The aim is to evaluate the prognostic value of immune-inflammation markers in patients with locally advanced cervical cancer undergoing treatment.
Utilized both nomogram and machine learning models for prediction.
Compared predictive accuracy over a 1-5 year follow-up period.
Machine learning models demonstrated higher predictive accuracy than nomograms.
Both models provided valuable insights into patient outcomes.
Abstract
Both nomogram and ML models provide valuable prognostic insights for LACC. The logistic regression ML model showed superior predictive accuracy compared to the nomogram during 1-5 years of follow-up.