Risk of HCC With Hepatitis B Viremia Among HIV/HBV‐Coinfected Persons in North America
Bibliographic record
Abstract
Background and Aims Chronic HBV is the predominant cause of HCC worldwide. Although HBV coinfection is common in HIV, the determinants of HCC in HIV/HBV coinfection are poorly characterized. We examined the predictors of HCC in a multicohort study of individuals coinfected with HIV/HBV. Approach and Results We included persons coinfected with HIV/HBV within 22 cohorts of the North American AIDS Cohort Collaboration on Research and Design (1995‐2016). First occurrence of HCC was verified by medical record review and/or cancer registry. We used multivariable Cox regression to determine adjusted HRs (aHRs [95% CIs]) of factors assessed at cohort entry (age, sex, race, body mass index), ever during observation (heavy alcohol use, HCV), or time‐updated (HIV RNA, CD4+ percentage, diabetes mellitus, HBV DNA). Among 8,354 individuals coinfected with HIV/HBV (median age, 43 years; 93% male; 52.4% non‐White), 115 HCC cases were diagnosed over 65,392 person‐years (incidence rate, 1.8 [95% CI, 1.5‐2.1] events/1,000 person‐years). Risk factors for HCC included age 40‐49 years (aHR, 1.97 [1.22‐3.17]), age ≥50 years (aHR, 2.55 [1.49‐4.35]), HCV coinfection (aHR, 1.61 [1.07‐2.40]), and heavy alcohol use (aHR, 1.52 [1.04‐2.23]), while time‐updated HIV RNA >500 copies/mL (aHR, 0.90 [0.56‐1.43]) and time‐updated CD4+ percentage <14% (aHR, 1.03 [0.56‐1.90]) were not. The risk of HCC was increased with time‐updated HBV DNA >200 IU/mL (aHR, 2.22 [1.42‐3.47]) and was higher with each 1.0 log 10 IU/mL increase in time‐updated HBV DNA (aHR, 1.18 [1.05‐1.34]). HBV suppression with HBV‐active antiretroviral therapy (ART) for ≥1 year significantly reduced HCC risk (aHR, 0.42 [0.24‐0.73]). Conclusion Individuals coinfected with HIV/HBV on ART with detectable HBV viremia remain at risk for HCC. To gain maximal benefit from ART for HCC prevention, sustained HBV suppression is necessary.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".