Suppressed HIV antibody responses following exposure to antiretrovirals—evidence from PrEP randomized trials and early antiretroviral treatment initiation studies
Bibliographic record
Abstract
BACKGROUND: Exposure to antiretrovirals at or early after HIV acquisition can suppress viral replication and blunt antibody (Ab) responses; a reduced HIV detectability could impact diagnosis and blood donation screening. METHODS: We used three antigen (Ag)/Ab assays and one nucleic acid test (NAT) to analyze samples collected in pre-exposure prophylaxis (PrEP) trials (iPrEx; Partners PrEP) before infection detection by Ab-only rapid diagnostic tests (RDTs), and in early antiretroviral treatment (ART) initiation studies (RV254; SIPP). RESULTS: Reactivity using NAT and Ag/Ab assays in samples collected up to 8 weeks prior to the first reactive RDT from 251 PrEP trials participants varied between 49-61% for active PrEP users and between 27-37% for placebo users. Among RV254 participants, reactivity in Ag/Ab assays was <100% at all timepoints, and lower among those initiating ART earlier. Seroreversions occurred for 29% (16/55), and blood donation screening with NAT and Ag/Ab assays could have missed up to 36% (20/55) of RV254 participants. For SIPP participants, who started ART at later timepoints, Ag/Ab assays identified infections with no evidence of reactivity waning. CONCLUSION: PrEP and early ART initiation can delay or reduce HIV detectability. Considerations for the implementation of NAT and Ag/Ab tests in PrEP/PEP programs relying on Ab-only RDTs should be balanced according to feasibility and public health impact. While blood transfusion services using Ab-only RDTs for HIV screening should adopt higher sensitivity tests, surveillance and further research are needed to determine the need for novel HIV testing algorithms for those already using NAT and Ag/Ab screening assays.
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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 | 0.054 | 0.116 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".