{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T07:12:25Z","timestamp":1793862745387,"version":"4.6.1"},"reference-count":35,"publisher":"SAGE Publications","issue":"1_suppl","license":[{"start":{"date-parts":[[2018,3,19]],"date-time":"2018-03-19T00:00:00Z","timestamp":1521417600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/100000054","name":"National Cancer Institute","doi-asserted-by":"publisher","award":["U01CA152958, U01CA199218, U01CA088278, U01CA088211"],"award-info":[{"award-number":["U01CA152958, U01CA199218, U01CA088278, U01CA088211"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Med Decis Making"],"published-print":{"date-parts":[[2018,4]]},"abstract":"<jats:p>The Cancer Intervention and Surveillance Modeling Network (CISNET) Breast Cancer Working Group is a consortium of National Cancer Institute\u2013sponsored investigators who use statistical and simulation modeling to evaluate the impact of cancer control interventions on long-term population-level breast cancer outcomes such as incidence and mortality and to determine the impact of different breast cancer control strategies. The CISNET breast cancer models have been continuously funded since 2000. The models have gone through several updates since their inception to reflect advances in the understanding of the molecular basis of breast cancer, changes in the prevalence of common risk factors, and improvements in therapy and early detection technology. This article provides an overview and history of the CISNET breast cancer models, provides an overview of the major changes in the model inputs over time, and presents examples for how CISNET breast cancer models have been used for policy evaluation.<\/jats:p>","DOI":"10.1177\/0272989x17737507","type":"journal-article","created":{"date-parts":[[2018,3,19]],"date-time":"2018-03-19T18:40:23Z","timestamp":1521484823000},"page":"3S-8S","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":42,"title":["Introduction to the Cancer Intervention and Surveillance Modeling Network (CISNET) Breast Cancer Models"],"prefix":"10.1177","volume":"38","author":[{"given":"Oguzhan","family":"Alagoz","sequence":"first","affiliation":[{"name":"Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Donald A.","family":"Berry","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, University of Texas M. D. Anderson Cancer Center, Houston, TX, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Harry J.","family":"de Koning","sequence":"additional","affiliation":[{"name":"Department of Public Health, Erasmus Medical Center, Rotterdam, the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eric J.","family":"Feuer","sequence":"additional","affiliation":[{"name":"Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sandra J.","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard Medical School and Department of Biostatistics, Harvard T. H. 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