Prediction of 30-day, 90-day, and 1-year mortality after colorectal cancer surgery using a data-driven approach.

Purpose: To develop prediction models for short-term mortality risk assessment following colorectal cancer surgery.

Methods: Data was harmonized from four Danish observational health databases into the Observational Medical Outcomes Partnership Common Data Model. With a data-driven approach using the Least Absolute Shrinkage and Selection Operator logistic regression on preoperative data, we developed 30-day, 90-day, and 1-year mortality prediction models.