Evaluation of the performance of the ACS NSQIP surgical risk calculator in gynecologic oncology patients undergoing laparotomy

Colleen Rivard, Rebi Nahum, Elizabeth Slagle, Megan Duininck, Rachel Isaksson Vogel, Deanna Teoh

Research output: Contribution to journalArticlepeer-review

45 Scopus citations

Abstract

Objective The objective of this study was to evaluate the ability of the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) surgical risk calculator to predict complications in gynecologic oncology patients undergoing laparotomy. Methods A chart review of patients who underwent laparotomy on the gynecologic oncology service at a single academic hospital from January 2009 to December 2013 was performed. Preoperative variables were abstracted and NSQIP surgical risk scores were calculated. The risk of any complication, serious complication, death, urinary tract infection, venous thromboembolism, cardiac event, renal complication, pneumonia and surgical site infection were correlated with actual patient outcomes using logistic regression. The c-statistic and Brier score were used to calculate the prediction capability of the risk calculator. Results Of the 1094 patients reviewed, the majority were < 65 years old (70.9%), independent (95.2%), ASA class 1-2 (67.3%), and overweight or obese (76.1%). Higher calculated risk scores were associated with an increased risk of the actual complication occurring for all events (p < 0.05). The calculator performed best for predicting death (c-statistic = 0.851, Brier = 0.008), renal failure (c-statistic = 0.752, Brier = 0.015) and cardiac complications (c-statistic = 0.708, Brier = 0.011). The calculator did not accurately predict most complications. Conclusions The NSQIP surgical risk calculator adequately predicts specific serious complications, such as postoperative death and cardiac complications. However, the overall performance of the calculator was worse for gynecologic oncology patients than reported in general surgery patients. A tailored prediction model may be needed for this patient population.

Original languageEnglish (US)
Pages (from-to)281-286
Number of pages6
JournalGynecologic oncology
Volume141
Issue number2
DOIs
StatePublished - May 1 2016

Bibliographical note

Funding Information:
Research reported in this publication was supported by The Masonic Cancer Center Women's Health Scholarship sponsored by the University of Minnesota Masonic Cancer Center, a comprehensive cancer center designated by the National Cancer Institute, and administrated by the University of Minnesota Deborah E. Powell Center for Women's Health.

Funding Information:
Ms. Isaksson Vogel's work is supported by NIH grant P30 CA77598 utilizing the Biostatistics and Bioinformatics Core shared resource of the Masonic Cancer Center, University of Minnesota and by the National Center for Advancing Translational Sciences of the National Institutes of Health Award Number UL1TR000114.

Funding Information:
Research reported in this publication was supported by NIH grant P30 CA77598 utilizing the Biostatistics and Bioinformatics Core shared resource of the Masonic Cancer Center, University of Minnesota and by the National Center for Advancing Translational Sciences of the National Institutes of Health Award Number UL1TR000114.

Publisher Copyright:
© 2016 Elsevier Inc. All rights reserved.

Keywords

  • Laparotomy
  • NSQIP
  • Postoperative complications
  • Surgical Risk

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