Predicting Severe Complications from Cytoreductive Surgery with Hyperthermic Intraperitoneal Chemotherapy: A Data-Driven, Machine Learning Approach to Augment Clinical Judgment.

Abstract

CRS-HIPEC provides oncologic benefit in well-selected patients with peritoneal carcinomatosis; however, it is a morbid procedure. Decision tools for preoperative patient selection are limited. We developed a risk score to predict severity of 90day complications for cytoreductive surgery with hyperthermic intraperitoneal chemotherapy (CRS-HIPEC). Adults who underwent CRS-HIPEC at the University of Pittsburgh Medical Center (March 2001-April 2020) were analyzed as part of this study. Primary endpoint was severe complications within 90days following CRS-HIPEC, defined using Comprehensive Complication Index (CCI) scores as a dichotomous (determined using restricted cubic splines) and continuous variable. Data were divided into training and test sets. Several machine learning and traditional algorithms were considered. For the 1959 CRS-HIPEC procedures included, CCI ranged from 0 to 100 (median 32.0). Adjusted restricted cubic splines model defined severe complications as CCI > 61. A minimum of 20 variables achieved optimal performance of any of the models. Linear regression achieved the highest area under the receiving operator characteristic curve (AUC, 0.74) and outperformed the NSQIP Surgical Risk calculator (AUC 0.80 vs. 0.66). Factors most positively associated with severe complications included peritoneal carcinomatosis index score, symptomatic status, and undergoing pancreatectomy, while American Society of Anesthesiologists 2 class, appendiceal diagnosis, and preoperative albumin were most negatively associated with severe complications. This study refines our ability to predict severe complications within 90days of discharge from a hospitalization in which CRS-HIPEC was performed. This advancement is timely and relevant given the growing interest in this procedure and may have implications for patient selection, patient and referring provider comfort, and survival.