Factors Associated With Discontinuation of Tuberculosis Preventive Treatment: Post Hoc Analysis of 2 Randomized, Controlled Trials
Bibliographic record
Abstract
BACKGROUND: Adherence to tuberculosis preventive treatment (TPT) is an important determinant of clinical benefit. We assessed the association of participant behaviors early in TPT with subsequent discontinuation. METHODS: We used data from a phase 3 randomized trial and the preceding phase 2 trial to compare 4 months of rifampin to 9 months of isoniazid for TPT. We excluded participants whose providers discontinued TPT due to adverse events or tuberculosis disease. We analyzed 4 outcomes: discontinuing TPT within the first month of treatment, discontinuing TPT between the first and second month, discontinuing TPT after the second month, and completing treatment but not per protocol. We analyzed the association of outcomes with regimen and participant characteristics and 4 behavioral predictors of discontinuation recorded at the month 1 and month 2 follow-up visits: reporting symptoms of intolerance, missing >20% of doses, rescheduling appointments, and not bringing their medication bottle. RESULTS: Overall, 6656 participants were included (phase 3, 5848; phase 2, 808), of whom 4318 (64.9%) completed treatment per protocol. Participant characteristics were inconsistently associated with discontinuation. Phase 3 trial participants with 1, 2, or 3-4 behavioral predictors at the month 1 follow-up had 5.0 (95% confidence interval, 3.6-6.7), 18.6 (13.3-26.1), and 79.4 (38.2-165.0), respectively, higher odds of discontinuing before the second month. The corresponding number of predictors at the month 2 follow-up had 1.8 (1.4-2.2), 4.7 (3.6-6.2), and 7.4 (4.6-11.9) higher odds of discontinuing before completing treatment; phase 2 findings were similar. CONCLUSIONS: Four behavioral predictors recorded early in therapy were more strongly associated with subsequent discontinuation than participant characteristics, particularly when more than 1 behavioral predictor was recorded. Clinical Trials Registration. NCT00170209; NCT00931736.
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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 | 0.071 | 0.117 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.027 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".