Expanding Antiretroviral Options in Resource-Limited Settings-A Cost-Effectiveness Analysis
Bibliographic record
Abstract
BACKGROUND: Current World Health Organization (WHO) guidelines for treatment of HIV in resource-limited settings call for 2 antiretroviral regimens. The effectiveness and cost-effectiveness of increasing the number of antiretroviral regimens is unknown. METHODS: Using a simulation model, we compared the survival and costs of current WHO regimens with two 3-regimen strategies: an initial regimen of 3 nucleoside reverse transcriptase inhibitors followed by the WHO regimens and the WHO regimens followed by a regimen with a second-generation boosted protease inhibitor (2bPI). We evaluated monitoring with CD4 counts only and with both CD4 counts and viral load. We used cost and effectiveness data from Cape Town and tested all assumptions in sensitivity analyses. RESULTS: Over the lifetime of the cohort, 25.6% of individuals failed both WHO regimens by virologic criteria. However, when patients were monitored using CD4 counts alone, only 6.5% were prescribed additional highly active antiretroviral therapy due to missed and delayed detection of failure. The life expectancy gain for individuals who took a 2bPI was 6.7-8.9 months, depending on the monitoring strategy. When CD4 alone was available, adding a regimen with a 2bPI was associated with an incremental cost-effectiveness ratio of $2581 per year of life gained, and when viral load was available, the ratio was $6519 per year of life gained. Strategies with triple-nucleoside reverse transcriptase inhibitor regimens in initial therapy were dominated. Results were sensitive to the price of 2bPIs. CONCLUSIONS: About 1 in 4 individuals who start highly active antiretroviral therapy in sub-Saharan Africa will fail currently recommended regimens. At current prices, adding a regimen with a 2bPI is cost effective for South Africa and other middle-income countries by WHO standards.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".