Artificial Intelligence Algorithm Predicts Response to Immune Checkpoint Inhibitors.

ABSTRACT:

Purpose

Cancer treatment has been revolutionized by immune checkpoint inhibitors (ICI). However, a subset of patients do not respond and/or they experience significant adverse events. Attempts to integrate reliable biomarkers of ICI response as part of standard care have been hampered by limited generalizability. We previously reported our supervised machine learning (ML) model in a retrospective cohort of metastatic melanoma.

Experimental design

In this study, we expanded our testing to include larger cohorts of patients with melanoma accrued at several sites, including patients enrolled in clinical trials in both adjuvant and metastatic settings. We examined pretreatment hematoxylin and eosin slides from 639 patients with stage III/IV melanoma treated with ICIs [anti-cytot

SUBMITTER: Fa'ak F 

PROVIDER: S-EPMC12351278 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature