Factors associated with time to relapse in pulmonary tuberculosis patients using penalized Cox models

Abstract

Abstract Background Pulmonary tuberculosis (TB) is a contagious bacterial infection caused by Mycobacterium tuberculosis that primarily affects the lungs. Despite advances in treatment, TB remains a major public health challenge, particularly in developing countries. This retrospective cohort study aimed to identify factors that influence the time to relapse in patients with pulmonary tuberculosis. Methods All smear-positive pulmonary tuberculosis patients (1548 patients) whose data were recorded in the tuberculosis registration system of Golestan University of Medical Sciences and Health Services from March 2014 to March 2019, and followed up until February 2021. To analyze the data, we applied LASSO, MCP, and SCAD penalized Cox models. Results Based on the AIC and BIC criteria, the MCP penalized model was better than the LASSO and SCAD penalized models. The variables of age at diagnosis (> 35 vs. $$\le$$ ≤ 35, HR = 2.77), marital status (married vs. single, HR = 8.49), chronic renal failure (Yes vs. No, HR = 5.36), and pre-treatment smear test results (+ 1 vs. 1-9Basil, HR = 0.65 and + 2 vs. 1-9Basil, HR = 0.96) influenced time to relapse according to the MCP penalized Cox regression model. Conclusions Health care systems should focus on identification of factors that influence time to relapse and developing interventions to reduce relapse rates.

Keywords

• Penalized Cox models
• Minimum concave penalty
• Smoothly clipped absolute deviation
• LASSO
• Pulmonary tuberculosis