Albumin and Machine Learning Model for Predicting 28-day All-cause Mortality in ICU Patients with Lung Cancer

Serum albumin reflects nutritional status, systemic inflammation, and disease burden. However, its prognostic significance in critically ill patients with lung cancer remains unclear. This study aimed to investigate the association between serum albumin and 28-day all-cause mortality in intensive care unit (ICU) patients with lung cancer and to assess its predictive value in machine learning (ML) models. This retrospective cohort study included 1,274 adult ICU patients with lung cancer from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Multivariable Cox proportional hazards models evaluated the association between serum albumin and 28-day mortality. Additional analyses included restricted cubic splines, Kaplan-Meier survival curves, and subgroup analyses. ML classifiers were developed using the least absolute shrinkage and selection operator (LASSO) and Boruta for feature selection. Logistic regression was selected as the optimal model, with SHapley Additive Explanations (SHAP) values used for interpretation. Among 1,274 patients, the 28-day mortality rate was 26.9%. Lower serum albumin levels were independently associated with higher 28-day mortality. The hazard ratio for each 1 g/dL increase in serum albumin was 0.729 (95% CI, 0.597-0.891; p = 0.002). An inverse association was observed across serum albumin quartiles (p for trend <0.001), and Kaplan-Meier analysis showed lower mortality among patients with albumin ≥2.9 g/dL (log-rank p < 0.0001). The logistic regression model achieved an AUC of 0.767 in the validation cohort, indicating good discrimination and calibration. SHAP analysis identified serum albumin as a key predictor of 28-day mortality. Lower serum albumin was independently associated with increased short-term mortality in ICU patients with lung cancer. Serum albumin may serve as a practical biomarker for early risk stratification in this population. ML models incorporating albumin demonstrated strong predictive performance and interpretability.