skip to content
Dovepress - Open Access to Scientific and Medical Research
View our mobile site

8852

Specifying exposure classification parameters for sensitivity analysis: family breast cancer history

Methodology

(2749) Views  (608) Full article downloads

Authors: Anne M Jurek, Timothy L Lash, George Maldonado

Published Date July 2009 Volume 2009:1 Pages 109 - 117
DOI: http://dx.doi.org/10.2147/CLEP.S5755

Anne M Jurek,1,2 Timothy L Lash,3 George Maldonado4

1Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA; 2University of Minnesota Masonic Cancer Center, Minneapolis, MN, USA; 3Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA; 4Division of Environmental Health Sciences, University of Minnesota School of Public Health, Minneapolis, MN,  USA

Abstract: One of the challenges to implementing sensitivity analysis for exposure misclassification is the process of specifying the classification proportions (eg, sensitivity and specificity). The specification of these assignments is guided by three sources of information: estimates from validation studies, expert judgment, and numerical constraints given the data. The purpose of this teaching paper is to describe the process of using validation data and expert judgment to adjust a breast cancer odds ratio for misclassification of family breast cancer history. The parameterization of various point estimates and prior distributions for sensitivity and specificity were guided by external validation data and expert judgment. We used both nonprobabilistic and probabilistic sensitivity analyses to investigate the dependence of the odds ratio estimate on the classification error. With our assumptions, a wider range of odds ratios adjusted for family breast cancer history misclassification resulted than portrayed in the conventional frequentist confidence interval.

Keywords: breast cancer, family cancer history, sensitivity analysis, sensitivity, specificity








Readers of this article also read:

Maintenance treatment with infliximab for the management of Crohn’s disease in adults
Collapsing high-end categories of comorbidity may yield misleading results
Role of aliskiren in cardio-renal protection and use in hypertensives with multiple risk factors
Potential misinterpretations caused by collapsing upper categories of comorbidity indices: An illustration from a cohort of older breast cancer survivors
Computer applications for prediction of protein–protein interactions and rational drug design
Improving regional variation using quality of care measures
Existing data sources for clinical epidemiology: the Danish National Pathology Registry and Data Bank
A study of the changes in how medically related events are reported in Japanese newspapers
Existing data sources for clinical epidemiology: Aarhus University Prescription Database
Transferability of health technology assessments and economic evaluations: a systematic review of approaches for assessment and application