Benign Breast Disease Team Project

Abbreviated Name

BBD Benign Breast

Lead Investigator

Engstrom, Paul — Fox Chase Cancer Center

Coordinating Investigator

Zheng, Yingye — Fred Hutchinson Cancer Center

Involved Investigators

Abstract

To identify women diagnosed with atypical ductal hyperplasia (ADH) who are at increased risk of developing invasive breast cancer (IBC) and who might benefit from risk reduction with the use of chemoprevention agents such as Tamoxifen. (Note: A companion protocol will study women with DCIS and their risk for invasive breast cancer.)

Aims

Biomarkers expressed in benign breast disease tissue of women who progresse to invasive breast cancer are quantitatively and/or qualitatively different from those expressed in tissue of matched women who do not progress to invasive breast cancer. A nested case-control design will be used to determine if available proteomic and methylation biomarkers predict risk for future invasive cancer (IBC). Women with ADH who are disease-free will be matched 2:1 to women with ADH who progress to IBC.

Analytic Method

The performance of each biomarker tested will be undertaken in three steps: A. Relative Risks Associated with Biomarker Values 1. Cox regression will be used. Time measured from BBD diagnosis. 2. Relative risks beyond those conferred by other predictors including age, family history, and histology will be examined. 3. Separate models will be fit for ADH versus UH versus NP if there are sufficient numbers; Analyses will be combined with stratification if appropriate. B. Capacity for Discrimination between Cases and Controls 1. Primary comparison groups: subjects who developed invasive breast cancer by 7 years versus controls who are alive and without cancer at 7 years after BBD 2. Secondary comparison groups: incident DCIS, invasive cancer after 7 years 3. ROC curves will be used to compare cases with primary controls. Calculations are complicated because they must handle varying follow-up and the quota method of selecting non-cases 4. Separate ROCs for BBD with and without atypia will be estimated if possible and compared. We will compare ROC curves for different biomarkers 5. We will develop a combination biomarker score based on markers that appear to perform well using Cox regression. We will calculate its ROC curve and compare with ROC for best individual biomarker C. Absolute Risk of IBC for Individual Decision Making 1. Calculate individual risk of IBC .5-7.0 years after BBD with and without biomarker 2. Compare risk distributions. How many people classified as high risk (>.75%X4.5) with and without the biomarker 3. Calculate risk distributions for subjects who develop IBC by 7 years (cases) and for subjects alive without IBC by 7years (controls) 4. Of subjects who develop IBC by 7 years, how many classified as high risk? This is the sensitivity (TPR) 5. Of subjects who are alive without IBC by 7 years, how many classified as low risk? This is the specificity (1-FPR) 6. Calculate the standardized net benefit that combines TPR and FPR into a single index 7. Compare for different biomarkers and for the most discriminating biomarker combination

Outcome

Publications

No publications available at this time for this protocol.

Biomarkers

Data Collections

There is one collection of data that has not yet been made public. Logging in may you give you access to the names of the non-public data collections.

Team Project

Start Date

Aug 13 2010

Estimated Finish Date

Jun 13 2013

Finish Date

Feb 18 2022

Protocol ID

331

Protocol Type

Reference Set

Fields of Research

Other
Proteomics

Collaborative Group

Breast and Gynecologic Cancers Research Group

Cancer Types

Malignant neoplasm of breast

Phased Status