Analysis of multivariate failure times in the presence of selection bias with application to breast cancer. Issue 3 (5th December 2014)

• Record Type: Journal Article
• Authors: Leclerc, Martin; EMBRACE Investigators; GEMO Study Collaborators; INHERIT Investigators; Antoniou, Antonis C.; Simard, Jacques; Lakhal‐Chaieb, Lajmi
• Is Part Of: Journal of the Royal Statistical Society. Volume 64:Issue 3(2015:May)
• Page Start: 525
• Page End: 541
• Publication Date: 2014-12-05
• Subjects: Statistics -- Periodicals; 519.5
• DOI: 10.1111/rssc.12091
• Languages: English
• ISSNs: 0035-9254

Abstract

<abstract abstract-type="main" id="rssc12091-abs-0001"> <title>Summary</title> <p>Identifying loci that modify the risk of cancer for mutation carriers is an important topic in oncogenetics. Within this research area, we are concerned with the analysis of the association between a genetic variant (single‐nucleotide polymorphism rs13281615) and breast cancer among women with a pathogenic mutation in the BRCA2 gene. As this mutation is rare, data were collected retrospectively according to a case‐study design through genetic screening programmes. This involves a selection bias and an intrafamilial correlation, which complicates the statistical analysis. We derive a Cramer–von Mises‐type statistic to test the equality of genotype‐specific survival functions when the proportional hazards model does not hold. A Clayton copula is specified to model the residual phenotype familial dependence and an innovative semiparametric bootstrap procedure is proposed to approximate the distribution of the test statistic under the null hypothesis. The test proposed is applied to data from European and North American mutation carriers and its performance is evaluated by simulations.</p> </abstract>