Brief Report: Cutaneous Melanoma Risk Among People With HIV in the United States and Canada
Bibliographic record
Abstract
BACKGROUND: Cutaneous melanoma incidence may be modestly elevated in people with HIV (PWH) vs. people without HIV. However, little is known about the relationship of immunosuppression, HIV replication, and antiretroviral therapy (ART) with melanoma risk. METHODS: PWH of white race in the North American AIDS Cohort Collaboration on Research and Design were included. A standardized incidence ratio was calculated comparing risk with the white general population, standardizing by age, sex, and calendar period. Associations between melanoma incidence and current, lagged, and cumulative measures of CD4 count, HIV RNA level, and ART use were estimated with Cox regression, adjusting for established risk factors such as age and annual residential ultraviolet B (UVB) exposure. RESULTS: Eighty melanomas were diagnosed among 33,934 white PWH (incidence = 40.75 per 100,000 person-years). Incidence was not elevated compared with the general population [standardized incidence ratio = 1.15, 95% confidence interval (95% CI) = 0.91 to 1.43]. Higher melanoma incidence was associated with older age [adjusted hazard ratio (aHR) per decade increase = 1.50, 95% CI = 1.20 to 1.89] and higher UVB exposure (aHR for exposure ≥35 vs. <35 mW/m = 1.62, 95% CI = 0.99 to 2.65). Current, lagged, and cumulative CD4 and HIV RNA were not associated with melanoma incidence. Melanoma incidence was higher among people ART-treated for a larger proportion of time in the previous 720 days (aHR per 10% increase = 1.16, 95% CI = 1.03 to 1.30). CONCLUSIONS: These results suggest that HIV-induced immune dysfunction does not influence melanoma development. The association between ART and melanoma risk may be due to increased skin surveillance among PWH engaged in clinical care. Associations with age and UVB confirmed those established in the general population.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".