Nomogram for Predicting Poor Prognosis of Newly Diagnosed Active Pulmonary Tuberculosis Based on PNI: Development and Internal Validation

Objective: To investigate the correlation between the Prognostic Nutrition Index (PNI) and adverse prognosis in treatment-naive patients with active pulmonary tuberculosis(TB), and to construct and validate an individualized risk prediction nomogram. Methods: A retrospective study included 165 patients with newly diagnosed active TB from January 2022 to February 2025. Treatment outcomes at 2 and 6 months were classified as good prognosis (markedly effective) or poor prognosis (effective, ineffective, deteriorated). Optimal PNI cut-offs were determined by ROC. Predictors were selected using LASSO regression. A nomogram was constructed by multivariate Logistic regression and internally validated with 1000 bootstrap samples. Model performance was evaluated by ROC, calibration curve and decision curve analysis. Results: Optimal PNI cut-offs for poor prognosis at 2 and 6 months were 44.85 and 42.6. The nomogram achieved an AUC of 0.789 at 2 months. Adding PNI significantly improved discrimination (NRI=0.396, IDI=0.054). Calibration was satisfactory, and the model showed clinical net benefit. PNI provided greater incremental value for short-term prognosis. Conclusion: A PNI-based nomogram can effectively predict poor prognosis in newly diagnosed active TB patients. A PNI threshold of < 45 is recommended for high-risk screening to enable early nutritional and immune intervention. External validation is needed before widespread application.