Validity of a method for identifying disease subtypes that are etiologically heterogeneous.

ABSTRACT: A focus of cancer epidemiologic research has become the identification of risk factors that influence specific subtypes of disease, a phenomenon known as etiologic heterogeneity. In previous work we developed a novel strategy to cluster tumor markers and identify disease subtypes that differ maximally with respect to known risk factors for use in the context of case-control studies. The method relies on the premise that unsupervised k-means clustering will find candidate solutions that are closely aligned with the sought-after etiologically distinct clusters, which may not be true in the presence of clusters of tumor markers that are not related to risk of disease. In this article, we investigate in detail the ability of the method to identify the "true" clusters in the presence of

SUBMITTER: Zabor EC 

PROVIDER: S-EPMC9425153 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature