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VOLUME 24 , ISSUE 4 ( April, 2020 ) > List of Articles

Original Article

Evaluation and Validation of Four Scoring Systems: the APACHE IV, SAPS III, MPM0 II, and ICMM in Critically Ill Cancer Patients

Keywords : Acute physiology and chronic health evaluation IV, Cancer, Intensive care unit cancer mortality model, Intensive care unit mortality, Intensive care unit outcome, Mortality probability models II at 0 hours, Severity-of-illness scoring systems, Simplified acute physiology score 3

Citation Information : Evaluation and Validation of Four Scoring Systems: the APACHE IV, SAPS III, MPM0 II, and ICMM in Critically Ill Cancer Patients. Indian J Crit Care Med 2020; 24 (4):263-269.

DOI: 10.5005/jp-journals-10071-23407

License: CC BY-NC 4.0

Published Online: 01-08-2019

Copyright Statement:  Copyright © 2020; The Author(s).


Background and aims: To evaluate and validate four severity-of-illness scores, acute physiology and chronic health evaluation IV (APACHE IV), simplified acute physiology score III (SAPS III), mortality probability models II at 0 hours (MPM0 II), and ICU cancer mortality model (ICMM), in a prospective cohort of critically ill cancer patients. Materials and methods: Single-center, prospective observational study performed in a 14-bedded combined medical–surgical ICU of a tertiary care cancer center of India, from July 2014 to November 2015. Score performance was judged by discrimination and calibration, using the area under receiver–operating characteristics (ROC) curve and Hosmer–Lemeshow goodness-of-fit test, respectively. Results: A total of 431 patients were included in the study. Intensive care unit (ICU) and hospital mortality were 37.4% and 41.1%, respectively. The area under ROC curve for APACHE IV, SAPS III, MPM0 II, and ICMM were 0.73, 0.70, 0.67, and 0.67, respectively. Calibration as calculated by Hosmer–Lemeshow analysis type C statistics for APACHE IV, SAPS III, MPM0 II, and ICMM shows good calibration with Chi-square values of 5.32, 9.285, 9.873, and 9.855 and p values of 0.723, 0.319, 0.274, and 0.275, respectively. Conclusion: All the four models had moderate discrimination and good calibration. However, none of the mortality prediction models could accurately discriminate between survivors and nonsurvivors in our patients.

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