Advanced ovarian cancer (OC) is associated with impaired performance status and comorbidities for many patients. These factors have an impact on the decision to perform extended surgical cytoreduction. However, the trade-off between short-term morbidity and overall survival is complex, and few data are available analyzing the combined effects of these variables.

The purpose of the study was to evaluate the impact of patients’ age and American Society of Anesthesiologists (ASA) and surgical complexity score (SCS) on short-term morbidity and overall survival.

Presurgical patient characteristics, surgical procedures performed, and outcomes were assessed in a cohort of consecutive primary OC patients. An SCS from 1 to 3 was developed to adjust for the extent of surgery (simple to complex, respectively). Primary outcomes were 30 day major morbidity (sepsis, thromboembolic, cardiac, or reoperation), 3 month mortality, and overall survival (OS).

Two hundred nineteen consecutive patients with stage IIIC-IV OC were included. We observed a correlation between ASA and both short-term morbidity (P = .006) and 3 month mortality (P = .006). Age was independently associated with both short-term morbidity (P = .010) and 3 month mortality (P = .005). SCS correlated directly with morbidity (P < .001) but was not correlated with mortality (P = .266). The independent predictors of morbidity (ASA, age, and SCS) were used to develop risk prediction categories: risk of expected complications ranged from 2.5% to 67.6%, depending on category. Despite the increased risk of complications, however, more complex surgery carried a survival benefit in all the risk groups, owing to the observation that residual disease (RD) and SCS held a prognostic significance independent of age and ASA (P < .001 and P = .001, respectively).

Because of the survival benefit from lower RD, a less aggressive surgical effort results in poorer OS. However, the risk of complications are substantial for complex surgeries in the highest-risk patients: risk stratification should be used to help plan perioperative care and consider optimal treatment planning.