Performance of Three Prognostic Models in Critically Ill Patients with Cancer: A Prospective Study

Abstract

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 was superior for APACHE-IICCP model (AROC 0.98) compared to APACHE-II (AROC 0.96), SAPS-3 (AROC 0.91), and SAPS-3 for Central and South American countries (SAPS-3CSA) (AROC 0.95) models. Calibration was good (p-valueof 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 model (standardized mortality ratio, SMR = 1.03). Further analysis showed that discrimination was better with APACHE-IICCP model than with APACHE-II, SAPS-3, and SAPS-3CSA models whether for patients with planned ICU admission (AROC 0.97 vs. 0.96, 0.95 and 0.95, respectively) or for patients with unplanned ICU admission (AROC 0.97 vs. 0.94, 0.86 and 0.95). When the SMR and calibration were analyzed, the APACHE-IICCP model was the only model to provide predicted mortality rates closer to the observed mortality for patients with planned and for patients with unplanned ICU admission. Conclusions: In this prospective study, APACHE-IICCP model was superior to APACHE-II, SAPS-3, and SAPS3CSA models in predicting hospital mortality.