Reproductive risk factors for breast cancer and association with novel breast density measurements among Hispanic, Black, and White women.

Purpose: There are differences in the distributions of breast cancer incidence and risk factors by race and ethnicity. Given the strong association between breast density and breast cancer, it is of interest describe racial and ethnic variation in the determinants of breast density.

Methods: We characterized racial and ethnic variation in reproductive history and several measures of breast density for Hispanic (n = 286), non-Hispanic Black (n = 255), and non-Hispanic White (n = 1694) women imaged at a single hospital.

Automated percent mammographic density, mammographic texture variation, and risk of breast cancer: a nested case-control study.

Percent mammographic density (PMD) is a strong breast cancer risk factor, however, other mammographic features, such as V, the standard deviation (SD) of pixel intensity, may be associated with risk. We assessed whether PMD, automated PMD (APD), and V, yielded independent associations with breast cancer risk. We included 1900 breast cancer cases and 3921 matched controls from the Nurses' Health Study (NHS) and the NHSII.

Empirically-derived synthetic populations to mitigate small sample sizes.

Limited sample sizes can lead to spurious modeling findings in biomedical research. The objective of this work is to present a new method to generate synthetic populations (SPs) from limited samples using matched case-control data (n = 180 pairs), considered as two separate limited samples. SPs were generated with multivariate kernel density estimations (KDEs) with unconstrained bandwidth matrices.

Early-Life and Adult Anthropometrics in Relation to Mammographic Image Intensity Variation in the Nurses' Health Studies.

Background: The V measure captures grayscale intensity variation on a mammogram and is positively associated with breast cancer risk, independent of percent mammographic density (PMD), an established marker of breast cancer risk. We examined whether anthropometrics are associated with V, independent of PMD.

Methods: The analysis included 1,700 premenopausal and 1,947 postmenopausal women without breast cancer within the Nurses' Health Study (NHS) and NHSII.

Calibrated Breast Density Measurements.

Rationale And Objectives: Mammographic density is an important risk factor for breast cancer, but translation to the clinic requires assurance that prior work based on mammography is applicable to current technologies. The purpose of this work is to evaluate whether a calibration methodology developed previously produces breast density metrics predictive of breast cancer risk when applied to a case-control study.

Materials And Methods: A matched case control study (n = 319 pairs) was used to evaluate two calibrated measures of breast density.

Sexual Assault and Depressive Symptoms in College Students: Do Psychological Needs Account for the Relationship?

In this study, authors examined basic psychological needs (namely, competence, autonomy, and relatedness) as potential mediators of the association between sexual assault and depressive symptoms in a sample of 342 college students. Results from conducting a multiple mediation test provided support for partial mediation involving the indirect effects of competence and autonomy. In contrast, no support for mediation was found involving relatedness.

Automated Percentage of Breast Density Measurements for Full-field Digital Mammography Applications.

Rationale And Objectives: Increased mammographic breast density is a significant risk factor for breast cancer. A reproducible, accurate, and automated breast density measurement is required for full-field digital mammography (FFDM) to support clinical applications. We evaluated a novel automated percentage of breast density measure (PDa) and made comparisons with the standard operator-assisted measure (PD) using FFDM data.

A comparison of calibration data from full field digital mammography units for breast density measurements.

Background: Breast density is a significant breast cancer risk factor measured from mammograms. The most appropriate method for measuring breast density for risk applications is still under investigation. Calibration standardizes mammograms to account for acquisition technique differences prior to making breast density measurements.

Comparison of percent density from raw and processed full-field digital mammography data.

Introduction: Mammographic density has been established as a strong risk factor for breast cancer, primarily using digitized film mammograms. Full-field digital mammography (FFDM) is replacing film mammography, has different properties than film, and provides both raw and processed clinical display representation images. We evaluated and compared FFDM raw and processed breast density measures and their associations with breast cancer.

Survival analysis of patients with stage I non-small-cell lung cancer using clinical and DNA repair pathway expression variables.

Background: Lung cancer is the leading cause of cancer-related mortality. Understanding patient attributes that enhance survival and predict recurrence is necessary to individualize treatment options.

Methods: Patients (N = 162) were dichotomized into favorable (n = 101) and unfavorable (n = 61) groups based on survival characteristics.

Statistical learning methods as a preprocessing step for survival analysis: evaluation of concept using lung cancer data.

Background: Statistical learning (SL) techniques can address non-linear relationships and small datasets but do not provide an output that has an epidemiologic interpretation.

Methods: A small set of clinical variables (CVs) for stage-1 non-small cell lung cancer patients was used to evaluate an approach for using SL methods as a preprocessing step for survival analysis. A stochastic method of training a probabilistic neural network (PNN) was used with differential evolution (DE) optimization.

Full field digital mammography and breast density: comparison of calibrated and noncalibrated measurements.

Rationale And Objectives: Mammographic breast density is an important and widely accepted risk factor for breast cancer. A statement about breast density in the mammographic report is becoming a requirement in many States. However, there is significant inter-observer variation between radiologists in their interpretation of breast density.