ArticleCancer causes & control : CCC2022
Joanne Knight Breast Health Cohort at Siteman Cancer Center.
Article in Cancer causes & control : CCC, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 19 citations in OpenAlex.
- Subsequent breast cancer risk after benign breast biopsy in racially diverse women: Siteman Cancer Center.Journal of the National Cancer Institute · 2026Article
- Investigating the relationship between breast cancer risk factors and an AI-generated mammographic texture feature in the Nurses' Health Study II.NPJ breast cancer · 2025Article
- Statistically Significant Association Does not Imply Improvement in Prediction of Clinical Outcomes.Cancer prevention research (Philadelphia, Pa.) · 2025Article
- Score Test for Functional Markov Process With Image Predictor.Statistics in medicine · 2025Article
- Validation of a Dynamic Risk Prediction Model Incorporating Prior Mammograms in a Diverse Population.JAMA network open · 2025Article
- Deriving a Mammogram-Based Risk Score from Screening Digital Breast Tomosynthesis for 5-Year Breast Cancer Risk Prediction.Cancer prevention research (Philadelphia, Pa.) · 2025Article
- Automated Breast Density Assessment for Full-Field Digital Mammography and Digital Breast Tomosynthesis.Cancer prevention research (Philadelphia, Pa.) · 2025Article
- Permutation Test for Image-on-Scalar Regression With an Application to Breast Cancer.Statistics in medicine · 2024Article
- Development and Validation of Dynamic 5-Year Breast Cancer Risk Model Using Repeated Mammograms.JCO clinical cancer informatics · 2024Article
- Modeling correlated pairs of mammogram images.Statistics in medicine · 2024Article
- Pectoral muscle removal in mammogram images: A novel approach for improved accuracy and efficiency.Cancer causes & control : CCC · 2024Article
- Causal mediation analysis using high-dimensional image mediator bounded in irregular domain with an application to breast cancer.Biometrics · 2023Article
- Association and Prediction Utilizing Craniocaudal and Mediolateral Oblique View Digital Mammography and Long-Term Breast Cancer Risk.Cancer prevention research (Philadelphia, Pa.) · 2023Article
- Supervised two-dimensional functional principal component analysis with time-to-event outcomes and mammogram imaging data.Biometrics · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 1 institution in 1 country.
Funding
Abstract
purposeThe Joanne Knight Breast Health Cohort was established to link breast cancer risk factors, mammographic breast density, benign breast biopsies and associated tissue markers, and blood markers in a diverse population of women undergoing routine mammographic screening to study risk factors and validate models for breast cancer risk prediction.
methodsWomen were recruited from November 2008 to April 2012 through the mammography service at the Joanne Knight Breast Health Center at Washington University in St. Louis, Missouri. Baseline questionnaire risk factors, blood, and screening mammograms were collected from 12,153 women. Of these, 1,672 were excluded for prior history of any cancer (except non-melanoma skin) or diagnosis of breast cancer within 6 months of blood draw/registration for the study, for a total of 10,481 women. Follow-up is through linking to electronic health records, tumor registry, and death register. Routine screening mammograms are collected every 1-2 years and incident benign breast biopsies and cancers are identified through record linkage to pathology and tumor registries. Formal fixed tissue samples are retrieved and stored for analysis. County-level measures of structural inequality were derived from publicly available resources.
resultsCohort Composition: median age at entry was 54.8 years and 26.7% are African American. Through 2020, 74% of participants have had a medical center visit within the past year and 80% within the past 2 years representing an average of 9.7 person-years of follow-up from date of blood draw per participant. 9,997 women are continuing in follow-up. Data collected at baseline include breast cancer risk factors, plasma and white blood cells, and mammograms prior to baseline, at baseline, and during follow-up.
conclusionThis cohort assembled and followed in a routine mammography screening and care setting that serves a diverse population of women in the St. Louis region now provides opportunities to integrate study of questionnaire measures, plasma and DNA markers, benign and malignant tissue markers, and repeated breast image features into prospective evaluation for breast cancer etiology and outcomes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.