Cancer burden attributable to cigarette smoking among HIV-infected people in North America
Bibliographic record
Abstract
OBJECTIVE: With combination-antiretroviral therapy, HIV-infected individuals live longer with an elevated burden of cancer. Given the high prevalence of smoking among HIV-infected populations, we examined the risk of incident cancers attributable to ever smoking cigarettes. DESIGN: Observational cohort of HIV-infected participants with 270 136 person-years of follow-up in the North American AIDS Cohort Collaboration on Research and Design consortium. Among 52 441 participants, 2306 were diagnosed with cancer during 2000-2015. MAIN OUTCOME MEASURES: Estimated hazard ratios and population-attributable fractions (PAF) associated with ever cigarette smoking for all cancers combined, smoking-related cancers, and cancers that were not attributed to smoking. RESULTS: People with cancer were more frequently ever smokers (79%) compared with people without cancer (73%). Adjusting for demographic and clinical factors, cigarette smoking was associated with increased risk of cancer overall [hazard ratios = 1.33 (95% confidence interval: 1.18-1.49)]; smoking-related cancers [hazard ratios = 2.31 (1.80-2.98)]; lung cancer [hazard ratios = 17.80 (5.60-56.63)]; but not nonsmoking-related cancers [hazard ratios = 1.12 (0.98-1.28)]. Adjusted PAFs associated with ever cigarette smoking were as follows: all cancers combined, PAF = 19% (95% confidence interval: 13-25%); smoking-related cancers, PAF = 50% (39-59%); lung cancer, PAF = 94% (82-98%); and nonsmoking-related cancers, PAF = 9% (1-16%). CONCLUSION: Among HIV-infected persons, approximately one-fifth of all incident cancer, including half of smoking-related cancer, and 94% of lung cancer diagnoses could potentially be prevented by eliminating cigarette smoking. Cigarette smoking could contribute to some cancers that were classified as nonsmoking-related cancers in this report. Enhanced smoking cessation efforts targeted to HIV-infected individuals are needed.
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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 | 0.000 | 0.000 |
| 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".