The association between hepatitis B virus infection and nonliver malignancies in persons living with HIV: results from the EuroSIDA study
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to assess the impact of hepatitis B virus (HBV) infection on non-liver malignancies in people living with HIV (PLWH). METHODS: All persons aged ≥ 18 years with known hepatitis B virus (HBV) surface antigen (HBsAg) status after the latest of 1 January 2001 and enrolment in the EuroSIDA cohort (baseline) were included in the study; persons were categorized as HBV positive or negative using the latest HBsAg test and followed to their first diagnosis of nonliver malignancy or their last visit. RESULTS: Of 17 485 PLWH included in the study, 1269 (7.2%) were HBV positive at baseline. During 151 766 person-years of follow-up (PYFU), there were 1298 nonliver malignancies, 1199 in those currently HBV negative [incidence rate (IR) 8.42/1000 PYFU; 95% confidence interval (CI) 7.94-8.90/1000 PYFU] and 99 in those HBV positive (IR 10.54/1000 PYFU; 95% CI 8.47-12.62/1000 PYFU). After adjustment for baseline confounders, there was a significantly increased incidence of nonliver malignancies in HBV-positive versus HBV-negative individuals [adjusted incidence rate ratio (aIRR) 1.23; 95% CI 1.00-1.51]. Compared to HBV-negative individuals, HBsAg-positive/HBV-DNA-positive individuals had significantly increased incidences of nonliver malignancies (aIRR 1.37; 95% CI 1.00-1.89) and NHL (aIRR 2.57; 95% CI 1.16-5.68). There was no significant association between HBV and lung or anal cancer. CONCLUSIONS: We found increased rates of nonliver malignancies in HBsAg-positive participants, the increases being most pronounced in those who were HBV DNA positive and for NHL. If confirmed, these results may have implications for increased cancer screening in HIV-positive subjects with chronic HBV infection.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".