This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Accuracy of MSI Testing in Predicting Germline Mutations of MSH2 and MLH1: A Case Study in Bayesian Meta-Analysis of Diagnostic Tests Without a Gold Standard

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Sining Chen (The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University)
Patrice Watson (Hereditary Cancer Institute, Creighton University School of Medicine, Omaha, NE)
Giovanni Parmigiani (Sydney Kimmel Comprehensive Cancer Center, Johns Hopkins University and Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health)
Abstract

Microsatellite instability (MSI) testing is a common screening procedure used to identify families that may harbor mutations of a mismatch repair gene and therefore may be at high risk for hereditary colorectal cancer. A reliable estimate of sensitivity and specificity of MSI for detecting germline mutations of mismatch repair genes is critical in genetic counseling and colorectal cancer prevention. Several studies published results of both MSI and mutation analysis on the same subjects. In this article we perform a meta-analysis of these studies and obtain estimates that can be directly used in counseling and screening. In particular we estimate the sensitivity of MSI for detecting mutations of MSH2 and MLH1 to be 0.78 (0.69--0.86). Statistically, challenges arise from the following: a) traditional mutation analysis methods used in these studies cannot be considered a gold standard for the identification of mutations; b) studies are heterogeneous in both the design and the populations considered; and c) studies may include different patterns of missing data resulting from partial testing of the populations sampled. We addressed these challenges in the context of a Bayesian meta-analytic implementation of the Hui-Walter design, designed to account for various forms of incomplete data. Posterior inference are handled via a Gibbs sampler.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.bepress.com/cgi/viewcontent.cgi?article=1043&context=jhubiostat
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by Berkeley Electronic Press in its series Johns Hopkins University Dept. of Biostatistics Working Paper Series with number 1043.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length:
Date of creation: 11 Jul 2004
Date of revision:
Handle: RePEc:bep:jhubio:1043

Note: oai:bepress.com:jhubiostat-1043
Contact details of provider:
Web page: http://www.bepress.com

For technical questions regarding this item, or to correct its listing, contact: (Christopher F. Baum).

Related research
Keywords: Sensitivity; Specificity; Diagnostic test; Microsatellite instability (MSI); Hereditary nonpolyposis colorectal cancer (HNPCC);

Statistics
Access and download statistics

Did you know? You too can volunteer with RePEc.

This page was last updated on 2009-12-15.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.