Earlier Initialization of Highly Active Antiretroviral Therapy Is Associated With Long-Term Survival and Is Cost-Effective
Bibliographic record
Abstract
BACKGROUND: Raising the guidelines for the initiation of antiretroviral therapy in resource-limited settings at CD4 T-cell counts of 350 cells per microliter raises concerns about feasibility and cost. We examined costs of this shift using data from Uganda for almost 10 years. METHODS: We projected total costs of earlier initiation with combined antiretroviral therapy, including inpatient and outpatient services, antiretroviral treatment and treatment for limited HIV-related opportunistic diseases, and benefits expressed in years-of-life-saved over 5- and 30-year time horizons using a deterministic economic model to examine the incremental cost-effectiveness ratio (ICER), expressed in cost per year-of-life-saved (YLS). RESULTS: The model generated ICERs for 5- and 30-year time horizons. Discounting both costs and benefits at 3% annually, for the 5-year analysis, the ICER was $695/YLS and $769 in the 30-year analysis. The results were most sensitive to program cost and the discount rate applied, but they were less sensitive to opportunistic infection treatment costs or the relative-risk reduction from earlier initiation. Program costs varied from 25% to 125%, and the ICER for the lower bound decreased to $491/YLS at 5-years and $574/YLS at 30 years. For the upper bound, the ICER increased to $899 for 5-years and $964 at 30-years. The budget impact of adoption, assuming the same level of program penetration in the community, is $261,651,942 for 5 years and $872,685,561 for 30 years. CONCLUSIONS: Our model showed that earlier initiation of combined antiretroviral therapy in Uganda is associated with improved long-term survival and is highly cost-effective, as defined by WHO-CHOICE.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".