Incidence of cervical, breast and colorectal cancers between 2010 and 2015 in people living with HIV in France
Bibliographic record
Abstract
BACKGROUND: We aimed to evaluate the incidence rates between 2010 and 2015 for invasive cervical cancer (ICC), breast cancer (BC), and colorectal cancer (CRC) in people living with HIV (PLWH) in France, and to compare them with those in the French general population. These cancers are targeted by the national cancer-screening program. SETTING: This is a retrospective study based on the longitudinal data of the French Dat'AIDS cohort. METHODS: Standardized incidence ratios (SIR) for ICC and BC, and incidence rates for all three cancers were calculated overall and for specific sub-populations according to nadir CD4 cell count, HIV transmission category, HIV diagnosis period, and HCV coinfection. RESULTS: The 2010-2015 CRC incidence rate was 25.0 [95% confidence interval (CI): 18.6-33.4] per 100,000 person-years, in 44,642 PLWH (both men and women). Compared with the general population, the ICC incidence rate was significantly higher in HIV-infected women both overall (SIR = 1.93, 95% CI: 1.18-3.14) and in the following sub-populations: nadir CD4 ≤ 200 cells/mm3 (SIR = 2.62, 95% CI: 1.45-4.74), HIV transmission through intravenous drug use (SIR = 5.14, 95% CI: 1.93-13.70), HCV coinfection (SIR = 3.52, 95% CI: 1.47-8.47) and HIV diagnosis before 2000 (SIR = 2.06, 95% CI: 1.07-3.97). Conversely, the BC incidence rate was significantly lower in the study sample than in the general population (SIR = 0.56, 95% CI: 0.42-0.73). CONCLUSION: The present study showed no significant linear trend between 2010 and 2015 in the incidence rates of the three cancers explored in the PLWH study sample. Specific recommendations for ICC screening are still required for HIV-infected women and should focus on sub-populations at greatest risk.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| 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".