ArticleMedical science monitor : international medical journal of experimental and clinical research2026
Prognostic Factors and Risk Stratification in Malignant Tumor Patients With Sepsis: A Retrospective Cohort Study.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
BACKGROUND Sepsis is a life-threatening complication in cancer patients and a major contributor to ICU admission and mortality. Although tumor-related factors affect outcomes, the prognostic value of ICU-specific clinical parameters remains insufficiently explored. This study aimed to identify ICU-related predictors of mortality beyond tumor characteristics in cancer patients with sepsis. MATERIAL AND METHODS We conducted a single-center retrospective cohort study including 4301 cancer patients with sepsis. Independent predictors of 28-day mortality were identified using multivariable logistic regression. Model performance was evaluated using discrimination, calibration, decision curve analysis (DCA), and clinical impact curves. RESULTS Nine independent predictors of 28-day mortality were identified (all P<0.05). A nomogram incorporating these predictors demonstrated strong discriminative performance (original cohort AUC, 0.741; 95% CI, 0.722-0.759; validation cohort AUC, 0.758; 95% CI, 0.730-0.786), outperforming SAPS III (original AUC, 0.726; 95% CI, 0.707-0.745; validation AUC, 0.740; 95% CI, 0.710-0.770) and SOFA scores (original AUC, 0.696; 95% CI, 0.676-0.716; validation AUC, 0.723; 95% CI, 0.692-0.753). Calibration analysis demonstrated good agreement between predicted and observed mortality (original cohort: calibration intercept, 0.036; slope, 0.868; Brier score, 0.185; validation cohort: intercept, 0.014; slope, 0.940; Brier score, 0.174). DCA showed superior net clinical benefit across a wide range of threshold probabilities compared with "treat-all" and "treat-none" strategies. Clinical impact curves confirmed effective risk stratification, with predicted high-risk cases closely aligning with observed mortality events. CONCLUSIONS In this large cohort of cancer patients with combined sepsis, we identified independent predictors of 28-day mortality, offering a practical tool for individualized mortality risk stratification in this vulnerable population.
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