Ten significant indicators (PLT, PCV, LYMPH, MONO%, NEUT, NEUT%, TBTL, ALT, UA, and Cys-C) were selected to generate the risk score. Internal validation was conducted by 10-fold cross-validation. We plotted the receiver operating characteristic (ROC) curve and calculated the area under the curve (AUC). Univariate and multivariate Cox regression models were used to assess the risk score, and the strength of association was expressed as the hazard ratio (HR) and 95% confidence interval (CI). We generated a risk score based on blood and biochemistry examination indicators by the least absolute shrinkage and selection operator (LASSO) Cox regression. We performed a two-stage study by recruiting 346 pulmonary tuberculosis patients diagnosed between 20 in Dafeng city as the training cohort and 132 patients diagnosed between 20 in Nanjing city as the external validation population. We conducted a prospective cohort study on patients with pulmonary tuberculosis to construct a clinical indicator-based model and estimate its performance. Identifying prognostic factors helps optimize the treatment regimen and promote favorable outcomes.
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