Risk Prediction Model of 90-Day Mortality After Esophagectomy for Cancer

Area of Science:

• Oncology
• Surgical Oncology
• Health Services Research

Background:

• Ninety-day mortality after esophagectomy is a key indicator of surgical quality.
• Accurate risk prediction is essential for informed patient and surgeon decision-making.

Purpose of the Study:

• To develop and validate a risk prediction model for 90-day mortality following esophagectomy for cancer.
• Utilize the International Esodata Study Group (IESG) database, the largest prospective, multicenter cohort with standardized outcomes.

Main Methods:

• Retrospective analysis of 8403 patients from 39 institutions across 19 countries (2015-2019).
• Development and validation cohorts were randomly assigned.
• A logistic regression model identified 10 weighted variables to create a prognostic score, categorized into 5 risk groups.

Main Results:

• The overall 90-day mortality rate was 4.2%.
• The model identified 10 predictive variables including age, sex, BMI, performance status, and comorbidities.
• Risk groups ranged from very low (1.8% mortality) to very high (18.2% mortality), with good calibration and discrimination (AUC 0.68/0.64).

Conclusions:

• The IESG risk prediction model effectively stratifies patients by 90-day mortality risk after esophagectomy based on preoperative variables.
• This tool can significantly aid decision-making processes and informed consent for esophageal cancer surgery.