Risk of hepatitis B virus reactivaton in HBsAg-negative, anti-hbc-positive patients receiving rituximab: A systematic review
Bibliographic record
Abstract
Abstract Background Rituximab is an anti-CD20 monoclonal antibody widely used in the treatment of hematologic malignancies and autoimmune conditions. It has been associated with hepatitis B virus (HBV) reactivation in individuals with both chronic (HBsAg-negative) and past HBV infection (HBsAg-negative, anti-HBc-positive). Current Canadian guidelines highlight this risk and recommend screening of HBsAg-status and HBcAb-status be completed. Variability in reactivation rates may be influenced by the treatment regimen, such as rituximab monotherapy, R-CHOP, or rituximab-containing chemotherapy, as well as by the presence or absence of anti-HBs antibodies. To our knowledge, no systematic review has evaluated rituximab-treated patients across various treatments with specific attention to anti-HBs serostatus subgroups. This review provides an overview of HBV reactivation rates across these serologic subtypes and treatment types to inform clinical risk assessment and support evidence-based prophylaxis decisions. Objective We conducted a systematic review and meta-analysis to determine the rate of HBV reactivation in HBsAg-negative, anti-HBc-positive patients with varying anti-HBs status treated with rituximab-based therapies, including rituximab monotherapy, R-CHOP, and other rituximab-containing chemotherapy regimens. We excluded studies that used antiviral therapy in patients at risk of reactivation to better understand the risk without such therapy. Methods We conducted a systematic review in accordance with PRISMA guidelines. We searched Ovid MEDLINE, EMBASE and Web of Science for relevant studies published up to August 2024, using a librarian-approved search strategy. Reference lists of included studies were also screened. All screening and data extraction was completed in duplicate. Studies were eligible if they were prospective or retrospective cohort studies or randomized controlled trials (RCTs) that enrolled at least 20 HBsAg-negative, anti-HBc-positive patients treated with any rituximab-based therapy at a dose of 375 mg/m². The primary outcome was HBV reactivation, as defined by individual studies. We calculated the weighted mean of reported reactivation rates, and where possible, stratified results by anti-HBs serostatus. Results A total of 2840 records were screened, and 22 studies (2059 patients) met inclusion criteria. All studies used a rituximab dose of 375 mg/m2.Eighteen studies (81.8%) were retrospective cohort studies and four (18.2%) were prospective cohort studies. Sixstudies used R-CHOP, 19 studiesused rituximab-containing chemotherapy regimen (which may have included R-CHOP however the study did not provide sufficient detail to extract that group), and 3 studies used rituximab monotherapy (only one of which reported HBSAg status). In R-CHOP treated patients (n = 627), the average reactivation rate was 15.6% (weighted mean 14.4%). Anti-HBs-negative patients had higher rates (average 21.3%; weighted mean 24.4%) compared to anti-HBs-positive patients (average 5.4%; weighted mean 7.2%). In the two other cohorts (n = 1,914), the average reactivation rate in HbcAb positive group was 11.6% (weighted mean 10.5%). The same trend based on HBsAg status was observed in these two groups as in the R-CHOP group: anti-HBs-negative patients had the highest rates (average 28.5%; weighted mean 21.6%) compared to lower rates in anti-HBs-positive individuals (average 6.2%; weighted 6.1%). In patients treated with rituximab monotherapy (n = 145), the average recurrence was 10.0% (weighted mean 9.7%). In the single rituximab monotherapy study that reported HbsAb status, the rate was 6.0% in anti-HBs positive patients and 28.5% in anti-HBs negative patients. Conclusion This systematic review and meta-analysis demonstrated that HBV reactivation occurs across all rituximab-based regimens in anti-HBc-positive patients, with relatively consistent rates between the treatment types (R-CHOP plus rituximab monotherapy, rituximab-containing chemotherapy plus rituximab monotherapy and rituximab monotherapy). Studies consistently found much higher reactivation rates in patients who were anti-HBs negative compared to those who were anti-HBs positive. These findings offer a practical synthesis of reported rates to support clinical awareness, guide risk stratification, and inform screening and prophylaxis considerations and support screening of all patients for HBV status prior to initiating rituximab therapy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.012 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".