Molecular and Clinical Epidemiology of CXCR4‐Using HIV‐1 in a Large Population of Antiretroviral‐Naive Individuals
Bibliographic record
Abstract
OBJECTIVE: We wished to characterize the epidemiological and clinical correlates of CXCR4-using human immunodeficiency virus type 1 (HIV-1) ("X4 variants") in a cross-sectional analysis of a large population of antiretroviral-naive individuals. METHODS: HIV-1 coreceptor use was determined in the last pretherapy plasma sample for 1191 individuals initiating triple-combination therapy in British Columbia, Canada. Baseline variables investigated included sociodemographic characteristics, plasma viral load (pVL), CD4 cell count, AIDS diagnosis, HIV-1 V3 loop sequence, and human CCR5 Delta 32 genotype. RESULTS: Individuals harboring X4 variants (n = 178 of 979 phenotyped samples; 18.2%) displayed a poorer baseline clinical profile than individuals harboring exclusively CCR5-using HIV-1 ("R5 variants") (median pVL, 175,000 vs. 120,000 copies of HIV-1 RNA/mL [P = .0006]; median CD4 cell count, 110 vs. 290 cells/mm(3) [P < .0001]). Individuals heterozygous for the CCR5 Delta 32 deletion (n = 128 of 967; 13.2%) were at 2.5 times higher risk of harboring X4 variants, compared with those without the deletion (multivariate P = .0005). The presence of basic amino acids at codon 11 and/or codon 25 of HIV-1 V3 (n = 109 of 955; 11.4%) was associated with a 9.1 times higher risk of harboring X4 variants (multivariate P < .0001), regardless of CCR5 Delta 32 genotype. In multivariate analyses adjusting for baseline parameters, HIV-1 coreceptor use was not found to be a significant predictor of survival or treatment response. CONCLUSION: Baseline CD4 cell count, pVL, HIV-1 V3 sequence, and CCR5 Delta 32 genotype were the strongest determinants of CXCR4-using HIV-1 in this population. After adjustment for baseline parameters, the presence of X4 variants before initiation of highly active antiretroviral therapy was not independently associated with a poorer outcome of therapy.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".