Evidence-based Definition for Extensively Drug-Resistant Tuberculosis
Bibliographic record
Abstract
Abstract Rationale Until 2020, extensively drug-resistant tuberculosis (XDR-TB) was defined as TB with resistance to rifampicin and isoniazid (multidrug-resistant TB [MDR-TB]), any fluoroquinolone (FQ), and any second-line injectable drug (SLID). In 2019, the World Health Organization issued new recommendations for treating patients with drug-resistant TB, substantially limiting the role of SLIDs in MDR-TB treatment and thus putting the definition of XDR-TB into question. Objectives To propose an up-to-date definition for XDR-TB. Methods We used a large data set to assess treatment outcomes for patients with MDR-TB exposed to any type of longer regimen. We included patients with bacteriologically confirmed MDR-TB and known FQ and SLID resistance results. We performed logistic regression to estimate the adjusted odds ratios (aORs) for an unfavorable treatment outcome (failure, relapse, death, loss to follow-up), and estimates were stratified by the resistance pattern (FQ and/or SLID) and group A drug use (moxifloxacin/levofloxacin, linezolid, and/or bedaquiline). Measurements and Main Results We included 11,666 patients with MDR-TB; 4,653 (39.9%) had an unfavorable treatment outcome. Resistance to FQs increased the odds of an unfavorable treatment outcome (aOR, 1.91; 95% confidence interval [CI], 1.63–2.23). Administration of bedaquiline and/or linezolid improved treatment outcomes regardless of resistance to FQs and/or SLIDs. Among patients with XDR-TB, compared with persons receiving no group A drug, aORs for an unfavorable outcome were 0.37 (95% CI, 0.20–0.69) with linezolid only, 0.40 (95% CI, 0.21–0.77) with bedaquiline only, and 0.21 (95% CI, 0.12–0.38) with both. Conclusions Our study supports a new definition of XDR-TB as MDR-TB and additional resistance to FQ plus bedaquiline and/or linezolid and helps assess the adequacy of this definition for surveillance and treatment choice.
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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 | 0.049 | 0.200 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.020 | 0.010 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".