A randomized trial to study first-line combination therapy with or without a protease inhibitor in HIV-1-infected patients
Bibliographic record
Abstract
OBJECTIVE: To compare one protease inhibitor (PI)-based and two PI-sparing antiretroviral therapy regimens. METHODS: International, open label, randomized study of antiretroviral drug-naive patients, with CD4 lymphocyte counts >/= 200 x 106 cells/l and plasma HIV-1 RNA levels > 500 copies/ml. Treatment assignment to stavudine and didanosine plus indinavir or nevirapine or lamivudine. Primary study endpoint was the percentage of patients with plasma HIV-1 RNA levels < 500 copies/ml after 48 weeks in the intention-to-treat analysis (ITT). RESULTS: In total, 298 patients were enrolled. After 48 weeks, the percentage of patients in the indinavir, nevirapine and lamivudine arms with HIV-1 RNA < 500 copies/ml was 57.0%, 58.4% and 58.7%, respectively, in an ITT analysis. After 96 weeks of follow-up, these percentages were 50.0%, 59.6% and 45.0%, respectively. The percentage of patients with HIV-1 RNA < 50 copies/ml was significantly less for those allocated to lamivudine in an on-treatment analysis after 48 and 96 weeks of follow-up. Patients in the nevirapine arm experienced a smaller increase in the absolute number of CD4 T lymphocytes. There were no significant differences in the incidence of serious adverse events. CONCLUSIONS: A comparable virological response can be achieved with first-line PI-base and PI-sparing regimens. The triple nucleoside regimen utilized may be less likely to result in viral suppression to < 50 copies/ml, while the nevirapine-based regimen is associated with a lower increase in CD4 T lymphocytes.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".