Please use this identifier to cite or link to this item: https://doi.org/10.1002/sim.4494
Title: The value of reusing prior nested case-control data in new studies with different outcome
Authors: Salim, A. 
Yang, Q.
Reilly, M.
Keywords: Cost effectiveness
Historical data
Population register
Study design
Survival analysis
Weighted estimation
Issue Date: May-2012
Source: Salim, A., Yang, Q., Reilly, M. (2012-05). The value of reusing prior nested case-control data in new studies with different outcome. Statistics in Medicine 31 (11-12) : 1291-1302. ScholarBank@NUS Repository. https://doi.org/10.1002/sim.4494
Abstract: Many epidemiological studies use a nested case-control (NCC) design to reduce cost while maintaining study power. However, because of the incidence density sampling used, reusing data from NCC studies for analysis of secondary outcomes is not straightforward. Recent methodological developments have opened the possibility for prior NCC data to be used to complement controls in a current study, thereby improving study efficiency. However, practical guidelines on the effectiveness of prior data relative to newly sampled subjects and the potential power gains are still lacking. Using simulated cohorts, we show in this paper how the efficiency of NCC studies that use a mixture of prior and newly sampled subjects depends on the number of newly sampled controls and prior subjects as well as the overlap in the distributions of the matching variables. We explore the feasibility and efficiency of a current study that gathers no controls, relying instead on prior data. Using the concept of effective number of controls, we show how researchers can assess the potential power gains from reusing prior data. We apply the method to analyses of anorexia and contralateral breast cancer in the Swedish population and show how power calculations can be done using publicly available software. This work has important applications in genetic and molecular epidemiology to make optimal use of costly exposure measurements. © 2012 John Wiley & Sons, Ltd.
Source Title: Statistics in Medicine
URI: http://scholarbank.nus.edu.sg/handle/10635/109077
ISSN: 02776715
DOI: 10.1002/sim.4494
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