In identifying associations between exposures and diseases researchers have a wide variety of study designs at their disposal. Although two-phase studies have been shown to provide substantial efficiency gains over the traditional case-control design, they have not been widely adopted. A recent survey of 4,792 studies in five top-line epidemiological/medical journals, published since 2002, found just a single study having employed the two-phase design. This may be due, in part, to a lack of published guidance on how to design and plan a two-phase study and the practical difficulties of not having general-purpose software. To address these issues and broad the use of two-phase studies, this research proposes to develop a flexible framework for investigating design considerations in the context of planning a two-phase study. This will involve two steps;(i) development of a conceptual framework which encompasses the decisions required at the planning stage and (ii) developing an algorithmic simulation-based framework which facilitates the investigation of potential choices in a variety of settings. Building on this, we propose to conduct an extensive and comprehensive simulation study to explore the impact of various choices associated with the design of a two-phase study. This proposal is motivated by ongoing and future research conducted by the Breast Cancer Surveillance Consortium (BCSC). As new opportunities for scientific research within the BCSC arise it will be important to make the best possible use of the existing database/infrastructure. The two-phase design provides a framework to achieve this, and improved guidance on the planning and design of such studies will be crucial for future cost-effective and yet statistically powerful studies. A key component of this work, therefore, will be the dissemination of methods and results, and the delivery of software;algorithms/code, together with documentation, will be developed in commonly used statistical packages and made publicly available.

Public Health Relevance

Although two-phase studies can provide substantial efficiency gains over the case-control design, they have not been widely adopted. In this research we seek to broaden their use by developing and conducting a comprehensive simulation study to explore design issues for two-phase studies. These results will provide improved guidance to researchers and will be crucial for designing future cost-effective and yet statistically powerful studies.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Small Research Grants (R03)
Project #
5R03CA135671-02
Application #
7779497
Study Section
Special Emphasis Panel (ZCA1-SRRB-D (J1))
Program Officer
Verma, Mukesh
Project Start
2009-09-01
Project End
2010-10-31
Budget Start
2010-09-01
Budget End
2010-10-31
Support Year
2
Fiscal Year
2010
Total Cost
$15,904
Indirect Cost
Name
Group Health Cooperative
Department
Type
DUNS #
078198520
City
Seattle
State
WA
Country
United States
Zip Code
98101
Haneuse, Sebastien; Schildcrout, Jonathan; Gillen, Daniel (2012) A two-stage strategy to accommodate general patterns of confounding in the design of observational studies. Biostatistics 13:274-88
Haneuse, Sebastien; Saegusa, Takumi; Lumley, Thomas (2011) osDesign: An R Package for the Analysis, Evaluation, and Design of Two-Phase and Case-Control Studies. J Stat Softw 43: