Machine Learning of Dose-Volume Histogram Parameters Predicting Overall Survival in Patients with Cervical Cancer Treated with Definitive Radiotherapy.

ABSTRACT:

Purpose

To analyze the effects of dosimetric parameters and clinical characteristics on overall survival (OS) by machine learning algorithms.

Methods and materials

128 patients with cervical cancer were treated with definitive pelvic radiotherapy with or without chemotherapy followed by image-guided brachytherapy. The elastic-net models with integrating DVH parameters and baseline clinical factors, only DVH parameters and only baseline clinical factors were constructed in 5-folds cross-validations for 100 iteration bootstrapping, and then were compared using concordance index (C-index) criteria. Finally, the selected important factors were used to build multivariable Cox-pH models for OS and also shown in nomograms for clinical usage.

Results

The median OS occurred wa

SUBMITTER: Xu Z 

PROVIDER: S-EPMC9213181 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature