Objectives: A previously published a predictive model in which the suboptimal rate at primary debulking surgery (PDS) for advanced ovarian carcinoma was directly proportional to a predictive value score based on 9 clinical and radiologic criteria. The objective of this study was to determine the feasibility of implementation and evaluate the accuracy of the predictive score.

Methods: From July 1, 2015 to June 30, 2017, all patients seen by a gynecologic oncologist and medically appropriate for surgical management at MSKCC were assigned a predictive value score. Patients with a score of 0-6 were deemed "low-risk" for a suboptimal surgical outcome and were recommended to have PDS. Patients with a score greater than or equal to 7 were considered "high-risk" and were triaged to a laparoscopic assessment of resectability.

Results: Of the 139 "low-risk" patients who received PDS, 96% had an optimal outcome, 78% attained complete gross resection (CGR), and 4% had suboptimal outcomes. The cytoreduction rates for the 22 "high-risk" patients who received PDS were 91% optimal, 55% CGR, and 9% suboptimal. Using our algorithm, 91% of "low-risk" patients and 50% of "high-risk" patients ultimately underwent PDS. Conclusions: Implementation of a preoperative scoring system to determine PDS resectability for ovarian cancer is feasible. With external validation, this tool may be utilized in pretreatment assessment in order to further optimize patient selection and cytoreductive outcomes.