{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T22:29:21Z","timestamp":1789770561169,"version":"4.0.1"},"reference-count":57,"publisher":"American Society of Clinical Oncology (ASCO)","issue":"9","content-domain":{"domain":["ascopubs.org"],"crossmark-restriction":true},"short-container-title":["JCO Precis Oncol"],"published-print":{"date-parts":[[2025,10]]},"abstract":"<jats:sec>\n                    <jats:title>PURPOSE<\/jats:title>\n                    <jats:p>Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA v7) predicts future breast cancer (BC) risk using data on cancer family history (FH), genetic markers, questionnaire-based risk factors, and mammographic density (MD) measured using the four-category Breast Imaging Reporting and Data System (BIRADS) classification. However, BIRADS requires manual reading, which is impractical on a large scale and may cause information loss. We extended BOADICEA to incorporate continuous MD measurements, calculated using the automated Volpara and STRATUS tools.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>We used data from the Karolinska Mammography Project for Risk Prediction of Breast Cancer cohort (60,276 participants; 1,167 incident BC). Associations between MD measurements and BC risk were estimated in a randomly selected training subset (two thirds of the data set). Percent MD residuals were calculated after regressing on age at mammography and BMI. Hazard ratios (HRs) were estimated using a Cox proportional hazards model, adjusting for FH and BOADICEA risk factors, and were incorporated into BOADICEA. The remaining one third of the cohort was used to assess the performance of the extended BOADICEA (v7.2) in predicting 5-year risks.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>The BC HRs per standard deviation of residual STRATUS density were estimated to be 1.48 (95% CI, 1.33 to 1.64) and 1.41 (95% CI, 1.27 to 1.56) for pre- and postmenopausal women, respectively. The corresponding estimates for Volpara density were 1.27 (95% CI, 1.15 to 1.40) and 1.38 (95% CI, 1.25 to 1.54). The extended BOADICEA showed improved discrimination in the testing data set over using BIRADS, with a 1%-4% increase in AUC across different combinations of risk factors. On the basis of 5-year BC risk with MD as the sole input, approximately 11% of the women were reclassified into lower risk categories and 18% into higher risk categories using the extended model.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSION<\/jats:title>\n                    <jats:p>Incorporating continuous MD measurements into BOADICEA enhances BC risk stratification and facilitates the use of automated MD measures for risk prediction.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1200\/po-25-00203","type":"journal-article","created":{"date-parts":[[2025,9,26]],"date-time":"2025-09-26T19:59:10Z","timestamp":1758916750000},"update-policy":"https:\/\/doi.org\/10.1200\/crossmark","source":"Crossref","is-referenced-by-count":5,"title":["Incorporating Continuous Mammographic Density Into the BOADICEA Breast Cancer Risk Prediction Model"],"prefix":"10.1200","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0577-1571","authenticated-orcid":true,"given":"Lorenzo","family":"Ficorella","sequence":"first","affiliation":[{"name":"Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8135-4270","authenticated-orcid":true,"given":"Mikael","family":"Eriksson","sequence":"additional","affiliation":[{"name":"Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom"},{"name":"Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kamila","family":"Czene","sequence":"additional","affiliation":[{"name":"Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5756-6222","authenticated-orcid":true,"given":"Goska","family":"Leslie","sequence":"additional","affiliation":[{"name":"Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0037-3790","authenticated-orcid":true,"given":"Xin","family":"Yang","sequence":"additional","affiliation":[{"name":"Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1508-3091","authenticated-orcid":true,"given":"Tim","family":"Carver","sequence":"additional","affiliation":[{"name":"Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7310-0338","authenticated-orcid":true,"given":"Adam E.","family":"Stokes","sequence":"additional","affiliation":[{"name":"Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2444-3247","authenticated-orcid":true,"given":"Douglas F.","family":"Easton","sequence":"additional","affiliation":[{"name":"Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom"},{"name":"Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5640-9126","authenticated-orcid":true,"given":"Per","family":"Hall","sequence":"additional","affiliation":[{"name":"Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden"},{"name":"Department of Oncology, S\u00f6dersjukhuset, Stockholm, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9223-3116","authenticated-orcid":true,"given":"Antonis C.","family":"Antoniou","sequence":"additional","affiliation":[{"name":"Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"233","reference":[{"key":"e_1_3_7_2_2","unstructured":"Cancer Research UK: Breast cancer statistics. https:\/\/www.cancerresearchuk.org\/health-professional\/cancer-statistics\/statistics-by-cancer-type\/breast-cancer"},{"key":"e_1_3_7_3_2","author":"World Health Organization","year":"2022","unstructured":"World Health Organization: Breast cancer, 2022. https:\/\/www.who.int\/news-room\/fact-sheets\/detail\/breast-cancer","journal-title":"Breast cancer"},{"key":"e_1_3_7_4_2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1412379"},{"key":"e_1_3_7_5_2","doi-asserted-by":"publisher","DOI":"10.1002\/ijc.32211"},{"key":"e_1_3_7_6_2","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2013.49.3122"},{"key":"e_1_3_7_7_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41571-020-0388-9"},{"key":"e_1_3_7_8_2","doi-asserted-by":"publisher","DOI":"10.1136\/jmedgenet-2022-108471"},{"key":"e_1_3_7_9_2","doi-asserted-by":"publisher","unstructured":"Ficorella L Yang X Mavaddat N et al: Adapting the BOADICEA breast and ovarian cancer risk models for the ethnically diverse UK population. Br J Cancer 10.1038\/s41416-025-03117-y [epub ahead of print on July 17 2025]","DOI":"10.1038\/s41416-025-03117-y"},{"key":"e_1_3_7_10_2","doi-asserted-by":"publisher","DOI":"10.1136\/jmg-2022-108806"},{"key":"e_1_3_7_11_2","doi-asserted-by":"publisher","DOI":"10.1158\/1055-9965.EPI-20-1319"},{"key":"e_1_3_7_12_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41436-018-0406-9"},{"key":"e_1_3_7_13_2","volume-title":"ACR BI-RADS\u00ae Atlas, Breast Imaging Reporting and Data System","author":"Sickles EA","year":"2013","unstructured":"Sickles EA, D'Orsi CJ, Bassett LW, et al: ACR BI-RADS\u00ae mammography, in ACR BI-RADS\u00ae Atlas, Breast Imaging Reporting and Data System. Reston, VA, American College of Radiology, 2013"},{"key":"e_1_3_7_14_2","first-page":"1133","article-title":"Mammographic densities and breast cancer risk","volume":"7","author":"Boyd NF","year":"1998","unstructured":"Boyd NF, Lockwood GA, Byng JW, et al: Mammographic densities and breast cancer risk. Cancer Epidemiol Biomarkers Prev 7:1133-1144, 1998","journal-title":"Cancer Epidemiol Biomarkers Prev"},{"key":"e_1_3_7_15_2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa062790"},{"key":"e_1_3_7_16_2","doi-asserted-by":"publisher","DOI":"10.1158\/1055-9965.EPI-06-0738"},{"key":"e_1_3_7_17_2","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2020201620"},{"key":"e_1_3_7_18_2","doi-asserted-by":"publisher","DOI":"10.1214\/19-STS729"},{"key":"e_1_3_7_19_2","doi-asserted-by":"publisher","DOI":"10.1158\/1055-9965.EPI-06-0034"},{"key":"e_1_3_7_20_2","doi-asserted-by":"publisher","DOI":"10.1023\/A:1008926607428"},{"key":"e_1_3_7_21_2","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2021.39161"},{"key":"e_1_3_7_22_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.breast.2005.04.019"},{"key":"e_1_3_7_23_2","doi-asserted-by":"publisher","DOI":"10.7326\/M15-2934"},{"key":"e_1_3_7_24_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10549-018-4690-5"},{"key":"e_1_3_7_25_2","doi-asserted-by":"crossref","unstructured":"Highnam R Brady M Yaffe MJ et al: Robust breast composition measurement\u2014Volpara\u2122 in Mart\u00ed J Oliver A Freixenet J Mart\u00ed R (eds): Digital Mammography. IWDM 2010. Lecture Notes in Computer Science Volume 6136. Berlin Heidelberg Springer 2010 pp 342-349","DOI":"10.1007\/978-3-642-13666-5_46"},{"key":"e_1_3_7_26_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-70538-3_5"},{"key":"e_1_3_7_27_2","doi-asserted-by":"publisher","DOI":"10.1093\/aje\/kwv193"},{"key":"e_1_3_7_28_2","doi-asserted-by":"publisher","DOI":"10.1093\/ije\/dyad086"},{"key":"e_1_3_7_29_2","doi-asserted-by":"publisher","DOI":"10.1002\/ijc.33396"},{"key":"e_1_3_7_30_2","doi-asserted-by":"publisher","DOI":"10.1093\/ije\/dyw357"},{"key":"e_1_3_7_31_2","doi-asserted-by":"publisher","DOI":"10.1158\/1055-9965.EPI-13-1219"},{"key":"e_1_3_7_32_2","doi-asserted-by":"publisher","DOI":"10.1186\/s13058-017-0820-y"},{"key":"e_1_3_7_33_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajhg.2018.11.002"},{"key":"e_1_3_7_34_2","doi-asserted-by":"publisher","DOI":"10.1186\/s13058-018-0954-6"},{"key":"e_1_3_7_35_2","first-page":"1","article-title":"MICE: Multivariate imputation by chained equations in R","volume":"45","author":"van Buuren S","year":"2011","unstructured":"van Buuren S, Groothuis-Oudshoorn K: MICE: Multivariate imputation by chained equations in R. J Stat Softw 45:1-67, 2011","journal-title":"J Stat Softw"},{"key":"e_1_3_7_36_2","volume-title":"The R Stats Package","author":"R Core Team","year":"2022","unstructured":"R Core Team: The R Stats Package (ed 4.2.1). Vienna, Austria, R Foundation for Statistical Computing, 2022","edition":"4"},{"key":"e_1_3_7_37_2","volume-title":"Package \u2018WeightedROC\u2019","author":"Hocking TD","year":"2020","unstructured":"Hocking TD: Package \u2018WeightedROC\u2019 (ed 2020.1.31), 2020 https:\/\/cran.r-project.org\/web\/packages\/WeightedROC\/index.html","edition":"2020"},{"key":"e_1_3_7_38_2","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2015.60.8869"},{"key":"e_1_3_7_39_2","doi-asserted-by":"publisher","DOI":"10.7326\/M13-1522"},{"key":"e_1_3_7_40_2","unstructured":"National Institute for Health and Care Excellence: Familial breast cancer: Classification care and managing breast cancer and related risks in people with a family history of breast cancer. 2023. https:\/\/www.nice.org.uk\/guidance\/cg164"},{"key":"e_1_3_7_41_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41416-024-02733-4"},{"key":"e_1_3_7_42_2","unstructured":"Cancer Research Ontario: Breast cancer screening for people at high risk. https:\/\/www.cancercareontario.ca\/en\/guidelines-advice\/cancer-continuum\/screening\/breast-cancer-high-risk"},{"key":"e_1_3_7_43_2","unstructured":"National Comprehensive Cancer Network: Guidelines; breast cancer screening and diagnosis. https:\/\/www.nccn.org"},{"key":"e_1_3_7_44_2","unstructured":"eviQ: Risk management. https:\/\/www.eviq.org.au\/cancer-genetics\/adult\/risk-management"},{"key":"e_1_3_7_45_2","unstructured":"NHS England: The surveillance of women at very high risk of developing breast cancer 2025. https:\/\/www.gov.uk\/government\/publications\/breast-screening-higher-risk-women-surveillance-protocols\/protocols-for-surveillance-of-women-at-higher-risk-of-developing-breast-cancer"},{"key":"e_1_3_7_46_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10549-019-05283-z"},{"key":"e_1_3_7_47_2","doi-asserted-by":"publisher","DOI":"10.1186\/s13058-017-0887-5"},{"key":"e_1_3_7_48_2","doi-asserted-by":"publisher","DOI":"10.1186\/s13058-018-1078-8"},{"key":"e_1_3_7_49_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12885-017-3871-7"},{"key":"e_1_3_7_50_2","doi-asserted-by":"publisher","DOI":"10.1001\/jamaoncol.2018.0174"},{"key":"e_1_3_7_51_2","doi-asserted-by":"publisher","DOI":"10.1186\/s13058-015-0653-5"},{"key":"e_1_3_7_52_2","doi-asserted-by":"publisher","DOI":"10.1186\/s13058-014-0451-5"},{"key":"e_1_3_7_53_2","doi-asserted-by":"publisher","DOI":"10.3390\/cancers15123246"},{"key":"e_1_3_7_54_2","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.22.01564"},{"key":"e_1_3_7_55_2","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/2327\/1\/012076"},{"key":"e_1_3_7_56_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacr.2023.10.018"},{"key":"e_1_3_7_57_2","doi-asserted-by":"publisher","DOI":"10.7326\/0003-4819-148-5-200803040-00004"},{"key":"e_1_3_7_58_2","doi-asserted-by":"publisher","DOI":"10.1093\/jncics\/pkae103"}],"container-title":["JCO Precision Oncology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/ascopubs.org\/doi\/pdfdirect\/10.1200\/PO-25-00203","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T13:45:52Z","timestamp":1761227152000},"score":1,"resource":{"primary":{"URL":"https:\/\/ascopubs.org\/doi\/10.1200\/PO-25-00203"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10]]},"references-count":57,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2025,10]]}},"alternative-id":["10.1200\/PO-25-00203"],"URL":"https:\/\/doi.org\/10.1200\/po-25-00203","relation":{},"ISSN":["2473-4284"],"issn-type":[{"value":"2473-4284","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10]]},"assertion":[{"value":"2025-03-06","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-07-18","order":1,"name":"revised","label":"Revised","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-08-15","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-09-26","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e2500203"}}