Predicting response to immunotherapy in oral squamous cell carcinoma via a CT-based radiomics model.

ABSTRACT:

Background

To investigate whether radiomics models derived from pretreatment CT could help to predict response to immunotherapy in oral squamous cell carcinoma (OSCC).

Methods

Retrospectively, a total of 40 patients with measurable OSCC were included. The patients were divided into responder group and non-responder group according to the comparison of pre-treatment and post-treatment CT findings. Radiomics features were extracted from pre-treatment CT images, and optimal features were selected by univariate analysis and the least absolute shrinkage and selection operator (LASSO) regression analysis. Neural network, support vector machine, random forest and logistic regression models were used to predict response to immunotherapy in OSCC, and leave-one-out cross validation wa

SUBMITTER: Ma Q 

PROVIDER: S-EPMC11460018 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature