Cancer-Attributable Mortality Among People With Treated Human Immunodeficiency Virus Infection in North America
Bibliographic record
Abstract
BACKGROUND: Cancer remains an important cause of morbidity and mortality in people with human immunodeficiency virus (PWHIV) on effective antiretroviral therapy (ART). Estimates of cancer-attributable mortality can inform public health efforts. METHODS: We evaluated 46956 PWHIV receiving ART in North American HIV cohorts (1995-2009). Using information on incident cancers and deaths, we calculated population-attributable fractions (PAFs), estimating the proportion of deaths due to cancer. Calculations were based on proportional hazards models adjusted for age, sex, race, HIV risk group, calendar year, cohort, CD4 count, and viral load. RESULTS: There were 1997 incident cancers and 8956 deaths during 267145 person-years of follow-up, and 11.9% of decedents had a prior cancer. An estimated 9.8% of deaths were attributable to cancer (cancer-attributable mortality rate 327 per 100000 person-years). PAFs were 2.6% for AIDS-defining cancers (ADCs, including non-Hodgkin lymphoma, 2.0% of deaths) and 7.1% for non-AIDS-defining cancers (NADCs: lung cancer, 2.3%; liver cancer, 0.9%). PAFs for NADCs were higher in males and increased strongly with age, reaching 12.5% in PWHIV aged 55+ years. Mortality rates attributable to ADCs and NADCs were highest for PWHIV with CD4 counts <100 cells/mm3. PAFs for NADCs increased during 1995-2009, reaching 10.1% in 2006-2009. CONCLUSIONS: Approximately 10% of deaths in PWHIV prescribed ART during 1995-2009 were attributable to cancer, but this fraction increased over time. A large proportion of cancer-attributable deaths were associated with non-Hodgkin lymphoma, lung cancer, and liver cancer. Deaths due to NADCs will likely grow in importance as AIDS mortality declines and PWHIV age.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".