External Evaluation of a Predictive Model of Suboptimal Cytoreduction in Advanced Ovarian Cancer

Objective: The aim of this thesis was to externally validate a predictive model of suboptimal surgery in advanced ovarian cancer, developed by doctors Escrig and Llueca. The model classifies patients pre-surgically to estimate the likelihood of incomplete cytoreductive surgery. Methods: A retrospective cohort comparison between two time periods was performed. Validation used a new cohort of 83 patients with advanced ovarian cancer, prospectively collected between 2017 and 2023 across five hospitals (experimental group). This group was compared with the original control cohort (2013-2016), which had served for model development. The predictive models (R3 and R4) are based on the Peritoneal Carcinomatosis Index (PCI) assessed by CT, laparoscopic PCI, and the presence of intestinal sub-obstruction. For model R4, intraoperative PCI was also included. Results: The experimental group had a lower rate of suboptimal cytoreduction compared with the control group (4.8% vs. 13.8%; p = 0.049). Significant differences were observed in ascites (49.4% vs. 27.5%; p = 0.002), and no patient in the experimental group presented intestinal sub-obstruction (0% vs. 8%; p = 0.002). Although at least 13 suboptimal surgeries were expected for validation, only four occurred. The predictive models did not classify any of these four cases as high risk, instead categorizing them as low or intermediate risk. Conclusions: Statistical external validation could not be performed due to event scarcity. This reduced incidence is attributed to selection bias: highly experienced surgical teams from participating centres likely applied criteria similar to those of the model, referring high risk patients (e.g., with intestinal sub-obstruction) to neoadjuvant therapy and thus avoiding suboptimal primary surgeries. Although direct validation was not possible, the findings indirectly suggest that the model is effective in guiding patient selection and improving surgical outcomes.