Risks and consequences of TB and its prevention in cost-utility analyses among immigrants: a systematic review
Bibliographic record
Abstract
BACKGROUND: In low-TB incidence countries, foreign-born populations bear a disproportionate share of the TB burden. Cost-utility analyses of TB preventive treatment (TPT) programs among immigrants, however, have yielded divergent conclusions. We conducted a systematic review to evaluate how studies have considered the risks and consequences of TB disease and TPT. METHODS: March 2025. We included modeling studies measuring health utility with quality-adjusted life years (QALYs) and evaluated TPT among immigrants to low TB incidence countries. Using a narrative synthesis, we examined how studies considered risks and consequences of TB disease and TPT and their impacts on health utility. RESULTS: Of the 5,142 records screened, 14 studies met the inclusion criteria. Major adverse events (AEs) were the most frequently considered consequence of TPT with estimated risk ranging from 0% to 6% and mean associated annual disutility from major AEs was 0.017 QALYs, which varied substantially (coefficient of variation [CV)]: 1.2). All studies considered health disutility due to TB disease, with annual disutility ranging from 0.04 to 0.2 (mean: 0.11, CV: 0.4). CONCLUSIONS: There is wide variation in how risks and consequences of TPT and TB disease are considered in studies evaluating TB infection treatment programs.
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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 | 0.013 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.011 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".