Performance of Three Prognostic Models in Patients with Cancer in Need of Intensive Care in a Medical Center in China

Abstract

ObjectiveThe aim of this study was to evaluate the performance of Acute Physiology and Chronic Health Evaluation II (APACHE II), Simplified Acute Physiology Score 3 (SAPS 3), and Acute Physiology and Chronic Health Evaluation IV (APACHE IV) in patients with cancer admitted to intensive care unit (ICU) in a single medical center in China.Materials and MethodsThis is a retrospective observational cohort study including nine hundred and eighty one consecutive patients over a 2-year period.ResultsThe hospital mortality rate was 4.5%. When all 981 patients were evaluated, the area under the receiver operating characteristic curve (AUROC, 95% Confidential Intervals) of the three models in predicting hospital mortality were 0.948 (0.914–0.982), 0.863 (0.804–0.923), and 0.873 (0.813–0.934) for SAPS 3, APACHE II and APACHE IV respectively. The p values of Hosmer-Lemeshow statistics for the models were 0.759, 0.900 and 0.878 for SAPS 3, APACHE II and APACHE IV respectively. However, SAPS 3 and APACHE IV underestimated the in-hospital mortality with standardized mortality ratio (SMR) of 1.5 and 1.17 respectively, while APACHE II overestimated the in-hospital mortality with SMR of 0.72. Further analysis showed that discrimination power was better with SAPS 3 than with APACHE II and APACHE IV whether for emergency surgical and medical patients (AUROC of 0.912 vs 0.866 and 0.857) or for scheduled surgical patients (AUROC of 0.945 vs 0.834 and 0.851). Calibration was good for all models (all p > 0.05) whether for scheduled surgical patients or emergency surgical and medical patients. However, in terms of SMR, SAPS 3 was both accurate in predicting the in-hospital mortality for emergency surgical and medical patients and for scheduled surgical patients, while APACHE IV and APACHE II were not.ConclusionIn this cohort, we found that APACHE II, APACHE IV and SAPS 3 models had good discrimination and calibration ability in predicting in-hospital mortality of critically ill patients with cancer in need of intensive care. Of these three severity scores, SAPS 3 was superior to APACHE II and APACHE IV, whether in terms of discrimination and calibration power, or standardized mortality ratios.

Utilization of a rapid response team and associated outcomes in patients with malignancy

“…The APACHE II scoring system is an accurate measurement of clinical severity and correlates strongly with outcome in critically ill patients [21]. Consistent with our results, previous studies demonstrated effectiveness of APACHE II score for predicting in-hospital mortality of critically ill patients with cancer in need of intensive care [22,23]. Our findings emphasize that the prognosis of cancer patients is determined by severity at the time of RRT activation regardless of malignancy status.…”

The Effectiveness of Scoring Systems in the Prediction of Diagnosis‐Based Mortality

“…In a study by Ulus et al, APACHE II was reported to be successful in determining the mortality rate in 100 patients with respiratory failure . In a similar study by Xing et al, SAPS III was found to be good in respect of discrimination and calibration, and good in the prediction of mortality in patients with respiratory system diseases and pneumonia . In the current study, SAPS III and APACHE IV were successful in terms of discrimination and calibration ability and highly successful in terms of estimating the SMR and mortality rates in the group of respiratory system diseases, including pneumonia patients, whereas APACHE II did not show the same success.…”

“…In a study by Chan et al, APACHE IV was found to be inadequate for predicting mortality in abdominal sepsis patients (12). In a study by Xing et alin which patients were separated into diagnosis groups, SAPS III was determined to have excellent discrimination and calibration capabilities and fairly good mortality accuracy in sepsis patients (13). In the present study, the discrimination capability of all the scoring systems was found to be average but the calibration was found to be very good in the sepsis patients group.…”

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

“…In critically ill cancer patients, Soares, et al [4] observed that discrimination was good using SAPS-3 and SAPS-3 CSA models. Recently, Xing, et al [5] validated APACHE-II, APACHE-IV, and SAPS-3 models. Authors found that the performance of the three models was good.…”

“…Cancer patients account for 13-18% of patients admitted to intensive care units (ICU) [2,3]. General predictive models have been evaluated in cancer patients admitted to ICU [4,5]; however, generalization is difficult because of the limitations of studies.…”