Effectiveness and safety of standardised shorter regimens for multidrug-resistant tuberculosis: individual patient data and aggregate data meta-analyses
Bibliographic record
Abstract
We assessed the effectiveness and safety of standardised, shorter multidrug-resistant tuberculosis (MDR-TB) regimens by pooling data from observational studies.Published studies were identified from medical databases; unpublished studies were identified from expert consultation. We conducted aggregate data meta-analyses to estimate pooled proportions of treatment outcomes and individual patient data (IPD) meta-regression to identify risk factors for unsuccessful treatment in patients treated with 9- to 12-month MDR-TB regimens composed of a second-line injectable, gatifloxacin/moxifloxacin, prothionamide, clofazimine, isoniazid, pyrazinamide and ethambutol.We included five studies in which 796 out of 1279 (62.2%) individuals with confirmed MDR-TB (98.4%) or rifampin-resistant TB (1.6%), and not previously exposed to second-line drugs, were eligible for shorter regimens. 669 out of 796 participants were successfully treated (83.0%, 95% CI 71.9-90.3%). In IPD meta-regression (three studies, n=497), failure/relapse was associated with fluoroquinolone resistance (crude OR 46, 95% CI 8-273), pyrazinamide resistance (OR 8, 95% CI 2-38) and no culture conversion by month 2 of treatment (OR 7, 95% CI 3-202). Two participants acquired extensive drug resistance. Four studies reported grade 3 or 4 adverse events in 55 out of 304 (18.1%) participants.Shorter regimens were effective in treating MDR-TB; however, there is uncertainty surrounding the generalisability of the high rate of treatment success to less selected populations, to programmatic settings and in the absence of drug susceptibility tests to key component drugs.
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How this classification was reachedexpand
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 | 0.016 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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, unvalidatedMachine predicted; a candidate call from one teacher head, 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".