Population-Based Sequencing of the V3-loop Can Predict the Virological Response to Maraviroc in Treatment-Naive Patients of the MERIT Trial
Bibliographic record
Abstract
BACKGROUND: MERIT was a randomized trial comparing maraviroc (MVC) + Combivir versus efavirenz (EFV) + Combivir in drug-naive patients screened as having R5 HIV-1 by the original Trofile assay (OTA). We retrospectively evaluated treatment response after rescreening for viral tropism using population-based V3-loop sequencing. METHODS: HIV env V3-loop was amplified in triplicate using reverse transcriptase-polymerase chain reaction from stored screening plasma and sequenced. Automated base calling was performed using custom software (RECall) and tropism inferred by geno2pheno (5.75% false-positive rate). Tropism results by genotype were compared with those of OTA and Enhanced Sensitivity Trofile assay (ESTA), where all results were available (n = 876). RESULTS: Approximately 8% of patients screened as having R5 virus by OTA were classified as having non-R5 virus by V3-loop genotyping. These patients were less likely to have early or sustained week-48 treatment response to MVC, but not EFV. When restricted to patients with R5 virus by genotype, reanalysis of the primary study endpoint (plasma viral load <50 copies/mL at week 48) showed noninferiority of MVC twice daily to EFV (67% vs. 68%). Rescreening by genotype and ESTA had 84% concordance; patients receiving MVC twice daily rescreened as having R5 virus had greater than 1 log10 copies per milliliter decrease in viral load over those rescreened as having non-R5 virus. Where genotype and ESTA screening results were discordant outcomes were similar. CONCLUSIONS: The exclusion of ∼8% of patients with CXCR4-using virus by population-based sequencing would likely have resulted in noninferior responses in the MVC twice-daily and EFV arms. Rescreening by ESTA and population-based sequencing predicted similar virological response.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.005 |
| 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) | 0.001 | 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".