The Cost of Antiretroviral Drug Resistance in HIV-Positive Patients
Bibliographic record
Abstract
INTRODUCTION: Antiretroviral (ARV) drug resistance limits treatment choices, often necessitating the selection of drugs with less desirable pill burdens, toxicity profiles, drug interactions and dosing schedules, and may increase cost. We examine the impact of resistance on the cost of HIV care. METHODS: All adult HIV-positive individuals newly referred for HIV care from 1 January 2007 to 1 January 2011 and followed until 31 December 2011 at the Southern Alberta Clinic, Calgary, AB, Canada, were included. We determined the cost of all ARV drugs, and HIV-related outpatient and inpatient care, reported as mean per patient per month (PPPM) costs in 2011 Canadian dollars (CDN). RESULTS: Overall, 78% of patients received genotypic antiretroviral resistance testing (GART); 57% among ARV-naive patients, 21% after suspected viral failure, and 20% during a treatment interruption. Resistance was detected in 6%, 49% and 21% of all tests respectively. The total mean PPPM cost for patients with GART was CDN 1,179. Patients with primary resistance had mean total PPPM costs of CDN 956. Patients with no resistance had mean PPPM costs of CDN 1,058, by contrast with the CDN 1,291 costs of patients with secondary/acquired resistance. Mean costs for one, two or three ARV class resistance was CDN 1,278, 1,337 and 1,801, respectively. Mean PPPM costs increased by 31% from CDN 1,068 to 1,396, respectively, before and after a positive resistance test. CONCLUSIONS: Transmission of resistant virus as well as emergence of resistance during ARV therapy leads to increased costs. Mean costs increased by number of resistant classes. Routine GART and optimizing ARV regimens to avoid resistance might minimize the long-term costs of HIV care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".