[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-349186-105":59,"doc-detail-349186-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","performance-of-three-breast-cancer-risk-assessment-tools-in-us-black-women","Performance of three breast cancer risk assessment tools in US Black women","","Breast cancer risk prediction models help identify high-risk women for earlier or more frequent screening, but commonly used U.S. models may underperform in Black women, potentially due to different proportions of estrogen-receptor positive breast cancer. A previously developed and externally validated BWHS model for Black women is compared here with two other U.S. models using a large cohort. Model calibration and discrimination evaluate performance across age strata and follow-up periods.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/performance-of-three-breast-cancer-risk-assessment-tools-in-us-black-women/349186/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/performance-of-three-breast-cancer-risk-assessment-tools-in-us-black-women/349186.png","ImageObject",300,407,{"name":92,"@type":93},"Cipher","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-24","2026-09-22",true,{"@type":102,"interactionType":103,"userInteractionCount":14},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"Why were breast cancer risk prediction models evaluated specifically in Black women?","Question",{"text":112,"@type":113},"The article explains that commonly used U.S. risk models appear to perform less well in Black women. It suggests this may relate to differences in the proportion of estrogen-receptor positive breast cancer.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"Which risk assessment tools were compared in the study?",{"text":117,"@type":113},"The comparison included the BWHS model, the NCI Breast Cancer Risk Assessment Tool (BCRAT) using the Black women option, and the IBIS model using clinical variables only.",{"name":119,"@type":110,"acceptedAnswer":120},"How did the BWHS model perform compared with BCRAT and IBIS?",{"text":121,"@type":113},"The BWHS model showed better calibration and discrimination in the reported comparison. It indicated improved discrimination relative to the other models, including for women under age 40.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},349186,1790246935,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":14,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":24,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":144},687208528416,"https://ap-avatar.wpscdn.com/davatar_9964176cb1d06d4a9deccf72a44ae3dc","Zirpoli et al. Breast Cancer Research (2026) 28:91  \n[https://doi.org/10.1186/s13058-026-02274-z](https://doi.org/10.1186/s13058-026-02274-z)  \nBreast Cancer Research  \nBRIEF REPORT Open Access  \nPerformance of three breast cancer risk assessment tools in US Black women  \nGary Zirpoli1, Ruth M. Pfeiffer2 and Julie R. Palmer 1,3*  \nAbstract  \nBackground Breast cancer risk prediction models aid identification of high-risk women for earlier or more frequent screening. The two most commonly used U. S. models appear to perform less well in Black women, possibly because Black women have a lower proportion of estrogen-receptor positive breast cancer. We recently developed and externally validated a model for use in Black women (BWHS model) . Here, we compare performance metrics ofthat model with the other two models using data from a large cohort of Black women.  \nResults We assessed the NCI Breast Cancer Risk Assessment Tool (BCRAT) using the option for Black women, the IBIS model, including clinical variables only, and the BWHS model in data from a cohort of 50,235 Black women followed over four sequential 5 year periods. Predictors were updated at the start of each 5 year period, and 2041 invasive breast cancers occurred. Calibration metrics, expected over observed number of cancers, were 0.99 (0 .94–1. 04), 0.97 (0 .93–1. 02), and 1.13 (1 .08–1. 18) from the BWHS, BCRAT, and IBIS models, respectively. The metrics for discriminatory accuracy, age-adjusted area under the curve (AUC), were 0.58 (0 .56–0. 59), 0.56 (0 .55–0. 57), and 0.56 (0 .55–0. 57), from the BWHS, BCRAT, and IBIS models, respectively.  \nConclusions In this comparison, the BWHS model had better calibration and discrimination than BCRAT and IBIS, including among women age \u003C 40, indicating a benefit to using the BWHS model for Black women. While models that incorporate mammographic features may have higher AUCs, models based on clinical factors are beneficial for young women and those without available mammography data.  \nKeywords Breast cancer incidence, Risk prediction model, Black women  \n*Correspondence:  \nJulie R. Palmer  \n[jpalmer@bu.edu](jpalmer@bu.edu)  \n1Slone Epidemiology Center at Boston University, 72 E. Concord Street, L-7, Boston, MA 02118, USA  \n2Division of Epidemiology and Cancer Genetics, National Cancer Institute, Bethesda, MD, USA  \n3Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA  \nIntroduction  \nAbsolute breast cancer risk prediction models estimate a woman’s risk of developing breast cancer over a given period (e.g. 5 years) in the presence of competing risksand are useful for recommending screening strategies and risk-reduction approaches [1]. However, many primary care providers do not use risk prediction calculators due to time constraints during primary care visits; thus, adding a new calculator for a specific population requires evidence of its relative benefit. To this end, we compared performance metrics of the BWHS calculator [2, 3], developed specifically for breast cancer risk assessment in Black women, with metrics from the two  \n© The Author(s) 2026. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds th","cbCaigGGPbTAsUVo","https://ap.wps.com/l/cbCaigGGPbTAsUVo","pdf",853541,"English","# Abstract\n# Introduction\n# Methods\n## Validation study population\n## BWHS model\n## BCRAT model","[{\"question\":\"Why were breast cancer risk prediction models evaluated specifically in Black women?\",\"answer\":\"The article explains that commonly used U.S. risk models appear to perform less well in Black women. It suggests this may relate to differences in the proportion of estrogen-receptor positive breast cancer.\"},{\"question\":\"Which risk assessment tools were compared in the study?\",\"answer\":\"The comparison included the BWHS model, the NCI Breast Cancer Risk Assessment Tool (BCRAT) using the Black women option, and the IBIS model using clinical variables only.\"},{\"question\":\"How did the BWHS model perform compared with BCRAT and IBIS?\",\"answer\":\"The BWHS model showed better calibration and discrimination in the reported comparison. It indicated improved discrimination relative to the other models, including for women under age 40.\"}]","Performance of three breast cancer risk assessment tools in US Black women | PDF",1790082102,13]