International Validation of the SORG Machine-learning Algorithm for Predicting the Survival of Patients with Extremity Metastases Undergoing Surgical Treatment
Journal
Clinical orthopaedics and related research
Journal Volume
480
Journal Issue
2
Pages
367
Date Issued
2022-02-01
Author(s)
Tseng, Ting-En
Yen, Hung-Kuan
Groot, Olivier Q
Bongers, Michiel E R
Karhade, Aditya V
Lai, Yi-Hsiang
Yang, Jing-Jen
Verlaan, Jorrit-Jan
Schwab, Joseph H
Abstract
The Skeletal Oncology Research Group machine-learning algorithms (SORG-MLAs) estimate 90-day and 1-year survival in patients with long-bone metastases undergoing surgical treatment and have demonstrated good discriminatory ability on internal validation. However, the performance of a prediction model could potentially vary by race or region, and the SORG-MLA must be externally validated in an Asian cohort. Furthermore, the authors of the original developmental study did not consider the Eastern Cooperative Oncology Group (ECOG) performance status, a survival prognosticator repeatedly validated in other studies, in their algorithms because of missing data.
Type
journal article