Predicting progression-free survival after systemic therapy in advanced head and neck cancer: Bayesian regression and model development.

ABSTRACT:

Background

Advanced head and neck squamous cell carcinoma (HNSCC) is associated with a poor prognosis, and biomarkers that predict response to treatment are highly desirable. The primary aim was to predict progression-free survival (PFS) with a multivariate risk prediction model.

Methods

Experimental covariates were derived from blood samples of 56 HNSCC patients which were prospectively obtained within a Phase 2 clinical trial (NCT02633800) at baseline and after the first treatment cycle of combined platinum-based chemotherapy with cetuximab treatment. Clinical and experimental covariates were selected by Bayesian multivariate regression to form risk scores to predict PFS.

Results

A 'baseline' and a 'combined' risk prediction model were generated, each of which featu

SUBMITTER: Barber PR 

PROVIDER: S-EPMC9815805 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature