Costs of 4 Months of Rifampin Versus 2 Months of Double-dose Rifampin for Tuberculosis Infection: Post-Hoc Analysis of a Phase 2b Randomized Trial
Bibliographic record
Abstract
Abstract Background Cost is an important consideration when implementing tuberculosis preventive treatment regimens (TPT). We used data from a phase 2b randomized trial of TPT to estimate overall cost and key drivers of costs for two TPT regimens. Methods We did a post-hoc analysis of 915 participants aged ≥10 years who were randomized 1:1 to 2 rifampin-based regimens: a four-month daily regimen at 10 mg/kg (4R10) and a 2-month daily regimen at 20 mg/kg (2R20; 461 participants). We collected country-specific costs for medications, evaluations, and medical follow-ups from the three participating countries (Canada, Indonesia, and Viet Nam), and converted all costs to 2024 Canadian dollars. We report the overall costs of each regimen and cost drivers. Results Overall, 454 participants received 4R10 and 461 participants received 2R20. We found no difference in the cost of 2R20 versus 4R10, with a cost ratio of 0.93 (95% CI: .79–1.07); this was consistent in analyses limited to only those who completed treatment and stratified by country. Costs for medications and the baseline visit accounted for 68%, 49%, and 55% of all costs in Canada, Indonesia, and Viet Nam, respectively. Corresponding costs of routine follow-up visits accounted for approximately 26%, 45%, and 42% of all costs. In all countries, a minority of costs (<10%) were due to additional visits or evaluations not specified in the protocol. Conclusions Most costs associated with TPT are due to medications and the baseline treatment initiation visit. TPT regimens requiring fewer follow-up visits may reduce overall cost, but the magnitude of this reduction varies by country.
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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 | 0.024 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.016 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| 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".