Development and validation of time-to-event models to predict metastatic recurrence of localized cutaneous melanoma.

ABSTRACT:

Background

The recent expansion of immunotherapy for stage IIB/IIC melanoma highlights a growing clinical need to identify patients at high risk of metastatic recurrence and, therefore, most likely to benefit from this therapeutic modality.

Objective

To develop time-to-event risk prediction models for melanoma metastatic recurrence.

Methods

Patients diagnosed with stage I/II primary cutaneous melanoma between 2000 and 2020 at Mass General Brigham and Dana-Farber Cancer Institute were included. Melanoma recurrence date and type were determined by chart review. Thirty clinicopathologic factors were extracted from electronic health records. Three types of time-to-event machine-learning models were evaluated internally and externally in the distant versus locoregional/non

SUBMITTER: Wan G 

PROVIDER: S-EPMC10843255 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature