Risk Prediction for Atherosclerotic Cardiovascular Disease With and Without Race Stratification

被引:5
|
作者
Ghosh, Arnab K. [1 ]
Venkatraman, Sara [1 ,2 ]
Nanna, Michael G. [3 ]
Safford, Monika M. [1 ]
Colantonio, Lisandro D. [4 ]
Brown, Todd M. [5 ]
Pinheiro, Laura C. [1 ]
Peterson, Eric D. [6 ]
Navar, Ann Marie [6 ]
Sterling, Madeline R. [1 ]
Soroka, Orysya [1 ]
Nahid, Musarrat [1 ]
Banerjee, Samprit [7 ]
Goyal, Parag [1 ]
机构
[1] Cornell Univ, Weill Cornell Med Coll, Dept Med, 525 E 68th St, New York, NY 10065 USA
[2] Cornell Univ, Dept Stat & Data Sci, New York, NY 10065 USA
[3] Yale Univ, Sch Med, Dept Internal Med, Sect Cardiovasc Med, New Haven, CT USA
[4] Univ Alabama Birmingham, Dept Epidemiol, Birmingham, AL USA
[5] Univ Alabama Birmingham, Div Cardiovasc Dis, Birmingham, AL USA
[6] UT Southwestern Med Ctr, Div Cardiol, Dallas, TX USA
[7] Cornell Univ, Weill Cornell Med Coll, Dept Populat Hlth Sci, New York, NY 10065 USA
关键词
CORONARY-HEART-DISEASE; NEIGHBORHOOD-DISADVANTAGE; SOCIOECONOMIC-STATUS; RACIAL-DIFFERENCES; LIFE-COURSE; HEALTH; ASSOCIATION; SEGREGATION; PATTERNS; COHORT;
D O I
10.1001/jamacardio.2023.4520
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Importance Use of race-specific risk prediction in clinical medicine is being questioned. Yet, the most commonly used prediction tool for atherosclerotic cardiovascular disease (ASCVD)-pooled cohort risk equations (PCEs)-uses race stratification.Objective To quantify the incremental value of race-specific PCEs and determine whether adding social determinants of health (SDOH) instead of race improves model performance.Design, Setting, and Participants Included in this analysis were participants from the biracial Reasons for Geographic and Racial Differences in Stroke (REGARDS) prospective cohort study. Participants were aged 45 to 79 years, without ASCVD, and with low-density lipoprotein cholesterol level of 70 to 189 mg/dL or non-high-density lipoprotein cholesterol level of 100 to 219 mg/dL at baseline during the period of 2003 to 2007. Participants were followed up to 10 years for incident ASCVD, including myocardial infarction, coronary heart disease death, and fatal and nonfatal stroke. Study data were analyzed from July 2022 to February 2023.Main outcome/measures Discrimination (C statistic, Net Reclassification Index [NRI]), and calibration (plots, Nam D'Agostino test statistic comparing observed to predicted events) were assessed for the original PCE, then for a set of best-fit, race-stratified equations including the same variables as in the PCE (model C), best-fit equations without race stratification (model D), and best-fit equations without race stratification but including SDOH as covariates (model E).Results This study included 11 638 participants (mean [SD] age, 61.8 [8.3] years; 6764 female [58.1%]) from the REGARDS cohort. Across all strata (Black female, Black male, White female, and White male participants), C statistics did not change substantively compared with model C (Black female, 0.71; 95% CI, 0.68-0.75; Black male, 0.68; 95% CI, 0.64-0.73; White female, 0.77; 95% CI, 0.74-0.81; White male, 0.68; 95% CI, 0.64-0.71), in model D (Black female, 0.71; 95% CI, 0.67-0.75; Black male, 0.68; 95% CI, 0.63-0.72; White female, 0.76; 95% CI, 0.73-0.80; White male, 0.68; 95% CI, 0.65-0.71), or in model E (Black female, 0.72; 95% CI, 0.68-0.76; Black male, 0.68; 95% CI, 0.64-0.72; White female, 0.77; 95% CI, 0.74-0.80; White male, 0.68; 95% CI, 0.65-0.71). Comparing model D with E using the NRI showed a net percentage decline in the correct assignment to higher risk for male but not female individuals. The Nam D'Agostino test was not significant for all race-sex strata in each model series, indicating good calibration in all groups.Conclusions Results of this cohort study suggest that PCE performed well overall but had poorer performance in both BM and WM participants compared with female participants regardless of race in the REGARDS cohort. Removal of race or the addition of SDOH did not improve model performance in any subgroup.
引用
收藏
页码:55 / 62
页数:8
相关论文
共 50 条
  • [1] Universal Risk Prediction for Individuals With and Without Atherosclerotic Cardiovascular Disease
    Mok, Yejin
    Dardari, Zeina
    Sang, Yingying
    Hu, Xiao
    Bancks, Michael P.
    Mathews, Lena
    Hoogeveen, Ron C.
    Koton, Silvia
    Blaha, Michael J.
    Post, Wendy S.
    Ballantyne, Christie M.
    Coresh, Josef
    Rosamond, Wayne
    Matsushita, Kunihiro
    [J]. JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, 2024, 83 (05) : 562 - 573
  • [2] Revising the atherosclerotic cardiovascular disease calculator without race
    Vyas, Darshali A.
    James, Aisha
    Kormos, William
    Essien, Utibe R.
    [J]. LANCET DIGITAL HEALTH, 2022, 4 (01): : E4 - E5
  • [3] Risk stratification of atherosclerotic cardiovascular disease in Chinese adults
    Yang XueLi
    Chen JiChun
    Li JianXin
    Cao Jie
    Lu XiangFeng
    Liu FangChao
    Hu DongSheng
    Liu XiaoQing
    Shen Chong
    Yu Ling
    Lu FangHong
    Wu XianPing
    Zhao LianCheng
    Huang JianFeng
    Li Ying
    Wu XiGui
    Gu DongFeng
    [J]. 慢性疾病与转化医学(英文), 2016, 2 (02) : 102 - 103-104-105-106-107-108-109
  • [4] AN EVALUATION OF RACE STRATIFICATION IN THE ATHEROSCLEROTIC CARDIOVASCULAR DISEASE POOLED COHORT RISK EQUATIONS USING A SEQUENTIAL MODELING STRATEGY
    Ghosh, Arnab K.
    Venkatraman, Sara
    Safford, Monika M.
    Goyal, Parag
    Colantonio, Lisandro D.
    Brown, Todd
    Banerjee, Samprit
    [J]. JOURNAL OF GENERAL INTERNAL MEDICINE, 2023, 38 : S154 - S154
  • [6] Proteomics and lipidomics in atherosclerotic cardiovascular disease risk prediction
    Nurmohamed, Nick S.
    Kraaijenhof, Jordan M.
    Mayr, Manuel
    Nicholls, Stephen J.
    Koenig, Wolfgang
    Catapano, Alberico L.
    Stroes, Erik S. G.
    [J]. EUROPEAN HEART JOURNAL, 2023, : 1594 - 1607
  • [7] Cardiovascular risk in elderly persons without established atherosclerotic cardiovascular disease
    Hudzik, B.
    Zuranski, W.
    Nowak, J.
    Danikiewicz, A.
    Zubelewicz-Szkodzinska, B.
    [J]. EUROPEAN HEART JOURNAL, 2023, 44
  • [8] Cardiovascular imaging for the assessment of atherosclerotic disease: Implications for cardiac risk stratification
    Makaryus A.N.
    [J]. Current Cardiovascular Risk Reports, 2008, 2 (2) : 107 - 112
  • [9] Effect of race on classification of atherosclerotic risk using a national cardiovascular risk prediction tool
    Beaudoin, Jarrett
    Curran, Jill
    Alexander, G. Caleb
    [J]. PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, 2023, 32 : 408 - 408
  • [10] COMPARISON OF ATHEROSCLEROTIC CARDIOVASCULAR DISEASE RISK PREDICTION BY LIPOPROTEIN(A) LEVELS BETWEEN PERSONS WITH AND WITHOUT PRIOR CARDIOVASCULAR DISEASE: THE UK BIOBANK
    Wong, Nathan D.
    Zhao, Yanglu
    El-Farra, Ailin Barseghian
    Wilkinson, Michael
    [J]. JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, 2021, 77 (18) : 1484 - 1484