Comparison of Abacavir/Lamivudine and Tenofovir/Emtricitabine Among Treatment-Naive HIV-Infected Patients Initiating Therapy
Bibliographic record
Abstract
BACKGROUND: Controversy about the relative performance of abacavir (ABC)/lamivudine (3TC) and tenofovir (TDF)/emtricitabine (FTC) in initial combination antiretroviral therapy (cART) exists. METHODS: We compared the times to regimen failure (composite of virologic failure or switching/stopping nucleosides for any reason) according to nucleoside backbone in treatment-naive patients starting cART in a retrospective observational cohort study. Additional endpoints included virologic failure, switching/stopping nucleosides for nonvirologic reasons, and virologic suppression. Treatment-naive noninjection drug user individuals in the Canadian Observational Cohort initiating ABC/3TC-containing or TDF/FTC-containing cART with efavirenz, nevirapine, lopinavir/ritonavir, or atazanavir/ritonavir with ≥6 months follow-up were included. Multivariable proportional hazards regression models accounting for competing risks were used to model outcomes. RESULTS: One thousand seven hundred sixty-four individuals (588 ABC/3TC, 1176 TDF/FTC) were included. Median (interquartile range) follow-up times were 34 (23-50) and 20 (13-30) months, respectively. Time to regimen failure was similar for ABC/3TC versus TDF/FTC [adjusted hazard ratio, (aHR) = 0.96, 95% CI = 0.80 to 1.17] after adjusting for baseline viral load (VL), sex, province, third antiretroviral agent, year of cART initiation, HLA-B*5701 test availability, and rate of VL testing. No differences were observed in time to virologic failure (aHR = 0.84, 95% CI = 0.58 to 1.20), switching/stopping nucleosides for nonvirologic reasons (aHR = 1.02, 95% CI = 0.81 to 1.28), or virologic suppression (aHR = 0.96, 95% CI = 0.83 to 1.10). There was no statistical interaction between backbone and baseline VL for any outcome. Results were similar when stratified by baseline VL ≤ 100,000 or > 100,000 copies per milliliter. CONCLUSIONS: In our naive noninjection drug user HIV-infected patients starting cART, there was no difference in time to regimen failure, virologic failure, switching/stopping nucleosides, or virologic suppression with ABC/3TC versus TDF/FTC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".