Performance of three prognostic models in critically ill patients with cancer: a prospective study.

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-II) 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-II (AROC 0.98), APACHE-II (AROC 0.96), SAPS-3 for Central and South American countries (SAPS-3) (AROC 0.95), and SAPS-3 (AROC 0.91). Calibration was good (p value of H-L test > 0.05) using APACHE-II, APACHE-II and SAPS-3 models. Estimation of the probability of death was more precise with APACHE-II (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-II 0.97, APACHE-II 0.96, SAPS-3 0.95, SAPS-3 0.95) or for patients with unplanned ICU admission (AROC APACHE-II 0.97, APACHE-II 0.94, SAPS-3 0.86, SAPS-3 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-II) are accurate in predicting hospital mortality. Other studies confirming these results are required.