Machine Learning Prediction of Prolonged Length of Stay in Older Patients with Lung Cancer: A Multicenter Study Using XGBoost with SHAP Interpretation

Background

Prolonged length of stay (PLOS) is common among older patients with lung cancer and is associated with increased risks of adverse outcomes, greater healthcare resource utilization, and reduced treatment efficiency. However, reliable risk stratification tools specifically designed for this population, particularly in the Chinese healthcare context, remain lacking.