Published online Nov 9, 2022. doi: 10.5492/wjccm.v11.i6.364
Peer-review started: April 26, 2022
First decision: June 8, 2022
Revised: June 12, 2022
Accepted: September 9, 2022
Article in press: September 9, 2022
Published online: November 9, 2022
Processing time: 191 Days and 9.6 Hours
Scoring systems have not been evaluated in oncology patients. We aimed to assess the performance of Acute Physiology and Chronic Health Evaluation (APACHE) II, APACHE III, APACHE IV, Simplified Acute Physiology Score (SAPS) II, SAPS III, Mortality Probability Model (MPM) II0 and Sequential Organ Failure Ass
To compare the efficacy of seven commonly employed scoring systems to predict outcomes of critically ill cancer patients.
We conducted a retrospective analysis of 400 consecutive cancer patients admitted in the medical intensive care unit over a two-year period. Primary outcome was hospital mortality and the secondary outcome measure was comparison of var
In our study, the overall intensive care unit and hospital mortality was 43.5% and 57.8%, respectively. All of the seven tested scores underestimated mortality. The mortality as predicted by MPM II0 predicted death rate (PDR) was nearest to the actual mortality followed by that predicted by APACHE II, with a standardized mortality rate (SMR) of 1.305 and 1.547, respectively. The best calibration was shown by the APACHE III score (χ2 = 4.704, P = 0.788). On the other hand, SOFA score (χ2 = 15.966, P = 0.025) had the worst calibration, although the difference was not statistically significant. All of the seven scores had acceptable discrimination with good efficacy however, SAPS III PDR and MPM II0 PDR (AUROC = 0.762), had a better performance as compared to others. The correlation between the different scoring sys
All the severity scores were tested under-predicted mortality in the present study. As the diff
Core Tip: Scoring systems are important for patient triaging, benchmarking intensive care unit (ICU) performance, comparing different ICUs and may also help in patient prognostication, selecting treatment options and resource utilization. However, validity and utility of these scores may be questionable in the patient population apart from where they were developed. Hence, these scores need to be tested and validated in different patient populations, in different geographical areas and over different time periods. There is a lack of an ideal score for prognostication of critically ill cancer patients. In our retrospective study, analyzing data from 400 patients and comparing seven commonly employed critical illness scores, we observed that all the scores had similar efficacy and under-predicted mortality. Therefore, the selection of severity of illness score should depend on the ease of use and local preferences.