabetes mellitus or fatty liver disease ( 18 - 20 ), was not comprehensively known for our study participants not developing HCC. As a result, we could not adjust for several important HCC risk factors in our model comparing the HCC rate between case- and control-patients. We did demonstrate, however, that case- and control-patients were similar in terms of certain key risk factors, such proportion with HCV-coinfection, HBV DNA level, hepatic inflammation as measured by ALT levels, and liver fibrosis as measured by APRI and Fib4. Finally, our results based on the AN population might not be generalizable to other populations. The risk for HCC varies by HBV genotype ( 11 ); AN persons infected with genotypes C and F have a higher incidence of HCC compared with persons infected with other genotypes ( 22 ). Differences in the prevalence of HBV genotypes between those found in AN persons compared with other geographic regions of the world could affect the incidence of HCC observed between persons with and without HBsAg seroclearance.

The goals of HBV treatment are to reduce the risk of developing cirrhosis, liver decompensation, and HCC. Therapy for HBV infection is indicated for patients in the immune-active phase but not for patients in the immune-inactive phase of HBV infection ( 40 ). Most patients in our study were in the immune-inactive phase of infection and did not receive HBV therapy. However, study patients were still at high risk for developing HCC and HBsAg seroclearance did not reduce the HCC risk. Given the effectiveness of nucleos(t)ide analogues in reducing HCC risk for persons with elevated HBV DNA levels ( 30 ), further research to better understand the factors early in the course of infection that predict future risk for developing HCC risk could help to identify a subset of immune-inactive patients who might benefit from early treatment.

Acknowledgments

Financial Support: This work was supported by the Centers for Disease Control and Prevention, NCHHSTP, Division of Viral Hepatitis (CA# 1U01PS004113).

Abbreviations

Conflict of interest: None of the authors have any conflicts to disclose.

Guarantor of article: PPG

Author contributions: BJM conceived the study question, interpreted data, and drafted manuscript. PPG designed the study, analyzed/interpreted data, drafted/revised manuscript. LRB designed study, conducted data analysis, interpreted results, and critical reviewed manuscript. MS, SN, PRS, and BSP contributed to the data acquisition and critically reviewed manuscript. All authors approve the final version of the manuscript, including authorship list, and assume responsibility for the accuracy/integrity of the work.

Disclaimer: The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.

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  • Published: 17 July 2007

Liver cancer risk, coffee, and hepatitis C virus infection: a nested case–control study in Japan

  • K Wakai 1   na1 ,
  • Y Kurozawa 2   na1 ,
  • A Shibata 3   na1 ,
  • Y Fujita 3   na1 ,
  • K Kotani 2   na1 ,
  • I Ogimoto 3   na1 ,
  • M Naito 1   na1 ,
  • K Nishio 1   na1 ,
  • H Suzuki 4   na1 ,
  • T Yoshimura 5   na1 &
  • A Tamakoshi 1   na1

for the JACC Study Group

British Journal of Cancer volume  97 ,  pages 426–428 ( 2007 ) Cite this article

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This article has been updated

We examined hepatocellular carcinoma mortality in relation to coffee consumption and anti-hepatitis C virus (HCV) antibody seropositivity in a nested case–control study involving 96 cases. The multivariate-adjusted odds ratios (95% confidence interval) for daily coffee drinkers vs non-drinkers were 0.49 (0.25–0.96), 0.31 (0.11–0.85), and 0.75 (0.29–1.92) in all cases, in HCV-positive and in HCV-negative individuals, respectively.

The inverse associations between coffee consumption and the risk of hepatocellular carcinoma (HCC) have recently been reported not only from case–control studies ( Gallus et al, 2002 ; Gelatti et al, 2005 ; Ohfuji et al, 2006 ; Montella et al, 2007 ; Tanaka et al, 2007 ) but also from Japanese cohort studies ( Inoue et al, 2005 ; Kurozawa et al, 2005 ; Shimazu et al, 2005 ). Cohort studies are superior to case–control studies in avoiding recall and selection bias ( Ohfuji et al, 2006 ). Previous prospective studies ( Inoue et al, 2005 ; Kurozawa et al, 2005 ; Shimazu et al, 2005 ), however, did not consider the infection status of hepatitis C virus (HCV) at baseline. As HCV is the major cause of HCC in Japan and certain other countries ( Heathcote, 2004 ), it would be important if protective factors against HCC could be found among the HCV-positive population. We therefore examined the relation of coffee use to risk of death from HCC by HCV infection status in a case–control study nested in a large cohort study in Japan.

Materials and methods

We carried out a nested case–control study as a part of the Japan Collaborative Cohort Study for Evaluation of Cancer Risk Sponsored by the Ministry of Education, Culture, Sports, Science and Technology of Japan (Mobusho), details of which are described elsewhere ( Tamakoshi et al, 2005 ). It involved 110 792 individuals, aged 40–79 years at baseline, from 45 areas throughout Japan. A self-administered questionnaire on lifestyle and medical factors was distributed in 1988–1990 covering habitual coffee consumption, with possible responses including ‘scarcely any’, ‘1–2 cups per month’, ‘1–2 cups per week’, ‘3–4 cups per week’, and ‘almost every day’. Those who answered ‘almost every day’ were asked to report the number of cups consumed per day. The questionnaire was validated using four 3-day dietary records as a reference; the Spearman correlation coefficient was 0.79 ( Iso et al, 2006 ).

In addition, those participants who underwent health-screening checks sponsored by municipalities were asked to donate blood samples at baseline and eventually, 39 242 subjects in 37 study areas did so ( Tamakoshi et al, 2005 ), these being stored at −80°C until analysed. Informed consent was obtained individually from subjects, except in certain areas in which it was provided at the group level after details had been explained to community leaders. The Ethics Committee of Kurume University School of Medicine approved this study.

We used population registries in the municipalities to determine the vital and residential status of the subjects. Causes of death were confirmed by review of death certificates with permission from the Ministry of Internal Affairs and Communications. Cases eligible for the present study consisted of those who died of HCC, ICD-10 coded C22.0.

During follow-up through the end of 1999, 106 eligible cases were identified among the participants with serum samples, from which two were excluded with insufficient samples and eight without information on coffee consumption. Of the remaining 96 cases, 60 (62.5%) were positive for HCV Ab. As potential controls, sera of 11 513 subjects from the same geographical areas as the cases were also screened for HCV Ab. After excluding those with missing data on coffee drinking, we found 912 HCV-Ab-positive subjects (8.2%) and 10 175 HCV-Ab-negative ones. From these, we chose as many controls per case as possible, matching for age (same 5-year strata), sex, and HCV-Ab seropositivity, selecting 420 HCV-Ab-positive controls (seven controls per case) and 3024 HCV-Ab-negative ones (84 controls per case).

Statistical analysis

Study participants were categorised into three groups by coffee consumption, that is, ⩾ 1 cup day −1 , <1 cup day −1 (‘1–2 cups month −1 ’, ‘1–2 cups week −1 ’, or ‘3–4 cups week −1 ’), and non-drinkers. Daily drinkers could not be further subdivided because of their small numbers. Odds ratios (OR) and the 95% confidence intervals (CI) by HCV-Ab positivity were estimated considering the matching using conditional logistic models ( Breslow and Day, 1980 ). Multivariate-adjusted OR were also computed after adjustment for area, smoking and drinking habits, and history of diabetes mellitus and liver diseases. For alcohol drinking, subjects were categorised into never drinkers, former drinkers, or current drinkers who consumed <2 or ⩾ 2 Japanese drinks per day (one Japanese drink is equivalent to 23 g of ethanol) in this analysis. The linear trend in HCC risk was tested by treating the coffee consumption category as an ordinal variable. The heterogeneity in the association of coffee drinking by HCV status was statistically tested by incorporating a multiplicative interaction term between HCV status and the coffee consumption category in the model. Missing values for each covariate were treated as an additional category in the variable and were included in the model. All P -values were two-sided, and all the analyses were carried out using the Statistical Analysis System version 9.1 (SAS Institute, Cary, NC, USA).

Cases and controls were well matched on age and sex in both the HCV-positive and -negative groups. The mean ages±s.d. were 62.9±6.6, 62.4±6.2, 63.6±7.5, and 63.4±7.3 years in the HCV-positive cases and controls and the HCV-negative cases and controls, respectively. Women accounted for 35.0% of both the HCV-positive cases and controls, and 36.1% of the HCV-negative cases and controls. Case subjects were more likely to currently smoke than controls in the HCV-positive group (56.6 vs 35.8%). Former drinkers and a history of diabetes mellitus and liver diseases were much more common in cases than in controls. In the HCV-positive cases, the proportions of former drinkers and those with diabetes and liver diseases were 28.6, 15.0, and 56.7%, respectively, against 6.6, 5.0, and 20.7% in the controls. The corresponding figures were 14.3, 13.9, and 27.8% in the HCV-negative cases and 4.4, 4.5, and 4.4% in the controls.

Drinking one or more cups of coffee per day was inversely associated with HCC mortality among all subjects ( Table 1 : multivariate-adjusted OR (OR2), 0.49; 95% CI, 0.25–0.96) and the anti-HCV-positive group (OR2, 0.31; 95% CI, 0.11–0.85). Although daily coffee drinkers in the HCV-negative group showed OR below unity, they did not reach statistical significance. The heterogeneity in the association of coffee drinking by HCV status was also not significant in the multivariate model ( P = 0.61).

Coffee drinking was significantly associated with a decreased risk of death from HCC in all subjects and those infected with HCV. Our results from this prospective cohort study support the findings in some ( Gelatti et al, 2005 ; Ohfuji et al, 2006 ), although not all ( Montella et al, 2007 ), case–control studies that suggested a protective effect of coffee among HCV-positive individuals. Some patients with hepatitis or liver cirrhosis, however, may have decreased coffee consumption at their physician's advice or due to impaired caffeine metabolism in the liver ( Hasegawa et al, 1989 ). Observational studies among subjects without active hepatitis or intervention studies will further clarify the role of coffee in the possible prevention of HCV-related HCC. Further, because a nonsignificant inverse association was found between coffee consumption and HCC risk in HCV-negative individuals in the present study, investigations with more HCV-negative HCC cases are also warranted.

Change history

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Acknowledgements

We thank Dr Katsuhiro Fukuda, Professor Emeritus, Kurume University School of Medicine, who was a leader of the liver cancer group in the JACC Study. We also express our sincere appreciation to Dr Kunio Aoki, Professor Emeritus, Nagoya University School of Medicine and the former chairman of the JACC Study, and Dr Haruo Sugano, the former Director of the Cancer Institute of the Japanese Foundation for Cancer Research, who greatly contributed to the initiation of this study. This work was supported by a Grant-in-Aid for Scientific Research on Priority Areas (2) (No. 14031223) from the Ministry of Education, Culture, Sports, Science and Technology of Japan and by a Grant-in-Aid for Research on Hepatitis from the Ministry of Health, Labour and Welfare. The JACC Study has also been supported by Grants-in-Aid for Scientific Research from the Ministry of Education, Culture, Sports, Science and Technology of Japan (Nos. 61010076, 62010074, 63010074, 1010068, 2151065, 3151064, 4151063, 5151069, 6279102, 11181101, 17015022, and 18014011).

Author information

K Wakai, Y Kurozawa, A Shibata, Y Fujita, K Kotani, I Ogimoto, M Naito, K Nishio, H Suzuki, T Yoshimura and A Tamakoshi: Study group members are listed in Appendix A .

Authors and Affiliations

Department of Preventive Medicine/Biostatistics and Medical Decision Making, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550, Japan

K Wakai, M Naito, K Nishio & A Tamakoshi

Department of Social Medicine, Division of Health Administration and Promotion, Faculty of Medicine, Tottori University, Nishimachi 86, Yonago, 683-8503, Japan

Y Kurozawa & K Kotani

Department of Public Health, Kurume University School of Medicine, 67 Asahi-machi, Kurume, 830-0011, Japan

A Shibata, Y Fujita & I Ogimoto

Department of Public Health, Graduate School of Medical and Dental Sciences, Niigata University, 1-757 Asahimachi-dori, Niigata, 951-8510, Japan

Fukuoka Institute of Health and Environmental Sciences, 39 Oaza-Mukaizano, Dazaifu, 818-0135, Japan

T Yoshimura

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Corresponding author

Correspondence to K Wakai .

Japan Collaborative Cohort Study Group The present investigators involved, with the co-authorship of this paper, in the JACC Study and their affiliations are as follows: Dr Akiko Tamakoshi (present chairman of the study group), Nagoya University Graduate School of Medicine; Dr Mitsuru Mori, Sapporo Medical University School of Medicine; Dr Yutaka Motohashi, Akita University School of Medicine; Dr Ichiro Tsuji, Tohoku University Graduate School of Medicine; Dr Yosikazu Nakamura, Jichi Medical School; Dr Hiroyasu Iso, Graduate School of Medicine, Osaka University; Dr Haruo Mikami, Chiba Cancer Center; Dr Yutaka Inaba, Juntendo University School of Medicine; Dr Yoshiharu Hoshiyama, University of Human Arts and Sciences; Dr Hiroshi Suzuki, Niigata University School of Medicine; Dr Hiroyuki Shimizu, Gifu University School of Medicine; Dr Hideaki Toyoshima and Dr Kenji Wakai, Nagoya University Graduate School of Medicine; Dr Shinkan Tokudome, Nagoya City University Graduate School of Medical Sciences; Dr Yoshinori Ito, Fujita Health University School of Health Sciences; Dr Shuji Hashimoto, Fujita Health University School of Medicine; Dr Shogo Kikuchi, Aichi Medical University School of Medicine; Dr Akio Koizumi, Graduate School of Medicine and Faculty of Medicine, Kyoto University; Dr Takashi Kawamura, Kyoto University Center for Student Health; Dr Yoshiyuki Watanabe, Kyoto Prefectural University of Medicine, Graduate School of Medical Science; Dr Tsuneharu Miki, Graduate School of Medical Science, Kyoto Prefectural University of Medicine; Dr Chigusa Date, Faculty of Human Life and Environment, Nara Women's University; Dr Kiyomi Sakata, Wakayama Medical University; Dr Youichi Kurozawa, Tottori University Faculty of Medicine; Dr Norihiko Hayakawa, Research Institute for Radiation Biology and Medicine, Hiroshima University; Dr Takesumi Yoshimura, Fukuoka Institute of Health and Environmental Sciences; Dr Akira Shibata, Kurume University School of Medicine; Dr Naoyuki Okamoto, Kanagawa Cancer Center; Dr Hideo Shio, Moriyama Municipal Hospital; Dr Yoshiyuki Ohno, Asahi Rosai Hospital; Dr Tomoyuki Kitagawa, Cancer Institute of the Japanese Foundation for Cancer Research; Dr Toshio Kuroki, Gifu University; and Dr Kazuo Tajima, Aichi Cancer Center Research Institute.

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Wakai, K., Kurozawa, Y., Shibata, A. et al. Liver cancer risk, coffee, and hepatitis C virus infection: a nested case–control study in Japan. Br J Cancer 97 , 426–428 (2007). https://doi.org/10.1038/sj.bjc.6603891

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Received : 03 April 2007

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nested case control study and hepatitis

ORIGINAL RESEARCH article

Describing immune factors associated with hepatitis b surface antigen loss: a nested case-control study of a chinese sample from wuwei city.

Xiaojie Yuan,&#x;

  • 1 Department of Epidemiology, School of Public Health, Air Force Medical University, Xi’an, China
  • 2 Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi’an, China
  • 3 Faculty of Health and Medicine, Division of Health Research, Lancaster University, Lancaster, United Kingdom
  • 4 Clinical Drug Experiment Institution, Gansu Wuwei Tumor Hospital, Wuwei, China
  • 5 Hepatobiliary Center, Gansu Wuwei Tumor Hospital, Wuwei, China

Background: Hepatitis B surface antigen (HBsAg) loss is considered a functional cure for chronic hepatitis B (CHB), however, several factors influence HBsAg loss.

Methods: 29 CHB patients who had achieved HBsAg loss, were selected and 58 CHB patients with persistent HBsAg were matched, according to gender and age (+/- 3 years). Logistic regression and restricted cubic spline (RCS) modelling were performed.

Results: Multivariate-adjusted logistic regression, based on stepwise selection, showed that baseline HBsAg levels negatively correlated with HBsAg loss (odds ratio [OR] = 0.99, 95% confidence interval [CI] = 0.98-0.99). Interferon treatment positively related with HBsAg loss (OR = 7.99, 95%CI = 1.62-44.88). After adjusting for age, HBsAg level, ALT level, HBeAg status and interferon treatment, MMP-1 (OR = 0.66, 95%CI = 0.44-0.97), CXCL9 (OR = 0.96, 95%CI = 0.93-0.99) and TNF-R1 (OR = 0.97, 95%CI = 0.94-0.99) baseline levels all negatively correlated with HBsAg loss. Our multivariate-adjusted RCS model showed that baseline CXCL10 was associated with HBsAg loss although the relationship was “U-shaped”.

Conclusions: Cytokines such as MMP-1, CXCL9, CXCL10 and TNF-R1 are important factors which influence HBsAg loss. It may be possible to develop a nomogram which intercalates these factors; however, further research should consider immune processes involved in HBsAg loss.

Introduction

Approximately 316 million people worldwide suffer with chronic hepatitis B virus infections (HBV) ( 1 ) although, each country has different prevalence rates. According to a relatively recent meta-analysis, the pooled estimated prevalence of HBV infections in the Chinese mainland population, between 2013 to 2017, was thought to be 6.89%. Anything between 5.00-7.99% is officially classified as a higher intermediate prevalence ( 2 ) although again prevalence rates vary regionally. Wuwei city, which is in the north-west of mainland China, is one area in China considered to have a particularly high prevalence of chronic hepatitis B (CHB), with 7.2% (95% CI: 6.3-8.1%) in 2010 ( 3 ). As such, Wuwei city has been targeted by Chinese public health organisations as a location for pilot HBV prevention and treatment programmes.

CHB patients are at a substantially higher risk of developing cirrhosis and hepatocellular carcinoma (HCC). These diseases are responsible for approximately 1.45 million deaths worldwide, each year ( 4 ) and therefore must be prevented. Hepatitis B surface antigen (HBsAg) seroclearance can occur spontaneously in CHB patients but can also be induced with anti-viral treatments. HBsAg loss is associated with improvements in liver histologies and a decreased risk of cirrhosis, HCC development and death ( 5 ). Therefore, HBsAg seroclearance is often regarded as the optimal endpoint for treatments according to clinical guidelines ( 6 , 7 ). However, HBsAg seroclearance is rare ( 8 , 9 ) and therefore, we must learn to understand HBsAg seroclearance as well as the factors that influence HBsAg loss.

Previous studies have identified several factors related to HBsAg loss e.g. gender, HBV DNA levels, Hepatitis B e antigen (HBeAg) status and ALT level at baseline ( 10 – 12 ). Apart from the direct action of immune cells, cytokines are also thought to mediate HBsAg loss ( 13 ). At present, Interferon (IFN)-α is the main antiviral therapy for CHB and Interleukins (IL) -4, IL-6, IL-17, and IL-28 act as key “coordinators” of inflammatory responses involved in HBsAg seroclearance ( 13 ). Serum interferon-inducible protein (IP) 10, also known as C-X-C motif ligand (CXCL) 10, and CXCL13 levels could also play an important role in predicting HBsAg seroclearance ( 14 , 15 ). However, the established knowledge base does not include a clear description of associations between cytokines, SNPs related to cytokines and HBsAg loss.

Materials and methods

Participants.

From August 2018 until January 2021, 4,000 individuals, aged 30–65 years with previous HBsAg seropositive results (for at least six months), were screened in Wuwei City, China. Potential participants were asked for formal consent to participate in this study which involved a survey, a physical examination and a direct consultation with a clinician at Gansu Wuwei Tumor Hospital. After excluding duplicate data (n = 16) and those who did not complete examinations (n = 22), 3,962 participants were recruited and engaged in routine examinations every six to twelve months until 31 st October 2021.

All research was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee in the Air Force Medical University. All participants were fully informed of the purpose and details of this study, and participants (or their legal guardians) were required to provide informed consent, before participating.

The baseline for this study was defined according to the time of recruitment. The events of interest during follow-up were HBsAg loss and HBsAg seroclearance. HBsAg loss was defined as serum HBsAg which reverted to negative from positive for CHB cases with (or without) treatment. HBsAg seroclearance was defined as maintaining a HBsAg negative status on two separate occasions over six months until the endpoint. 29 participants with HBsAg loss were initially assessed using blood samples at baseline. 58 participants with persistent HBsAg(+) status were matched, according to gender and age (+/- 3 years). A flow chart of the selection and assignment process is presented in Supplementary Figure 1.

Data collection

A questionnaire was specifically designed for Prevention and Control of Infectious Diseases studies in China. Trained investigators collected information through face-to-face interviews. Physical examinations were performed locally in Gansu Wuwei Tumor Hospital and results were collated. Details of examinations have been described in Supplementary Materials, Methods .

Quantitative examination of HBsAg

Blood samples were obtained through standard forearm venipunctures and samples were processed within 1 h of collection. Blood samples were centrifuged at 12,000 g for 10 mins at 4°C and then supernatants were transferred into microcentrifuge tubes, which were stored at −80°C. Chemiluminescence analysis reagents (Snibe Ltd. Shenzhen, China) were used for quantitative HBsAg examinations in the Tianbo Medical Laboratory. The range was 0.02-1000 IU/mL.

An RD systems Luminex ® Discovery Assay Human Premixed Multi-Analyte Kit (Kit Catalog Number: LXSAHM-17, Lit Lot Number: L141528) was used to detect 17 types of cytokines, including IL-6, IL-8, IL-21, IL-23, IL-33, matrix metalloproteinases (MMP)-1, MMP-2, MMP-3, C-X-C motif ligand (CXCL) 9, CXCL10, CXCL11, CXCL13, C-C motif ligand (CCL2), tumor necrosis factor (TNF) -α TNF-R1, IFN-γ, and B cell activating factor (BAFF) using a Luminex xPONENT ® for FLEXMAP3D ® analyzer. These 17 cytokines were chosen according to an associated pilot study we conducted focusing on CHB patients compared to healthy controls (in press).

A standard curve was created for each analyte through data reduction, using milliplex analyst (5.1) which is capable of generating a five-parameter logistic (5-PL) curve-fit. Cytokines below the lower limit were recorded as lower limit values. Replacement numbers for each cytokine were listed as follows: IL-8 (1/87), IL-23 (12/87), IL-33 (8/87), MMP-3 (1/87), CXCL9 (3/87), CXCL11 (6/87), TNF-α (1/87) and IFN-γ (7/87). Considering the magnitude of cytokines, we transformed MMP-1, MMP-2 and MMP-3 from pg/mL to 1000 pg/mL, and CXCL9, CXCL10, CXCL11, CXCL13, TNF-α, TNF- R1, IFN-γ, BAFF and CCL2 from pg/mL to 10 pg/mL. This enabled us to perform more sophisticated logistic regression and RCS modelling.

Genomic DNA was isolated from whole blood samples using Human Genome Whole Blood Extraction Kit (Tianlong Technology, Xi’an, China). 14 single nucleotide polymorphisms (SNP) related to cytokines (rs1061624, rs1143634, rs12979860, rs1799724, rs1799964, rs1800469, rs1800795, rs1800872, rs1800896, rs2055979, rs2069762, rs2227306, rs3025058 and rs3806798) were assessed with TaqMan ® MGB SNP Genotyping Kit (Fuyuan Biotechnology Ltd, Shanghai, China) using a real-time polymerase chain reaction allelic discrimination system (Tianlong Technology, Xi’an, China). Shannon entropy (SE) for human SNPs were calculated according to the following formula ( 16 ), where i means genotypes and pi means the percentage of each genotype.

Statistical analysis

Variables are presented as means with corresponding standard deviations (SD), or as medians with quartiles, or just as simple numbers with percentages. These data points were compared using Student’s T test, Wilcoxon’s test, or by way of a standard Chi-square tests (or Fisher’s Exact tests), according to HBsAg status. Person-time at follow-up was calculated for each participant from the date of the first survey to the end of follow-up on the 31 th October, 2021.

Unadjusted and multivariable-adjusted (i.e., adjusting for age, HBsAg level, ALT level, HBeAg status, and interferon treatment) logistic regression models were used to analyze associations between variables and HBsAg loss. Odds ratios (OR) with 95% confidence intervals (CI) were estimated. Restricted cubic spline (RCS) methods with three knots (p5, p50 and p95) were applied to assess the linearity of relationships using “%RCS_REG” microprogram developed by Desquilbet ( 17 ). Details of RCS modelling process are described in the Supplementary Materials, Method Section . RCS plots were performed with proportion distribution.

Correlations between cytokines were assessed using Spearman’s correlation analysis. To consider relations among cytokines, we established each dataset as independent and integral. Standardized cytokines were calculated according to normalized Z-scores. Partial Least Squares Discriminant Analysis (PLS-DA) and Permutational Multivariate Analysis of Variance (PERMANOVA) with Euclidean distance were also performed to compare fundamental differences between the two groups using “mixOmics” R package ( http://mixomics.org/,v6.8.5 ) ( 18 ).

Statistical analyses were performed using SAS, version 9.4 (SAS Institute Inc, Cary, NC) and with R software, version 2.13.2 ( http://cran.r-project.org/ ). A p value of 0.05 was established as the threshold for statistical significance.

Baseline characteristics

3,962 participants were initially included at baseline, of whom 212 were HBsAg(–) and 3,750 were HBsAg(+). Among the 3,750 CHB cases with HBsAg(+), 1,694 were followed-up for a median of 1.5 years. 62 participants achieved HBsAg loss, corresponding to an annual loss rate of 2.41 per 100 person-years and with a cumulative incidence of 3.66%. Those with HBsAg loss were predominantly male, urban employees, taking antiviral treatments (specifically IFN), had a longer HBV duration since infection, and had higher levels of ALT, AST, DBIL, ALB, GGT and LSM. However, there was a small proportion of participants with HBsAg loss who were HBeAg(+) and who had lower HBV DNA loads ( Table 1 ).

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Table 1 Population characteristics for HBsAg consistence and HBsAg loss groups.

According to a strict definition of HBsAg seroclearance, we observed 21 participants who achieved HBsAg seroclearance, corresponding to an annual incidence of 0.82 per 100 person-years. The majority of participants who achieved HBsAg seroclearance were also taking antivirals (specifically IFN), had longer HBV duration since infection, and had the highest levels of ALT, AST, DBIL, ALB and GGT, but lower level of HBV DNA ( Supplementary Table 3 ).

Characteristics of the nested case-control groups

29 participants who achieved HBsAg loss were selected and matched with 58 who had not, according to gender and age (+/- 3 years). The HBsAg loss group also had a lower proportion of HBeAg(+) cases and a lower HBV DNA load, overall. Additionally, the HBsAg loss group had a higher proportion of people who were prescribed a IFN treatment and who had an HBV vaccine history. Within this group there was also a smaller proportion who had a family history of HBV infection ( Table 1 ).

Univariate logistic modelling showed that having a family history of HBV infection, taking IFN treatment, an HBV vaccine history, HBsAg level, HBV DNA level, and HBeAg status significantly associated with HBsAg loss. Multivariate-adjusted modelling with stepwise selection showed that baseline HBsAg levels negatively correlated with HBsAg loss (OR = 0.99, 95%CI = 0.98-0.99). However, IFN treatments also positively related with HBsAg loss (OR = 7.99, 95%CI = 1.62-44.88) under multivariate-adjusted modelling. Please see Table 2 for further details.

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Table 2 Logistic regression analysis of general features.

In order to explore non-linear relationships, we performed RCS with three knots, adjusting for age, ALT level, HBeAg status, and IFN treatment intake. Results showed that baseline HBsAg levels negatively correlated with HBsAg loss in a linear manner (overall: p < 0.001; non-linear: p = 0.766, Figure 1A ).

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Figure 1 Linear association between HBsAg, cytokines and HBsAg loss using restricted cubic spline with three knots (p5, p50 and p95) (A) HBsAg, adjusting for age, ALT level, HBeAg status and interferon treatment; (B-D) MMP-1, TNF-R1, and CXCL10, adjusting for age, HBsAg level, ALT level, HBeAg status and interferon treatment.

Cytokines and HBsAg loss

Cytokine levels at baseline between HBsAg consistency and HBsAg loss were compared. Participants who achieved HBsAg loss had lower TNF-R1 ( Figure 2A and Supplementary Figure 2 ) . The multivariate-adjusted logistic model showed that baseline MMP-1 (OR = 0.66, 95%CI = 0.44-0.97), CXCL9 (OR = 0.96, 95%CI = 0.93-0.99) and TNF-R1 (OR = 0.97, 95%CI = 0.94-0.99) levels negatively associated with HBsAg loss ( Table 3 ).

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Figure 2 Cytokines comparation between HBsAg consistence and HBsAg loss group (A) TNF-R1 level between HBsAg consistence and HBsAg loss group; (B) Spearman correlation among cytokines. Red, means positive correlation; blue, means negative correlation; * p < 0.05 in Spearman correlation test. (C) Partial least squares discriminant analysis of cytokines.

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Table 3 Association between cytokines and HBsAg loss.

In order to assess the linearity of relations between cytokines and HBsAg loss, we performed multivariate-adjusted RCS with three knots of P5, P50 and P95. We observed baseline MMP-1 (overall: p = 0.049; non-linear: p = 0.176) and TNF-R1 (overall: p = 0.047; non-linear: p = 0.072) had decreasing associations with HBsAg loss, but this correlation appears linear ( Figures 1B, C ) . Baseline CXCL10 associated with HBsAg loss although the relationship appeared “U-shaped” (overall: p = 0.049; non-linear: p = 0.016). When CXCL10 < 500 pg/ml, CXCL10 had a negative relationship with HBsAg loss; and when CXCL10 ≥ 500 pg/ml, CXCL10 had an increasingly association with HBsAg loss ( Figure 1D ) .

As can be seen in Figure 2B , spearman correlation analysis suggests that cytokines highly correlate, in general. Among the cytokines, IL-21 had a strong positive association with IL-33 (r = 0.711, p < 0.001) and IFN-γ (r = 0.635, p < 0.001) at baseline, and with IL-33 with IFN-γ (r = 0.909, p < 0.001). We took cytokines as integral and used PLS-DA to present the global difference ( Figure 2C ). PERMANOVA with Euclidean distance was used to compare fundamental differences between the two groups. Findings suggest there is no significant difference at baseline for integral cytokine levels ( p = 0.222).

Cytokine SNPs and HBsAg loss

Percentages for SNPs related to cytokines have been provided in Supplementary Figure 3 . The AT genotype for rs3806798 was significantly higher in those who encountered HBsAg loss compared to those with consistent HBsAg ( Supplementary Figure 3B ). Univariate logistic regression results showed the AT genotype of rs3806798 associated with an increased likelihood of HBsAg loss (OR = 3.52, 95%CI = 1.11-11.19). Please see Table 4 for further details. However, after adjusting for age, HBsAg, ALT, HBeAg status, and IFN treatment, statistically significant association disappeared ( Table 4 ). SE, as a measure of genetic diversity, was calculated although no difference between the groups was observed using Wilcoxon’s test ( p = 0.713; Supplementary Figure 3O ).

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Table 4 Association between SNPs in relation to cytokines and HBsAg loss.

In this cohort study of HBV patients from Wuwei city, 2.41% encountered HBsAg loss and 0.82% achieved HBsAg seroclearance. In this instance, both scenarios were either spontaneous or initiated through antiviral treatments. During the nested case-control analysis of HBsAg carriers, lower HBsAg levels at baseline and IFN treatment were associated with an increased likelihood of encountering HBsAg loss. In addition, participants with lower levels of MMP-1, CXCL9 and TNF-R1 at baseline appear more likely to achieve HBsAg loss. Baseline CXCL10 appears to be associated with HBsAg loss although the relationship appears to be “U-shaped”.

We found that lower HBsAg levels at baseline is associated with an increased likelihood of encountering HBsAg loss. Lower HBsAg levels at baseline also appear to hold the greatest predictive value for HBsAg seroclearance, as participants with lower HBsAg levels achieve HBsAg loss easier and sooner ( 19 , 20 ). We also found that IFN treatment was associated with an increased likelihood of HBsAg loss which may be indicative of other outcomes. A meta-analysis based on six clinical controlled trials recently reported that IFN could increase the likelihood of HBsAg seroclearance ( 21 ). In addition, IFN-based therapy can lead to more significant HBsAg reduction compared to therapies based on nucleoside and/or nucleotide analogues, leading to an increased likelihood of HBsAg seroclearance ( 22 , 23 ). This provides evidence to support the use of IFN with (or without) NUC for both naïve and NUC-exposed patients ( 23 ). Although, local and regional experience tells us that the use of IFN therapies in the north-west of China remains uncommon. This is something which could be addressed relatively quickly with training or by updating the current Chinese guidelines.

A recent study found that baseline CXCL10/IP10 could be used to predict HBsAg decline in HBeAg-negative patients receiving Entecavir. This is because patients with baseline IP10 > 350 pg/ml were also found to achieve significantly more rapid HBsAg decline i.e. ≥ 0.5 log10 (HR = 4.39, 95%CI = 1.63-11.83) ( 24 ). Likewise, a cross-sectional study observed higher level of IP10 in CHB patients with HBsAg seroclearance ( 25 ). However, Wong et al. found that lower serum IP-10 levels at year zero (i.e. the time of achieving HBsAg seroclearance) is the only cytokine associated with HBsAg seroclearance (HR per 100 pg/mL = 0.82, 95% CI 0.85-0.99) ( 14 ).

Interestingly, we observed that CXCL10 was associated with HBsAg loss and this relationship appears “U-shaped” with the lowest point in the trough occurring at 500 pg/mL. That is to say, the plot highlights a substantial reduction in risk within the lower range of CXCL10, which is consistent with previous studies which have reported the lowest risk of around 500 pg/mL followed by an increase. However, the number of participants in our study was relatively small, especially for those with higher IP10 levels, therefore our study provides only a potential explanation for the aforementioned inconsistencies. Secondly, research suggests that CXCL10 declines before increasing over the treatment period ( 14 , 24 ). Therefore, CXCL10 levels taken at different times may also become an important measure for assessing relationships.

We also observed an association between lower levels of plasma CXCL9 at baseline and a higher likelihood of HBsAg loss in CHB patients. Similar results have only been found in one acute hepatitis study, where CXCL9, CXCL10, CXCL11 and CXCL13 elevated during the acute phase but then decreased in conjunction with an HBsAg decline ( 26 ). However, some researchers have suggested this is not the case for CHB patients ( 26 , 27 ). Such inconsistent results may be due to differences between study populations, limited sample sizes and variations in outcome definitions. Although, CXCL9 and CXCL10, also known as MIG and IP-10, are all members of CXCL family and could promote Th1 responses as well as initiate CD8+ and natural killer (NK) cell trafficking ( 28 , 29 ). Increased NK cell functions and HBV-specific CD8+ T cell responses are also associated with HBsAg seroclearance ( 30 ). This of course requires further basic medical research but could be relatively easily confirmed.

MMP-1 is one metalloproteinase that has a role in both degrading and denaturing interstitial collagens, types I, II and III. In this study, we observed an association between lower levels of plasma MMP-1 and a greater likelihood of HBsAg loss, which has not yet been reported. On the other hand, the positive relationship between MMP-1 and adverse outcomes for CHB patients has been reported. For example, Flisiak et al. found that MMP-1 levels continue to rise during the first four weeks of acute viral hepatitis, which seems connected to hepatocytes damage ( 31 ). Yang et al. ( 32 ) also found that MMP-1 significantly increases in HCC patients and could therefore be useful biomarkers for the early HCC detection and in prognostics. Although, the role of MMP-1 during HBsAg loss is not fully understood and requires further investigation.

TNF-R1 appears on almost all cell types and mediates inflammatory responses, cytotoxic action, antiviral activity, and cell proliferation ( 33 ). Yang et al. ( 34 ) found that TNF-R1 is required to eliminate the natural cccDNA transcriptional template during natural HBV infection. Likewise, Tai et al. ( 35 ) observed soluble TNF-R1 levels are higher in CHB patients compared to healthy controls, and that TNF-R1 levels correlate with liver inflammation in CHB cases. In our study, we observed a negative association between plasma TNF-R1 at baseline and the likelihood of HBsAg loss. This may support the theory that participants with reduced inflammation are more likely to lose HBsAg although again further research is required.

In this study, we assumed that participants with HBsAg loss were more likely to present with an anti-inflammatory mode of cytokines, characterized by lower levels of MMP-1, CXCL9, CXCL10 and TNF-R1 at baseline. Therefore, we performed PLS-DA analysis to compare the fundamental differences between the two groups. We did not observe any significant differences although we did manage to develop a more comprehensive description of cytokines.

Before making any recommendations, it is important to first discuss the limitations involved. Firstly, we choose HBsAg loss rather than seroclearance as the main outcome of interest. One reason for this was that our cohort was based on only three years and 71.1% were followed less than twice. This meant we were unable to meet follow-up time criteria for HBsAg seroclearance. We also chose HBsAg loss hoping to gain insight into how HBsAg seroclearance is achieved. However, we accept that we still need to develop our understanding of the relationship between HBsAg loss and HBsAg seroclearance. Secondly, we only observed 62 participants who had achieved HBsAg loss and among these only 29 had complete data. This sample is small however we implemented a matching process (ratio 1:2) to increase inspection efficiency. Finally, we only examined the association between baseline characteristics and HBsAg loss. Some characteristics are time-specific and vary during follow-up. This variability may also influence HBsAg loss although further research is required.

This was a nested case-control study of HBsAg carriers from a cohort in Wuwei city, China. Lower levels of HBsAg, MMP-1, CXCL9 and TNF-R1 at baseline and IFN treatment were associated with an increased likelihood of HBsAg loss. Baseline CXCL10 also appears associated with HBsAg loss but the relationship appears U-shaped, which requires further investigation. It may be possible to develop a nomogram which intercalates these factors; however, researchers should consider immune processes involved in HBsAg loss. In order to improve interventions efficacy we should pay attention to immune activities related HBsAg loss.

Data availability statement

The datasets used in this study can be found in the Supplementary Material .

Ethics statement

The studies involving human participants were reviewed and approved by The Ethics Committee of the Air Force Medical University. The patients/participants provided their written informed consent to participate in this study.

Author contributions

ZS and WlZ designed the study, reviewed, and revised the manuscript. XY and TF analyzed the data and wrote the manuscript. LX, ZH, HZ, XK, SZ, QZ and YL did laboratory tests. ZJ and SS revised the manuscript and helped to interpret the results. WhZ and YY managed the cohort. WJ, CL, HT and FW collected data. All authors read and approved the final manuscript.

This study was supported by China Special Grant for the Prevention and Control of Infection Diseases (2017ZX10105011), National Natural Science Foundation of China (81773488), and the Natural Science Foundation of Shaanxi Province (2021JQ-341).

Acknowledgments

The authors thank the participants who agreed to participate and made this cohort study possible.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu.2022.1025654/full#supplementary-material

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Keywords: HBsAg, interferon, chemokine, MMP-1, TNF-R1

Citation: Yuan X, Fu T, Xiao L, He Z, Ji Z, Seery S, Zhang W, Ye Y, Zhou H, Kong X, Zhang S, Zhou Q, Lin Y, Jia W, Liang C, Tang H, Wang F, Zhang W and Shao Z (2022) Describing immune factors associated with Hepatitis B surface antigen loss: A nested case-control study of a Chinese sample from Wuwei City. Front. Immunol. 13:1025654. doi: 10.3389/fimmu.2022.1025654

Received: 23 August 2022; Accepted: 20 September 2022; Published: 11 October 2022.

Reviewed by:

Copyright © 2022 Yuan, Fu, Xiao, He, Ji, Seery, Zhang, Ye, Zhou, Kong, Zhang, Zhou, Lin, Jia, Liang, Tang, Wang, Zhang and Shao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Zhongjun Shao, [email protected] ; Weilu Zhang, [email protected]

† These authors have contributed equally to this work and share first authorship

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

  • Open access
  • Published: 08 April 2021

Risk factors for losing hepatitis B virus surface antibody in patients with HBV surface antigen negative/surface antibody positive serostatus receiving biologic disease-modifying anti-rheumatic drugs: a nested case-control study

  • Ming-Hui Hung 1 ,
  • Ya-Chih Tien 1 &
  • Ying-Ming Chiu   ORCID: orcid.org/0000-0003-4548-5331 2  

Advances in Rheumatology volume  61 , Article number:  22 ( 2021 ) Cite this article

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Hepatitis B virus (HBV) reactivation consequent to immunosuppressive therapy is an increasingly prevalent problem with serious clinical implications. Treatment with biologic agents conduces to the loss of protective antibody to HBV surface antigen (anti-HBs), which significantly increases the risk of HBV reactivation. Hence, we investigated the risk factors for losing anti-HBs in patients with rheumatic diseases and HBV surface antigen negative/anti-HBs positive (HBsAg−/anti-HBs+) serostatus during treatment with biologic disease-modifying anti-rheumatic drugs (DMARDs).

Using a nested case-control design, we prospectively enrolled patients with rheumatoid arthritis, ankylosing spondylitis, psoriatic arthritis/psoriasis, or juvenile idiopathic arthritis, who were treated with biologic DMARDs at Changhua Christian Hospital, Taiwan, from January 2013 to June 2019 and had HBsAg−/anti-HBs+ serostatus; the analytic sample excluded all patients with HBsAg+ or anti-HBs− serostatus. Anti-HBs titers were monitored 6-monthly and cases were defined as anti-HBs < 10 mIU/ml during follow-up. Cases were matched one-to-all with controls with anti-HBs ≥ 10 mIU/ml on the same ascertainment date and equivalent durations of biologic DMARDs treatment (control patients could be resampled and could also become cases during follow-up). Between-group characteristics were compared and risk factors for anti-HBs loss were investigated by conditional logistic regression analyses.

Among 294 eligible patients, 23 cases were matched with 311 controls. The incidence of anti-HBs loss was ~ 2.7%/person-year during biologic DMARDs treatment. Besides lower baseline anti-HBs titer (risk ratio 0.93, 95% CI 0.89–0.97), cases were significantly more likely than controls to have diabetes mellitus (risk ratio 4.76, 95% CI 1.48–15.30) and chronic kidney disease (risk ratio 14.00, 95% CI 2.22–88.23) in univariate analysis. Risk factors remaining significantly associated with anti-HBs loss in multivariate analysis were lower baseline anti-HBs titer (adjusted risk ratio 0.93, 95% CI 0.88–0.97) and chronic kidney disease (adjusted risk ratio 45.68, 95% CI 2.39–871.5).

Conclusions

Besides lower baseline anti-HBs titer, chronic kidney disease also strongly predicts future anti-HBs negativity in patients with HBsAg−/anti-HBs+ serostatus who receive biologic DMARDs to treat rheumatic diseases. Patients with low anti-HBs titer (≤ 100 mIU/ml) and/or chronic kidney disease should be monitored during biologic DMARDs therapy, to enable timely prophylaxis to preempt potential HBV reactivation.

Hepatitis B virus (HBV) infection is a global public health concern [ 1 ]. Morbid HBV reactivation is characterized by viral replication and the recurrence of active necro-inflammatory liver disease, which may presage severe hepatitis or even death [ 1 , 2 , 3 , 4 , 5 , 6 ]. Rising prevalence of cancer and autoimmune diseases and more frequent use of chemotherapeutic or immunosuppressive treatment strategies, have made HBV reactivation consequent to such therapies an exigent problem [ 1 , 2 , 3 , 4 , 5 ]. Iatrogenic HBV reactivation is best known in HBV surface-antigen carriers (HBsAg+), and comprehensive guidelines cover this high-risk group [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 ]. Recently, attention has increasingly focused on patients who are HBsAg-negative with antibodies against HBV core-antigen or surface-antigen (HBsAg−/anti-HBc+ or anti-HBs+), among whom baseline HBV DNA and anti-HBs negative (anti-HBs−) serostatus are known risk factors for HBV reactivation [ 9 , 10 , 11 , 12 , 13 ].

Although serum HBV DNA is a defining characteristic of HBV reactivation [ 1 , 2 , 3 , 4 ], it does not inevitably progress to morbid viremia but may manifest transiently without symptoms, especially whilst anti-HBs serostatus remains positive [ 5 , 6 , 10 , 11 , 12 ]. On the other hand, anti-HBs loss consequent to immunosuppressive treatment of patients with HBsAg−/anti-HBc+ serostatus significantly increases the risk of progression from clinically silent to symptomatic HBV reactivation [ 9 , 10 , 12 , 13 ]. Previous studies have shown that anti-HBs can decline to seronegative during immunosuppressive therapies, especially in patients with a low baseline anti-HBs titer [ 11 , 14 ], but none have systematically investigated whether there are other predisposing factors.

In this context, especially given burgeoning use of tumor necrosis factor inhibitors (anti-TNF) and other biologic disease-modifying anti-rheumatic drugs (DMARDs) to treat autoimmune diseases, and elevated HBV reactivation rates in this setting [ 2 , 4 , 5 ], it is imperative to further elucidate risk factors for anti-HBs loss. To this end, we prospectively studied patients with HBsAg−/anti-HBc+ serostatus during/after biologic DMARDs therapy for rheumatic diseases.

Study subjects

The study sample comprised patients at Changhua Christian Hospital, Taiwan, with rheumatoid arthritis, ankylosing spondylitis, psoriasis, psoriatic arthritis, or juvenile idiopathic arthritis, who were treated with biologic DMARDs from January 2013 to June 2019. Only patients with HBsAg−/anti-HBs+ serostatus were included and all with HBsAg+ or HBsAg−/anti-HBs− serostatus were excluded (Fig.  1 ). All study subjects fulfilled international diagnostic criteria for these diseases and were treated according to Taiwan Rheumatology Association guidelines for screening and management of viral hepatitis [ 15 ].

figure 1

Case-control selection flow chart. DMARDs, disease-modifying anti-rheumatic drugs; HBV, hepatitis B virus; DNA, deoxyribonucleic acid; anti-HBs, HBV surface antibody; HBsAg, HBV surface-antigen; mIU, million International Units. a One patient could serve as a control repeatedly during follow-up and control subjects could become cases during the study

Hepatitis B serologic testing and HBV DNA

HBV serology and DNA assays were done every 6 months according to Taiwan Rheumatology Association recommendations [ 15 ]. HBV assays included serum HBsAg, anti-HBs and anti-HBc, measured by Architect i2000SR chemiluminescent microparticle immunoassay (Abbott Laboratories, Abbot Park, Illinois, USA). HBV immunization history of people with anti-HBs+/anti-HBc− serostatus was not ascertained.

Anti-HBs titer < 10 mIU/ml was defined as seronegative. Low anti-HBs titer was defined as 10–100 mIU/ml, based on evidence of significantly increased likelihood of anti-HBs loss and detectable HBV DNA at anti-HBs titers below 100 mIU/ml and protection against HBV reactivation above this threshold [ 11 , 14 ]. Serum HBV DNA viral load was quantified by Abbott RealTime HBV (Abbott Laboratories, Abbott Park, Illinois, USA), with a minimal sensitivity of 10 IU/ml. HBV DNA titer ≥ 10 mIU/ml was defined as detectable viral load [ 11 ], while the criteria defining clinical HBV reactivation at any serial 6-monthly follow-up check, were HBV replication ≥ 2 log increase from baseline or a new appearance of HBV DNA to ≥ 100 IU/ml in people with previously stable or undetectable levels [ 1 ].

Covariate information

Baseline data included: age, sex, type of rheumatic disease (rheumatoid arthritis, ankylosing spondylitis, psoriatic arthritis/psoriasis, juvenile idiopathic arthritis), accumulated doses of conventional DMARDs (prednisolone, hydroxychloroquine, sulfasalazine, methotrexate, leflunomide, cyclosporine) and biologic DMARDs (etanercept, adalimumab, golimumab, ustekinumab, secukinumab, tocilizumab, rituximab, abatacept, tofacitinib). Chronic kidney disease was defined as estimated glomerular filtration rate < 60 ml/min/1.73 m 2 . Chronic liver disease status was determined from medical charts or hepatic ultrasound results and included cirrhosis, fatty liver, and “parenchymal liver disease”, which is a term used in Taiwan, to denote ultrasound findings intermediate between “normal” and “cirrhosis”, based on sonographic evaluation criteria for liver surface, liver parenchyma, hepatic vessels, and spleen size [ 16 ].

Nested case-control design

We used a nested case-control design, which enables efficient analysis of time-dependent exposures on rare outcomes where only a limited sample from a larger population is practical, without compromising statistical power [ 17 , 18 , 19 ]. Unlike conventional cohort studies, which compare cases versus controls from a fully enumerated population, a nested case-control design identifies occurrences of events of interest in a defined sub-population and matches these with a specified number of control subjects drawn from the same sub-sample, but who were not yet affected by the same event when it occurred in their corresponding case [ 18 , 19 ]. This design means that controls can become cases later during follow-up and that each patient may serve as a control repeatedly (though at different times); thus, cases are compared with controls from the same patient sample, which lessens the likelihood of selection bias [ 17 , 18 , 19 , 20 ].

The first prescription of a biologic DMARD defined the start point. Cases were defined upon occurrences of serum anti-HBs titer < 10 mIU/ml during follow-up, with the date when anti-HBs loss was ascertained designated the event date. Each case was matched one-to-all with subjects whose serum HBsAb titer was ≥ 10 mIU/ml on the respective case ascertainment date and who had an equivalent duration of biologic DMARDs treatment.

Data analysis and statistics

All analyses were done using nonparametric statistical software (LogXact 11, Cytel Software Corp, Cambridge, MA, USA) with penalized maximum likelihood to remove first-order bias. A p -value < 0.05 for two-sided tests was considered statistically significant. Continuous variables were expressed as means plus/minus standard deviation or mean [range], categorical variables as numbers (percentages). Conditional logistic regression analysis was used to estimate risk ratios and 95% confidence intervals for loss of anti-HBs; putative associated factors included age, sex, type of rheumatic disease, conventional DMARDs, biologic DMARDs (anti-TNF or others), comorbidity, and baseline anti-HBs titer.

Demographic characteristics and clinical status

The analytic samples drawn from 294 patients with HBsAg−/anti-HBs+ serostatus at baseline, comprised 23 cases and 311 matched controls (Fig. 1 ); Table  1 shows their demographic and clinical characteristics. Mean age and rheumatic disease types were similar between case and control groups. No patients with HBsAg−/anti-HBs+ serostatus had detectable HBV DNA at enrolment. Compared with controls, cases had lower baseline serum anti-HBs titers, more prevalent comorbidities (including hepatitis C virus infection, chronic liver disease, diabetes mellitus, chronic kidney disease), and relatively higher accumulated doses of sulfasalazine, leflunomide, and prednisolone. Most people in both groups used anti-TNF agents (etanercept, adalimumab, golimumab). No study subjects were kidney transplant recipients.

Incidence of anti-HBs loss and associated risk factors

The incidence rate of anti-HBs loss in 294 patients with HBsAg−/anti-HBs+ serostatus during biologic DMARDs treatment was 23/852 person-years: ~ 2.7%/person-year.

Table  2 shows risk factors associated with loss of anti-HBs in univariate and multivariate conditional logistic regression analyses. Besides lower baseline anti-HBs titer (risk ratio 0.93, 95% CI 0.89–0.97), cases were significantly more likely than controls to have diabetes mellitus (risk ratio 4.76, 95% CI 1.48–15.30) and chronic kidney disease (risk ratio 14.00, 95% CI 2.22–88.23) in the univariate analysis. However, the only factors remaining significant in the multivariate model, were lower baseline serum anti-HBs titer (adjusted risk ratio 0.93, 95% CI 0.88–0.97) and chronic kidney disease (adjusted risk ratio 45.68, 95% CI 2.39–871.5).

Clinical features and outcomes of subjects with anti-HBs loss

Thirteen cases had rheumatoid arthritis (Table  3 ). All cases’ baseline anti-HBs titers were low (≤ 100 mIU/ml), mean 22.6. Fourteen were prescribed anti-TNF agents: four etanercept, six adalimumab, and four golimumab. Three were prescribed tofacitinib. Two cases each were prescribed ustekinumab or tocilizumab, while one each received abatacept or rituximab.

No cases (nor anti-HBs+ controls) had clinical HBV reactivation during follow-up (852 person-years), and no cases developed alanine transaminase elevation, or received any anti-viral treatment during median follow-up of 30 months (range 0–77) after anti-HBs loss. Only one of the 16/23 cases whose serum HBV DNA was monitored after anti-HBs loss ever had a detectable viral load (Table 3 ), which was observed only once, with no recurrence as of August 2020.

We believe this to be the first report of risk factors associated with loss of anti-HBs in rheumatic patients during biologic DMARDs therapy, after controlling for putative risk factors. We discovered that besides lower baseline anti-HBs titer, chronic kidney disease independently predicts anti-HBs loss.

Our finding that lower pretreatment anti-HBs titer (≤ 100 mIU/ml) is a risk factor for loss of anti-HBs, is consistent with a study of rituximab-based therapy for lymphoma [ 14 ]. Moreover, baseline anti-HBs positivity was protective against HBV reactivation among patients with HBsAg−/anti-HBc+ serostatus who received immunosuppressive or biologic agents [ 9 , 10 , 11 , 12 , 13 , 14 ]. Therefore, our results suggest that anti-HBs may be lost during/after immunosuppressive/biologic therapy, especially in people with a low baseline titer, with consequently elevated risk of HBV reactivation.

Although we detected no cases of morbid viremia and just one occurrence of minimal HBV DNA during follow-up, this was not necessarily inconsistent with evidence that anti-HBs negativity increases the risk of HBV reactivation in patients with HBsAg−/anti-HBc+ serostatus. Anti-HBs may remain persistently low or negative during treatment, with HBV DNA detected periodically but without progression to morbid reactivation [ 5 , 6 , 11 , 12 ]. Reported rates of HBV DNA manifestation during/after immunosuppressive therapy in patients with HBsAg−/anti-HBs−/anti-HBc+ serostatus are in the order of 1–10%, with symptomatic reactivation in a smaller fraction of cases [ 9 , 10 , 11 , 12 ]; therefore, 23 cases may have been too few to detect occasional reactivation events. The follow-up duration (median 30 months after anti-HBs loss) may also have been insufficient. HBV DNA in such patients usually appears late, after several cycles of therapy have diminished anti-HBs to undetectable levels [ 6 ], and clinical reactivation may not occur until several years since commencing immunosuppressive therapy [ 10 , 11 , 12 ]; median time from starting immunosuppressive therapy to HBV reactivation in a cohort of 1042 rheumatic disease patients with resolved HBV infections was 66 months [ 12 ]. However, 18/23 cases in our study had total follow-up of < 66 months.

This is the first indication of which we know that chronic kidney disease might be a risk factor for loss of anti-HBs in patients treated with biologic DMARDs. This is an important contemporary issue because chronic kidney disease is prevalent among patients with rheumatic diseases, consequent to older age, diabetes-related nephropathy, and widespread use of nephrotoxic medications such as non-steroidal anti-inflammatory drugs or cyclosporine. Studies have shown that patients with chronic kidney disease lose anti-HBs faster than healthy subjects do [ 21 , 22 ]; anti-HBs loss in chronic kidney disease or dialysis patients has been attributed to diminished interleukin-2 secretion, impaired macrophage function, decreasing memory B cell counts, and a weak amnestic response [ 23 , 24 , 25 ].

Consistent with reports of increased likelihood of anti-HBs loss in patients with diabetes mellitus [ 26 , 27 ], we found a significant association in univariate analysis; however, statistical significance was lost in multivariate analysis, probably because only 4/23 cases had diabetes.

Previous guidelines or reviews have propounded baseline anti-HBs screening prior to using biologic DMARDs, because patients with baseline anti-HBs− serostatus have higher risk of HBV reactivation [ 1 , 5 , 7 , 8 ]. However, current guidelines, particularly those focused on biologic DMARDs users, neither describe nor elucidate the potential risk of anti-HBs loss during biologic DMARDs therapy [ 2 , 5 , 8 ]. Our results imply that there is a window of opportunity to prevent morbid HBV reactivation in patients at increased risk. We contend that clinicians should closely monitor patients with low baseline anti-HBs titer (≤ 100 mIU/ml) and/or chronic kidney disease during subsequent biologic DMARDs therapy, including follow-up of anti-HBs and HBV DNA titers upon anti-HBs loss, to enable timely intervention with appropriate prophylaxis to preempt potential HBV reactivation. Expert opinion supports this approach; for example, advocating HBV follow-up and immunization to reduce the risk of reactivation during anti-TNF treatment [ 4 ].

This study had limitations, foremost the small sample size. With few cases or control group patients with chronic kidney disease, the result of multivariate analysis could reflect over-fitting, as the wide confidence interval suggests; larger-scale studies are warranted to corroborate this novel but tentative finding. We acknowledge that direct serum HBV DNA assays are the ideal way to monitor patients at risk of HBV reactivation; nevertheless, based on our findings, monitoring patients with risk factors for anti-HBs loss may be a convenient and cost-effective way of targeting hepatitis B prevention, especially in HBV-endemic regions. Admittedly, only direct monitoring can detect HBV reactivation due to immune-escape HBsAg mutations in anti-HBs+ biologic DMARDs recipients; however, this is a very rare phenomenon [ 28 , 29 ] and, excepting such cases, detectable HBV DNA loads in anti-HBs+ patients otherwise occur only sporadically, and are self-limiting and clinically benign [ 11 ]. Despite considerable research into whether or not the risks of anti-HBs loss or HBV reactivation differ between biologic DMARDs, results to date have been inconclusive [ 30 , 31 ]; with only 23 cases, we were unable to ascertain whether individual biologic DMARDs carried similar risks of anti-HBs loss.

This prospective single-center study found that lower baseline anti-HBs titer (≤ 100 mIU/ml) and chronic kidney disease strongly predicted loss of anti-HBs in patients having biologic DMARDs therapy for rheumatic diseases. These insights can be applied to identify patients at increased risk of becoming anti-HBs− and monitor them for potential HBV reactivation from the onset of biologic DMARDs therapy. More research is needed to elucidate other risk factors for loss of anti-HBs and so refine the monitoring strategy to prevent HBV reactivation in patients receiving biologic DMARDs to treat rheumatic diseases.

Availability of data and materials

The datasets used and/or analysed during this study are available from the corresponding author on reasonable request.

Abbreviations

Hepatitis B virus

HBV surface antigen

Antibody to HBV core antigen

Antibody to HBV surface antigen

Deoxy-ribonucleic acid

Tumor necrosis factor inhibitor

Disease-modifying anti-rheumatic drug

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Acknowledgements

David Neil, of Dr. Word Ltd., Taiwan, provided professional editorial services, which were funded by Dr Ying-Ming Chiu. Ya-Chu Yang provided technical assistance with laboratory work.

No specific funding was received from any funding bodies in the public, commercial, or not-for-profit sectors to carry out the work described in this report.

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MHH made substantial contributions to conceiving and designing the study, analyzing and interpreting data, and drafting the manuscript. YMC made substantial contributions to conceiving and designing the study, analyzing and interpreting data, and critical revision of the manuscript for intellectually important content. YCT was involved in revising the manuscript. All authors had full control of all primary data, read and approved the final article, and agree to be accountable for all aspects of the work described.

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Hung, MH., Tien, YC. & Chiu, YM. Risk factors for losing hepatitis B virus surface antibody in patients with HBV surface antigen negative/surface antibody positive serostatus receiving biologic disease-modifying anti-rheumatic drugs: a nested case-control study. Adv Rheumatol 61 , 22 (2021). https://doi.org/10.1186/s42358-021-00173-9

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  • Hepatitis B virus (HBV)
  • HBV surface-antigen negative/surface antibody positive (HBsAg−/anti-HBs+)
  • Rheumatic diseases
  • Biologic disease-modifying anti-rheumatic drug (DMARD)
  • Anti-HBs loss
  • Chronic kidney disease

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nested case control study and hepatitis

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Nested case-control study: hepatocellular carcinoma risk after hepatitis B surface antigen seroclearance.

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  • Gounder PP 1
  • Bulkow LR 1
  • McMahon BJ 1, 2
  • Snowball M 2
  • Simons BC 2
  • Spradling PR 3

Alimentary Pharmacology & Therapeutics , 08 Apr 2016 , 43(11): 1197-1207 https://doi.org/10.1111/apt.13621   PMID: 27061300  PMCID: PMC5053330

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Abstract 

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Nested Case-Control Study: Hepatocellular Carcinoma Risk After Hepatitis B Surface Antigen Seroclearance

Prabhu p. gounder.

1 Arctic Investigations Program, Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Disease, Centers for Disease Control and Prevention (CDC), Anchorage, Alaska

Lisa R. Bulkow

Mary snowball.

2 Liver Disease and Hepatitis Program, Alaska Native Tribal Health Consortium, Anchorage, Alaska

Susan Negus

Philip r. spradling.

3 Division of Viral Hepatitis, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, CDC, Atlanta, Georgia

Brenna C. Simons

Brian j. mcmahon.

Hepatocellular carcinoma (HCC) risk after resolving chronic hepatitis B virus (HBV) infection is unclear.

To compare HCC risk between Alaska Native (AN) patients with and without hepatitis B surface antigen (HBsAg) seroclearance.

We selected persons with (case-patients) and without (control-patients) HBsAg seroclearance from a cohort of 1,346 chronically HBV-infected AN patients followed during 1982–2013. We attempted to match 2 control-patients/case-patient on sex, HBV genotype, and age. Person-years of follow-up for case-patients began on the date of HBsAg resolution and for control-patients began on the date equivalent to the cohort entry date plus the years of HBsAg duration for their corresponding case-patient. We compared HCC risk using a Cox proportional hazards model.

The 238 case-patients (4 with HCC) and 435 control-patients (9 with HCC) were similar in age (p-value [p]: 0.30), sex (p: 0.53) and HBV genotype (p: 0.99). Case-patients had longer person-years of follow-up than control patients (11.7 versus 10.1 years; p: 0.04). The HCC rate/100,000 persons was similar between case- (132) and control-patients (178; p: 0.65). The adjusted hazard ratio comparing case- and control-patients was similar for HCC (0.7; 95% confidence interval [CI]: 0.2–2.4), increased for each 1-year increment for age (1.1; CI: 1.0–1.1; p <0.01), and was greater if the initial HBeAg was positive (3.5; CI: 1.1–11.0; p: 0.03).

HBsAg seroclearance was not associated with reduced HCC risk; the HCC risk estimates are limited by wide CIs. Persons meeting HCC surveillance indications prior to HBsAg seroclearance could benefit from continued surveillance after seroclearance.

  • INTRODUCTION

Approximately 248 million persons worldwide have chronic hepatitis B virus (HBV) infection ( ​ (1). 1 ). Persons with chronic HBV infection are at increased risk for cirrhosis and hepatocellular carcinoma (HCC) ( 2 ). Depending on genotype, 0.5-2% of HBV infected persons will clear hepatitis B surface antigen (HBsAg) annually ( 3 - 5 ). The American Association for the Study of Liver Diseases HCC practice guidelines state that HCC surveillance is cost-effective in populations where the HCC incidence exceeds 0.2%/year. No recommendations for HCC surveillance exist for persons with spontaneous HBsAg seroclearance because of conflicting data on HCC risk in this population ( 6 ).

Demographic and Clinical Characteristics of Case-Patients (Persons With HBsAg Seroclearance) and Matched Control-Patients (Persons Without HBsAg Seroclearance) Selected from a Cohort of HBV-Infected Alaska Native Persons Followed During 1982–2013 a

Symbols and abbreviations: --, not available; +HBeAg, serology positive for hepatitis B e antigen serum; +HBsAg, serology positive for hepatitis B surface antigen; anti-HBs, antibody to HBsAg; HBV, hepatitis B virus; Max, maximum; Min, minimum; No., number

Previous studies evaluating HCC risk after HBsAg seroclearance have reached diverging conclusions ( 7 - 10 ). Reasons for the variation in reported HCC risk include differences in the predominant circulating genotype (HCC risk varies with genotype)( 11 ), study design (clinic-based versus population-based cohort), and lack of uniform follow-up after HBsAg seroclearance (since time of seroclearance is unknown for persons in some studies). In addition, those previous studies included the years of follow-up prior to HBsAg clearance when calculating the HCC incidence among persons who resolve HBsAg. Recent evidence indicates that the eventual risk for developing HCC might be substantially influenced by factors early in the course of disease such as the HBV DNA level at the time of diagnosis ( 10 , 12 ). Therefore, restricting the HCC risk analysis to the time period after HBsAg seroclearance can provide a more precise estimate of the effect of HBsAg seroclearance on the subsequent risk for HCC.

During 1982–1987, 53,000 AN persons representing 84% of the Alaska Native (AN) population in Alaska were tested for HBsAg as part of a statewide HBV vaccination campaign ( 13 ). All persons testing positive for HBsAg during/after the vaccination campaign were provided healthcare through the Alaska Tribal Health System (ATHS) and offered HCC surveillance regardless of age or risk factors ( 14 ). Previous studies of this cohort of AN HBV carriers have documented an HBsAg seroclearance rate of 0.5–0.7%/year ( 5 , 15 ). We conducted a nested case-control study among this cohort of HBV-infected AN persons to compare the risk for developing HCC after HBsAg seroclearance with the risk for HCC among persons who did not clear HBsAg. We specifically aimed to evaluate the HCC risk only during the time period after HBsAg seroclearance for case-patients or the equivalent time period of time for control-patients.

  • PATIENTS AND METHODS

Study population

There were approximately 143,000 AN persons in Alaska in 2013 ( 16 ). All AN persons with chronic HBV, defined as having two positive HBsAg results >6 months apart, have been entered into an HBV clinical registry maintained by the ATHS. The clinical registry helps track when patients are due for routine screening exams and records clinical outcomes. Persons newly diagnosed with chronic HBV infection were continuously added to the clinical registry. Additionally, the names of newly diagnosed patients with HBV infection were cross-referenced with the Alaska Area Specimen Bank, which contains >266,000 biological specimen from persons who participated in research studies dating back to 1961 ( 17 ); if serum specimen from these persons were located, it was tested for HBsAg to more precisely estimate the date of infection.

Case- and control-patients

We selected case- and control-patients from among HBV registry patients who were followed during 1982–2013 and consented to participate in study ( Figure 1 ) ( 5 , 13 , 15 ). Case-patients were defined as persons with HBsAg seroclearance and control-patients as persons without HBsAg clearance. We attempted to match two control-patients for each case-patient on sex, HBV genotype, and age group at cohort entry (control age group ±2.5 years if case aged <30 years, ±7.5 years if case aged 30–50 years, and ±10 years if case aged ≥50 years). For a cohort person to be eligible for selection as a control-patient, the documented HBsAg duration must have been at least as long as their corresponding case-patient’s HBsAg duration. Because this study used data from an observational clinical cohort, rather than a prospective cohort designed specifically to study HCC in HBV-infected persons, the presence of other risk factors for HCC, such as hepatitis C virus (HCV)-coinfection, diabetes mellitus, family history of HCC, or non-alchoholic steatohepatitis ( 18 - 21 ), were not comprehensively documented for study participants not developing HCC. Therefore, we were unable to exclude HBV-infected patients with other risk factors for HCC from analysis.

nested case control study and hepatitis

Abbreviations: AN, Alaska Native; HBsAg, hepatitis B surface antigen; HBV, hepatitis B virus; HCC, hepatocellular carcinoma

a Case-patients (persons with HBsAg seroclearance) and control-patients (persons without HBsAg seroclearance) were selected from a cohort of 1,346 chronically HBV-infected AN persons; matched two control-patients for each case-patient on sex, HBV genotype, and age group at cohort entry (control age group ±2.5 years if case aged <30 years, ±7.5 years if case aged 30–50 years, and ±10 years if case aged ≥50 years)

b Cohort patients without HBsAg seroclearance who were not followed for at least as long as corresponding case-patient’s HBsAg duration were ineligible for selection as control-patients

c Person years of follow-up for calculating HCC incidence began on case-patient’s HBsAg seroclearance date (time = 0) or the corresponding number of years after cohort entry for control-patients; years of follow-up shaded in gray were excluded for calculating HCC incidence.

Laboratory testing

All AN persons with chronic HBV infection in the clinical registry were reminded semiannually by mail to go to their clinical provider for a blood draw. The sera were sent to the Alaska Native Medical Center in Anchorage, Alaska for testing. Since 1982, sera have been tested for HBsAg and alpha-fetoprotein (AFP) semiannually, and for hepatitis B e antigen (HBeAg) and antibody to HBe (anti-HBe) annually. Beginning in 2001, sera were also tested for liver function tests semiannually, including aspartate and alanine aminotransferase (AST and ALT, respectively) levels, and to obtain a baseline HBV DNA level and HBV genotype. The HBV DNA level was repeated every 6–12 months for persons with a baseline HBV DNA level >2,000 IU/mL, a family history of HCC, or if aminotransferase levels were elevated. We tested for HBeAg, anti-HBe, antibody to HBsAg (anti-HBs), antibody to hepatitis B core antigen (anti-HBc), and HBV DNA using commercially available assays as previously described ( 5 , 22 ). Complete blood count, which includes a platelet count, was not routinely requested because of specimen instability associated with the time required to transport specimen from certain rural Alaskan villages to the Alaska Native Medical Center for testing.

Identification of persons with HCC

Most AN persons with HCC were initially detected by the ATHS HCC surveillance program. Because many AN persons live in small rural Alaskan communities that are inaccessible by road and without ultrasound capability, the ATHS has offered HCC surveillance to all AN persons with chronic HBV infection by semiannual AFP measurements. The AFP threshold for referring for liver imaging was >25 ng/mL during 1982–1992 and was reduced to >15 ng/mL beginning in 1993, and >10 ng/ml after 2000. Persons with an elevated AFP, a family history of HCC, or cirrhosis were also offered diagnostic liver imaging by ultrasound or computed tomography. All persons with radiologic findings concerning for HCC were offered further evaluation/treatment at the Alaska Native Medical Center; histologic confirmation of HCC was available for persons who received a biopsy/surgical resection of their tumor. Persons who declined biopsy/resection of their liver lesion were diagnosed with HCC based on their clinical presentation, including an elevated AFP level, and compatible findings on radiographic imaging. We likely captured all HCC cases in the study population because all patients received care at the Alaska Native Medical Center. To ensure no study patients were diagnosed/treated for HCC at another hospital in Alaska, we cross-referenced the names of study patients with the Alaska Native Tumor Registry, a National Cancer Institute Surveillance, Epidemiology and End Results Program registry in operation since 1969 ( 23 ).

Statistical analysis

Demographic and clinical characteristics between case- and control-patients were compared by using the Wilcoxon rank-sum test for ordered variables, and chi-squared or Fisher’s exact test for categorical variables. Median values are reported with 25 th and 75 th percentiles (Q 1 -Q 3 ). Person-years of follow-up for case-patients began on the date of HBsAg resolution ( Figure 1 ). The equivalent time zero to mark the start of control-patient’s person-years of follow-up began on the date equivalent to the control-patient’s cohort entry date plus the years of HBsAg duration for their corresponding case-patient. We estimated the date of HBsAg resolution as the midpoint between the last HBsAg-positive and the first HBsAg-negative test. Person-years of follow-up ended for case- and control-patients on the date of HCC diagnosis, death, or end of study period. Case-patients without at least one matching control-patient were excluded from analysis. Patients who are simultaneously positive for HBeAg and anti-HBe are considered HBeAg-positive for analysis. The initial HBeAg test was defined as the first test done after cohort entry and the final HBeAg test was defined as the last test done before end of follow-up. The duration of HBeAg positivity was defined as the difference between the first and last positive HBeAg test results.

We calculated the unadjusted HCC rate/100,000 person-years by dividing the total number of HCC tumors in case- and control-patients by their respective person-years of follow-up after time zero. We compared the HCC rate between case- and control-patients by using a Cox proportional hazards model that adjusted for exact age and initial HBeAg status (the first recorded HBeAg level after cohort entry).

Analysis was conducted with STATA 10. P-values [p] <0.05 were considered statistically significant, and all tests were two-sided.

Human subjects review

This study was approved by the Institutional Review Boards of the Alaska Area and the Centers for Disease Control and Prevention. It also received review and approval by the Alaska Native Tribal Health Consortium.

Study Cohort Characteristics

A total of 1,346 chronically HBV-infected AN persons were enrolled in the study cohort during 1982–2013. Among cohort persons, 58% (782) were male, the median age at cohort entry was 23 years (minimum–maximum years: 0–87), 35% (476/1,343) and 4% (53/1,343) had a positive HBeAg result on the initial and final tests, respectively, 19% (254) had HBsAg seroclearance, 4% (51) developed HCC, and 34% (460) died (all-causes; proportion liver-related unknown).

Characteristics of Case- and Control-Patients

We identified 435 matched control-patients, who remained HBsAg-positive throughout the follow-up period, for 238 case-patients, who had HBsAg seroclearance (41 case-patients had only one matching control-patient); we excluded from analysis 16 case-patients without any matching control-patients ( Table 1 ). There were no significant differences between case- and control-patients with respect to the matching criteria of age, sex, and HBV genotype ( Table 1 ). Case-patients were followed for a median of 28.9 years (Q 1 -Q 3 : 24.4–30.2 years) prior to HBsAg clearance and matched to control-patients who were followed for at least a median of 28.9 years (Q 1 -Q 3 : 20.7–30.3 years). Case-patients were followed for a median of 11.7 years (Q 1 -Q 3 : 6.5–18.3 years) after HBsAg clearance; the equivalent median years of follow-up for control-patients was 10.1 years (Q 1 -Q 3 : 4.8–17.9 years). Case- compared with control-patients were less likely to have an initial positive HBeAg result (22% versus 37%; p <0.01) and less likely to have received antiviral therapy for HBV infection (1% versus 7%; p <0.01). The two case-patients who received antiviral therapy were treated with lamivudine for immune active HBV infection, which possibly facilitated HBsAg seroclearance; an additional five case-patients were placed on antiviral therapy after HBsAg seroclearance ahead of planned immunosuppressive therapy. Case- and control-patients were similar in terms of the percentage that died during follow-up (28% versus 33%) and the percentage with HCV coinfection (4% versus 3%). Among the patients selected for the nested case-control study, three had HIV coinfection (one control-patient, one case-patient before HBsAg seroclearance, and one case-patient after HBsAg seroclearance), and 13 developed HCC (four case-patients and nine control-patients). An additional two cohort patients developed HCC prior to HBsAg seroclearance; these patients were not included as case-patients because person-years of follow-up for this analysis began after HBsAg seroclearance. There were no significant differences between case- and control-patients developing HCC in terms of the percentage that died (100% versus 78%), had HCV-coinfection (25% versus 11%), had cirrhosis at time of HCC diagnosis (25% versus 63%), or a family history of HCC (0% versus 50%). The specific characteristics of the 13 case- and control-patients who developed HCC are detailed in Table 2 .

Characteristics of Case-Patients (Persons With HBsAg Seroclearance) and Control-Patients (Persons Without HBsAg Seroclearance) Who Developed Hepatocellular Carcinoma (HCC)

Abbreviations: ALT, alanine aminotransferase; HBeAg, hepatitis B e antigen; HBsAg, hepatitis B surface antigen; HBV, hepatitis B virus; HCV, hepatitis C virus; N/A, not applicable; Neg, negative; Pos, positive. Note: No patients with HCC had autoimmune hepatitis

A platelet count necessary to calculate an aspartate aminotransferase–to-platelet ratio index (APRI), a non-invasive marker for liver fibrosis, was available for 131 (55%) case-patients and 258 (59%) control-patients ( 24 ). Among case-patients with an APRI, 88% had an index <0.5, 9% had an index 0.5–1.5, and 2% had an index >1.5. Among control-patients with an APRI, 81% had an index <0.5, 14% had an index 0.5–1.5, and 5% had an index >1.5. A FIB-4 index, another non-invasive liver fibrosis marker calculated using platelets, alanine aminotransferase, aspartate aminotransferase, and patient age, was available for 131 (55%) case-patients and 256 (59%) control-patients ( 25 ). Among case-patients with a FIB-4 index, 69% had an index <1.45, 24% had an index 1.45–3.25, and 7% had an index >3.25. Among control-patients with a FIB-4 index, 71% had an index <1.45, 19% had an index 1.45–3.25, and 10% had an index >3.25. There was no difference between case- and control-patients in the percentage of patients with an APRI >1.5 versus ≤1.5 (p: 0.19) or in the percentage with a Fib4 score >3.25 versus a score ≤3.25 (p: 0.34).

Hepatocellular Carcinoma Rate

The HCC rate/100,000 persons was similar between case-patients with HBsAg seroclearance (132; 95% confidence interval [CI]: 36–338) and control-patients without HBsAg seroclearance (178; CI: 81–338). The risk for HCC did not differ significantly between case- and control-patients in the multivariable Cox proportional hazards model (adjusted hazard ratio [aHR]: 0.7; CI: 0.2–2.4). The risk for HCC was associated with greater age at cohort entry (aHR for each 1-year increment: 1.1; CI: 1.0–1.1; p <0.01) and having a positive initial HBeAg result compared with a negative result (aHR: 3.5; CI: 1.1–11.0).

HBV DNA and ALT Levels

The distribution (statistical spread of values) of HBV DNA levels among case-patients was compared with control-patients at time periods before and after HBsAg seroclearance ( Table 3 ). At least one HBV DNA measurement was available for 97% of case-patients (median: 2 measurements; Q 1 -Q 3 : 1–4 measurements) and 82% of control-patients (median: 3 measurements; Q 1 -Q 3 : 1–6); the time periods for aggregating HBV DNA measurements were selected to optimize sample size for analysis. There was no difference in the distribution of the HBV DNA level between case- and control-patients ≥9 years prior to HBsAg seroclearance (p: 0.39) and <9 years prior to HBsAg seroclearance (p: 0.12). The HBV DNA level was lower among case-patients compared with control-patients <9 years after HBsAg seroclearance (median: 0 versus 212 IU/mL; % with HBV DNA >0 IU/mL: 40% versus 87%; % with HBV DNA >2,000 IU/mL: 1% versus 28%; p <0.01) and ≥9 years after HBsAg seroclearance (median: 0 versus 259 IU/mL; % with HBV DNA >0 IU/mL: 48% versus 92%; % with HBV DNA >2,000 IU/mL: 2% versus 29%; p <0.01). Among the 98 case-patients followed for ≥9 years after HBsAg seroclearance, 95% (93) were anti-HBs positive on the last serum specimen tested before end of follow-up and 51% (47) had detectable HBV DNA. The 5 case-patients who were followed for ≥9 years after HBsAg seroclearance and remained anti-HBs negative also had detectable HBV DNA on their final serum sample tested before end of follow-up.

Hepatitis B Virus (HBV) DNA Level Relative to Case-Patient Hepatitis B Surface Antigen (HBsAg) Seroclearance Date a

Abbreviations: No., number of patients contributing an HBV DNA result during the specified follow-up time period

We also compared the distribution of ALT levels among case-patients with control-patients at time periods before and after HBsAg seroclearance ( Table 4 ). The ALT level was similar between case- and control-patients ≥9 years prior to HBsAg seroclearance (p: 0.39) and <9 years prior to HBsAg seroclearance (p: 0.99). The ALT level was lower among case-patients compared with control-patients <9 years after HBsAg seroclearance (p <0.01) and ≥9 years after HBsAg seroclearance (p: 0.03).

Alanine Aminotransferase (ALT) Level Relative to Case-Patient Hepatitis B Surface Antigen (HBsAg) Seroclearance Date a

Abbreviations: IQR, interquartile range; No., number of patients contributing an ALT result during the specified follow-up time period

  • CONCLUSIONS

Previous studies evaluating the risk for HCC associated with HBsAg loss have included the time during which persons were seropositive for HBsAg in calculating the HCC rate ( 3 , 7 , 9 , 10 ). Our study is unique because we attempted to isolate the effect of HBsAg seroclearance on subsequent risk for developing HCC. The results indicate that HBsAg seroclearance was not associated with reduced risk for HCC. Although the small number of persons who developed HCC limits the strength of our conclusion, our case- and control-patients were sampled from one of the largest and longest followed population-based cohorts of persons with HBV infection in the world. As a result, this present study includes more persons with resolved HBsAg (including those who developed HCC) than similar previous studies that have evaluated the risk of HCC after resolving HBV infection ( 3 , 8 , 9 , 26 ). Because it is unlikely a more precise estimate of HCC risk following HBsAg seroclearance can be obtained in the near future, it would be reasonable to offer HCC surveillance after HBsAg seroclearance for persons meeting AASLD practice guidelines criteria for surveillance prior to resolving HBV infection ( 6 ).

Cirrhosis is an important risk factor for developing HCC among persons with chronic HBV infection. The presence of cirrhosis was not comprehensively known for our study participants who did not develop HCC in part because many patients lived in rural communities without ready access to liver biopsy capable facility. Therefore, we were unable to match case- and control-patients according to their cirrhosis status. For the subset of case- and control-patients with APRI and Fib4 available, we are reassured that there was no difference between the two groups in the proportion with advanced liver fibrosis as measured by these noninvasive makers. Furthermore, knowing the cirrhosis status only for case-patients who developed HCC still provides insights into the risk for HCC. Unlike previous studies where the majority of patients who developed HCC after resolving chronic HBV infection had cirrhosis at the time of HBsAg seroclearance ( 3 , 9 , 26 ), only one out of the four case-patients with HCC in our study had cirrhosis. However, the other three case-patients without cirrhosis would have met AASLD age/sex criteria for continuing HCC surveillance after HBsAg seroclearance ( 6 ).

The reasons for why HBsAg seroclearance was not associated with reduced HCC rate are unknown but likely multifactorial. It is possible that factors early in the course of HBV infection, such as the HBV DNA level or degree of hepatic necroinflammation, might have had a greater influence on HCC risk ( 10 , 12 , 27 ). We compared the distribution of HBV DNA level for the time periods before and after HBsAg seroclearance among case-patients and for the corresponding time periods among control-patients. The lack of difference in HCC rate between case- and control-patients corresponds with the similarity in HBV DNA levels among case-patients compared with control-patients before HBsAg clearance. These results support previous reports that the HBV DNA level before HBsAg seroclearance is an important predictor for developing HCC ( 10 , 12 ). It is likely for that reason that treatment with nucleos(t)ide analogues decreases both the risk for developing HCC and the risk of HCC recurrence after surgical resection ( 28 - 31 ). One mechanism by which HBV infection causes HCC could be through the integration of HBV DNA into the host hepatocyte genome and as covalently closed circular (ccc) DNA in hepatocyte nuclei ( 27 , 32 ). The integrated viral DNA and cccDNA that result from HBV viremia persist after HBsAg seroclearance and might promote the development of HCC. Furthermore, a substantial proportion of case-patients in our study had a detectable HBV DNA level after HBsAg seroclearance. Thus, it is possible that ongoing low-level HBV DNA replication with continued integration into the host hepatocyte also contributes to the persistent HCC risk after HBsAg seroclearance.

Additionally, the degree of HBV-associated hepatic inflammation, which can be assessed by measuring ALT levels, correlates with the risk for developing HCC ( 27 ). The ALT level before HBsAg seroclearance was similar among case-patients compared with control-patients. The ALT level together with the HBV DNA level indicates that the majority of case- and control-patients were in the immune-inactive phase of HBV infection prior to HBsAg seroclearance. Results from this present study confirm previous evaluations in this cohort demonstrating that most patients with chronic HBV infection are HBeAg-negative and remain in the immune-inactive phase after HBeAg clearance ( 33 , 34 ). The lack of difference in the degree of hepatic inflammation between case- and control-patients prior to HBsAg could also partly account for the lack of association between HBsAg seroclearance and reduced HCC risk.

Our adjusted analysis indicates that the initial HBeAg status and increasing age at cohort entry were associated with HCC risk. The presence of HBeAg, indicating immune-active phase of disease, is associated with high HBV DNA levels and intermittent ALT elevations ( 35 ). Therefore, HBeAg seropositivity could be associated with increased risk for HCC because it is a surrogate marker for HBV DNA level and hepatic inflammation ( 7 , 36 ). Our adjusted analysis also confirmed results from previous studies indicating that increasing age in HBV-infected persons is a risk factor for HCC ( 2 , 37 , 38 ). Although the exact date of HBV infection is unknown for patients in our study, it is likely that most patients acquired HBV infection in early childhood or at birth ( 39 ). Thus, the age at cohort entry probably correlates with the duration of infection for most study patients. Since our control-patients were matched with case-patients on age and duration of follow-up, the results additionally suggest that increasing age might be a risk factor for HCC independent of duration of HBV infection.

This study has limitations. First, our HCC risk estimates had wide confidence intervals because few case- and control-patients developed HCC. Thus, we could have failed to detect a real reduction in HCC risk associated with HBsAg seroclearance because of insufficient statistical power. It is important to note, however, that both HBsAg seroclearance and development of HCC are rare events, and our study has more persons with HBsAg seroclearance and HCC than other similar studies ( 3 , 8 - 10 , 26 ). Furthermore, it is important to note that the HCC incidence for a population cannot be calculated in a case-control study since the number of cases and controls are prespecified. The HCC rates we present allow for comparing the HCC risk between groups in this paper, but the absolute rates cannot be compared with the HCC incidence reported elsewhere. Additionally, the presence of other HCC risk factors, such as HCV-coinfection, family history of HCC, diabetes mellitus or fatty liver disease ( 18 - 20 ), was not comprehensively known for our study participants not developing HCC. As a result, we could not adjust for several important HCC risk factors in our model comparing the HCC rate between case- and control-patients. We did demonstrate, however, that case- and control-patients were similar in terms of certain key risk factors, such proportion with HCV-coinfection, HBV DNA level, hepatic inflammation as measured by ALT levels, and liver fibrosis as measured by APRI and Fib4. Finally, our results based on the AN population might not be generalizable to other populations. The risk for HCC varies by HBV genotype ( 11 ); AN persons infected with genotypes C and F have a higher incidence of HCC compared with persons infected with other genotypes ( 22 ). Differences in the prevalence of HBV genotypes between those found in AN persons compared with other geographic regions of the world could affect the incidence of HCC observed between persons with and without HBsAg seroclearance.

The goals of HBV treatment are to reduce the risk of developing cirrhosis, liver decompensation, and HCC. Therapy for HBV infection is indicated for patients in the immune-active phase but not for patients in the immune-inactive phase of HBV infection ( 40 ). Most patients in our study were in the immune-inactive phase of infection and did not receive HBV therapy. However, study patients were still at high risk for developing HCC and HBsAg seroclearance did not reduce the HCC risk. Given the effectiveness of nucleos(t)ide analogues in reducing HCC risk for persons with elevated HBV DNA levels ( 30 ), further research to better understand the factors early in the course of infection that predict future risk for developing HCC risk could help to identify a subset of immune-inactive patients who might benefit from early treatment.

  • Acknowledgments

Financial Support: This work was supported by the Centers for Disease Control and Prevention, NCHHSTP, Division of Viral Hepatitis (CA# 1U01PS004113).

  • Abbreviations

Conflict of interest: None of the authors have any conflicts to disclose.

Guarantor of article: PPG

Author contributions: BJM conceived the study question, interpreted data, and drafted manuscript. PPG designed the study, analyzed/interpreted data, drafted/revised manuscript. LRB designed study, conducted data analysis, interpreted results, and critical reviewed manuscript. MS, SN, PRS, and BSP contributed to the data acquisition and critically reviewed manuscript. All authors approve the final version of the manuscript, including authorship list, and assume responsibility for the accuracy/integrity of the work.

Disclaimer: The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.

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nested case control study and hepatitis

Apr 08 2016

  • Source: Aliment Pharmacol Ther. 43(11):1197-1207.
  • Alternative Title: Aliment Pharmacol Ther
  • Personal Author: Gounder, Prabhu P. ; Bulkow, Lisa R. ; Snowball, Mary ; Negus, Susan ; Spradling, Philip R. ; ... More + Gounder, Prabhu P. ; Bulkow, Lisa R. ; Snowball, Mary ; Negus, Susan ; Spradling, Philip R. ; Simons, Brenna C. ; McMahon, Brian J. Less -
  • Description: Background Hepatocellular carcinoma (HCC) risk after resolving chronic hepatitis B virus (HBV) infection is unclear. Aim To compare HCC risk between Alaska Native (AN) patients with and without hepatitis B surface antigen (HBsAg) seroclearance. Methods We selected persons with (case-patients) and without (control-patients) HBsAg seroclearance from a cohort of 1,346 chronically HBV-infected AN patients followed during 1982–2013. We attempted to match 2 control-patients/case-patient on sex, HBV genotype, and age. Person-years of follow-up for case-patients began on the date of HBsAg resolution and for control-patients began on the date equivalent to the cohort entry date plus the years of HBsAg duration for their corresponding case-patient. We compared HCC risk using a Cox proportional hazards model. Results The 238 case-patients (4 with HCC) and 435 control-patients (9 with HCC) were similar in age (p-value [p]: 0.30), sex (p: 0.53) and HBV genotype (p: 0.99). Case-patients had longer person-years of follow-up than control patients (11.7 versus 10.1 years; p: 0.04). The HCC rate/100,000 persons was similar between case- (132) and control-patients (178; p: 0.65). The adjusted hazard ratio comparing case- and control-patients was similar for HCC (0.7; 95% confidence interval [CI]: 0.2–2.4), increased for each 1-year increment for age (1.1; CI: 1.0–1.1; p Conclusions HBsAg seroclearance was not associated with reduced HCC risk; the HCC risk estimates are limited by wide CIs. Persons meeting HCC surveillance indications prior to HBsAg seroclearance could benefit from continued surveillance after seroclearance. More ▼ -->
  • Subjects: [+] Adolescent Adult Aged Aged, 80 And Over Article Cancer Screening Carcinoma, Hepatocellular Case-Control Studies Child Child, Preschool Epidemiology Female Hepatitis B, Chronic Hepatitis B E Antigens Hepatitis B Surface Antigens Hepatitis B Virus Humans Infant Liver Cancer Liver Neoplasms Male Middle Aged Proportional Hazards Models Risk Risk Factors Young Adult
  • Pubmed ID: 27061300
  • Pubmed Central ID: PMC5053330
  • Document Type: Journal Article
  • Funding: CC999999/Intramural CDC HHS/United States ; U01 PS004113/PS/NCHHSTP CDC HHS/United States CC999999/Intramural CDC HHS/United States ; U01 PS004113/PS/NCHHSTP CDC HHS/United States Less -
  • Collection(s): CDC Public Access
  • Main Document Checksum: [+] urn:sha256:f9277ba53e6c3add268082ae7e97927beb2e3746cc6d743276f819578e1c5d3a
  • Download URL: https://stacks.cdc.gov/view/cdc/42180/cdc_42180_DS1.pdf

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  • Published: 19 February 2024

Hepatitis E outbreak in the health district of Bocaranga-Koui, Central African Republic, 2018–2019

  • Marina Prisca de Marguerite Nombot-Yazenguet 1 ,
  • Joël Wilfried Doté 2 ,
  • Giscard Wilfried Koyaweda 3 ,
  • Philippe Armand Zemingui-Bembete 1 ,
  • Benjamin Selekon 4 ,
  • Ulrich Vickos 5 ,
  • Alexandre Manirakiza 6 ,
  • Emmanuel Nakoune 4 ,
  • Ionela Gouandjika-Vasilache 2 &
  • Narcisse Patrice Joseph Komas 1  

BMC Infectious Diseases volume  24 , Article number:  215 ( 2024 ) Cite this article

Metrics details

Hepatitis E virus (HEV) is a major public health disease causing large outbreaks and sporadic cases of acute hepatitis. We investigated an outbreak of HEV infection that occurred in September 2018 in the health district (HD) of Bocaranga-Koui, located in the northwestern part of Central African Republic (CAR).

Blood samples were collected from 352 patients aged 0–85 years suspected to be infected with yellow fever (YF), according to the World Health Organization YF case definition. The notification forms from recorded cases were used. Water consumed in the HD were also collected. Human samples found negative for anti-YF IgM were then tested by ELISA for anti-HEV IgM and IgG antibodies. Positive anti-HEV (IgM and/or IgG) samples and collected water were then subjected to molecular biology tests using a real time RT-PCR assay, followed by a nested RT-PCR assay for sequencing and phylogenetic analysis.

Of the 352 icterus patients included, anti-HEV IgM was found in 142 people (40.3%) and anti-HEV IgG in 175 (49.7%). Although HEV infection was detected in all age groups, there was a significant difference between the 0–10 age groups and others age groups ( P  = 0.001). Elevated levels of serum aminotransferase were observed in anti-HEV IgM-positive subjects. Phylogenetic analysis showed HEV genotype 1e in infected patients as well as in the contaminated water.

This epidemic showed that CAR remains an HEV-endemic area. The genotype 1e strain was responsible for the HEV outbreak in Bocaranga-Koui HD. It is necessary to implement basic conditions of hygiene and sanitation to prevent further outbreaks of a HEV epidemics, to facilitate access to clean drinking water for the population, to launch intensive health education for basic hygiene measures, to sett up targeted hygiene promotion activities and, finally, to ensure that formal health care is available.

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Introduction

Hepatitis E virus (HEV) is a major public health disease causing large outbreaks and sporadic cases of acute hepatitis. It is estimated that one-third of the world’s population is living in an HEV endemic area [ 1 , 2 ]. HEV is the most common cause of acute viral hepatitis, in both resource-poor and wealthy countries [ 3 ]. HEV is a spherical, non-enveloped, single-stranded RNA virus belonging to the Hepeviridae family and the genus Paslahepevirus [ 4 ]. Although more than 8 HEV genotypes have been proposed to exist [ 5 ], four major HEV genotypes with 24 subtypes have been well described in humans [ 6 , 7 ]: i) genotypes 1 and 2, which exclusively infect humans through fecal–oral transmission, circulate predominantly in regions with low sanitary level such as Africa, Asia, Latin America and Middle Eastern countries; ii) genotypes 3 and 4 are of zoonotic origin, predominate in developed countries [ 8 , 9 ] and are globally distributed. Usually the HEV infection is self-limiting, but occasionally causes serious disease, such as fulminant hepatitis leading to neurological sequelae, spontaneous abortions, and sometimes death [ 10 , 11 ]. Several outbreaks of HEV have occurred in low-income countries, often resulting in fulminant hepatitis with a case/fatality rate between 1 and 2% in the population of young adults, and this rate can increase to 20% among pregnant women during their last trimester of pregnancy [ 12 , 13 ]. HEV is therefore potentially devastating in areas with degraded security situations, where access to essential sanitation is limited.

In September 2018, an outbreak of jaundice was notified in the health district (HD) of Bocaranga-Koui, in the northwestern part of Central African Republic (CAR) (Fig.  1 ), through the yellow fever (YF) national surveillance system (YFNSS). In this study, we report HEV infection through differential diagnosis of YF and molecular characterization of the HEV strains identified during this outbreak.

figure 1

Map showing districts reporting suspect cases, northwestern Central African Republic, 2018–2019

Materials and methods

Studied population and data collection.

Blood was collected from all individuals living in Bocaranga-Koui HD who presented with jaundice and a fever, according to the WHO YF-case definition [ 14 ]. The notification forms and blood samples were transported to the Institut Pasteur de Bangui (IPB). In addition, the clinical features observed in patients were reported by consulting physicians, and samples of water from several locations consumed by the population of these two districts were collected in sterile containers, packed with ice packs, and transported via the reverse cold chain to IPB for testing.

Water samples preparation

Collected water samples were first processed using the 2-phase separation method with Dextran T40 and PEG 6000 and then a double treatment with 20% chloroform, according to the WHO- developed protocol for poliovirus testing for concentrating water [ 15 ]. Briefly, 500 ml of the collected water was centrifuged at 1500 g at + 4 °C for 20 min. The supernatant was collected, and the pellet was kept at + 4 °C. The supernatant (pH 7.0—7.4) was mixed with polyethylene glycol (PEG 6000), Dextran T40 and NaCl 5N. This mixture was homogenized for at least one hour and then poured into a separating funnel and kept at + 4 °C overnight. The low and intermediate phases were collected in a sterile tube. The starting pellet, together with 20% chloroform and 1 g of sterile glass ball, were added to the collected phases. The mixture was vigorously shaken and then centrifuged at 1500 g for 20 min at + 4 °C. Approximately 5 ml of supernatant was collected and used for viral RNA extraction. Extracted RNA were submitted for molecular biology tests using a real time RT-PCR assay, followed by a nested RT-PCR assay for sequencing and phylogenetic analysis.

Biological and biochemistry testing

Serum samples collected during the epidemic in the Bocaranga-Koui HD through the YF surveillance that were found negative for anti-YF IgM were retrospectively tested by HEV IgM and IgG ELISA Dia.Pro kit reference EVM.CE (Diagnostic Bioprobes srl, Milan, Italy) [ 16 , 17 ] and by real-time RT-PCR, as previously described [ 18 ]. A HEV case was confirmed if the sample was positive for IgM antibodies and/or for real time RT-PCR (Fig.  2 ). Samples which were found positive for YF were discarded from our study (Fig.  2 ).

figure 2

Flow chart of HEV detection in blood samples

For the RT-PCR testing, viral RNA was extracted from 140 µl serum samples positive for HEV IgM ELISA and concentrated water samples, using QIAamp Viral RNA Mini Kit (QIAGEN, Courtaboeuf, France), and then retrotranscribed into cDNA using the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Foster City, CA, USA) according to the manufacturer's instructions. Real-time RT-PCR was carried out in 96-well plates using the TaqMan® Universal RT-PCR Master Mix Reagent (Applied Biosystems, Foster City, CA, USA), the reaction mixture contained the following ingredients: 12,5 μl of 2X PCR Master mix, 5 μl of the resulting cDNA, 1 µM for each primers and probe, and sterile water to make up the final volume of 25 µl, according to the manufacturers' recommendation. The primers and probe (10 μM) employed were: Taq HEV-F (5´-GCCCGGTCAGCCGTCTGG-3´); Taq HEV-R (5´-CTGAGAATCAACCCGGTCAC-3´); TaqHEV-S (5´-FAM- CGGTTCCGGCGGTGGTTTCT-TAMRA-3´) [ 18 ]. Real-time RT-PCR amplification was performed using an ABI PRISM® 7500 real-time PCR instrument (Applied Biosystems, Foster City, CA, USA) under the following conditions: 50 °C for 2 min and 95 °C for 10 min, followed by 45 cycles at 95 °C for 15 s and 60 °C for 1 min. A sample was considered positive if the cycle threshold ( C T ) was < 37 amplification cycles.

For all suspected cases, serum samples were analyzed for alanine aminotransferase (ALAT) and aspartate aminotransferase (ASAT) using ABX Pentra 400 (RAB1251FR).

Phylogenetic analysis

A nested RT-PCR amplifying a 348-bp portion of the open reading frame 2 region was performed as previously described [ 19 ] on RNA samples that tested positive with the real-time RT-PCR using the thermocycler Gene Amp PCR System 97,000 (Applied Biosystems). Briefly, 2 mM of each primers 3156N (5’-AATTAGCYCAGTAYCGRGTTG-3’) and 3157N (5-CCCTTRTCYTGCTGMGCATTCTC-3’) and Titan One Tube RT-PCR kit (Roche, diagnosis, Germany) were used. Cycling for the first reaction were as follows: 50 °C for 30 min, 94 °C for 2 min followed by 40 cycles of 94 °C for 30 s, 42 °C for 1 min, 68 °C for 1 min, and a final extension at 68 °C for 7 min. The second reaction was performed with 01 mM of each primers 3158N (5’GTWATGCTYATWCATGGCT-3’) and 3159N (5’- AGCCGAAATCAATTCTGTC-3’) and Taq DNA polymerase Kit (Roche, Diagnosis, Germany) were used. Cycling for the second reaction were as follows: 94 °C for 3 min, 40 cycles at 94 °C for 45 s, 42 °C for 45 s, and 72 °C for 45 s, and a final elongation step at 72 °C for 5 min. Amplified PCR products of the second reaction were separated by 3% (w/v) agarose gel electrophoresis. The amplicons were purified using QIAquick PCR Purification Kit (QIAGEN, Hilden, Germany) and then sent to GATC Biotech (Konstanz, Germany) for direct sequencing. Phylogenetic analysis of the partial ORF2 gene of HEV was conducted with MEGA7 software ( www.megasoftware.net ) and aligned by CLUSTAL Muscle algorithm. A Phylogenetic tree was constructed using the neighbour-joining method and the Kimura-2 model with 1000 bootstrap replicates using MEGA 7 [ 20 ]. HEV reference strains of genotypes/subtypes were included [ 21 ]. The sequences obtained in this study were deposited in GenBank with accession numbers MN901844 to MN901869 and MW258967 to MW258978.

Statistical analysis

Data analysis was performed using STATA version 14 (Stata Corp LP, College Station, TX, United States). Odds ratios (OR) and their respective 95% confidence intervals (CI) were calculated for each association. Pearson chi-squared or, when necessary, Fisher exact tests were used to compare distribution for categorical variables for the different groups. Statistical significance was assumed at P  < 0.05 in the univariate analysis.

Blood samples were collected from 352 people living in the Bocaranga-Koui HD, including 172 women (48.3%) and 180 men (51.7%), with a sex ratio of 1.07, aged between 0 and 85 years (mean, 22.6 years, SD ± 17.4).

The serology results reported in Table  1 shows that, by ELISA analysis, 142 people (40.3%) had HEV-positive IgM antibodies, indicating that a high proportion of the population had an ongoing HEV infection, with more infected women (43.3%) than men (38.9%). A similar observation was made in the case of HEV IgG antibodies, with 53.0% of women infected and 50.6% of men. The difference observed between genders was not statistically significant in either case ( P  = 0.39). However, the distribution of HEV serology (IgM and IgG) showed a statistically significant difference according to age group, with the 21–30-year-old age group and those over 40 years of age being significantly more positive for HEV IgM antibodies than the 0–20 year-old and 31–40 year-old groups ( P  = 0.001).

Among those who were IgM anti-HEV antibody positive, three patients (a 30-year-old pregnant woman, a 35-year-old man and a 12 month-old child) died during this epidemic.

More than 50% of patients who were anti-HEV IgM antibody positive had higher than average ALT (59.8%) and AST (71.8%) values during this epidemic (Table  1 ). Dual amplification by real-time RT-PCR and nested RT-PCR resulted in 73 (51.4%) of the 142 sera being amplified as IgM anti-HEV positive (Fig.  2 ).

The clinical characteristics and source of drinking water of patients who were anti-HEV IgM positive during this epidemic are described in Table  2 .

The clinical symptoms most frequently observed in these patients were jaundice (71.8%), followed by fever (62.6%), and other signs such as general fatigue (11.9%), abdominal pain (7.7%), dark-colored urine (7.7%), and loss of appetite (6.3%). Regarding the origin of water drunk by anti-HEV IgM antibody-positive patients, well water was the most frequently consumed (68.3%), followed by other water sources (10.5%), and the combination of well water and hand-pump water (8.4%). It should be noted that at least 7% of people who consumed only public fountain water were also found to be IgM antibody positive, and only 4% of these patients consumed only pump water. Determination of the persistence of infection in the population was measured from September 2018, considering the variation in positive anti-HEV antibodies IgM (Fig.  3 ). The highest prevalence was recorded in November, three months after the onset of the epidemic. From December 2018, prevalence fell back to a lower level and remained constant until May 2019.

figure 3

Distribution of anti-HEV IgM per month (From September 2018 to July 2019)

HEV genotyping

In total, 39 out of the 73 samples that were positive by RT-PCR and one water sample from one of the wells out of the 52 water samples used by the patients were amplified and sequenced. Phylogenetic analysis of the sequences (Fig.  4 ) showed that the HEV strains isolated from the different samples belonged to genotype 1e and were close to strains already isolated in 2008 and 2009 during previous epidemics in CAR [ 22 ].

figure 4

During the hepatitis E epidemic in the HD of Bocaranga-Koui, over 40% of sampled people were recently infected (IgM) with HEV, and 49% had already been in contact with this virus. This prevalence in patients with acute jaundice shows that hepatitis E is endemic in the CAR causing major epidemics [ 22 , 23 , 24 ].

This high prevalence is not surprising, because the Bocaranga-Koui HD is in an area of social instability, with persistent military-political conflicts that have long-term effects. In addition, the region has a very high crime rate, forcing most of the population to live in the bush or in host communities where hygiene conditions are precarious. Among those infected, more women than men carried HEV antibodies, although we found that this difference was not statistically significant. This observation has been reported in previous studies [ 25 ], in which more women than men were infected during these epidemics. In our study, this high prevalence of HEV infection among women can be explained by the fact that most household activities are carried out by women in this rebel-held health district. In addition, to avoid capture by rebels, many men have left this area for security reasons. In any case, this observation confirms that HEV infection is not inherently linked to gender, but rather because of it is waterborne and thus linked to certain professional and/or household activities [ 25 ]. The proportion of HEV cases during this epidemic varied with age, but was not significantly different. Two age groups, namely those aged 21 to 30 years old and those over 40 years old were more infected than those under 21 years old and between 30 and 40 years old. This finding may result from the fact that people 21–30 and over 40 are more active in daily activities of caring for their families and may therefore be in more frequent contact with this virus, especially during epidemics. This situation may be aggravated by insecurity in densely populated sites, where hygiene conditions are far from optimal, as previously reported [ 26 ]. Data from the UN Office for the Coordination of Humanitarian Affairs (OCHA) estimates that 146,251 people lived in this health district in 2018, and that over 25,000 are "internally displaced persons, IDPs" living in conditions of humanitarian distress. In addition, to this population are voluntary returnees from Cameroon and Chad who had taken refuge in these countries during the 2013 military-political crisis in CAR. These displaced people live under extremely precarious conditions, characterized by a lack of sanitation and hygiene services, which may account for the spread of infections from one region to another and can lead to epidemics if the population’s collective immunity is low [ 27 ].

The main risk factor for HEV contamination in this district would be drinking water. Indeed, the main sources of water consumed and used by households in this health district were untreated well water, stored rainwater, water from river springs, or the rivers themselves. The proximity of latrines to these main water sources meant that the likelihood of contamination from these sources is high, given overcrowding in the area. Indeed, the exposure to diseases among populations living in displaced persons' camps where hygiene and sanitation services are lacking has been well described in the literature [ 28 ].

Two main symptoms were reported during this epidemic, namely jaundice (71.8%) and fever (62.6%). These symptoms were similar to those reported in other HEV epidemics [ 9 ], confirming that jaundice and fever are the main symptoms of this infection in HEV-endemic areas. It is therefore important to undertake a differential diagnosis between yellow fever and HEV infection whenever these symptoms are present, so that the infection can be managed properly at an early stage.

Transaminase levels were two to five times higher than normal in HEV-infected individuals, confirming the presence of hepatic cytolysis that usually accompanies HEV infection [ 29 ].

This epidemic resulted in three deaths during the time frame of the study, giving a case-fatality rate of 0.8%. Among these deaths was a woman in her last trimester of amenorrhea who died following a spontaneous abortion, probably due to HEV infection as previously reported [ 30 ]. This is not surprising, as pregnant women constitute a high-risk group, with a mortality rate in the third trimester of pregnancy of around 20% [ 12 ]. It is likely that there were other cases of death linked to this epidemic that were not identified in this study.

The epidemic curve, based on the presence of detected HEV antibodies, enabled us to assess the intensity and duration of the epidemic. Many more people had been infected with HEV in the first three months of the epidemic, between September to December 2018, coinciding with the rainy season as reported in previous studies [ 22 ].

Molecular analysis of HEV strains, obtained from infected patients, revealed that genotype 1e was the source of contamination during this epidemic. These results from our phylogenetic analysis are consistent with previous findings regarding the subtypes circulating in the CAR [ 22 , 31 ] and neighboring countries [ 32 , 33 ], and with waterborne transmission usually associated with HEV genotypes 1 and 2. Our genotypes 1e strains formed a cluster which were close to those found in the country during the 2008–2009 outbreak and in neighboring countries [ 22 , 32 , 34 ]. Our results show that HEV evolves very little and has circulated endemically in this area for almost 15 years. This demonstrates the capacity of HEV to persist for many years in the environment and because transmission is essentially fecal–oral, to cause an epidemic under certain conditions, notably low levels of hygiene, political and social insecurity and the contamination of the water supply.

We investigated the origin of the infection by analyzing water from HD wells. The results of the molecular analysis revealed only one positive water sample from one of the wells. The most likely wells water contaminated with human, or animal feces could be a major source of the epidemic, especially because wells are the main sources of drinking water. Although we found HEV in water samples from just one well, it is likely that HEV transmission during this epidemic may have resulted from well water consumption and then amplified by direct human-to-human transmission, as previously demonstrated [ 35 ]. Fecal contamination of tap water as the source of the hepatitis E epidemic has been reported in various studies in regions where HEV is endemic [ 22 , 24 , 32 , 36 ]. The cessation of the epidemic after the distribution of non-food item (NFI) kits, the treatment of water points in the district, and awareness-raising on good hygiene and sanitation practices all support the hypothesis that fecal contamination of water was the source of this epidemic.

This epidemic showed that CAR remains an HEV-endemic area. In such regions, the eruption of an epidemic takes just a small perturbation in hygiene and sanitation conditions to trigger an HEV epidemic. The differential diagnosis of HEV/yellow fever in all cases of conjunctival icterus accompanied by fever must be carried out as a matter of urgency, to detect early cases of HEV infection, and thus to curb the onset of a hepatitis E epidemic at an early stage. However, for full operative results, it is also necessary to implement the minimum conditions of hygiene and sanitation to prevent the outbreak of a hepatitis E epidemic, to facilitate full access to clean drinking water, carry out educational campaigns on basic hygiene measures, sett up targeted hygiene promotion activities and, finally, to ensure that formal health care is available to all. All of these measures require a peaceful social and political environment.

Availability of data and materials

All data generated or analyzed during this study are included in this published article. The sequences obtained in this study were deposited in GenBank with accession numbers MN901844 to MN901869 and MW258967 to MW258978.

Abbreviations

Alanine aminotransferase

Aspartate aminotransferase

  • Central African Republic

Health district

Hepatitis E virus

Immunoglobulin G

Immunoglobulin M

Institut Pasteur de Bangui

Non Food Items

UN Office for the Coordination of Humanitarian Affairs

Odds ratios

Reverse transcriptase-polymerase chain reaction

World Health Organization

Yellow fever

Yellow fever national surveillance system

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Acknowledgements

Authors acknowledge the Ministry of public Health & population, CAR, in supporting the investigation, the World Health Organization [WHO] and the « Médecins Sans Frontières » team in CAR for providing logistic support for transporting samples to the viral hepatitis laboratory at Institut Pasteur de Bangui, Dr Brice Yambiyo for his help in statistical analysis, Dr Gilles Ngaya and the health agents of medical laboratory of the Institut Pasteur de Bangui for their help in biochemical tests. We also thank the rural communities of Bocaranga-Koui for their cooperation and are grateful to the health agents at the health district of Bocaranga and Koui for their help in blood and water sample collection. We are also grateful to Dr Marc Benhamou, Nicole Meyers and Tamara Giles-Vernick for their critical reading of the manuscript and checking the English.

WHO grant number 2021/1098759–0.

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Contributions

Conceptualization: NPJK, MPMNY, UV and EN. Data curation: MPMNY, BS, EN and NPJK. Formal analysis: MPMNY, GWK, BS, UV, AM, and NPJK. Funding acquisition: NPJK and EN. Investigation: MPMNY, PAZ, BS and NPJK. Methodology: NPJK and MPMNY. Supervision: NPJK. Writing ± original draft: MPMNY, JWD, GWK, UV, IGV and NPJK. Writing ± review & editing: All authors reviewed the manuscript.

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Correspondence to Narcisse Patrice Joseph Komas .

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Ethics approval and consent to participate.

The research was approved by the Ethics and Scientific Committee of the Faculty of Health Sciences, University of Bangui, Central African Republic (decision number N°38/UB/FACSS/IPB/CES.023) and conducted within the guidelines of the Declaration of Helsinki. Because samples were taken as part of the national surveillance of yellow fever, and that the differential diagnosis of yellow fever is hepatitis E virus infection, the informed consent of the participants was not required.

Written informed consent was waived by the « Comité Éthique et Scientifique/Faculté des Sciences, Université de Bangui/Institut Pasteur de Bangui (CES). Hence the CES gave authorization to publish the results from yellow fever national surveillance data used in the differential diagnosis of HEV infection without requiring informed consent. As the state of hepatitis E outbreak had been declared by the Ministry of Health and Population of the Central African Republic in this health district during this time, any person presenting conjunctival jaundice accompanied by a fever had to be systematically sampled for a HEV serological test, and symptomatic treatment was initiated if the serology (anti-HEV-IgM antibodies) of the HEV infection was positive.

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de Marguerite Nombot-Yazenguet, M.P., Doté, J.W., Koyaweda, G.W. et al. Hepatitis E outbreak in the health district of Bocaranga-Koui, Central African Republic, 2018–2019. BMC Infect Dis 24 , 215 (2024). https://doi.org/10.1186/s12879-024-09116-3

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Received : 03 November 2023

Accepted : 08 February 2024

Published : 19 February 2024

DOI : https://doi.org/10.1186/s12879-024-09116-3

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  • Hepatitis E outbreak
  • Molecular characterization
  • Bocaranga-Koui health district

BMC Infectious Diseases

ISSN: 1471-2334

nested case control study and hepatitis

Associations between multiple metal exposure and fertility in women: A nested case-control study

Affiliations.

  • 1 Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, Jiangsu, China.
  • 2 Nanjing Municipal Centre for Disease Control and Prevention, Nanjing, China.
  • 3 Maternal and Child Health Center of Gulou District, Nanjing, China.
  • 4 Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, Jiangsu, China. Electronic address: [email protected].
  • PMID: 38310826
  • DOI: 10.1016/j.ecoenv.2024.116030

Metal pollution can cause a decline in female fertility, however, previous studies have focused more on the effect of a single metal on fertility. In this study, we evaluated the effect of metal mixtures on female fertility based on nested case-control samples. The plasma levels of 22 metal elements from 180 women were determined by an inductively coupled plasma mass spectrometer (ICP-MS). Minimum absolute contraction and selection operator (LASSO) penalty regression selected metals with the greatest influence on clinical outcome. Logistic regression was used to analyze the correlation between single metals and fertility while a Bayesian kernel function regression (BKMR) model was used to analyze the effect of mixed metals. Eight metals (Calcium (Ca), Chromium (Cr), Cobalt (Co), Copper (Cu), Zinc (Zn), Rubidium (Rb), Strontium (Sr) and Zirconium (Zr)) were selected by LASSO regression for subsequent analysis. After adjusting for covariates, the logistic model showed that Cu (Odds Ratio(OR):0.33, 95% CI: 0.13 - 0.84) and Co (OR:0.38, 95% CI: 0.15 -0.94) caused a significant reduction in fertility, and identified the protective effect of Zn (OR: 2.96, 95% CI:1.21 -7.50) on fertility. Trend tests showed that increased Cr, Cu, and Rb levels were associated with reduced fertility. The BKMR model showed that Cr, Co, Cu, and Rb had a nonlinear relationship with fertility decline when controlling for the concentrations of other metals and suggested that Cu and Cr might exert an influence on fertility. Analysis showed a negative correlation between Cu, Cr, Co, Rb, and fertility, and a positive correlation between Zn and fertility. Furthermore, we found evidence for the interaction between Cu and Cr. Our findings require further validation and may identify new mechanisms in the future.

Keywords: BKMR; Fertility; ICP-MS; Metal; Plasma.

Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.

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