Efficacy and tolerability of long-term efavirenz plus nucleoside reverse transcriptase inhibitors for HIV-1 infection
Bibliographic record
Abstract
OBJECTIVE: To compare the long-term efficacy and tolerability of two efavirenz-containing regimens with those of an indinavir-containing regimen in the initial use of HAART. METHOD: HIV-1-infected patients (N = 1266) were randomly assigned to receive one of three regimens: efavirenz, zidovudine plus lamivudine, n = 422; efavirenz plus indinavir, n = 429; or indinavir, zidovudine plus lamivudine, n = 415. Entrance criteria included baseline viral load greater than 10 000 copies/ml HIV-1 RNA, CD4 cell count 50 cells/mul or greater, and no previous use of lamivudine, any non-nucleoside reverse-transcriptase inhibitor or protease inhibitor. The primary endpoint was the proportion of patients (response rate) in each regimen with a viral load under 400 copies/ml at 168 weeks of treatment. RESULTS: Response rates at 168 weeks were 30% in the indinavir, zidovudine, lamivudine group, 48% in the efavirenz, zidovudine, lamivudine group (P < 0.0001, difference estimate; 97.5% confidence interval (CI) 18.5; 10.9, 26), and 40% in the efavirenz plus indinavir group (P = 0.0018, difference estimate; 97.5% CI 10.2; 2.9, 17.6). Median CD4 cell counts increased above respective baselines by 292 cells/mul (efavirenz, zidovudine, lamivudine and indinavir, zidovudine, lamivudine) and 300 cells/mul (efavirenz plus indinavir). Total discontinuations were 54% (efavirenz, zidovudine, lamivudine), 63% (efavirenz plus indinavir), and 69% (indinavir, zidovudine, lamivudine) of which 13, 12 and 26%, respectively, were caused by adverse events. No new or unexpected increases in the rates or severity of adverse events occurred from long-term treatment with efavirenz-containing regimens. CONCLUSION: Long-term HIV therapy with efavirenz-containing regimens, particularly efavirenz, zidovudine, lamivudine, provides significantly greater antiviral activity and tolerability than a regimen of indinavir, zidovudine plus lamivudine.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".