Bedaquiline safety, efficacy, utilization and emergence of resistance following treatment of multidrug-resistant tuberculosis patients in South Africa: a retrospective cohort analysis
Bibliographic record
Abstract
Abstract Background This retrospective cohort study assessed benefits and risks of bedaquiline treatment in multidrug-resistant-tuberculosis (MDR-TB) combination therapy by evaluating safety, effectiveness, drug utilization and emergence of resistance to bedaquiline. Methods Data were extracted from a register of South African drug-resistant-tuberculosis (DR-TB) patients (Electronic DR-TB Register [EDRWeb]) for newly diagnosed patients with MDR-TB (including pre-extensively drug-resistant [XDR]-TB and XDR-TB and excluding rifampicin-mono-resistant [RR]-TB, as these patients are by definition not multidrug-resistant), receiving either a bedaquiline-containing or non-bedaquiline-containing regimen, at 14 sites in South Africa. Total duration of treatment and follow-up was up to 30 months, including 6 months’ bedaquiline treatment. WHO treatment outcomes within 6 months after end-of-treatment were assessed in both patient groups. Longer term mortality (up to 30 months from treatment start) was evaluated through matching to the South African National Vital Statistics Register. Multivariable Cox proportional hazards analyses were used to predict association between receiving a bedaquiline-containing regimen and treatment outcome. Results Data were extracted from EDRWeb for 5981 MDR-TB patients (N = 3747 bedaquiline-treated; N = 2234 non-bedaquiline-treated) who initiated treatment between 2015 and 2017, of whom 40.7% versus 80.6% had MDR-TB. More bedaquiline-treated than non-bedaquiline-treated patients had pre-XDR-TB (27.7% versus 9.5%) and XDR-TB (31.5% versus 9.9%) per pre-2021 WHO definitions. Most patients with treatment duration data (94.3%) received bedaquiline for 6 months. Treatment success (per pre-2021 WHO definitions) was achieved in 66.9% of bedaquiline-treated and 49.4% of non-bedaquiline-treated patients. Death was reported in fewer bedaquiline-treated (15.4%) than non-bedaquiline-treated (25.6%) patients. Bedaquiline-treated patients had increased likelihood of treatment success and decreased risk of mortality versus non-bedaquiline-treated patients. In patients with evaluable drug susceptibility testing data, 3.5% of bedaquiline-susceptible isolates at baseline acquired phenotypic resistance. Few patients reported bedaquiline-related treatment-emergent adverse events (TEAEs) (1.8%), TEAE-related bedaquiline discontinuations (1.4%) and QTcF values > 500 ms (2.5%) during treatment. Conclusion Data from this large cohort of South African patients with MDR-TB showed treatment with bedaquiline-containing regimens was associated with survival and effectiveness benefit compared with non-bedaquiline-containing regimens. No new safety signals were detected. These data are consistent with the positive risk–benefit profile of bedaquiline and warrant continued implementation in combination therapy for MDR-TB treatment.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Dataset About the Canadian research system: no · About a Canadian topic: no | Observational | medium |
| gpt | no category Domain: not available · Genre: Dataset About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.269 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".