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

<b>Background:</b> 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. <b>Methods:</b> A retrospective cohort of 207 clinical episodes from male patients with lung cancer and COPD was analyzed. Participants were categorized into Planned Readmission (PR, <i>n</i> = 165) and Unplanned Readmission (UR, <i>n</i> = 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). <b>Results:</b> 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, <i>p</i> < 0.001). Advanced cancer stage (III-IV) was also a significant predictor (OR = 3.590, 95% CI: 1.301-9.909, <i>p</i> = 0.014), while prealbumin (OR = 0.950, 95% CI: 0.896-1.007, <i>p</i> = 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. <b>Conclusions:</b> 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.