Surgical risk score predicts suboptimal debulking or a major perioperative complication in patients with advanced epithelial ovarian, fallopian tube, or primary peritoneal cancer

Background: Patients who present with an advanced ovarian cancer are typically treated with primary debulking surgery (PDS) or neoadjuvant chemotherapy (NAC) followed by interval debulking surgery. The accurate pretreatment identification of patients best suited for PDS versus NAC is challenging. A paradigm for selecting one approach over the other could improve patient outcomes. In this study, we developed a prediction model for ''successful surgery'' (defined as optimal residual disease and no major perioperative complication) in patients who underwent PDS. Patients: Preoperative clinical characteristics, laboratory values, computed tomography findings, and surgical outcomes of 106 consecutive medically fit patients with advanced ovarian, tubal, or peritoneal cancer were reviewed. Preoperative predictors of suboptimal residual disease and major perioperative complications were determined using regression analysis. A surgical risk score (SRS) that minimized the false-negative rate (ie, likelihood of incorrectly predicting successful surgery) was constructed. Results: Sixty (57%) of the 106 patients were optimally cytoreduced. Fifty-six "radical procedures" were performed, and there were a total of 24 major perioperative complications. Diffuse peritoneal studding (P < 0.0001), para-aortic lymphadenopathy (P < 0.0001), and mesenteric involvement (Mes, P = 0.006) were associated with suboptimal (>1 cm) residual disease. Low albumin (P = 0.04) and splenic disease (spleen, P = 0.02) were the only 2 parameters associated with a higher risk of a major perioperative complication. The median SRSs of patients who had successful and "unsuccessful surgery" were 1 (0-4) and 3 (0-6), respectively. The false-negative rate of the SRS was only 7%. Conclusions: We developed a model that incorporated complications, in addition to residual disease status, into predicting surgical outcome for medically fit patients with advanced ovarian cancer. The SRS might be useful in determining the initial treatment strategy (ie, PDS vs NAC) for these patients. The accuracy of the SRS needs to be validated in a prospective manner.