Graham Colditz, MD, DrPH

Background: It is clinically important to refine strategies to manage women with dense breasts as they represent approximately 50% of all women screened. Change in breast density is related to risk of breast cancer.1 We also must understand this change in density over time in women with dense and non-dense breasts. While population level data have been reported to estimate decrease in density with age, this has largely used digitized film images.2 Expanding use of digital mammography and repeated screening generates a large library of images for each woman, offering the potential to use more of the image data. Methods: We use longitudinal latent class analysis to cluster women and estimate their change in density over time. To evaluate the groups of women with different patterns of change in density we fit latent class models to our previously published data.1 This includes 289 pathology confirmed …

Tables, figures, and additional simulation and application results.

Background Treatments for multiple myeloma (MM) have evolved over time and improved MM survival. While racial differences in MM treatment and prognosis between non‐Hispanic African American (NHAA) and non‐Hispanic White (NHW) patients are well‐established, it is unclear whether they have persisted after the introduction of novel agents. Methods Using the Surveillance, Epidemiology, and End Results‐Medicare linked database, our study investigated racial difference in the receipt of treatment within 1 year following diagnosis and assessed survival outcomes among Medicare beneficiaries (≥66 years) diagnosed with MM from 2007 to 2017. We applied multivariable Cox proportional hazards models to estimate the association between race and survival and presented hazard ratios (HRs). Results Of 2094 NHAA and 11,983 NHW older patients with MM, 59.5% and 64.8% received treatment …

Introduction: Breast cancer incidence is rising in premenopausal, hence, there is a critical need to understand factors underlying premenopausal breast cancer development in order to guide targeted prevention. Mammographic breast density is a strong risk factor for, as well as an intermediate phenotype for premenopausal breast cancer. Yet, the molecular mechanisms underlying the associations of dense breasts with breast cancer are not well understood. Our objectives in this study are to perform proteomic analysis in breast tissues to (i) identify proteins that are associated with breast cancer development in premenopausal women; (ii) determine which of these proteins are also associated with dense breasts. Methods: We performed proteomic analysis on tumor and adjacent normal tissues from 50 premenopausal women with breast cancer who had breast tissue samples archived at the St. Louis Breast Tumor …

Early life factors are important risk factors for breast cancer. The association between weight gain after age 18 and breast cancer risk is inconsistent across previous epidemiologic studies. To evaluate this association, we conducted a meta-analysis according to PRISMA guidelines and the established inclusion criteria. We performed a comprehensive literature search using Medline (Ovid), Embase, Scopus, Cochrane Library, and ClinicalTrials.gov to identify relevant studies published before June 3, 2022. Two reviewers independently reviewed the articles for final inclusion. Seventeen out of 4,725 unique studies met the selection criteria. The quality of studies was assessed using the Newcastle-Ottawa Scale (NOS), and all were of moderate to high quality with NOS scores ranging from 5 to 8. We included 17 studies (11 case-control, 6 cohort) in final analysis. In case-control studies, weight gain after age 18 was …

PURPOSETo identify dietary factors that are related to premature aging in adult survivors of childhood cancer, we examined the associations between plant food intakes and age-related deficit accumulation.METHODSA total of 3,322 childhood cancer survivors (age 18-65 years, mean = 31, standard deviation = 8.4) in the St Jude Lifetime Cohort had total fruit, total vegetables and subgroups, whole grains, refined grains, nuts/seeds, and nutrients intake assessed using a food frequency questionnaire. Premature aging at baseline was assessed by the deficit accumulation index (DAI) and categorized as low, medium, and high risk. Multinomial logistic regressions (reference: low risk) adjusting for confounders estimated odds ratios (ORs) and 95% CIs. Multivariable linear regression of a continuous intake against a continuous DAI was also performed.RESULTSDark green vegetable (ORhigh v low = 0.47 [95% CI, 0.28 …

Background Multiple sources of ~omic data can be generated from women at different stages of developing breast cancer, the leading cancer diagnosed in women worldwide. Traditionally interrogation of risk factors to study associations and develop prediction models for future breast events has been limited to one or few risk factors, or summary scores of clinical and tumor characteristics. Methods to bring mammography images and breast biopsies of precancer lesions together to summarize risk of cancer developing in the breast are urgently needed. Integration of these two sources has not been performed to date, but has potential to increase accuracy of risk prediction. Approach The Repository of Archival Human Breast Tissue (RAHBT) was established in 2007 at Washington University School of Medicine (WUSM) and maintains biospecimens and medical record data of women treated with breast-conserving …

Mammography remains the primary screening strategy for breast cancer, which continues to be the most prevalent cancer diagnosis among women globally. Because screening mammograms capture both the left and right breast, there is a nonnegligible correlation between the pair of images. Previous studies have explored the concept of averaging between the pair of images after proper image registration; however, no comparison has been made in directly utilizing the paired images. In this paper, we extend the bivariate functional principal component analysis over triangulations to jointly characterize the pair of imaging data bounded in an irregular domain and then nest the extracted features within the survival model to predict the onset of breast cancer. The method is applied to our motivating data from the Joanne Knight Breast Health Cohort at Siteman Cancer Center. Our findings indicate that there was no …