A preoperative personalized risk assessment calculator for elderly ovarian cancer patients undergoing primary cytoreductive surgery

- A risk assessment tool can predict complication after ovarian cancer surgery.
- Objective empiric preoperative data are predictive of complication.
- Risk assessment tools can be used to help triage patients between initial therapies.

ObjectiveCytoreductive surgery for ovarian cancer has higher rates of postoperative complication than neoadjuvant chemotherapy followed by surgery. If patients at high risk of postoperative complication were identified preoperatively, primary therapy could be tailored. Our objective was to develop a predictive model to estimate the risk of major postoperative complication after primary cytoreductive surgery among elderly ovarian cancer patients.MethodsPatients who underwent primary surgery for ovarian cancer between 2005 and 2013 were identified from the National Surgical Quality Improvement Project. Patients were selected using primary procedure CPT codes. Major complications were defined as grade 3 or higher complications on the validated Claviden-Dindo scale. Using logistic regression, we identified demographic and clinical characteristics predictive of postoperative complication.ResultsWe identified 2101 ovarian cancer patients of whom 35.9% were older than 65. Among women older than 65, the rate of major postoperative complication was 16.4%. Complications were directly associated with preoperative laboratory values (serum creatinine, platelets, white blood cell count, hematocrit), ascites, white race, and smoking status, and indirectly associated with albumin. Our predictive model had an area under receiver operating characteristic curve of 0.725. In order to not deny patients necessary surgery, we chose a 50% population rate of postoperative complication which produced model sensitivity of 9.8% and specificity of 98%.DiscussionOur predictive model uses easily and routinely obtained objective preoperative factors to estimate the risk of postoperative complication among elderly ovarian cancer patients. This information can be used to assess risk, manage postoperative expectations, and make decisions regarding initial treatment.