Factors Associated With Viral Rebound in HIV-1-Infected Individuals Enrolled in a Therapeutic HIV-1 gag Vaccine Trial
Bibliographic record
Abstract
BACKGROUND: Human immunodeficiency virus type 1 (HIV-1) vaccines directed to the cell-mediated immune system could have a role in lowering the plasma HIV-1 RNA set point, which may reduce infectivity and delay disease progression. METHODS: Randomized, placebo-controlled trial involving HIV-1-infected participants who received a recombinant adenovirus serotype 5 (rAd5) HIV-1 gag vaccine or placebo. Sequence-based HLA typing was performed for all 110 participants who initiated analytic treatment interruption (ATI) to assess the role of HLA types previously associated with HIV prognosis. Plasma HIV-1 gag and pol RNA sequences were obtained during the ATI. Virologic endpoints and HLA groups were compared between treatment arms using the 2-sample rank sum test. A linear regression model was fitted to derive independent correlates of ATI week 16 plasma viral load (w16 PVL). RESULTS: Vaccinated participants with neutral HLA alleles had lower median w16 PVLs than did vaccinated participants with protective HLA alleles (P = .01) or placebo participants with neutral HLA alleles (P = .02). Factors independently associated with lower w16 PVL included lower pre-antiretroviral therapy PVL, greater Gag sequence divergence from the vaccine sequence, decreased proportion of HLA-associated polymorphisms in Gag, and randomization to the vaccine arm. CONCLUSIONS: Therapeutic vaccination with a rAd5-HIV gag vaccine was associated with lower ATI week 16 PVL even after controlling for viral and host genetic factors. CLINICAL TRIALS REGISTRATION: NCT00080106.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.004 | 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".