Cancer risks and trends between 1997 and 2018, and effects of restored immunity in people living with <scp>HIV</scp> : Results from the <scp>ANRS CO4</scp> French hospital database on <scp>HIV</scp>
Bibliographic record
Abstract
Abstract We assessed long‐term trends in cancer incidence among people with HIV (PWH) in France between 1997 and 2018, focusing on AIDS‐defining cancers (ADC) (Kaposi's sarcoma, non‐Hodgkin's lymphoma, and cervical cancer), three virus‐related non‐AIDS‐defining cancers (Hodgkin lymphoma, liver, and anal cancer), and four virus‐unrelated cancers (lung, colorectal, prostate, and breast cancer). Using data from the ANRS CO4‐French Hospital Database on HIV and cancer registries in the general population, we calculated age‐standardized incidence rates and standardized incidence ratios (SIRs) across four time periods. Special attention was given to PWH with controlled viral load and restored CD4 during 2008–2018. Among 154,733 individuals contributing nearly 2 million person‐years, 9572 cancers were diagnosed. Incidence rates of ADC and virus‐related non‐ADC declined over time but remained significantly higher than in the general population, with SIRs ranging from 3 to 420, even in recent years. Rates of prostate and colorectal cancers increased overtime, while breast cancer incidence remained stable. For these three cancers, the relative risk compared to the general population remained close to 1. In PWH with CD4 ≥ 500/mm 3 for at least 2 years and with recent viral load ≤50 copies/mL, risks of virus‐related cancers (KS, NHL, HL, liver, and anal cancer) remained significantly higher relative to the general population, albeit to a lesser extent than in PWH overall, while risks of lung and cervical cancers were similar. Over 20 years, the incidence of all virus‐related cancers continued to fall but in the most recent period, the risks still remained higher than in the general population.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".