Comparison of the cox regression to machine learning in predicting the survival of anaplastic thyroid carcinoma.

ABSTRACT:

Background

To compare the ability of the Cox regression and machine learning algorithms to predict the survival of patients with Anaplastic thyroid carcinoma (ATC).

Methods

Patients diagnosed with ATC were extracted from the Surveillance, Epidemiology, and End Results database. The outcomes were overall survival (OS) and cancer-specific survival (CSS), divided into: (1) binary data: survival or not at 6 months and 1 year; (2): time-to-event data. The Cox regression method and machine learnings were used to construct models. Model performance was evaluated using the concordance index (C-index), brier score and calibration curves. The SHapley Additive exPlanations (SHAP) method was deployed to interpret the results of machine learning models.

Results

For binary outcomes

SUBMITTER: Xu L 

PROVIDER: S-EPMC10249166 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature