ArticleBMC infectious diseases2023
Development and validation of a prediction model for unsuccessful treatment outcomes in patients with multi-drug resistance tuberculosis.
Article in BMC infectious diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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11 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Systematic review and meta-analysis of predictive accuracy of prognostic models for poor treatment outcome of drug resistance tuberculosis.Scientific reports · 2026Pooled it
- New Strategies in Tuberculosis Prediction: TB-CAST, an Explainable Baseline Score for Two-Month Sputum Culture Positivity.Life (Basel, Switzerland) · 2026Article
- Clinical epidemiology and risk prediction of unsuccessful treatment outcomes in pulmonary tuberculosis with diabetes mellitus.BMC medicine · 2026Article
- A Novel Clinical Nomogram for Predicting Unfavorable Tuberculosis Treatment Outcomes: A Logistic Regression Risk Model.Journal of epidemiology and global health · 2026Article
- Development and validation of a clinical nomogram for predicting suboptimal concentration of valproate in pediatric with epilepsy: a retrospective study.Frontiers in pharmacology · 2026Article
- The Predictive Value of Dynamic Changes in Procalcitonin and C-Reactive Protein in Evaluating Response of Patients with Pulmonary Tuberculosis in the Early Treatment.Infection and drug resistance · 2026Article
- Identification of risk factors for latent tuberculosis infection in Xinjiang using machine learning.BMC public health · 2025Article
- Treatment outcomes of short-regimen multi-drug resistant tuberculosis in uMkhanyakude district (2018-2022) South Africa: a retrospective, cross-sectional study.BMC infectious diseases · 2025Article
- A nomogram for predicting unfavorable outcomes of antituberculosis treatment among individuals with AIDS combined with pulmonary tuberculosis in China.Frontiers in immunology · 2025Article
- Malnutrition and unsuccessful tuberculosis treatment among people with multi-drug resistant tuberculosis in Uganda: A retrospective analysis.Journal of clinical tuberculosis and other mycobacterial diseases · 2024Article
- Applying a Combined Model to Evaluate the Risk of Poor Treatment Outcomes in Rifampicin Resistant Tuberculosis Patients: A Multicenter Retrospective Study.Infection and drug resistance · 2024Article
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe World Health Organization has reported that the treatment success rate of multi-drug resistance tuberculosis is approximately 57% globally. Although new drugs such as bedaquiline and linezolid is likely improve the treatment outcome, there are other factors associated with unsuccessful treatment outcome. The factors associated with unsuccessful treatment outcomes have been widely examined, but only a few studies have developed prediction models. We aimed to develop and validate a simple clinical prediction model for unsuccessful treatment outcomes in patients with multi-drug resistance pulmonary tuberculosis (MDR-PTB).
methodsThis retrospective cohort study was performed between January 2017 and December 2019 at a special hospital in Xi'an, China. A total of 446 patients with MDR-PTB were included. Least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression were used to select prognostic factors for unsuccessful treatment outcomes. A nomogram was built based on four prognostic factors. Internal validation and leave-one-out cross-validation was used to assess the model.
resultsOf the 446 patients with MDR-PTB, 32.9% (147/446) cases had unsuccessful treatment outcomes, and 67.1% had successful outcomes. After LASSO regression and multivariate logistic analyses, no health education, advanced age, being male, and larger extent lung involvement were identified as prognostic factors. These four prognostic factors were used to build the prediction nomograms. The area under the curve of the model was 0.757 (95%CI 0.711 to 0.804), and the concordance index (C-index) was 0.75. For the bootstrap sampling validation, the corrected C-index was 0.747. In the leave-one-out cross-validation, the C-index was 0.765. The slope of the calibration curve was 0.968, which was approximately 1.0. This indicated that the model was accurate in predicting unsuccessful treatment outcomes.
conclusionsWe built a predictive model and established a nomogram for unsuccessful treatment outcomes of multi-drug resistance pulmonary tuberculosis based on baseline characteristics. This predictive model showed good performance and could be used as a tool by clinicians to predict who among their patients will have an unsuccessful treatment outcome.
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