Multidrug-resistant tuberculosis (MDR-TB) is burgeoning globally, and has been a serious challenge in TB management. Clinically, the ability to identify MDR-TB is still limited, especially in smear-negative TB. The aim of this study was to develop a nomogram for predicting MDR-TB. Demographics and clinical characteristics of both MDR-TB and drug-susceptible TB patients were utilized to develop a nomogram for predicting MDR-TB. The LASSO regression method was applied to filter variables and select predictors, and multivariate logistic regression was used to construct a nomogram. The discriminatory ability of the model was determined by calculating the area under the curve (AUC). Moreover, calibration analysis and decision curve analysis (DCA) of the model were performed. This study involved a second analysis of a completed prospective cohort study conducted in a country with a high TB burden. Five variables of TB patients were selected through the LASSO regression method, and a nomogram was built based on these variables. The predictive model yielded an AUC of 0.759 (95% CI, 0.719–0.799), and in the internal validation, the AUC was 0.757 (95% CI, 0.715–0.793). The predictive model was well-calibrated, and DCA showed that if the threshold probability of MDR-TB was between 70 and 90%, using the proposed nomogram to predict MDR-TB would obtain a net benefit. In this study, a nomogram was constructed that incorporated five demographic and clinical characteristics of TB patients. The nomogram may be of great value for the prediction of MDR-TB in patients with sputum-free or smear-negative TB.

中文翻译：

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用线照相术可以预测耐多药结核病。

耐多药结核病（MDR-TB）在全球范围内迅速发展，并且一直是结核病管理中的严峻挑战。临床上，鉴定耐多药结核病的能力仍然有限，尤其是在涂片阴性结核病中。这项研究的目的是开发用于预测耐多药结核病的诺模图。耐多药结核病和药物敏感性结核病患者的人口统计学和临床​​特征被用于开发诺模图以预测耐多药结核病。LASSO回归方法用于过滤变量和选择预测变量，多元logistic回归用于构造列线图。模型的区分能力是通过计算曲线下的面积（AUC）来确定的。此外，进行了模型的校准分析和决策曲线分析（DCA）。这项研究包括对在结核病高负担国家进行的一项完整的前瞻性队列研究的第二次分析。通过LASSO回归方法选择了五个结核病患者变量，并基于这些变量构建了列线图。预测模型得出的AUC为0.759（95％CI，0.719-0.799），而在内部验证中，AUC为0.757（95％CI，0.715-0.793）。预测模型已得到很好的校准，DCA显示，如果耐多药结核病的阈值概率在70％至90％之间，使用拟议的诺模图预测耐多药结核病将获得净收益。在这项研究中，构造了诺模图，其中包含了结核病患者的五个人口统计学和临床​​特征。诺模图对于无痰或涂片阴性结核病患者的MDR-TB预测可能具有重要价值。