{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T20:02:16Z","timestamp":1784404936507,"version":"3.55.0"},"reference-count":33,"publisher":"Wiley","issue":"21","license":[{"start":{"date-parts":[[2022,4,6]],"date-time":"2022-04-06T00:00:00Z","timestamp":1649203200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100007316","name":"Division of Cancer Prevention, National Cancer Institute","doi-asserted-by":"publisher","award":["K01 CA181547"],"award-info":[{"award-number":["K01 CA181547"]}],"id":[{"id":"10.13039\/100007316","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Cancer Institute","doi-asserted-by":"publisher","award":["CA181547"],"award-info":[{"award-number":["CA181547"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Cancer Institute","doi-asserted-by":"publisher","award":["K01"],"award-info":[{"award-number":["K01"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Cancer Medicine"],"published-print":{"date-parts":[[2022,11]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Identifying women with high risk of breast cancer is necessary to study high\u2010risk experiences and deliver risk\u2010management care. Risk prediction models estimate individuals' lifetime risk but have rarely been applied in community\u2010based settings among women not yet receiving specialized care. Therefore, we aimed: (1) to apply three breast cancer risk prediction models (i.e., Gail, Claus, and IBIS) to a racially diverse, community\u2010based sample of women, and (2) to assess risk prediction estimates using survey data.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>An online survey was administered to women who were determined by a screening instrument to have potentially high risk for breast cancer. Risk prediction models were applied using their self\u2010reported family and medical history information. Inclusion in the <jats:italic>high\u2010risk subsample<\/jats:italic> required \u226520% lifetime risk per \u22651 model. Descriptive statistics were used to compare the proportions of women identified as high risk by each model.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p><jats:italic>N<\/jats:italic>\u00a0=\u00a01053 women were initially eligible and completed the survey. All women, except one, self\u2010reported the information necessary to run at least one model; 90% had sufficient information for &gt;1 model. The <jats:italic>high\u2010risk subsample<\/jats:italic> included 717 women, of which 75% were identified by one model only; 96% were identified by IBIS, 3% by Claus, &lt;1% by Gail. In the high\u2010risk subsample, 20% were identified by two models and 3% by all three models.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Assessing breast cancer risk using self\u2010reported data in a community\u2010based sample was feasible. Different models identify substantially different groups of women who may be at high risk for breast cancer; use of multiple models may be beneficial for research and clinical care.<\/jats:p><\/jats:sec>","DOI":"10.1002\/cam4.4721","type":"journal-article","created":{"date-parts":[[2022,4,7]],"date-time":"2022-04-07T05:34:35Z","timestamp":1649309675000},"page":"4043-4052","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Predicting breast cancer risk in a racially diverse, community\u2010based sample of potentially high\u2010risk women"],"prefix":"10.1002","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6949-4932","authenticated-orcid":false,"given":"Rachel J.","family":"Meadows","sequence":"first","affiliation":[{"name":"Center for Epidemiology &amp; Healthcare Delivery Research JPS Health Network  Fort Worth Texas USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wilson","family":"Figueroa","sequence":"additional","affiliation":[{"name":"The Ohio State University Center for Health Outcomes and Policy Evaluation Studies, College of Public Health  Columbus Ohio USA"},{"name":"Division of Health Services Management &amp; Policy College of Public Health, The Ohio State University  Columbus Ohio USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kate P.","family":"Shane\u2010Carson","sequence":"additional","affiliation":[{"name":"Division of Human Genetics, Department of Internal Medicine Ohio State University Comprehensive Cancer Center  Columbus Ohio USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tasleem J.","family":"Padamsee","sequence":"additional","affiliation":[{"name":"Division of Health Services Management &amp; Policy College of Public Health, The Ohio State University  Columbus Ohio USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2022,4,6]]},"reference":[{"key":"e_1_2_13_2_1","doi-asserted-by":"publisher","DOI":"10.6004\/jnccn.2021.0001"},{"key":"e_1_2_13_3_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2019.10987"},{"key":"e_1_2_13_4_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13058-017-0826-5"},{"key":"e_1_2_13_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.amjsurg.2016.06.010"},{"key":"e_1_2_13_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/jgc4.1413"},{"key":"e_1_2_13_7_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12905-021-01279-4"},{"key":"e_1_2_13_8_1","doi-asserted-by":"publisher","DOI":"10.1080\/13557858.2018.1562053"},{"key":"e_1_2_13_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10549-017-4247-z"},{"key":"e_1_2_13_10_1","doi-asserted-by":"publisher","DOI":"10.1093\/jnci\/djv042"},{"key":"e_1_2_13_11_1","doi-asserted-by":"publisher","DOI":"10.1002\/1097-0142(19940201)73:3<643::aid-cncr2820730323>3.0.co;2-5"},{"key":"e_1_2_13_12_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.1668"},{"key":"e_1_2_13_13_1","doi-asserted-by":"publisher","DOI":"10.1093\/jnci\/djz177"},{"key":"e_1_2_13_14_1","doi-asserted-by":"publisher","DOI":"10.1245\/s10434-019-07814-w"},{"key":"e_1_2_13_15_1","doi-asserted-by":"publisher","DOI":"10.1158\/1940-6207.CAPR-20-0002"},{"key":"e_1_2_13_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10552-017-0858-2"},{"key":"e_1_2_13_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11606-017-4224-6"},{"key":"e_1_2_13_18_1","doi-asserted-by":"publisher","DOI":"10.1158\/1055-9965.EPI-12-0570"},{"key":"e_1_2_13_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.clbc.2019.02.009"},{"key":"e_1_2_13_20_1","unstructured":"Bright Pink.Assess your risk. 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