To analyze the treatment situation of multi-drug resistant pulmonary tuberculosis in a certain area, and to build a prediction model for the treatment compliance of such patients.

All of 148 patients with multidrug-resistant pulmonary tuberculosis admitted to our hospital from March 2019 to December 2022 were selected as the research object, and the treatment status of the patients was followed up for 6 months. 39 patients with Morisky medication adherence scale (MMAS) <6 points were the observation group, and 109 patients with MMAS 6-8 points were the control group, the influencing factors of treatment compliance were confirmed by multivariate Logistic regression equation, which was used to construct a nomogram prediction model of poor treatment compliance of patients with drug-resistant tuberculosis.

Sputum culture in 81 cases (54.73%) turned negative, MMAS score was (6.15±1.03), 67 cases (45.27%) did not turn negative, MMAS score was (5.76±1.05) points (P<0.05). The age of the observation group [(51.05±8.23) vs. (46.18±7.59)] years, the number of drug types (>6) [27 cases (69.23%) vs. 52 cases (47.71%)] and the adverse reactions after medication [12 cases (30.77%) vs. 16 cases (14.68%)] were higher than those of the control group. Years of education [(9.65±2.62) vs. (11.20±3.17)], average monthly personal income (<3 000 yuan) [19 cases (48.72%) vs. 21 cases (19.27%)], SSRS score [(35.15±4.02) vs. (40.36±6.18)] and the proportion of disease education [18 cases (46.15%) vs. 71 cases (65.14%)] were lower than those in the control group (P<0.05). Multivariate Logistic regression coefficient analysis showed that age (OR=1.158), years of education (OR=0.815), personal average monthly income (<3, 000 yuan) (OR=27.408) and SSRS score (OR=0.860) were independent influencing factors of treatment compliance of patients with multidrug-resistant pulmonary tuberculosis (P<0.05). The nomogram prediction model shows that the score of nomogram model increases by 9 points every time the patient′s age increases by 5 years; For every 2 years of education, the score of nomogram model will increase by 5 points; The nomogram score corresponding to an average monthly income of less than 3, 000 yuan is 27.5 points; For every 5 points of SSRS score reduction, the nomogram model increases by 13.5 points. The ROC curve shows that the AUC of the nomogram prediction model is 0.871 (95%CI: 0.811-0.931). The slope of calibration curve and Hosmer-Lemeshow goodness-of-fit test (χ²=7.347, P=0.500) showed that the nomogram model predicted the risk of treatment noncompliance in patients with multi-drug-resistant tuberculosis and the actual risk was in good agreement.

After 6 months of treatment, 54.73% of patients with multi-drug-resistant pulmonary tuberculosis turned negative. Age, years of education, average monthly income and low level of social support are the independent risk factors of patients′poor treatment compliance. The nomogram model of patients′poor treatment compliance formed by integrating these risk factors can be applied to predict the risk of patients′poor treatment compliance in clinic and provide value for improving the treatment effect of diseases.