Coronary Artery Calcium Score and Polygenic Risk Score for the Prediction of Coronary Heart Disease Events
Coronary artery calcium score and polygenic risk score have each separately been proposed as novel markers to identify risk of coronary heart disease (CHD), but no prior studies have directly compared these markers in the same cohorts. To evaluate change in CHD risk prediction when a coronary artery...
Uloženo v:
| Vydáno v: | JAMA : the journal of the American Medical Association Ročník 329; číslo 20; s. 1768 |
|---|---|
| Hlavní autoři: | , , , , , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
United States
23.05.2023
|
| Témata: | |
| ISSN: | 1538-3598, 1538-3598 |
| On-line přístup: | Zjistit podrobnosti o přístupu |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | Coronary artery calcium score and polygenic risk score have each separately been proposed as novel markers to identify risk of coronary heart disease (CHD), but no prior studies have directly compared these markers in the same cohorts.
To evaluate change in CHD risk prediction when a coronary artery calcium score, a polygenic risk score, or both are added to a traditional risk factor-based model.
Two observational population-based studies involving individuals aged 45 years through 79 years of European ancestry and free of clinical CHD at baseline: the Multi-Ethnic Study of Atherosclerosis (MESA) study involved 1991 participants at 6 US centers and the Rotterdam Study (RS) involved 1217 in Rotterdam, the Netherlands.
Traditional risk factors were used to calculate CHD risk (eg, pooled cohort equations [PCEs]), computed tomography for the coronary artery calcium score, and genotyped samples for a validated polygenic risk score.
Model discrimination, calibration, and net reclassification improvement (at the recommended risk threshold of 7.5%) for prediction of incident CHD events were assessed.
The median age was 61 years in MESA and 67 years in RS. Both log (coronary artery calcium+1) and polygenic risk score were significantly associated with 10-year risk of incident CHD (hazards ratio per SD, 2.60; 95% CI, 2.08-3.26 and 1.43; 95% CI, 1.20-1.71, respectively), in MESA. The C statistic for the coronary artery calcium score was 0.76 (95% CI, 0.71-0.79) and for the polygenic risk score, 0.69 (95% CI, 0.63-0.71). The change in the C statistic when each was added to the PCEs was 0.09 (95% CI, 0.06-0.13) for the coronary artery calcium score, 0.02 (95% CI, 0.00-0.04) for the polygenic risk score, and 0.10 (95% CI, 0.07-0.14) for both. Overall categorical net reclassification improvement was significant when the coronary artery calcium score (0.19; 95% CI, 0.06-0.28) but was not significant when the polygenic risk score (0.04; 95% CI, -0.05 to 0.10) was added to the PCEs. Calibration of the PCEs and models with coronary artery calcium and/or polygenic risk scores was adequate (all χ2<20). Subgroup analysis stratified by the median age demonstrated similar findings. Similar findings were observed for 10-year risk in RS and in longer-term follow-up in MESA (median, 16.0 years).
In 2 cohorts of middle-aged to older adults from the US and the Netherlands, the coronary artery calcium score had better discrimination than the polygenic risk score for risk prediction of CHD. In addition, the coronary artery calcium score but not the polygenic risk score significantly improved risk discrimination and risk reclassification for CHD when added to traditional risk factors. |
|---|---|
| AbstractList | Coronary artery calcium score and polygenic risk score have each separately been proposed as novel markers to identify risk of coronary heart disease (CHD), but no prior studies have directly compared these markers in the same cohorts.ImportanceCoronary artery calcium score and polygenic risk score have each separately been proposed as novel markers to identify risk of coronary heart disease (CHD), but no prior studies have directly compared these markers in the same cohorts.To evaluate change in CHD risk prediction when a coronary artery calcium score, a polygenic risk score, or both are added to a traditional risk factor-based model.ObjectiveTo evaluate change in CHD risk prediction when a coronary artery calcium score, a polygenic risk score, or both are added to a traditional risk factor-based model.Two observational population-based studies involving individuals aged 45 years through 79 years of European ancestry and free of clinical CHD at baseline: the Multi-Ethnic Study of Atherosclerosis (MESA) study involved 1991 participants at 6 US centers and the Rotterdam Study (RS) involved 1217 in Rotterdam, the Netherlands.Design, Setting, and ParticipantsTwo observational population-based studies involving individuals aged 45 years through 79 years of European ancestry and free of clinical CHD at baseline: the Multi-Ethnic Study of Atherosclerosis (MESA) study involved 1991 participants at 6 US centers and the Rotterdam Study (RS) involved 1217 in Rotterdam, the Netherlands.Traditional risk factors were used to calculate CHD risk (eg, pooled cohort equations [PCEs]), computed tomography for the coronary artery calcium score, and genotyped samples for a validated polygenic risk score.ExposureTraditional risk factors were used to calculate CHD risk (eg, pooled cohort equations [PCEs]), computed tomography for the coronary artery calcium score, and genotyped samples for a validated polygenic risk score.Model discrimination, calibration, and net reclassification improvement (at the recommended risk threshold of 7.5%) for prediction of incident CHD events were assessed.Main Outcomes and MeasuresModel discrimination, calibration, and net reclassification improvement (at the recommended risk threshold of 7.5%) for prediction of incident CHD events were assessed.The median age was 61 years in MESA and 67 years in RS. Both log (coronary artery calcium+1) and polygenic risk score were significantly associated with 10-year risk of incident CHD (hazards ratio per SD, 2.60; 95% CI, 2.08-3.26 and 1.43; 95% CI, 1.20-1.71, respectively), in MESA. The C statistic for the coronary artery calcium score was 0.76 (95% CI, 0.71-0.79) and for the polygenic risk score, 0.69 (95% CI, 0.63-0.71). The change in the C statistic when each was added to the PCEs was 0.09 (95% CI, 0.06-0.13) for the coronary artery calcium score, 0.02 (95% CI, 0.00-0.04) for the polygenic risk score, and 0.10 (95% CI, 0.07-0.14) for both. Overall categorical net reclassification improvement was significant when the coronary artery calcium score (0.19; 95% CI, 0.06-0.28) but was not significant when the polygenic risk score (0.04; 95% CI, -0.05 to 0.10) was added to the PCEs. Calibration of the PCEs and models with coronary artery calcium and/or polygenic risk scores was adequate (all χ2<20). Subgroup analysis stratified by the median age demonstrated similar findings. Similar findings were observed for 10-year risk in RS and in longer-term follow-up in MESA (median, 16.0 years).ResultsThe median age was 61 years in MESA and 67 years in RS. Both log (coronary artery calcium+1) and polygenic risk score were significantly associated with 10-year risk of incident CHD (hazards ratio per SD, 2.60; 95% CI, 2.08-3.26 and 1.43; 95% CI, 1.20-1.71, respectively), in MESA. The C statistic for the coronary artery calcium score was 0.76 (95% CI, 0.71-0.79) and for the polygenic risk score, 0.69 (95% CI, 0.63-0.71). The change in the C statistic when each was added to the PCEs was 0.09 (95% CI, 0.06-0.13) for the coronary artery calcium score, 0.02 (95% CI, 0.00-0.04) for the polygenic risk score, and 0.10 (95% CI, 0.07-0.14) for both. Overall categorical net reclassification improvement was significant when the coronary artery calcium score (0.19; 95% CI, 0.06-0.28) but was not significant when the polygenic risk score (0.04; 95% CI, -0.05 to 0.10) was added to the PCEs. Calibration of the PCEs and models with coronary artery calcium and/or polygenic risk scores was adequate (all χ2<20). Subgroup analysis stratified by the median age demonstrated similar findings. Similar findings were observed for 10-year risk in RS and in longer-term follow-up in MESA (median, 16.0 years).In 2 cohorts of middle-aged to older adults from the US and the Netherlands, the coronary artery calcium score had better discrimination than the polygenic risk score for risk prediction of CHD. In addition, the coronary artery calcium score but not the polygenic risk score significantly improved risk discrimination and risk reclassification for CHD when added to traditional risk factors.Conclusions and RelevanceIn 2 cohorts of middle-aged to older adults from the US and the Netherlands, the coronary artery calcium score had better discrimination than the polygenic risk score for risk prediction of CHD. In addition, the coronary artery calcium score but not the polygenic risk score significantly improved risk discrimination and risk reclassification for CHD when added to traditional risk factors. Coronary artery calcium score and polygenic risk score have each separately been proposed as novel markers to identify risk of coronary heart disease (CHD), but no prior studies have directly compared these markers in the same cohorts. To evaluate change in CHD risk prediction when a coronary artery calcium score, a polygenic risk score, or both are added to a traditional risk factor-based model. Two observational population-based studies involving individuals aged 45 years through 79 years of European ancestry and free of clinical CHD at baseline: the Multi-Ethnic Study of Atherosclerosis (MESA) study involved 1991 participants at 6 US centers and the Rotterdam Study (RS) involved 1217 in Rotterdam, the Netherlands. Traditional risk factors were used to calculate CHD risk (eg, pooled cohort equations [PCEs]), computed tomography for the coronary artery calcium score, and genotyped samples for a validated polygenic risk score. Model discrimination, calibration, and net reclassification improvement (at the recommended risk threshold of 7.5%) for prediction of incident CHD events were assessed. The median age was 61 years in MESA and 67 years in RS. Both log (coronary artery calcium+1) and polygenic risk score were significantly associated with 10-year risk of incident CHD (hazards ratio per SD, 2.60; 95% CI, 2.08-3.26 and 1.43; 95% CI, 1.20-1.71, respectively), in MESA. The C statistic for the coronary artery calcium score was 0.76 (95% CI, 0.71-0.79) and for the polygenic risk score, 0.69 (95% CI, 0.63-0.71). The change in the C statistic when each was added to the PCEs was 0.09 (95% CI, 0.06-0.13) for the coronary artery calcium score, 0.02 (95% CI, 0.00-0.04) for the polygenic risk score, and 0.10 (95% CI, 0.07-0.14) for both. Overall categorical net reclassification improvement was significant when the coronary artery calcium score (0.19; 95% CI, 0.06-0.28) but was not significant when the polygenic risk score (0.04; 95% CI, -0.05 to 0.10) was added to the PCEs. Calibration of the PCEs and models with coronary artery calcium and/or polygenic risk scores was adequate (all χ2<20). Subgroup analysis stratified by the median age demonstrated similar findings. Similar findings were observed for 10-year risk in RS and in longer-term follow-up in MESA (median, 16.0 years). In 2 cohorts of middle-aged to older adults from the US and the Netherlands, the coronary artery calcium score had better discrimination than the polygenic risk score for risk prediction of CHD. In addition, the coronary artery calcium score but not the polygenic risk score significantly improved risk discrimination and risk reclassification for CHD when added to traditional risk factors. |
| Author | Guo, Xiuqing Bos, Daniel Uitterlinden, André G Kavousi, Maryam Allen, Norrina B Bos, Maxime M Mosley, Jonathan D Post, Wendy S Aday, Aaron Rotter, Jerome I Lloyd-Jones, Donald M Zhu, Fang Khan, Sadiya S Greenland, Philip Budoff, Matthew J Sedaghati-Khayat, Bahar van Rooij, Jeroen Tan, Jingyi |
| Author_xml | – sequence: 1 givenname: Sadiya S surname: Khan fullname: Khan, Sadiya S organization: Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois – sequence: 2 givenname: Wendy S surname: Post fullname: Post, Wendy S organization: Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland – sequence: 3 givenname: Xiuqing surname: Guo fullname: Guo, Xiuqing organization: The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, California – sequence: 4 givenname: Jingyi surname: Tan fullname: Tan, Jingyi organization: The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, California – sequence: 5 givenname: Fang surname: Zhu fullname: Zhu, Fang organization: Department of Epidemiology Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands – sequence: 6 givenname: Daniel surname: Bos fullname: Bos, Daniel organization: Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands – sequence: 7 givenname: Bahar surname: Sedaghati-Khayat fullname: Sedaghati-Khayat, Bahar organization: Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands – sequence: 8 givenname: Jeroen surname: van Rooij fullname: van Rooij, Jeroen organization: Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands – sequence: 9 givenname: Aaron surname: Aday fullname: Aday, Aaron organization: Vanderbilt Translational and Clinical Cardiovascular Research Center, Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, Tennessee – sequence: 10 givenname: Norrina B surname: Allen fullname: Allen, Norrina B organization: Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois – sequence: 11 givenname: Maxime M surname: Bos fullname: Bos, Maxime M organization: Department of Epidemiology Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands – sequence: 12 givenname: André G surname: Uitterlinden fullname: Uitterlinden, André G organization: Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands – sequence: 13 givenname: Matthew J surname: Budoff fullname: Budoff, Matthew J organization: Department of Medicine, Lundquist Research Institute at Harbor-UCLA Medical Center, Torrance, California – sequence: 14 givenname: Donald M surname: Lloyd-Jones fullname: Lloyd-Jones, Donald M organization: Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois – sequence: 15 givenname: Jonathan D surname: Mosley fullname: Mosley, Jonathan D organization: Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee – sequence: 16 givenname: Jerome I surname: Rotter fullname: Rotter, Jerome I organization: The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, California – sequence: 17 givenname: Philip surname: Greenland fullname: Greenland, Philip organization: Senior Editor, JAMA – sequence: 18 givenname: Maryam surname: Kavousi fullname: Kavousi, Maryam organization: Department of Epidemiology Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/37219552$$D View this record in MEDLINE/PubMed |
| BookMark | eNpNkEtPwzAQhC1URB9w5Yh85JJiO3GdHKtQKFIlKh7namtvwCWxi50g9d8TiYLYy6w0n0a7MyYD5x0ScsnZlDPGb3bQwFQwkU6VVPKEjLhM8ySVRT74tw_JOMYd64en6owMUyV4IaUYkV3pg3cQDnQeWuylhFrbrqHP2gek4Axd-_rwhs5q-mTjx9GofKDtO9J1QGN1a72jvqJ_YUuE0NJbGxEi0sUXujaek9MK6ogXR52Q17vFS7lMVo_3D-V8lUCW5W2iKmOAaxQy45Ll1RZyZLL_QhmDWsqKKV4IaYqZnkmlOa8KYAIBdFag2GoxIdc_ufvgPzuM7aaxUWNdg0PfxY3Iec5mLJO8R6-OaLdt0Gz2wTb9-ZvffsQ39r5qCg |
| CitedBy_id | crossref_primary_10_1016_j_atherosclerosis_2023_117194 crossref_primary_10_1136_heartjnl_2023_322928 crossref_primary_10_1161_CIRCOUTCOMES_123_010763 crossref_primary_10_3389_fgene_2025_1587274 crossref_primary_10_1161_ATVBAHA_123_319818 crossref_primary_10_1093_eurjpc_zwae005 crossref_primary_10_1016_j_jtct_2025_03_014 crossref_primary_10_1186_s40001_025_02887_8 crossref_primary_10_7759_cureus_51874 crossref_primary_10_1016_j_mayocp_2023_12_020 crossref_primary_10_1016_j_heliyon_2024_e34205 crossref_primary_10_1016_j_ajpc_2024_100661 crossref_primary_10_1093_ehjci_jeaf100 crossref_primary_10_1016_j_jtocrr_2025_100813 crossref_primary_10_1016_j_jacc_2025_02_016 crossref_primary_10_1002_art_42769 crossref_primary_10_1016_j_tcm_2024_11_001 crossref_primary_10_31083_j_jin2312222 crossref_primary_10_1186_s13019_025_03427_5 crossref_primary_10_1001_jama_2024_24037 crossref_primary_10_1016_j_tcm_2024_10_003 crossref_primary_10_1007_s00394_025_03649_2 crossref_primary_10_1007_s11883_025_01318_7 crossref_primary_10_1093_ckj_sfaf034 crossref_primary_10_1016_j_jcmg_2024_11_001 crossref_primary_10_1016_j_compbiomed_2024_109295 crossref_primary_10_1016_j_atherosclerosis_2025_119115 crossref_primary_10_1097_RLI_0000000000001199 crossref_primary_10_1016_j_jcmg_2024_07_026 crossref_primary_10_1093_eurheartj_ehae342 crossref_primary_10_1016_j_jacadv_2023_100759 crossref_primary_10_1016_j_jcmg_2024_06_015 crossref_primary_10_3390_biomedicines12092151 crossref_primary_10_1186_s12920_024_01802_0 crossref_primary_10_1186_s12933_025_02876_5 crossref_primary_10_7759_cureus_88513 crossref_primary_10_3389_fmed_2025_1475362 crossref_primary_10_1016_j_atherosclerosis_2024_119103 crossref_primary_10_1007_s12170_024_00741_w crossref_primary_10_1038_s41591_025_03648_0 crossref_primary_10_1016_j_pcad_2024_05_004 crossref_primary_10_1161_CIR_0000000000001303 crossref_primary_10_1016_j_jacc_2025_02_032 crossref_primary_10_3389_fmed_2025_1655229 crossref_primary_10_1038_s41598_024_62945_9 crossref_primary_10_1161_ATVBAHA_124_321846 crossref_primary_10_1161_CIRCIMAGING_124_016516 crossref_primary_10_1093_clinchem_hvad150 crossref_primary_10_1161_CIR_0000000000001191 crossref_primary_10_1016_j_jcmg_2023_07_004 crossref_primary_10_1161_CIRCULATIONAHA_123_065657 crossref_primary_10_36011_cpp_2025_7_e14 |
| ContentType | Journal Article |
| DBID | CGR CUY CVF ECM EIF NPM 7X8 |
| DOI | 10.1001/jama.2023.7575 |
| DatabaseName | Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed MEDLINE - Academic |
| DatabaseTitle | MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) MEDLINE - Academic |
| DatabaseTitleList | MEDLINE - Academic MEDLINE |
| Database_xml | – sequence: 1 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: 7X8 name: MEDLINE - Academic url: https://search.proquest.com/medline sourceTypes: Aggregation Database |
| DeliveryMethod | no_fulltext_linktorsrc |
| Discipline | Medicine |
| EISSN | 1538-3598 |
| ExternalDocumentID | 37219552 |
| Genre | Multicenter Study Research Support, Non-U.S. Gov't Journal Article Observational Study Research Support, N.I.H., Extramural |
| GrantInformation_xml | – fundername: NHLBI NIH HHS grantid: N01 HC095168 – fundername: NCATS NIH HHS grantid: UL1 TR001881 – fundername: NHLBI NIH HHS grantid: R01 HL159250 – fundername: NHLBI NIH HHS grantid: R21 HL165376 – fundername: NHLBI NIH HHS grantid: N01 HC095165 – fundername: NHLBI NIH HHS grantid: N01 HC095169 – fundername: NHLBI NIH HHS grantid: R01 HL105756 – fundername: NHLBI NIH HHS grantid: N01 HC095166 – fundername: NCATS NIH HHS grantid: UL1 TR000040 – fundername: NCATS NIH HHS grantid: UL1 TR001079 |
| GroupedDBID | --- -ET -~X .55 .XZ 0R~ 0WA 186 18M 29J 2CT 2FS 2KS 2WC 354 39C 4.4 53G 5GY 5RE 6TJ 85S AAIKC AAMNW AAQQT AAWTL ABBLC ABCQX ABEHJ ABIVO ABOCM ABPMR ABPPZ ABRSH ABWJO ACAHW ACGFS ACNCT ACPRK ADBBV ADUKH ADXHL AFCHL AFFNX AFRAH AGHSJ AHMBA ALMA_UNASSIGNED_HOLDINGS AMJDE ANMPU ARBJA BKOMP BRYMA C45 CGR CJ0 CS3 CUY CVF EAM EBD EBS ECM EIF EJD EMOBN EX3 F5P H13 HF~ KOO KQ8 L7B MVM N4W N9A NEJ NPM OBH OCB OGEVE OHH OMK OVD P2P PQQKQ RAJ RNS SJN SV3 TEORI TN5 UHB UKR UPT VVN WH7 WOW X7M XHN XSW XZL YFH YOC YPV YQT YQY YR2 YR5 YSK YYM YZZ ZCA ~H1 7X8 |
| ID | FETCH-LOGICAL-a448t-7fdda1ce2541508fba8e053597ddec55f071925d96c657c11f9a02eaac49e2bc2 |
| IEDL.DBID | 7X8 |
| ISICitedReferencesCount | 61 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001003941900022&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1538-3598 |
| IngestDate | Thu Sep 04 19:55:58 EDT 2025 Mon Jul 21 06:04:31 EDT 2025 |
| IsDoiOpenAccess | false |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 20 |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-a448t-7fdda1ce2541508fba8e053597ddec55f071925d96c657c11f9a02eaac49e2bc2 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Undefined-3 |
| OpenAccessLink | https://www.ncbi.nlm.nih.gov/pmc/articles/10208141 |
| PMID | 37219552 |
| PQID | 2818060451 |
| PQPubID | 23479 |
| ParticipantIDs | proquest_miscellaneous_2818060451 pubmed_primary_37219552 |
| PublicationCentury | 2000 |
| PublicationDate | 2023-05-23 |
| PublicationDateYYYYMMDD | 2023-05-23 |
| PublicationDate_xml | – month: 05 year: 2023 text: 2023-05-23 day: 23 |
| PublicationDecade | 2020 |
| PublicationPlace | United States |
| PublicationPlace_xml | – name: United States |
| PublicationTitle | JAMA : the journal of the American Medical Association |
| PublicationTitleAlternate | JAMA |
| PublicationYear | 2023 |
| References | 37646389 - AJR Am J Roentgenol. 2024 Apr;222(4):e2330030 |
| References_xml | – reference: 37646389 - AJR Am J Roentgenol. 2024 Apr;222(4):e2330030 |
| SSID | ssj0000137 |
| Score | 2.6139991 |
| Snippet | Coronary artery calcium score and polygenic risk score have each separately been proposed as novel markers to identify risk of coronary heart disease (CHD),... |
| SourceID | proquest pubmed |
| SourceType | Aggregation Database Index Database |
| StartPage | 1768 |
| SubjectTerms | Aged Atherosclerosis - diagnostic imaging Calcium Coronary Disease - diagnostic imaging Coronary Vessels - diagnostic imaging Coronary Vessels - pathology Humans Middle Aged Risk Assessment Risk Factors |
| Title | Coronary Artery Calcium Score and Polygenic Risk Score for the Prediction of Coronary Heart Disease Events |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/37219552 https://www.proquest.com/docview/2818060451 |
| Volume | 329 |
| WOSCitedRecordID | wos001003941900022&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LS8NAEF7Uinjx_agvVvAabTbdTXISqZZeWoIP6C1s9gHRmtSmFfrvnUlS60UQvCSHJEvY-Wb2m53lG0KutDAisO3E8VsSEhRrEiexAvwKpVcCzRlXsmw24Q8GwXAYRvWGW1Efq1zExDJQ61zhHvkNqhah0At3b8cfDnaNwupq3UJjlTQ8oDKIan8Y_JCPKjUzS6dGpbqFaONSdYh51z73-e_0slxmutv__cEdslUTTHpXIWKXrJhsj2z06xL6PnntoGaBnMzxFQO3jhypdPZOn1DQkspM0ygfzQFXqaKPafFWPwByS4Es0miCQ6E5aW7p92A98Jgpva_KPfQBT1EWB-Sl-_Dc6Tl1wwVHQpY2dXyrtXSVgaQRZeJtIgPsHAE5BwRBxbkFPhIyrkOhBPeV69pQtpiRUrVDwxLFDslalmfmmFDFlSdx6dMMkOCKJJFtbURouE6EMa0muVzMYgyAxiqFzEw-K-LlPDbJUWWKeFwpb8Qe5Ksh5-zkD1-fkk20L1b6mXdGGhbc2ZyTdfU5TYvJRYkUuA6i_hdJSMn9 |
| linkProvider | ProQuest |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Coronary+Artery+Calcium+Score+and+Polygenic+Risk+Score+for+the+Prediction+of+Coronary+Heart+Disease+Events&rft.jtitle=JAMA+%3A+the+journal+of+the+American+Medical+Association&rft.au=Khan%2C+Sadiya+S&rft.au=Post%2C+Wendy+S&rft.au=Guo%2C+Xiuqing&rft.au=Tan%2C+Jingyi&rft.date=2023-05-23&rft.issn=1538-3598&rft.eissn=1538-3598&rft.volume=329&rft.issue=20&rft.spage=1768&rft_id=info:doi/10.1001%2Fjama.2023.7575&rft.externalDBID=NO_FULL_TEXT |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1538-3598&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1538-3598&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1538-3598&client=summon |