SurvMaximin: Robust federated approach to transporting survival risk prediction models.

ABSTRACT:

Objective

For multi-center heterogeneous Real-World Data (RWD) with time-to-event outcomes and high-dimensional features, we propose the SurvMaximin algorithm to estimate Cox model feature coefficients for a target population by borrowing summary information from a set of health care centers without sharing patient-level information.

Materials and methods

For each of the centers from which we want to borrow information to improve the prediction performance for the target population, a penalized Cox model is fitted to estimate feature coefficients for the center. Using estimated feature coefficients and the covariance matrix of the target population, we then obtain a SurvMaximin estimated set of feature coefficients for the target population. The target population can be an e

SUBMITTER: Wang X 

PROVIDER: S-EPMC9707637 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature