Developing an AI Algorithm to Analyze Skin Damage Around Melanoma Scars as a Predictor of Response to Anti-PD-1 Immunotherapy in Advanced Skin Cancers

What this Trial Is About

Researchers are investigating metastatic melanoma and other advanced skin cancers to improve treatment decisions involving immune checkpoint inhibitors like anti-PD-1. Although these immunotherapies have changed care for advanced melanoma, only some patients benefit. This research aims to develop an artificial intelligence AI tool that analyzes visible skin damage called dermatoheliosis near the melanoma scar, which may predict response to anti-PD-1 therapy. The study is observational and includes both retrospective and prospective patient groups. The study collects photographs of the skin around melanoma scars to train and validate the AI algorithm. This tool will assess dermatoheliosis as a marker linked to tumor mutation burden TMB and treatment response. The research also examines skin and tumor samples to study genetic and immune profiles. The goal is to create a straightforward, non-invasive method to help doctors select the best immunotherapy for patients with unresectable locally advanced or metastatic melanoma or inoperable skin carcinomas. Participants provide skin photographs and may have their tumor and skin analyzed using advanced genetic and immune testing. Researchers will monitor tumor progression over six months to evaluate the AIs predictive performance. The study lasts from July 2023 to July 2028 and includes follow-up assessments. Participation involves no treatment changes, focusing on data and image collection to support future clinical decisions.

Generation of an Artificial Intelligence Algorithm Based on the Analysis of Melanoma Peri-scar Dermatoheliosis, as a Predictive Factor of Response to Anti-PD-1