{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T03:19:51Z","timestamp":1791429591019,"version":"4.3.3"},"reference-count":30,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"1","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["Circ: Genomic and Precision Medicine"],"published-print":{"date-parts":[[2025,2]]},"abstract":"<jats:sec>\n                    <jats:title>BACKGROUND:<\/jats:title>\n                    <jats:p>Lipoprotein(a) [Lp(a)] is a predictor of atherosclerotic cardiovascular disease (ASCVD); however, there are few algorithms incorporating Lp(a), especially from real-world settings. We developed an electronic health record (EHR)-based risk prediction algorithm including Lp(a).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS:<\/jats:title>\n                    <jats:p>Utilizing a large EHR database, we categorized Lp(a) cut points at 25, 50, and 75 mg\/dL and constructed 10-year ASCVD risk prediction models incorporating Lp(a), with external validation in a pooled cohort of 4 US prospective studies. Net reclassification improvement was determined among borderline-intermediate risk patients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS:<\/jats:title>\n                    <jats:p>We included 5902 patients aged \u226518 years (mean age 48.7\u00b116.7 years, 51.2% women, and 7.7% Black). Our EHR model included Lp(a), age, sex, Black race\/ethnicity, systolic blood pressure, total and high-density lipoprotein cholesterol, diabetes, smoking, and hypertension medication. Over a mean follow-up of 6.8 years, ASCVD event rates (per 1000 person-years) ranged from 8.7 to 16.7 across Lp(a) groups. A 25 mg\/dL increment in Lp(a) was associated with an adjusted hazard ratio of 1.23 (95% CI, 1.10\u20131.37) for composite ASCVD. Those with Lp(a) \u226575 mg\/dL had an 88% higher risk of ASCVD (hazard ratio, 1.88 [95% CI, 1.30\u20132.70]) and more than double the risk of incident stroke (hazard ratio, 2.55 [95% CI, 1.54\u20134.23]). C-statistics for our EHR and EHR+Lp(a) models in our EHR training data set were 0.7475 and 0.7556, respectively, with external validation in our pooled cohort (n=21\u2005864) of 0.7350 and 0.7368, respectively. Among those at borderline\/intermediate risk, the net reclassification improvement was 21.3%.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSIONS:<\/jats:title>\n                    <jats:p>We show the feasibility of developing an improved ASCVD risk prediction model incorporating Lp(a) based on a real-world adult clinic population. The inclusion of Lp(a) in ASCVD prediction models can reclassify risk in patients who may benefit from more intensified ASCVD prevention efforts.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1161\/circgen.124.004631","type":"journal-article","created":{"date-parts":[[2025,1,24]],"date-time":"2025-01-24T05:00:49Z","timestamp":1737694849000},"update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":20,"title":["Lipoprotein(a) Atherosclerotic Cardiovascular Disease Risk Score Development and Prediction in Primary Prevention From Real-World Data"],"prefix":"10.1161","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6652-9431","authenticated-orcid":true,"given":"Wenjun","family":"Fan","sequence":"first","affiliation":[{"name":"Mary and Steve Wen Cardiovascular Division, Department of Medicine (W.F., N.D.W.), University of California, Irvine"},{"name":"Department of Epidemiology and Biostatistics (W.F., N.D.W.), University of California, Irvine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-6322-1260","authenticated-orcid":true,"given":"Chuyue","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Epidemiology (C.W., N.D.W.), University of California, Los Angeles."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1102-7324","authenticated-orcid":true,"given":"Nathan D.","family":"Wong","sequence":"additional","affiliation":[{"name":"Mary and Steve Wen Cardiovascular Division, Department of Medicine (W.F., N.D.W.), University of California, Irvine"},{"name":"Department of Epidemiology and Biostatistics (W.F., N.D.W.), University of California, Irvine"},{"name":"Department of Epidemiology (C.W., N.D.W.), University of California, Los Angeles."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.3390\/jcm12237432"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacc.2016.11.042"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2009.1063"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacc.2012.12.023"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa0902604"},{"key":"e_1_3_3_7_2","doi-asserted-by":"publisher","DOI":"10.1038\/ng.2480"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacc.2023.10.039"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.1161\/01.cir.0000437741.48606.98"},{"key":"e_1_3_3_10_2","doi-asserted-by":"publisher","DOI":"10.1161\/CIR.0000000000001191"},{"key":"e_1_3_3_11_2","doi-asserted-by":"publisher","DOI":"10.1093\/eurheartj\/ehac056"},{"key":"e_1_3_3_12_2","doi-asserted-by":"publisher","DOI":"10.1161\/ATV.0000000000000147"},{"key":"e_1_3_3_13_2","doi-asserted-by":"publisher","DOI":"10.1093\/eurheartj\/ehac361"},{"key":"e_1_3_3_14_2","doi-asserted-by":"publisher","DOI":"10.1161\/CIR.0000000000000625"},{"key":"e_1_3_3_15_2","doi-asserted-by":"publisher","DOI":"10.1093\/eurheartj\/ehab309"},{"key":"e_1_3_3_16_2","doi-asserted-by":"publisher","DOI":"10.1161\/atvbaha.120.315291"},{"key":"e_1_3_3_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacc.2014.03.061"},{"key":"e_1_3_3_18_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.atherosclerosis.2023.117217"},{"key":"e_1_3_3_19_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacc.2023.12.031"},{"key":"e_1_3_3_20_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacc.2024.02.031"},{"key":"e_1_3_3_21_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajpc.2023.100476"},{"key":"e_1_3_3_22_2","doi-asserted-by":"publisher","DOI":"10.1161\/JAHA.123.031255"},{"key":"e_1_3_3_23_2","doi-asserted-by":"publisher","DOI":"10.1016\/0021-9150(92)90271-h"},{"key":"e_1_3_3_24_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.atherosclerosis.2022.03.004"},{"key":"e_1_3_3_25_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacc.2024.01.004"},{"key":"e_1_3_3_26_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacl.2024.03.001"},{"key":"e_1_3_3_27_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cjca.2021.03.016"},{"key":"e_1_3_3_28_2","doi-asserted-by":"publisher","DOI":"10.1093\/oxfordjournals.aje.a115184"},{"key":"e_1_3_3_29_2","doi-asserted-by":"publisher","DOI":"10.1016\/0895-4356(88)90080-7"},{"key":"e_1_3_3_30_2","first-page":"S6-4","article-title":"Toward resolution of cardiovascular health disparities in African Americans: design and methods of the Jackson Heart Study.","volume":"15","author":"Taylor HA","year":"2005","unstructured":"Taylor HA, Jr, Wilson JG, Jones DW, Sarpong DF, Srinivasan A, Garrison RJ, Nelson C, Wyatt SB. 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