RESUMEN
BACKGROUND: The aim of the study was to evaluate the performance of "Acute Physiology and Chronic Health Evaluation II" (APACHE-II), "Simplified Acute Physiology Score 3" (SAPS-3), and "APACHE-II Score for Critically Ill Patients with a Solid Tumor" (APACHE-IICCP) models in cancer patients admitted to ICU. METHODS: Prospective cohort study of 414 patients with an active solid tumor. Discrimination was assessed by area under receiver operating characteristic (AROC) curves and calibration by Hosmer-Lemeshow goodness-of-fit C test (H-L). RESULTS: The hospital mortality rate was 32.6%. In the total cohort, discrimination for prognostic models were: APACHE-IICCP (AROC 0.98), APACHE-II (AROC 0.96), SAPS-3 for Central and South American countries (SAPS-3CSA) (AROC 0.95), and SAPS-3 (AROC 0.91). Calibration was good (p value of H-L test > 0.05) using APACHE-IICCP, APACHE-II and SAPS-3CSA models. Estimation of the probability of death was more precise with APACHE-IICCP (standardized mortality ratio, SMR = 1.03) and SAPS-3 (SMR = 1.08) models. Further analysis showed that discrimination was high with all prognostic model whether for patients with planned ICU admission (AROC APACHE-IICCP 0.97, APACHE-II 0.96, SAPS-3 0.95, SAPS-3CSA 0.95) or for patients with unplanned ICU admission (AROC APACHE-IICCP 0.97, APACHE-II 0.94, SAPS-3 0.86, SAPS-3CSA 0.95). Calibration was good for all predictive models in both subgroups (p value of H-L test > 0.05, except for APACHE-II model inpatients with planned ICU admission). CONCLUSIONS: In this prospective study, general predictive models (e.g., APACHE-II, SAPS-3) and cancer-specific models (e.g., APACHE-IICCP) are accurate in predicting hospital mortality. Other studies confirming these results are required.