Single-center versus multi-center data sets for molecular prognostic modeling: a simulation study.

ABSTRACT:

Background

Prognostic models based on high-dimensional omics data generated from clinical patient samples, such as tumor tissues or biopsies, are increasingly used for prognosis of radio-therapeutic success. The model development process requires two independent discovery and validation data sets. Each of them may contain samples collected in a single center or a collection of samples from multiple centers. Multi-center data tend to be more heterogeneous than single-center data but are less affected by potential site-specific biases. Optimal use of limited data resources for discovery and validation with respect to the expected success of a study requires dispassionate, objective decision-making. In this work, we addressed the impact of the choice of single-center and multi-center

SUBMITTER: Samaga D 

PROVIDER: S-EPMC7227093 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature