P-POSSUM Falls Short: Predicting Morbidity in Ovarian Cancer (OC) Cytoreductive Surgery

Area of Science:

• Oncology
• Surgical Outcomes
• Predictive Analytics

Background:

• The P-POSSUM scale is a standard tool for predicting perioperative risk.
• Its efficacy in predicting outcomes after cytoreductive surgery (CRS) for ovarian cancer (OC) remains under-investigated.
• Accurate risk assessment is crucial for optimizing patient care in complex oncologic surgeries.

Purpose of the Study:

• To evaluate the predictive performance of the P-POSSUM scale for morbidity in patients undergoing CRS for OC.
• To explore the potential of incorporating additional clinical variables to enhance the predictive accuracy of existing models.

Main Methods:

• Retrospective analysis of 161 patients undergoing OC CRS.
• Data collected included demographics, P-POSSUM scores, Edmonton Frail Scale (EFS) scores, and preoperative albumin.
• Performance evaluated using ROC curves; stepwise regression identified additional predictors (EFS, BMI) for an improved model.

Main Results:

• P-POSSUM demonstrated poor predictive performance for morbidity (AUC=0.539) and mortality (AUC=0.569) in OC CRS.
• Forty percent of patients experienced postoperative complications (Clavien-Dindo grade ≥1).
• A combined model (P-POSSUM + EFS + BMI) showed improved, though not statistically significant, morbidity prediction (AUC=0.655).

Conclusions:

• The P-POSSUM scale is inadequate for predicting morbidity in OC CRS.
• Current models require enhancement with additional clinical factors like EFS and BMI.
• Further validation of refined predictive models is essential for clinical application in gynecologic oncology.