Statistical methods for studying disease subtype heterogeneity

Molin Wang, Donna Spiegelman, Aya Kuchiba, Paul Lochhead, Sehee Kim, Andrew T. Chan, Elizabeth M. Poole, Rulla Tamimi, Shelley S. Tworoger, Edward Giovannucci, Bernard Rosner, Shuji Ogino

Research output: Contribution to journalArticlepeer-review

172 Scopus citations

Abstract

A fundamental goal of epidemiologic research is to investigate the relationship between exposures and disease risk. Cases of the disease are often considered a single outcome and assumed to share a common etiology. However, evidence indicates that many human diseases arise and evolve through a range of heterogeneous molecular pathologic processes, influenced by diverse exposures. Pathogenic heterogeneity has been considered in various neoplasms such as colorectal, lung, prostate, and breast cancers, leukemia and lymphoma, and non-neoplastic diseases, including obesity, type II diabetes, glaucoma, stroke, cardiovascular disease, autism, and autoimmune disease. In this article, we discuss analytic options for studying disease subtype heterogeneity, emphasizing methods for evaluating whether the association of a potential risk factor with disease varies by disease subtype. Methods are described for scenarios where disease subtypes are categorical and ordinal and for cohort studies, matched and unmatched case-control studies, and case-case study designs. For illustration, we apply the methods to a molecular pathological epidemiology study of alcohol intake and colon cancer risk by tumor LINE-1 methylation subtypes. User-friendly software to implement the methods is publicly available.

Original languageEnglish
Pages (from-to)782-800
Number of pages19
JournalStatistics in Medicine
Volume35
Issue number5
DOIs
StatePublished - 28 Feb 2016
Externally publishedYes

Keywords

  • Heterogeneity test
  • Molecular pathologic epidemiology
  • Omics
  • Pathogenesis
  • Pathology

Fingerprint

Dive into the research topics of 'Statistical methods for studying disease subtype heterogeneity'. Together they form a unique fingerprint.

Cite this