{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T08:11:53Z","timestamp":1790151113705,"version":"4.0.1"},"reference-count":27,"publisher":"Wiley","license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Institut de Recherche en Sant\u00e9 Publique"},{"DOI":"10.13039\/501100004099","name":"Ligue Nationale Contre le Cancer","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100004099","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100010463","name":"Institut Curie","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100010463","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational and Mathematical Methods in Medicine"],"published-print":{"date-parts":[[2017]]},"abstract":"<jats:p>When considering a genetic disease with variable age at onset (e.g., familial amyloid neuropathy, cancers), computing the individual risk of the disease based on family history (FH) is of critical interest for both clinicians and patients. Such a risk is very challenging to compute because <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M1\"><mml:mrow><mml:mfenced separators=\"|\"><mml:mrow><mml:mn fontstyle=\"italic\">1<\/mml:mn><\/mml:mrow><\/mml:mfenced><\/mml:mrow><\/mml:math> the genotype <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M2\"><mml:mrow><mml:mi>X<\/mml:mi><\/mml:mrow><\/mml:math> of the individual of interest is in general unknown, <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M3\"><mml:mrow><mml:mfenced separators=\"|\"><mml:mrow><mml:mn fontstyle=\"italic\">2<\/mml:mn><\/mml:mrow><\/mml:mfenced><\/mml:mrow><\/mml:math> the posterior distribution <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M4\"><mml:mi mathvariant=\"double-struck\">P<\/mml:mi><mml:mfenced separators=\"|\"><mml:mrow><mml:mi>X<\/mml:mi><mml:mrow><mml:mo>\u2223<\/mml:mo><\/mml:mrow><mml:mi mathvariant=\"normal\">F<\/mml:mi><mml:mi mathvariant=\"normal\">H<\/mml:mi><mml:mo>,<\/mml:mo><mml:mi>T<\/mml:mi><mml:mo>&gt;<\/mml:mo><mml:mi>t<\/mml:mi><\/mml:mrow><\/mml:mfenced><\/mml:math> changes with <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M5\"><mml:mrow><mml:mi>t<\/mml:mi><\/mml:mrow><\/mml:math> (<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M6\"><mml:mrow><mml:mi>T<\/mml:mi><\/mml:mrow><\/mml:math> is the age at disease onset for the targeted individual), and <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M7\"><mml:mrow><mml:mfenced separators=\"|\"><mml:mrow><mml:mn fontstyle=\"italic\">3<\/mml:mn><\/mml:mrow><\/mml:mfenced><\/mml:mrow><\/mml:math> the competing risk of death is not negligible. In this work, we present modeling of this problem using a Bayesian network mixed with (right-censored) survival outcomes where hazard rates only depend on the genotype of each individual. We explain how belief propagation can be used to obtain posterior distribution of genotypes given the FH and how to obtain a time-dependent posterior hazard rate for any individual in the pedigree. Finally, we use this posterior hazard rate to compute individual risk, with or without the competing risk of death. Our method is illustrated using the Claus-Easton model for breast cancer. The competing risk of death is derived from the national French registry.<\/jats:p>","DOI":"10.1155\/2017\/9193630","type":"journal-article","created":{"date-parts":[[2017,11,9]],"date-time":"2017-11-09T23:31:36Z","timestamp":1510270296000},"page":"1-14","source":"Crossref","is-referenced-by-count":5,"title":["Computing Individual Risks Based on Family History in Genetic Disease in the Presence of Competing Risks"],"prefix":"10.1155","volume":"2017","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9910-2354","authenticated-orcid":true,"given":"Gregory","family":"Nuel","sequence":"first","affiliation":[{"name":"LPMA, UMR CNRS 7599, Paris, France"},{"name":"UPMC, Sorbonne Universit\u00e9s, Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexandra","family":"Lefebvre","sequence":"additional","affiliation":[{"name":"UPSud, Paris-Saclay, Orsay, France"},{"name":"Institut Curie, Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Olivier","family":"Bouaziz","sequence":"additional","affiliation":[{"name":"MAP5, UMR CNRS 8145, Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","reference":[{"key":"15","doi-asserted-by":"publisher","DOI":"10.1126\/science.2270482"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1002\/1097-0142(19940201)73:3<643::AID-CNCR2820730323>3.0.CO;2-5"},{"key":"23","first-page":"369","volume":"30:0","year":"2016","journal-title":"Medical Journal of The Islamic Republic of Iran"},{"key":"26","doi-asserted-by":"publisher","DOI":"10.1136\/jmg.40.11.e120"},{"key":"1","doi-asserted-by":"publisher","DOI":"10.1002\/gepi.20390"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1093\/aje\/kwu202"},{"key":"28","doi-asserted-by":"publisher","DOI":"10.1177\/0962280216631360"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1111\/j.1532-5415.2010.02767.x"},{"issue":"2","key":"8","first-page":"232","volume":"48","year":"1991","journal-title":"American Journal of Human Genetics"},{"issue":"4","key":"12","first-page":"678","volume":"520","year":"1993","journal-title":"American Journal of Human Genetics"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1038\/sj.bjc.6602175"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1001\/jama.296.12.1479"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1016\/j.femme.2014.03.004"},{"key":"21","series-title":"Oxford Statistical Science Series","volume":"17","year":"1996"},{"key":"24","doi-asserted-by":"publisher","DOI":"10.1086\/301904"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/18.suppl_1.S189"},{"key":"22","doi-asserted-by":"publisher","DOI":"10.1214\/ss\/1081443232"},{"key":"25","doi-asserted-by":"publisher","DOI":"10.1002\/gepi.20635"},{"key":"27","doi-asserted-by":"publisher","DOI":"10.1186\/1297-9686-41-52"},{"key":"18","series-title":"Adaptive Computation and Machine Learning","year":"2009"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1038\/sj.bjc.6600008"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.1159\/000154043"},{"key":"20","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btt187"},{"issue":"6","key":"19","first-page":"1347","volume":"58","year":"1996","journal-title":"American Journal of Human Genetics"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1016\/S0004-3702(00)00069-2"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4612-4348-9"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4385"}],"container-title":["Computational and Mathematical Methods in Medicine"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/cmmm\/2017\/9193630.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cmmm\/2017\/9193630.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cmmm\/2017\/9193630.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,5,18]],"date-time":"2020-05-18T14:02:15Z","timestamp":1589810535000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/cmmm\/2017\/9193630\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"references-count":27,"alternative-id":["9193630","9193630"],"URL":"https:\/\/doi.org\/10.1155\/2017\/9193630","relation":{},"ISSN":["1748-670X","1748-6718"],"issn-type":[{"value":"1748-670X","type":"print"},{"value":"1748-6718","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017]]}}}