{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,20]],"date-time":"2025-06-20T05:03:32Z","timestamp":1750395812206,"version":"3.37.3"},"reference-count":44,"publisher":"Oxford University Press (OUP)","issue":"12","license":[{"start":{"date-parts":[[2023,8,3]],"date-time":"2023-08-03T00:00:00Z","timestamp":1691020800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","award":["R01-HG009129"],"award-info":[{"award-number":["R01-HG009129"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,11,17]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>To determine whether data-driven family histories (DDFH) derived from linked EHRs of patients and their parents can improve prediction of patients\u2019 10-year risk of diabetes and atherosclerotic cardiovascular disease (ASCVD).<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Materials and Methods<\/jats:title>\n                  <jats:p>A retrospective cohort study using data from Israel\u2019s largest healthcare organization. A random sample of 200\u00a0000 subjects aged 40\u201360\u00a0years on the index date (January 1, 2010) was included. Subjects with insufficient history (&amp;lt;1\u00a0year) or insufficient follow-up (&amp;lt;10\u00a0years) were excluded. Two separate XGBoost models were developed\u20141 for diabetes and 1 for ASCVD\u2014to predict the 10-year risk for each outcome based on data available prior to the index date of January 1, 2010.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Overall, the study included 110\u00a0734 subject-father-mother triplets. There were 22\u00a0153 cases of diabetes (20%) and 11\u00a0715 cases of ASCVD (10.6%). The addition of parental information significantly improved prediction of diabetes risk (P\u2009&amp;lt;\u2009.001), but not ASCVD risk. For both outcomes, maternal medical history was more predictive than paternal medical history. A binary variable summarizing parental disease state delivered similar predictive results to the full parental EHR.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Discussion<\/jats:title>\n                  <jats:p>The increasing availability of EHRs for multiple family generations makes DDFH possible and can assist in delivering more personalized and precise medicine to patients. Consent frameworks must be established to enable sharing of information across generations, and the results suggest that sharing the full records may not be necessary.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>DDFH can address limitations of patient self-reported family history, and it improves clinical predictions for some conditions, but not for all, and particularly among younger adults.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/jamia\/ocad154","type":"journal-article","created":{"date-parts":[[2023,8,3]],"date-time":"2023-08-03T18:25:48Z","timestamp":1691087148000},"page":"1915-1924","source":"Crossref","is-referenced-by-count":2,"title":["The value of parental medical records for the prediction of diabetes and cardiovascular disease: a novel method for generating and incorporating family histories"],"prefix":"10.1093","volume":"30","author":[{"given":"Yuval","family":"Barak-Corren","sequence":"first","affiliation":[{"name":"Predictive Medicine Group, Computational Health Informatics Program, Boston Children\u2019s Hospital , Boston, Massachusetts, USA"}]},{"given":"David","family":"Tsurel","sequence":"additional","affiliation":[{"name":"Predictive Medicine Group, Computational Health Informatics Program, Boston Children\u2019s Hospital , Boston, Massachusetts, USA"},{"name":"Clalit Research Institute , Ramat Gan, Israel"},{"name":"The Hebrew University of Jerusalem , Jerusalem, Israel"}]},{"given":"Daphna","family":"Keidar","sequence":"additional","affiliation":[{"name":"Predictive Medicine Group, Computational Health Informatics Program, Boston Children\u2019s Hospital , Boston, Massachusetts, USA"},{"name":"Clalit Research Institute , Ramat Gan, Israel"}]},{"given":"Ilan","family":"Gofer","sequence":"additional","affiliation":[{"name":"Clalit Research Institute , Ramat Gan, Israel"}]},{"given":"Dafna","family":"Shahaf","sequence":"additional","affiliation":[{"name":"The Hebrew University of Jerusalem , Jerusalem, Israel"}]},{"given":"Maya","family":"Leventer-Roberts","sequence":"additional","affiliation":[{"name":"Clalit Research Institute , Ramat Gan, Israel"},{"name":"Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai , New York, New York, USA"},{"name":"Department of Pediatrics, Icahn School of Medicine at Mount Sinai , New York, New York, USA"}]},{"given":"Noam","family":"Barda","sequence":"additional","affiliation":[{"name":"Clalit Research Institute , Ramat Gan, Israel"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9908-5523","authenticated-orcid":false,"given":"Ben Y","family":"Reis","sequence":"additional","affiliation":[{"name":"Predictive Medicine Group, Computational Health Informatics Program, Boston Children\u2019s Hospital , Boston, Massachusetts, USA"},{"name":"Harvard Medical School , Boston, Massachusetts, USA"}]}],"member":"286","published-online":{"date-parts":[[2023,8,3]]},"reference":[{"issue":"22","key":"2023111709555244000_ocad154-B1","doi-asserted-by":"crossref","first-page":"2333","DOI":"10.1056\/NEJMsb042979","article-title":"The family history \u2013 more important than ever","volume":"351","author":"Guttmacher","year":"2004","journal-title":"N Engl J Med"},{"issue":"1","key":"2023111709555244000_ocad154-B2","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1007\/s10897-009-9264-6","article-title":"Primary care providers\u2019 responses to patient-generated family history","volume":"19","author":"Fuller","year":"2010","journal-title":"J Genet Couns"},{"issue":"4","key":"2023111709555244000_ocad154-B3","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1097\/00125817-200207000-00009","article-title":"Can family history be used as a tool for public health and preventive medicine?","volume":"4","author":"Yoon","year":"2002","journal-title":"Genet Med"},{"issue":"2","key":"2023111709555244000_ocad154-B4","doi-asserted-by":"crossref","first-page":"115","DOI":"10.3390\/jpm4020115","article-title":"Formative evaluation of clinician experience with integrating family history-based clinical decision support into clinical practice","volume":"4","author":"Doerr","year":"2014","journal-title":"J Pers Med"},{"volume-title":"Family History Implementation in the Challenging Setting of Routine Clinical Care","year":"2012","author":"NHGRI","key":"2023111709555244000_ocad154-B5"},{"issue":"2","key":"2023111709555244000_ocad154-B6","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/S0002-9149(00)01303-5","article-title":"Usefulness of cardiovascular family history data for population-based preventive medicine and medical research (the Health Family Tree Study and the NHLBI Family Heart Study)","volume":"87","author":"Williams","year":"2001","journal-title":"Am J Cardiol"},{"key":"2023111709555244000_ocad154-B7","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.ypmed.2014.04.007","article-title":"Improving long-term prediction of first cardiovascular event: the contribution of family history of coronary heart disease and social status","volume":"64","author":"Veronesi","year":"2014","journal-title":"Prev Med"},{"issue":"18","key":"2023111709555244000_ocad154-B8","doi-asserted-by":"crossref","first-page":"2204","DOI":"10.1001\/jama.291.18.2204","article-title":"Parental cardiovascular disease as a risk factor for cardiovascular disease in middle-aged adults: a prospective study of parents and offspring","volume":"291","author":"Lloyd-Jones","year":"2004","journal-title":"JAMA"},{"issue":"25","key":"2023111709555244000_ocad154-B9","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1093\/oxfordjournals.jncimonographs.a024184","article-title":"Risk perception and risk communication for cancer screening behaviors: a review","volume":"1999","author":"Vernon","year":"1999","journal-title":"J Natl Cancer Inst Monogr"},{"issue":"11","key":"2023111709555244000_ocad154-B10","doi-asserted-by":"crossref","first-page":"1158","DOI":"10.1037\/a0031622","article-title":"The influence of family history on cognitive heuristics, risk perceptions, and prostate cancer screening behavior","volume":"32","author":"McDowell","year":"2013","journal-title":"Health Psychol"},{"issue":"2","key":"2023111709555244000_ocad154-B11","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/S0749-3797(02)00588-3","article-title":"Family history of diabetes as a potential public health tool","volume":"24","author":"Harrison","year":"2003","journal-title":"Am J Prev Med"},{"issue":"Pt 1","key":"2023111709555244000_ocad154-B12","first-page":"13","article-title":"Do physicians take action on high risk family history information provided by patients outside of a clinic visit?","volume":"129","author":"Volk","year":"2007","journal-title":"Stud Health Technol Inform"},{"issue":"10","key":"2023111709555244000_ocad154-B13","doi-asserted-by":"crossref","first-page":"761","DOI":"10.1038\/gim.2013.72","article-title":"The Electronic Medical Records and Genomics (eMERGE) Network: past, present, and future","volume":"15","author":"Gottesman","year":"2013","journal-title":"Genet Med"},{"issue":"79","key":"2023111709555244000_ocad154-B14","doi-asserted-by":"crossref","first-page":"79re1","DOI":"10.1126\/scitranslmed.3001807","article-title":"Electronic medical records for genetic research: results of the eMERGE consortium","volume":"3","author":"Kho","year":"2011","journal-title":"Sci Transl Med"},{"issue":"3","key":"2023111709555244000_ocad154-B15","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1093\/oxfordjournals.aje.a009259","article-title":"Comparison of self-reported and database-linked family history of cancer data in a case-control study","volume":"146","author":"Kerber","year":"1997","journal-title":"Am J Epidemiol"},{"issue":"2","key":"2023111709555244000_ocad154-B16","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1016\/S0749-3797(02)00593-7","article-title":"Validation of family history data in cancer family registries","volume":"24","author":"Ziogas","year":"2003","journal-title":"Am J Prev Med"},{"issue":"10","key":"2023111709555244000_ocad154-B17","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1111\/j.1440-1754.2010.01798.x","article-title":"When is family history obtained? \u2013 lack of timely documentation of family history among overweight and hypertensive paediatric patients","volume":"46","author":"Benson","year":"2010","journal-title":"J Paediatr Child Health"},{"issue":"1","key":"2023111709555244000_ocad154-B18","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1016\/j.jclinepi.2011.05.003","article-title":"Accuracy of self-reported family history is strongly influenced by the accuracy of self-reported personal health status of relatives","volume":"65","author":"Janssens","year":"2012","journal-title":"J Clin Epidemiol"},{"key":"2023111709555244000_ocad154-B19","doi-asserted-by":"crossref","DOI":"10.1002\/0471142905.hg0921s66","article-title":"The application of computer-based tools in obtaining the genetic family history","author":"Giovanni","year":"2010","journal-title":"Curr Protoc Hum Genet"},{"issue":"2","key":"2023111709555244000_ocad154-B20","doi-asserted-by":"crossref","first-page":"125","DOI":"10.3109\/13814788.2013.840825","article-title":"Family history tools for primary care are not ready yet to be implemented. A systematic review","volume":"20","author":"de Hoog","year":"2014","journal-title":"Eur J Gen Pract"},{"issue":"1","key":"2023111709555244000_ocad154-B21","first-page":"A33","article-title":"Developing family healthware, a family history screening tool to prevent common chronic diseases","volume":"6","author":"Yoon","year":"2008","journal-title":"Prev Chronic Dis"},{"issue":"3","key":"2023111709555244000_ocad154-B22","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1111\/j.1525-1497.2004.30401.x","article-title":"Reconsidering the family history in primary care","volume":"19","author":"Rich","year":"2004","journal-title":"J Gen Intern Med"},{"issue":"3","key":"2023111709555244000_ocad154-B23","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1097\/00125817-200005000-00004","article-title":"Family history-taking in community family practice: Implications for genetic screening","volume":"2","author":"Acheson","year":"2000","journal-title":"Genet Med"},{"issue":"11","key":"2023111709555244000_ocad154-B24","first-page":"879","article-title":"Chronic disease prevention in general practice \u2013 applying the family history","volume":"35","author":"Reid","year":"2006","journal-title":"Aust Fam Physician"},{"issue":"2","key":"2023111709555244000_ocad154-B25","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1093\/eurpub\/ckz152","article-title":"Constructing data-derived family histories using electronic health records from a single healthcare delivery system","volume":"30","author":"Leventer-Roberts","year":"2020","journal-title":"Eur J Public Health"},{"issue":"25","key":"2023111709555244000_ocad154-B26","doi-asserted-by":"crossref","first-page":"e34","DOI":"10.1056\/NEJMoa1800389","article-title":"Primary prevention of cardiovascular disease with a mediterranean diet supplemented with extra-virgin olive oil or nuts","volume":"378","author":"Estruch","year":"2018","journal-title":"N Engl J Med"},{"issue":"2\u20133","key":"2023111709555244000_ocad154-B27","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.healthpol.2011.07.008","article-title":"Switching sickness funds in Israel: adverse selection or risk selection? Some insights from the analysis of the relative costs of switchers","volume":"102","author":"Shmueli","year":"2011","journal-title":"Health Policy"},{"issue":"1","key":"2023111709555244000_ocad154-B28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12916-014-0241-z","article-title":"Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement","volume":"13","author":"Collins","year":"2015","journal-title":"BMC Med"},{"issue":"1","key":"2023111709555244000_ocad154-B29","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1038\/s41746-020-00331-1","article-title":"Machine learning and atherosclerotic cardiovascular disease risk prediction in a multi-ethnic population","volume":"3","author":"Ward","year":"2020","journal-title":"NPJ Digit Med"},{"key":"2023111709555244000_ocad154-B30","doi-asserted-by":"crossref","first-page":"2935","DOI":"10.1016\/j.jacc.2013.11.005","article-title":"2013 ACC\/AHA Guideline on the Assessment of Cardiovascular Risk: a report of the American College of Cardiology\/American Heart Association Task Force on practice guidelines","volume":"63 (25 Pt B)","author":"Goff","year":"2014","journal-title":"J Am Coll Cardiol"},{"issue":"8","key":"2023111709555244000_ocad154-B31","doi-asserted-by":"crossref","first-page":"e009952","DOI":"10.1136\/bmjopen-2015-009952","article-title":"Systematic review of validated case definitions for diabetes in ICD-9-coded and ICD-10-coded data in adult populations","volume":"6","author":"Khokhar","year":"2016","journal-title":"BMJ Open"},{"issue":"6","key":"2023111709555244000_ocad154-B32","doi-asserted-by":"crossref","first-page":"1347","DOI":"10.2337\/dc09-1444","article-title":"Derivation and validation of a new cardiovascular risk score for people with type 2 diabetes: the new zealand diabetes cohort study","volume":"33","author":"Elley","year":"2010","journal-title":"Diabetes Care"},{"issue":"1","key":"2023111709555244000_ocad154-B33","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1038\/s41746-021-00537-x","article-title":"Prediction across healthcare settings: a case study in predicting emergency department disposition","volume":"4","author":"Barak-Corren","year":"2021","journal-title":"NPJ Digit Med"},{"issue":"11","key":"2023111709555244000_ocad154-B34","doi-asserted-by":"crossref","first-page":"e050989","DOI":"10.1136\/bmjopen-2021-050989","article-title":"Predictive model and risk analysis for diabetic retinopathy using machine learning: a retrospective cohort study in China","volume":"11","author":"Li","year":"2021","journal-title":"BMJ Open"},{"issue":"2","key":"2023111709555244000_ocad154-B35","doi-asserted-by":"crossref","first-page":"e001802","DOI":"10.1136\/openhrt-2021-001802","article-title":"Machine learning approaches improve risk stratification for secondary cardiovascular disease prevention in multiethnic patients","volume":"8","author":"Sarraju","year":"2021","journal-title":"Open Heart"},{"key":"2023111709555244000_ocad154-B36","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1186\/1471-2105-12-77","article-title":"pROC: an open-source package for R and S+ to analyze and compare ROC curves","volume":"12","author":"Robin","year":"2011","journal-title":"BMC Bioinformatics"},{"issue":"3","key":"2023111709555244000_ocad154-B37","doi-asserted-by":"crossref","first-page":"837","DOI":"10.2307\/2531595","article-title":"Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach","volume":"44","author":"DeLong","year":"1988","journal-title":"Biometrics"},{"issue":"9","key":"2023111709555244000_ocad154-B38","doi-asserted-by":"crossref","first-page":"1167","DOI":"10.1016\/j.mayocp.2018.07.010","article-title":"Family history of cardiovascular disease: how detailed should it be?","volume":"93","author":"Bittencourt","year":"2018","journal-title":"Mayo Clin Proc"},{"issue":"2","key":"2023111709555244000_ocad154-B39","doi-asserted-by":"crossref","first-page":"40","DOI":"10.4239\/wjd.v4.i2.40","article-title":"Parental transmission of type 2 diabetes mellitus in a highly endogamous population","volume":"4","author":"Bener","year":"2013","journal-title":"World J Diabetes"},{"issue":"1","key":"2023111709555244000_ocad154-B40","doi-asserted-by":"crossref","first-page":"19","DOI":"10.2174\/1573399812666151022143502","article-title":"Family history of type 2 diabetes: does having a diabetic parent increase the risk?","volume":"13","author":"Papazafiropoulou","year":"2017","journal-title":"Curr Diabetes Rev"},{"issue":"6","key":"2023111709555244000_ocad154-B41","doi-asserted-by":"crossref","first-page":"938","DOI":"10.2337\/diacare.22.6.938","article-title":"Excess maternal transmission of type 2 diabetes. The Northern California Kaiser Permanente Diabetes Registry","volume":"22","author":"Karter","year":"1999","journal-title":"Diabetes Care"},{"issue":"8","key":"2023111709555244000_ocad154-B42","doi-asserted-by":"crossref","first-page":"1702","DOI":"10.1007\/s00125-016-3973-9","article-title":"Excess maternal transmission of variants in the THADA gene to offspring with type 2 diabetes","volume":"59","author":"Prasad","year":"2016","journal-title":"Diabetologia"},{"issue":"12","key":"2023111709555244000_ocad154-B43","doi-asserted-by":"crossref","first-page":"e0163334","DOI":"10.1371\/journal.pone.0163334","article-title":"Parental age of onset of cardiovascular disease as a predictor for offspring age of onset of cardiovascular disease","volume":"11","author":"Allport","year":"2016","journal-title":"PLoS One"},{"issue":"7","key":"2023111709555244000_ocad154-B44","doi-asserted-by":"crossref","first-page":"1692","DOI":"10.1016\/j.cell.2018.04.032","article-title":"Disease heritability inferred from familial relationships reported in medical records","volume":"173","author":"Polubriaginof","year":"2018","journal-title":"Cell"}],"container-title":["Journal of the American Medical Informatics Association"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/jamia\/article-pdf\/30\/12\/1915\/53477665\/ocad154.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/jamia\/article-pdf\/30\/12\/1915\/53477665\/ocad154.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,17]],"date-time":"2023-11-17T13:29:37Z","timestamp":1700227777000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/jamia\/article\/30\/12\/1915\/7236560"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,3]]},"references-count":44,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2023,8,3]]},"published-print":{"date-parts":[[2023,11,17]]}},"URL":"https:\/\/doi.org\/10.1093\/jamia\/ocad154","relation":{},"ISSN":["1067-5027","1527-974X"],"issn-type":[{"type":"print","value":"1067-5027"},{"type":"electronic","value":"1527-974X"}],"subject":[],"published-other":{"date-parts":[[2023,12,1]]},"published":{"date-parts":[[2023,8,3]]}}}