More than 40% of Americans will develop cancer in their lifetime and approximately 1 in 5 will die of cancer. However, screening can reduce cancer mortality and decrease incidence for some cancers. Identifying effective screening regimens- who should be screened for cancer, how often, and by what method- is key to public health. Most of the data used to make these decisions relate to the performance of individual screening tests. Relatively little research has focused on comparing alternative screening regimens, yet this information is needed to provide evidence for screening guidelines. The overall goal of this research is to develop statistical methods for characterizing harms (false-positive test results and missed cancers) and benefits (screen- detected cancers) after the multiple rounds of screening comprising a regimen in order to facilitate guideline setting and decision making. Our work will address three specific aims: (1) To develop new statistical methods for simultaneously estimating the cumulative risk of harms and benefits of repeat cancer screening; (2) To develop new statistical methods to estimate the expected number of false-positive test results experienced over the course of a screening regimen; (3) To use our newly developed statistical methods to analyze risk- based screening mammography regimens using 15 years of data from the Breast Cancer Surveillance Consortium (BCSC). Unbiased estimation of harms and benefits of repeat breast cancer screening tailored to women's individual breast cancer risk levels previously has not been possible because existing methods fail to account for important features of the observation scheme.
Under Aim 3 we will analyze data from the BCSC using statistical methods developed under Aims 1 and 2 and will compare alternative breast cancer screening regimens tailored to women's breast cancer risk profiles. By contributing information about the potential harms and benefits of risk-based breast cancer screening regimens, this work will inform policy-makers and facilitate communication between patients and providers. This will aid both individual decision makers and development of evidence-based guidelines.

Public Health Relevance

Statistical methods for estimation of benefits & harms of repeat cancer screening Project narrative: This project will develop new statistical methods for estimating the harms and benefits of cancer screening regimens and will apply these methods to comparisons of risk-based screening mammography strategies. This work will inform policy-makers and facilitate communication between patients and providers about risks and benefits of different cancer screening options. This will aid both individual decision makers and development of evidence-based guidelines for breast and other cancers.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Small Research Grants (R03)
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Special Emphasis Panel (ZCA1-SRLB-D (O1))
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Verma, Mukesh
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University of Pennsylvania
Biostatistics & Other Math Sci
Schools of Medicine
United States
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Ripping, Theodora Maria; Hubbard, Rebecca A; Otten, Johannes D M et al. (2016) Towards personalized screening: Cumulative risk of breast cancer screening outcomes in women with and without a first-degree relative with a history of breast cancer. Int J Cancer 138:1619-25
Miglioretti, Diana L; Lange, Jane; van den Broek, Jeroen J et al. (2016) Radiation-Induced Breast Cancer Incidence and Mortality From Digital Mammography Screening: A Modeling Study. Ann Intern Med 164:205-14
Hubbard, Rebecca A; Ripping, Theodora M; Chubak, Jessica et al. (2016) Statistical Methods for Estimating the Cumulative Risk of Screening Mammography Outcomes. Cancer Epidemiol Biomarkers Prev 25:513-20
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Kemp Jacobsen, Katja; O'Meara, Ellen S; Key, Dustin et al. (2015) Comparing sensitivity and specificity of screening mammography in the United States and Denmark. Int J Cancer 137:2198-207