Characterizing Human Immunodeficiency Virus Antiretroviral Therapy Interruption and Resulting Disease Progression Using Population-Level Data in British Columbia, 1996–2015
Bibliographic record
Abstract
BACKGROUND: Suboptimal retention is among the biggest challenges to realize the full benefits of combination antiretroviral therapy (ART). We aimed to describe ART interruption patterns and identify determinants of disease progression while off ART in British Columbia, Canada. METHODS: With population-level data on ART utilization and laboratory testing in British Columbia (1996-2015), we described the timing, frequency, and duration of ART interruptions (a gap of ≥90 days in ART dispensation records). A 4-state continuous-time Markov model was implemented to identify determinants of disease progression during individuals' first ART interruption episode. Disease progression was measured according to CD4-based state transitions (cells/μL: ≥500 to 200-499; 200-499 to <200; ≥500 to death; 200-499 to death; and <200 to death). RESULTS: Among individuals initiating ART, 3129 (38.6%) interrupted ART over a median 8-year follow-up (interquartile range [IQR], 4.3-13.5 years). Those interrupting ART had a median of 1 interruption (IQR, 1.0-3.0), with the first interruption occurring 12.8 (IQR, 4.0-36.1) months after ART initiation, lasting for 7.5 (IQR, 4.1-20.3) months. The proportion of individuals interrupting ART within the first year of ART initiation decreased over time; however, the absolute number of individuals interrupting ART remained high. In a multivariable analysis, age, historical plasma viral load, and ART regimen changes prior to interruption were associated with increased hazard of CD4 decline and death. CONCLUSIONS: Our results demonstrate that ART interruptions are common even in a high-resource setting with universal free access to human immunodeficiency virus care. Further efforts are needed to promote ART reengagement and may consider prioritizing individuals with poorer prognostic factors.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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".