JMIR cancer
Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer Using Routinely Collected Clinical Data: Multicenter Retrospective Machine Learning Model Development and External Validation Study
By Xu G, Sun X, Jiang J and 5 others.
Abstract
Background
Preoperative nodal assessment in colorectal cancer (CRC) remains imperfect, and uncertainty regarding pathological lymph node metastasis (LNM) may persist despite conventional imaging. Machine learning using routinely available preoperative information may provide complementary patient-level risk estimates without requiring radiomic feature extraction or molecular testing.
Objective
This study aimed to develop and externally validate machine learning models for preoperative estimation of pathologically confirmed LNM risk in patients with newly diagnosed CRC undergoing direct radical surgery without preoperative anticancer treatment, and to assess whether multivariable prediction adds information beyond clinical tumor stage (cT) alone.