The American College of Surgeon's surgical risk calculator's ability to predict disposition in older gynecologic oncology patients undergoing laparotomy

Abstract

Objectives: The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) surgical risk calculator calculates risk of postoperative complications utilizing clinically apparent preoperative variables. If validated for patients with gynecologic , this can be an effective tool in to use for shared decision-making, especially in the older (70+ years of age) patient population for whom surgical risks and potential loss of independence is increased. The primary objective of this study was to evaluate the ability of the ACS NSQIP surgical risk calculator to predict discharge to a post-acute care among older (age 70+ years) gynecologic oncology patients undergoing laparotomy. The secondary objectives were to assess its ability to predict postoperative complications and death. Methods: This was a retrospective cohort study of gynecologic oncology patients 70+ years of age undergoing laparotomy. Surgical procedures, 21 preoperative variables, postoperative complications, and patient disposition were abstracted from the medical record. Risk scores for seven postoperative complications and discharge to post-acute care were calculated. The association between risk scores and outcomes were assessed using logistic regression and predictive ability was evaluated using the c-statistic and Brier score. Results: 204 surgeries were performed on 200 patients between January 1, 2009 and December 31, 2013. The mean age was 76.3±5.1 years; 87% were independent at baseline. A total of 79 (41%) were discharged to post-acute care. The calculator's ability to predict discharge to post-* Corresponding author at: Mayo Mail Code 395, 420 Delaware St SE, Minneapolis, MN 55417. AUTHOR CONTRIBUTIONS SS contributed to the data acquisition, quality control of data and algorithms, data analysis and interpretation, manuscript preparation, editing, and review. CR contributed to the study concepts and study design, manuscript editing, and manuscript review. RN contributed to the data acquisition, manuscript editing, and manuscript review. RIV contributed to the data analysis and interpretation, statistical analysis, manuscript preparation, editing, and review. DT contributed to the study design and concepts, quality control of data and algorithms, data analysis and interpretation, manuscript preparation, editing, and review.

A Prediction Model for Severe Complications after Elective Colorectal Cancer Surgery in Patients of 70 Years and Older

“…Moreover, the accuracy of the universal ACS-NSQIP model for severe complications and its performance for outcomes in older CRC patients have not been published. The accuracy of the universal ACS-SNQIP model for severe complications in 200 older gynecologic oncology patients undergoing laparotomy (2009-2013) was only 0.62, also with poor calibration [39] To account for possible heterogeneity between cohorts [29], external validation of the proposed prediction models is required. Changes in the healthcare setting and geographic differences are also reasons for periodic updating and recalibration [40].…”

Predicting Risk of Post-Operative Morbidity and Mortality following Gynaecological Oncology Surgery (PROMEGO): A Global Gynaecological Oncology Surgical Outcomes Collaborative Led Study

“…Due to the widespread use of the ACS NSQIP calculator within gynecological oncology, there have been numerous retrospective studies that have attempted to validate it within a gynecological oncology cohort. All of these studies, without exception, have found the predictive ability of the ACS NSQIP calculator in gynecological oncology patients to be inferior compared to its performance within a colorectal surgical cohort, which served as the original validation dataset for the calculator [ 23 , 25 , 26 , 27 ].…”