A Scoring System Based on Laboratory Parameters and Clinical Features to Predict Unfavorable Treatment Outcomes in Multidrug- and Rifampicin-Resistant Tuberculosis Patients

基于实验室参数和临床特征的评分系统预测多重耐药和利福平耐药结核病患者的不良治疗结果

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Abstract

BACKGROUND: The growth of antibiotic resistance to Mycobacterium TB represents a major barrier to the goal of "Ending the global TB epidemics". This study aimed to develop and validate a simple clinical scoring system to predict the unfavorable treatment outcomes (UTO) in multidrug- and rifampicin-resistant tuberculosis (MDR/RR-TB) patients. METHODS: A total of 333 MDR/RR-TB patients were recruited retrospectively. The clinical, radiological and laboratory features were gathered and selected by lasso regression. These variables with area under the receiver operating characteristic curve (AUC)>0.6 were subsequently submitted to multivariate logistic analysis. The binomial logistic model was used for establishing a scoring system based on the nomogram at the training set (N = 241). Then, another independent set was used to validate the scoring system (N = 92). RESULTS: The new scoring system consists of age (8 points), education level (10 points), bronchiectasis (4 points), red blood cell distribution width-coefficient of variation (RDW-CV) (7 points), international normalized ratio (INR) (7 points), albumin to globulin ratio (AGR) (5 points), and C-reactive protein to prealbumin ratio (CPR) (6 points). The scoring system identifying UTO has a discriminatory power of 0.887 (95% CI=0.835-0.939) in the training set, and 0.805 (95% CI=0.714-0.896) in the validation set. In addition, the scoring system is used exclusively to predict the death of MDR/RR-TB and has shown excellent performance in both training and validation sets, with AUC of 0.930 (95% CI=0.872-0.989) and 0.872 (95% CI=0.778-0.967), respectively. CONCLUSION: This novel scoring system based on seven accessible predictors has exhibited good predictive performance in predicting UTO, especially in predicting death risk.

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