Long‐term effectiveness of initiating non‐nucleoside reverse transcriptase inhibitor‐ versus ritonavir‐boosted protease inhibitor‐based antiretroviral therapy: implications for first‐line therapy choice in resource‐limited settings
Bibliographic record
Abstract
INTRODUCTION: In many resource-limited settings, combination antiretroviral therapy (cART) failure is diagnosed clinically or immunologically. As such, there is a high likelihood that patients may stay on a virologically failing regimen for a substantial period of time. Here, we compared the long-term impact of initiating non-nucleoside reverse transcriptase inhibitor (NNRTI)- versus boosted protease inhibitor (bPI)-based cART in British Columbia (BC), Canada. METHODS: We followed prospectively 3925 ART-naïve patients who started NNRTIs (N=1963, 50%) or bPIs (N=1962; 50%) from 1 January 2000 until 30 June 2013 in BC. At six months, we assessed whether patients virologically failed therapy (a plasma viral load (pVL) >50 copies/mL), and we stratified them based on the pVL at the time of failure ≤500 versus >500 copies/mL. We then followed these patients for another six months and calculated their probability of achieving subsequent viral suppression (pVL <50 copies/mL twice consecutively) and of developing drug resistance. These probabilities were adjusted for fixed and time-varying factors, including cART adherence. RESULTS: At six months, virologic failure rates were 9.5 and 14.3 cases per 100 person-months for NNRTI and bPI initiators, respectively. NNRTI initiators who failed with a pVL ≤500 copies/mL had a 16% higher probability of achieving subsequent suppression at 12 months than bPI initiators (0.81 (25th-75th percentile 0.75-0.83) vs. 0.72 (0.61-0.75)). However, if failing NNRTI initiators had a pVL >500 copies/mL, they had a 20% lower probability of suppressing at 12 months than pVL-matched bPI initiators (0.37 (0.29-0.45) vs. 0.46 (0.38-0.54)). In terms of evolving HIV drug resistance, those who failed on NNRTI performed worse than bPI in all scenarios, especially if they failed with a viral load >500 copies/mL. CONCLUSIONS: Our results show that patients who virologically failed at six months on NNRTI and continued on the same regimen had a lower probability of subsequently achieving viral suppression and a higher chance of evolving HIV drug resistance. These results suggest that improving access to regular virologic monitoring is critically important, especially if NNRTI-based cART is to remain a preferred choice for first-line therapy in resource-limited settings.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".