Trends in Multidrug Treatment Failure and Subsequent Mortality among Antiretroviral Therapy–Experienced Patients with HIV Infection in North America
Bibliographic record
Abstract
BACKGROUND: Although combination antiretroviral therapy continues to evolve, with potentially more effective options emerging each year, the ability of therapy to prevent multiple regimen failure and mortality in clinical practice remains poorly defined. METHODS: Sixteen cohorts representing over 60 sites contributed data on all individuals who initiated combination antiretroviral therapy. We identified those individuals who experienced virologic failure (defined as a human immunodeficiency virus [HIV] RNA level >1000 copies/mL), received modified therapy, and subsequently had a second episode of virologic failure. Multivariate Cox regression was used to assess factors associated with time to second regimen failure and the time to death after the onset of second regimen failure. RESULTS: Of the 42,790 individuals who received therapy, 7159 experienced a second virologic failure. The risk of second virologic failure decreased from 1996 (56 cases per 100 person-years) through 2005 (16 cases per 100 person-years; P < .001). The cumulative mortality after onset of second virologic failure was 26% at 5 years and decreased over time. A history of AIDS, a lower CD4(+) T cell count, and a higher plasma HIV RNA level were each independently associated with mortality. Similar trends were observed when analysis was limited to the subset of previously treatment-naive patients CONCLUSIONS: Although the rates of multiple regimen failure have decreased dramatically over the past decade, mortality rates for those who have experienced failure of at least 2 regimens have remained high. Plasma HIV RNA levels, CD4(+) T cell counts at time of treatment failure, and a history of AIDS remain independent risk factors for death, which emphasizes that these factors remain important targets for those in need of more-aggressive therapeutic interventions.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".