A Novel Nomogram Integrating Systemic Immune-Inflammation Index and Serum Prealbumin for Predicting Unplanned Readmission in Male Patients with Coexisting Lung Cancer and Chronic Obstructive Pulmonary Disease.

Patients with coexisting lung cancer and COPD are highly susceptible to unplanned readmissions. This study aimed to develop and internally validate a robust predictive nomogram based on the "inflammation-nutrition-tumor" framework to quantify this risk. A retrospective cohort of 207 clinical episodes from male patients with lung cancer and COPD was analyzed. Participants were categorized into Planned Readmission (PR, = 165) and Unplanned Readmission (UR, = 42) groups. Independent risk factors were identified via univariate and multivariable analyses using Generalized Estimating Equations (GEE). A nomogram was subsequently constructed, and its performance was rigorously evaluated using the Area Under the Curve (AUC), calibration plots, and Decision Curve Analysis (DCA). Multivariable GEE analysis demonstrated that the Systemic Immune-Inflammation Index (SII) was a highly significant independent risk factor (OR for a 500-unit increase = 1.490, 95% CI: 1.234-1.798, < 0.001). Advanced cancer stage (III-IV) was also a significant predictor (OR = 3.590, 95% CI: 1.301-9.909, = 0.014), while prealbumin (OR = 0.950, 95% CI: 0.896-1.007, = 0.087) was identified as a key nutritional predictor. The integrated four-variable nomogram (age, cancer stage, SII, prealbumin) demonstrated good discriminative ability with an AUC of 0.809 (95% CI: 0.733-0.885). The calibration plot indicated excellent agreement, and DCA confirmed a substantial clinical net benefit. This SII-based nomogram provides a reliable and practical tool for individualized risk stratification, facilitating targeted clinical interventions to mitigate unplanned readmission rates in this vulnerable population.