A novel risk factor for predicting anti-tuberculosis drug resistance in patients with tuberculosis complicated with type 2 diabetes mellitus.

This study aimed to explore the relationship between glycosylated hemoglobin (HbA1c) and the risk of anti-tuberculosis (TB) drug resistance for TB-type 2 diabetes mellitus (T2DM) patients. From March 2014 to June 2019, medical records from multiple centers were searched. Logistic regression analyses were performed. A predictive model for multidrug-resistance (MDR) was developed and validated. Calibration and discrimination of the model were assessed. Inconsistent results were found in the systemic review. A multicenter chart review with 657 records was thus conducted. The HbA1c <7% group and HbA1c ≥7% group had 390 and 267 patients, respectively. The HbA1c<7% group had a lower risk of developing rifampicin resistance, isoniazid resistance and MDR, with odd ratios (ORs) of 1.904 (p=0.001), 2.896 (p<0.001) and 3.228 (p<0.001), respectively. The between-group differences in the risk of anti-TB drug resistance were analyzed based on data from three provinces in China. After adding HbA1c grading, the predictive model for MDR (https://mengyuan.shinyapps.io/Shinyapp/) showed excellent capacity with an AUC of 75.4% in the training set (Sichuan and Gansu) and 73.9% in the internal validation set (Henan). The performances in calibration, prediction probabilities and net clinical benefit were significantly improved by HbA1c grading. HbA1c grading was an independent risk factor for isoniazid resistance and MDR in TB-T2DM patients.

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