ArticlePeerJ2025
Development and validation of a nomogram predicting multidrug-resistant tuberculosis risk in East China.
Article in PeerJ, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Development and validation of a LASSO-derived nomogram for predicting unfavorable treatment outcomes in drug-resistant pulmonary tuberculosis.BMC infectious diseases · 2026Article
- Predictive Analysis of Drug-Resistant Tuberculosis: Integrating Molecular Markers, Clinical Governance, and Community-Engaged Education in Rural South Africa.Diseases (Basel, Switzerland) · 2026Article
- Accuracy of Machine Learning in Identifying Drug Resistance in Tuberculosis: A Systematic Review and Meta-Analysis.Health science reports · 2025Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Multidrug-resistant tuberculosis (MDR-TB) is a global health threat. Our study aimed to develop and externally validate a nomogram to estimate the probability of MDR-TB in patients with TB. Methods: A total of 453 patients with TB in Anhui Chest Hospital between January 2019 and December 2020 were included in the training cohort. In addition, 116 patients with TB from Anhui Provincial Hospital Infection District between January 2015 and November 2023 were included in the validation cohort. Multivariable logistic regression analysis was applied to build a predictive model by combining the feature selected in the least absolute shrinkage and selection operator regression model. The Results: Eight variables of patients with TB were selected using the best penalization parameter of the LASSO regression method, and the nomogram was established. The model displayed good discrimination with a Conclusion: In this study, we constructed the LASSO regression model based on eight clinical traits and outcomes of laboratory tests, providing a novel insight for evaluating MDR-TB.
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