Objectives: 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.
Methods: 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.
Results: 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.
Conclusions: HbA1c grading was an independent risk factor for isoniazid resistance and MDR in TB-T2DM patients.
Keywords: Diabetes mellitus; Drug resistance; HbA1c; Predictive model; Tuberculosis.
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