Resistance Analyses of Integrase Strand Transfer Inhibitors within Phase 3 Clinical Trials of Treatment-Naive Patients
Bibliographic record
Abstract
The integrase (IN) strand transfer inhibitors (INSTIs), raltegravir (RAL), elvitegravir (EVG) and dolutegravir (DTG), comprise the newest drug class approved for the treatment of HIV-1 infection, which joins the existing classes of reverse transcriptase, protease and binding/entry inhibitors. The efficacy of first-line regimens has attained remarkably high levels, reaching undetectable viral loads in 90% of patients by Week 48; however, there remain patients who require a change in regimen due to adverse events, virologic failure with emergent resistance or other issues of patient management. Large, randomized clinical trials conducted in antiretroviral treatment-naive individuals are required for drug approval in this population in the US, EU and other countries, with the primary endpoint for virologic success at Week 48. However, there are differences in the definition of virologic failure and the evaluation of drug resistance among the trials. This review focuses on the methodology and tabulation of resistance to INSTIs in phase 3 clinical trials of first-line regimens and discusses case studies of resistance.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".