CD4 cell count and viral load monitoring in patients undergoing antiretroviral therapy in Uganda: cost effectiveness study
Bibliographic record
Abstract
OBJECTIVE: To examine the cost and cost effectiveness of quarterly CD4 cell count and viral load monitoring among patients taking antiretroviral therapy (ART). DESIGN: Cost effectiveness study. SETTING: A randomised trial in a home based ART programme in Tororo, Uganda. PARTICIPANTS: People with HIV who were members of the AIDS Support Organisation and had CD4 cell counts <250 × 10(6) cells/L or World Health Organization stage 3 or 4 disease. MAIN OUTCOME MEASURES: Outcomes calculated for the study period and projected 15 years into the future included costs, disability adjusted life years (DALYs), and incremental cost effectiveness ratios (ICER; $ per DALY averted). Cost inputs were based on the trial and other sources. Clinical inputs derived from the trial; in the base case, we assumed that point estimates reflected true differences even if non-significant. We conducted univariate and multivariate sensitivity analyses. INTERVENTIONS: Three monitoring strategies: clinical monitoring with quarterly CD4 cell counts and viral load measurement (clinical/CD4/viral load); clinical monitoring and quarterly CD4 counts (clinical/CD4); and clinical monitoring alone. RESULTS: With the intention to treat (ITT) results per 100 individuals starting ART, we found that clinical/CD4 monitoring compared with clinical monitoring alone increases costs by $20,458 (£12,780, €14,707) and averts 117.3 DALYs (ICER = $174 per DALY). Clinical/CD4/viral load monitoring compared with clinical/CD4 monitoring adds $142,458, and averts 27.5 DALYs ($5181 per DALY). The superior ICER for clinical/CD4 monitoring is robust to uncertainties in input values, and that strategy is dominant (less expensive and more effective) compared with clinical/CD4/viral load monitoring in one quarter of simulations. If clinical inputs are based on the as treated analysis starting at 90 days (after laboratory monitoring was initiated), then clinical/CD4/viral load monitoring is dominated by other strategies. CONCLUSIONS: Based on this trial, compared with clinical monitoring alone, monitoring of routine CD4 cell count is considerably more cost effective than additionally including routine viral load testing in the monitoring strategy and is more cost effective than ART.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".