ArticleFrontiers in immunology2025
A nomogram for predicting unfavorable outcomes of antituberculosis treatment among individuals with AIDS combined with pulmonary tuberculosis in China.
Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- A Novel Clinical Nomogram for Predicting Unfavorable Tuberculosis Treatment Outcomes: A Logistic Regression Risk Model.Journal of epidemiology and global health · 2026Article
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13 authors.
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Abstract
Background: Acquired Immune Deficiency Syndrome (AIDS) combined with tuberculosis (TB) is one of the key factors affecting global TB control, and timely and effective treatment is essential to improve the prognosis in this population. However, data from the WHO have shown that patients with AIDS combined with TB have a lower anti-TB treatment success rate than HIV-negative individuals do, which may lead to an increased incidence of treatment relapse and drug resistance. Therefore, exploring the risk factors affecting the outcome of anti-TB treatment in patients with AIDS combined with TB and developing relevant predictive models will help clinicians rapidly identify patients at greater risk of treatment failure, which is highly valuable for clinical management. Methods: We conducted a retrospective cohort study including inpatients with AIDS combined with pulmonary tuberculosis (PTB) who were treated at Beijing Youan Hospital between January 2020 and January 2024. The baseline data and laboratory test data of all enrolled patients were collected from the electronic medical records system. We randomly divided the participants into a training set and a validation set at a ratio of 2:1 and established a LASSO Cox model on the basis of the training set to identify risk factors affecting the outcome of anti-TB treatment. The selected prognostic factors were then used to construct the final Cox model, which was visualized using a nomogram. The receiver operating characteristic (ROC) curves, concordance index (C-index), and calibration curves of the training set and validation set were used to evaluate the discrimination ability and consistency of the model, respectively. Decision curve analysis (DCA) was used to assess the clinical applicability of the prognostic models. Patients were subsequently risk stratified according to the optimal cutoff value selected by X-tile software for better clinical decision-making by clinicians. Results: A total of 203 inpatients with AIDS combined with PTB were enrolled in this study, including 141 (69.5%) with treatment success and 62 (30.5%) with unfavorable outcome. The results of the LASSO Cox regression model revealed that the CRP/albumin ratio (CAR), extrapulmonary disseminated tuberculosis, other pulmonary infectious diseases, and pulmonary cavitation were independent risk factors for unfavorable outcomes in patients with AIDS combined with PTB, whereas the CD4 Conclusion: We identified prognostic factors for unfavorable anti-TB treatment outcomes and constructed a predictive nomogram to assess the risk of treatment failure in patients with AIDS combined with PTB. Our model performed satisfactorily and can be used for the clinical screening and management of high-risk patients.
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