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Diao JA, Shi I, Murthy VL, Buckley TA, Patel CJ, Pierson E, Yeh RW, Kazi DS, Wadhera RK, Manrai AK. Projected Changes in Statin and Antihypertensive Therapy Eligibility With the AHA PREVENT Cardiovascular Risk Equations. JAMA 2024; 332:989-1000. [PMID: 39073797 PMCID: PMC11287447 DOI: 10.1001/jama.2024.12537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Accepted: 06/07/2024] [Indexed: 07/30/2024]
Abstract
Importance Since 2013, the American College of Cardiology (ACC) and American Heart Association (AHA) have recommended the pooled cohort equations (PCEs) for estimating the 10-year risk of atherosclerotic cardiovascular disease (ASCVD). An AHA scientific advisory group recently developed the Predicting Risk of cardiovascular disease EVENTs (PREVENT) equations, which incorporated kidney measures, removed race as an input, and improved calibration in contemporary populations. PREVENT is known to produce ASCVD risk predictions that are lower than those produced by the PCEs, but the potential clinical implications have not been quantified. Objective To estimate the number of US adults who would experience changes in risk categorization, treatment eligibility, or clinical outcomes when applying PREVENT equations to existing ACC and AHA guidelines. Design, Setting, and Participants Nationally representative cross-sectional sample of 7765 US adults aged 30 to 79 years who participated in the National Health and Nutrition Examination Surveys of 2011 to March 2020, which had response rates ranging from 47% to 70%. Main Outcomes and Measures Differences in predicted 10-year ASCVD risk, ACC and AHA risk categorization, eligibility for statin or antihypertensive therapy, and projected occurrences of myocardial infarction or stroke. Results In a nationally representative sample of 7765 US adults aged 30 to 79 years (median age, 53 years; 51.3% women), it was estimated that using PREVENT equations would reclassify approximately half of US adults to lower ACC and AHA risk categories (53.0% [95% CI, 51.2%-54.8%]) and very few US adults to higher risk categories (0.41% [95% CI, 0.25%-0.62%]). The number of US adults receiving or recommended for preventive treatment would decrease by an estimated 14.3 million (95% CI, 12.6 million-15.9 million) for statin therapy and 2.62 million (95% CI, 2.02 million-3.21 million) for antihypertensive therapy. The study estimated that, over 10 years, these decreases in treatment eligibility could result in 107 000 additional occurrences of myocardial infarction or stroke. Eligibility changes would affect twice as many men as women and a greater proportion of Black adults than White adults. Conclusion and Relevance By assigning lower ASCVD risk predictions, application of the PREVENT equations to existing treatment thresholds could reduce eligibility for statin and antihypertensive therapy among 15.8 million US adults.
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Affiliation(s)
- James A. Diao
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
- Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Ivy Shi
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | | | - Thomas A. Buckley
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
| | - Chirag J. Patel
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
| | - Emma Pierson
- Department of Computer Science, Cornell University, New York, New York
- Department of Population Health Sciences, Weill Cornell Medical College, New York, New York
| | - Robert W. Yeh
- Division of Cardiology, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- Richard A. and Susan F. Smith Center for Outcomes Research, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Dhruv S. Kazi
- Division of Cardiology, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- Richard A. and Susan F. Smith Center for Outcomes Research, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Rishi K. Wadhera
- Division of Cardiology, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- Richard A. and Susan F. Smith Center for Outcomes Research, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Arjun K. Manrai
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
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Zinzuwadia AN, Mineeva O, Li C, Farukhi Z, Giulianini F, Cade B, Chen L, Karlson E, Paynter N, Mora S, Demler O. Tailoring Risk Prediction Models to Local Populations. JAMA Cardiol 2024:2823894. [PMID: 39292486 PMCID: PMC11411452 DOI: 10.1001/jamacardio.2024.2912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/19/2024]
Abstract
Importance Risk estimation is an integral part of cardiovascular care. Local recalibration of guideline-recommended models could address the limitations of existing tools. Objective To provide a machine learning (ML) approach to augment the performance of the American Heart Association's Predicting Risk of Cardiovascular Disease Events (AHA-PREVENT) equations when applied to a local population while preserving clinical interpretability. Design, Setting, and Participants This cohort study used a New England-based electronic health record cohort of patients without prior atherosclerotic cardiovascular disease (ASCVD) who had the data necessary to calculate the AHA-PREVENT 10-year risk of developing ASCVD in the event period (2007-2016). Patients with prior ASCVD events, death prior to 2007, or age 79 years or older in 2007 were subsequently excluded. The final study population of 95 326 patients was split into 3 nonoverlapping subsets for training, testing, and validation. The AHA-PREVENT model was adapted to this local population using the open-source ML model (MLM) Extreme Gradient Boosting model (XGBoost) with minimal predictor variables, including age, sex, and AHA-PREVENT. The MLM was monotonically constrained to preserve known associations between risk factors and ASCVD risk. Along with sex, race and ethnicity data from the electronic health record were collected to validate the performance of ASCVD risk prediction in subgroups. Data were analyzed from August 2021 to February 2024. Main Outcomes and Measures Consistent with the AHA-PREVENT model, ASCVD events were defined as the first occurrence of either nonfatal myocardial infarction, coronary artery disease, ischemic stroke, or cardiovascular death. Cardiovascular death was coded via government registries. Discrimination, calibration, and risk reclassification were assessed using the Harrell C index, a modified Hosmer-Lemeshow goodness-of-fit test and calibration curves, and reclassification tables, respectively. Results In the test set of 38 137 patients (mean [SD] age, 64.8 [6.9] years, 22 708 [59.5]% women and 15 429 [40.5%] men; 935 [2.5%] Asian, 2153 [5.6%] Black, 1414 [3.7%] Hispanic, 31 400 [82.3%] White, and 2235 [5.9%] other, including American Indian, multiple races, unspecified, and unrecorded, consolidated owing to small numbers), MLM-PREVENT had improved calibration (modified Hosmer-Lemeshow P > .05) compared to the AHA-PREVENT model across risk categories in the overall cohort (χ23 = 2.2; P = .53 vs χ23 > 16.3; P < .001) and sex subgroups (men: χ23 = 2.1; P = .55 vs χ23 > 16.3; P < .001; women: χ23 = 6.5; P = .09 vs. χ23 > 16.3; P < .001), while also surpassing a traditional recalibration approach. MLM-PREVENT maintained or improved AHA-PREVENT's calibration in Asian, Black, and White individuals. Both MLM-PREVENT and AHA-PREVENT performed equally well in discriminating risk (approximate ΔC index, ±0.01). Using a clinically significant 7.5% risk threshold, MLM-PREVENT reclassified a total of 11.5% of patients. We visualize the recalibration through MLM-PREVENT ASCVD risk charts that highlight preserved risk associations of the original AHA-PREVENT model. Conclusions and Relevance The interpretable ML approach presented in this article enhanced the accuracy of the AHA-PREVENT model when applied to a local population while still preserving the risk associations found by the original model. This method has the potential to recalibrate other established risk tools and is implementable in electronic health record systems for improved cardiovascular risk assessment.
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Affiliation(s)
| | | | - Chunying Li
- Brigham & Women's Hospital, Boston, Massachusetts
| | - Zareen Farukhi
- Brigham & Women's Hospital, Boston, Massachusetts
- Massachusetts General Hospital, Boston
| | | | - Brian Cade
- Brigham & Women's Hospital, Boston, Massachusetts
| | - Lin Chen
- Brigham & Women's Hospital, Boston, Massachusetts
| | | | - Nina Paynter
- Brigham & Women's Hospital, Boston, Massachusetts
| | - Samia Mora
- Brigham & Women's Hospital, Boston, Massachusetts
| | - Olga Demler
- Brigham & Women's Hospital, Boston, Massachusetts
- ETH Zurich, Zurich, Switzerland
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Zamor RL, Liberman DB, Hall JE, Rees CA, Hartford EA, Chaudhari PP, Portillo EN, Johnson MD. Collecting Sociodemographic Data in Pediatric Emergency Research: A Working Group Consensus. Pediatrics 2024; 154:e2023065277. [PMID: 39044723 PMCID: PMC11291964 DOI: 10.1542/peds.2023-065277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 05/15/2024] [Accepted: 05/16/2024] [Indexed: 07/25/2024] Open
Abstract
Understanding and addressing health care disparities relies on collecting and reporting accurate data in clinical care and research. Data regarding a child's race, ethnicity, and language; sexual orientation and gender identity; and socioeconomic and geographic characteristics are important to ensure equity in research practices and reported outcomes. Disparities are known to exist across these sociodemographic categories. More consistent, accurate data collection could improve understanding of study results and inform approaches to resolve disparities in child health. However, published guidance on standardized collection of these data in children is limited, and given the evolving nature of sociocultural identities, requires frequent updates. The Pediatric Emergency Care Applied Research Network, a multi-institutional network dedicated to pediatric emergency research, developed a Health Disparities Working Group in 2021 to support and advance equitable pediatric emergency research. The working group, which includes clinicians involved in pediatric emergency medical care and researchers with expertise in pediatric disparities and the conduct of pediatric research, prioritized creating a guide for approaches to collecting race, ethnicity, and language; sexual orientation and gender identity; and socioeconomic and geographic data during the conduct of research in pediatric emergency care settings. Our aims with this guide are to summarize existing barriers to sociodemographic data collection in pediatric emergency research, highlight approaches to support the consistent and reproducible collection of these data, and provide rationale for suggested approaches. These approaches may help investigators collect data through a process that is inclusive, consistent across studies, and better informs efforts to reduce disparities in child health.
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Affiliation(s)
- Ronine L. Zamor
- Division of Pediatric Emergency Medicine, Emory University School of Medicine, Atlanta, Georgia
- Division of Emergency Medicine, Children’s Healthcare of Atlanta, Atlanta, Georgia
| | - Danica B. Liberman
- Division of Emergency and Transport Medicine, Children’s Hospital Los Angeles, Los Angeles, California
- Departments of Pediatrics
- Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Jeanine E. Hall
- Division of Emergency and Transport Medicine, Children’s Hospital Los Angeles, Los Angeles, California
- Departments of Pediatrics
| | - Chris A. Rees
- Division of Pediatric Emergency Medicine, Emory University School of Medicine, Atlanta, Georgia
- Division of Emergency Medicine, Children’s Healthcare of Atlanta, Atlanta, Georgia
| | - Emily A. Hartford
- Division of Emergency Medicine, Department of Pediatrics, University of Washington, Seattle, Washington
| | - Pradip P. Chaudhari
- Division of Emergency and Transport Medicine, Children’s Hospital Los Angeles, Los Angeles, California
- Departments of Pediatrics
| | - Elyse N. Portillo
- Division of Pediatric Emergency medicine, Baylor College of Medicine, Texas Children’s Hospital, Houston, Texas
| | - Michael D. Johnson
- Division of Pediatric Emergency Medicine, Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, Utah
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Rout A, Duhan S, Umer M, Li M, Kalra D. Atherosclerotic cardiovascular disease risk prediction: current state-of-the-art. Heart 2024; 110:1005-1014. [PMID: 37918900 DOI: 10.1136/heartjnl-2023-322928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/04/2023] Open
Affiliation(s)
- Amit Rout
- Cardiology, University of Louisville, Louisville, Kentucky, USA
| | - Sanchit Duhan
- Cardiology, Sinai Health System, Baltimore, Maryland, USA
| | - Muhammad Umer
- Cardiology, University of Louisville, Louisville, Kentucky, USA
| | - Miranda Li
- Cardiology, University of Washington School of Medicine, Seattle, Washington, USA
| | - Dinesh Kalra
- Cardiology, University of Louisville, Louisville, Kentucky, USA
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Zhao J, O’Hagan A, Salter-Townshend M. How group structure impacts the numbers at risk for coronary artery disease: polygenic risk scores and nongenetic risk factors in the UK Biobank cohort. Genetics 2024; 227:iyae086. [PMID: 38781512 PMCID: PMC11339605 DOI: 10.1093/genetics/iyae086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 03/22/2024] [Accepted: 05/08/2024] [Indexed: 05/25/2024] Open
Abstract
The UK Biobank (UKB) is a large cohort study that recruited over 500,000 British participants aged 40-69 in 2006-2010 at 22 assessment centers from across the United Kingdom. Self-reported health outcomes and hospital admission data are 2 types of records that include participants' disease status. Coronary artery disease (CAD) is the most common cause of death in the UKB cohort. After distinguishing between prevalence and incidence CAD events for all UKB participants, we identified geographical variations in age-standardized rates of CAD between assessment centers. Significant distributional differences were found between the pooled cohort equation scores of UKB participants from England and Scotland using the Mann-Whitney test. Polygenic risk scores of UKB participants from England and Scotland and from different assessment centers differed significantly using permutation tests. Our aim was to discriminate between assessment centers with different disease rates by collecting data on disease-related risk factors. However, relying solely on individual-level predictions and averaging them to obtain group-level predictions proved ineffective, particularly due to the presence of correlated covariates resulting from participation bias. By using the Mundlak model, which estimates a random effects regression by including the group means of the independent variables in the model, we effectively addressed these issues. In addition, we designed a simulation experiment to demonstrate the functionality of the Mundlak model. Our findings have applications in public health funding and strategy, as our approach can be used to predict case rates in the future, as both population structure and lifestyle changes are uncertain.
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Affiliation(s)
- Jinbo Zhao
- Insight Centre for Data Analytics, University College Dublin, Belfield, Dublin D04V1W8, Ireland
- School of Mathematics and Statistics, University College Dublin, Belfield, Dublin D04V1W8, Ireland
| | - Adrian O’Hagan
- Insight Centre for Data Analytics, University College Dublin, Belfield, Dublin D04V1W8, Ireland
- School of Mathematics and Statistics, University College Dublin, Belfield, Dublin D04V1W8, Ireland
| | - Michael Salter-Townshend
- School of Mathematics and Statistics, University College Dublin, Belfield, Dublin D04V1W8, Ireland
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Leff LE, Koperwas ML. Calculated Medicine: Seven Decades of Accelerating Growth. Am J Med 2024; 137:582-588. [PMID: 38556036 DOI: 10.1016/j.amjmed.2024.03.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 03/11/2024] [Accepted: 03/11/2024] [Indexed: 04/02/2024]
Abstract
The field of Calculated Medicine has grown substantially over the last 7 decades. Comprised of objective, evidence-based medical decision tools, Calculated Medicine has broad application in medical practice, medical research, and health care management. This article reviews the history and varied methodologies of Calculated Medicine, starting with the 1953 Apgar score and concluding with a look into modern computational tools of the field: machine learning, natural language processing, artificial intelligence, and in silico research techniques. We'll also review and quantify the rapidly accelerating growth of Calculated Medicine in the medical literature. Our database of journal articles referring to the field has accumulated over 1.8 million citations, with more than 460 new citations (on average) posted every day. Using natural language processing, we examine and analyze this burgeoning database. Lastly, we examine an important new direction of Calculated Medicine: self-reflection on its potential effect on racial and ethnic disparities in health care. Our field is making great strides promoting health care egality, and some of the most prominent contributions will be reviewed.
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Affiliation(s)
- Louis E Leff
- University of Pittsburgh School of Medicine, Pa.
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Pedroso Camargos A, Barreto S, Brant L, Ribeiro ALP, Dhingra LS, Aminorroaya A, Bittencourt M, Figueiredo RC, Khera R. Performance of contemporary cardiovascular risk stratification scores in Brazil: an evaluation in the ELSA-Brasil study. Open Heart 2024; 11:e002762. [PMID: 38862252 PMCID: PMC11168182 DOI: 10.1136/openhrt-2024-002762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2024] [Accepted: 05/29/2024] [Indexed: 06/13/2024] Open
Abstract
AIMS Despite notable population differences in high-income and low- and middle-income countries (LMICs), national guidelines in LMICs often recommend using US-based cardiovascular disease (CVD) risk scores for treatment decisions. We examined the performance of widely used international CVD risk scores within the largest Brazilian community-based cohort study (Brazilian Longitudinal Study of Adult Health, ELSA-Brasil). METHODS All adults 40-75 years from ELSA-Brasil (2008-2013) without prior CVD who were followed for incident, adjudicated CVD events (fatal and non-fatal MI, stroke, or coronary heart disease death). We evaluated 5 scores-Framingham General Risk (FGR), Pooled Cohort Equations (PCEs), WHO CVD score, Globorisk-LAC and the Systematic Coronary Risk Evaluation 2 score (SCORE-2). We assessed their discrimination using the area under the receiver operating characteristic curve (AUC) and calibration with predicted-to-observed risk (P/O) ratios-overall and by sex/race groups. RESULTS There were 12 155 individuals (53.0±8.2 years, 55.3% female) who suffered 149 incident CVD events. All scores had a model AUC>0.7 overall and for most age/sex groups, except for white women, where AUC was <0.6 for all scores, with higher overestimation in this subgroup. All risk scores overestimated CVD risk with 32%-170% overestimation across scores. PCE and FGR had the highest overestimation (P/O ratio: 2.74 (95% CI 2.42 to 3.06)) and 2.61 (95% CI 1.79 to 3.43)) and the recalibrated WHO score had the best calibration (P/O ratio: 1.32 (95% CI 1.12 to 1.48)). CONCLUSION In a large prospective cohort from Brazil, we found that widely accepted CVD risk scores overestimate risk by over twofold, and have poor risk discrimination particularly among Brazilian women. Our work highlights the value of risk stratification strategies tailored to the unique populations and risks of LMICs.
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Affiliation(s)
- Aline Pedroso Camargos
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Sandhi Barreto
- Social and Preventive Medicine, Hospital das Clinicas da Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Luisa Brant
- Social and Preventive Medicine, Hospital das Clinicas da Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Antonio Luiz P Ribeiro
- Departament of Clinical Medicine, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
- Centro de Telessaude, Hospital das Clinicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Lovedeep S Dhingra
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Arya Aminorroaya
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Marcio Bittencourt
- Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | | | - Rohan Khera
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
- Center for Outcomes Research and Evaluation (CORE), Yale New Haven Hospital, New Haven, Connecticut, USA
- Section of Health Informatics, Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, USA
- Department of Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, Connecticut, USA
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Miller HE, Tierney S, Stefanick ML, Mayo JA, Sedan O, Rosas LG, Melbye M, Boyd HA, Stevenson DK, Shaw GM, Winn VD, Hlatky MA. Vascular health years after a hypertensive disorder of pregnancy: The EPOCH study. Am Heart J 2024; 272:96-105. [PMID: 38484963 PMCID: PMC11070303 DOI: 10.1016/j.ahj.2024.03.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 03/07/2024] [Accepted: 03/07/2024] [Indexed: 04/07/2024]
Abstract
BACKGROUND Preeclampsia is associated with a two-fold increase in a woman's lifetime risk of developing atherosclerotic cardiovascular disease (ASCVD), but the reasons for this association are uncertain. The objective of this study was to examine the associations between vascular health and a hypertensive disorder of pregnancy among women ≥ 2 years postpartum. METHODS Pre-menopausal women with a history of either a hypertensive disorder of pregnancy (cases: preeclampsia or gestational hypertension) or a normotensive pregnancy (controls) were enrolled. Participants were assessed for standard ASCVD risk factors and underwent vascular testing, including measurements of blood pressure, endothelial function, and carotid artery ultrasound. The primary outcomes were blood pressure, ASCVD risk, reactive hyperemia index measured by EndoPAT and carotid intima-medial thickness. The secondary outcomes were augmentation index normalized to 75 beats per minute and pulse wave amplitude measured by EndoPAT, and carotid elastic modulus and carotid beta-stiffness measured by carotid ultrasound. RESULTS Participants had a mean age of 40.7 years and were 5.7 years since their last pregnancy. In bivariate analyses, cases (N = 68) were more likely than controls (N = 71) to have hypertension (18% vs 4%, P = .034), higher calculated ASCVD risk (0.6 vs 0.4, P = .02), higher blood pressures (systolic: 118.5 vs 111.6 mm Hg, P = .0004; diastolic: 75.2 vs 69.8 mm Hg, P = .0004), and higher augmentation index values (7.7 vs 2.3, P = .03). They did not, however, differ significantly in carotid intima-media thickness (0.5 vs 0.5, P = .29) or reactive hyperemia index (2.1 vs 2.1, P = .93), nor in pulse wave amplitude (416 vs 326, P = .11), carotid elastic modulus (445 vs 426, P = .36), or carotid beta stiffness (2.8 vs 2.8, P = .86). CONCLUSION Women with a prior hypertensive disorder of pregnancy had higher ASCVD risk and blood pressures several years postpartum, but did not have more endothelial dysfunction or subclinical atherosclerosis.
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Affiliation(s)
- Hayley E Miller
- Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA
| | - Seda Tierney
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
| | - Marcia L Stefanick
- Department of Medicine, Stanford University School of Medicine, Stanford, CA; Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA
| | - Jonathan A Mayo
- Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA; Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
| | - Oshra Sedan
- Department of Health Policy, Stanford University School of Medicine, Stanford, CA
| | - Lisa G Rosas
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA; Department of Medicine, Stanford University School of Medicine, Stanford, CA
| | - Mads Melbye
- Danish Cancer Institute, Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Heather A Boyd
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - David K Stevenson
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
| | - Gary M Shaw
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
| | - Virginia D Winn
- Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA
| | - Mark A Hlatky
- Department of Health Policy, Stanford University School of Medicine, Stanford, CA; Department of Medicine, Stanford University School of Medicine, Stanford, CA.
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Perni S, Prokopovich P. Risk equations for prosthetic joint infections (PJIs) in UK: a retrospective study using the Clinical Practice Research Datalink (CPRD) AURUM and GOLD databases. BMJ Open 2024; 14:e082501. [PMID: 38719289 PMCID: PMC11086542 DOI: 10.1136/bmjopen-2023-082501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 04/26/2024] [Indexed: 05/12/2024] Open
Abstract
BACKGROUND Prosthetic joint infections (PJIs) are a serious negative outcome of arthroplasty with incidence of about 1%. Risk of PJI could depend on local treatment policies and guidelines; no UK-specific risk scoring is currently available. OBJECTIVE To determine a risk quantification model for the development of PJI using electronic health records. DESIGN Records in Clinical Practice Research Datalink (CPRD) GOLD and AURUM of patients undergoing hip or knee arthroplasty between January 2007 and December 2014, with linkage to Hospital Episode Statistics and Office of National Statistics, were obtained. Cohorts' characteristics and risk equations through parametric models were developed and compared between the two databases. Pooled cohort risk equations were determined for the UK population and simplified through stepwise selection. RESULTS After applying the inclusion/exclusion criteria, 174 905 joints (1021 developed PJI) were identified in CPRD AURUM and 48 419 joints (228 developed PJI) in CPRD GOLD. Patients undergoing hip or knee arthroplasty in both databases exhibited different sociodemographic characteristics and medical/drug history. However, the quantification of the impact of such covariates (coefficients of parametric models fitted to the survival curves) on the risk of PJI between the two cohorts was not statistically significant. The log-normal model fitted to the pooled cohorts after stepwise selection had a C-statistic >0.7. CONCLUSIONS The risk prediction tool developed here could help prevent PJI through identifying modifiable risk factors pre-surgery and identifying the patients most likely to benefit from close monitoring/preventive actions. As derived from the UK population, such tool will help the National Health Service reduce the impact of PJI on its resources and patient lives.
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Chen C, Shi H, Yang J, Bao X, Sun Y. The risk of breast cancer and gynecologic malignancies after ovarian stimulation: Meta-analysis of cohort study. Crit Rev Oncol Hematol 2024; 197:104320. [PMID: 38479585 DOI: 10.1016/j.critrevonc.2024.104320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 01/31/2024] [Accepted: 03/01/2024] [Indexed: 03/25/2024] Open
Abstract
The effects of ovarian stimulation on breast and gynecological tumor incidence remain controversial. Therefore, the aim of this meta-analysis was to study the risk of cancer in ovarian stimulation. Of the 22713 studies initially identified, 28 were eligible for inclusion. The results revealed that the impact of ovarian cancer (RR = 1.33, [1.05; 1.69]) and cervical cancer (RR = 0.67, [0.46; 0.97]) is significant among the overall effects. In subgroup analysis, in the nulliparous population (RR = 0.81 [0.68; 0.96]) was the protective factor for the breast cancer. In the Caucasians subgroup (RR = 1.45, [1.12; 1.88]), the ovarian cancer incidence was statistically significant. In the Asian subgroup (RR = 1.51, [1.00; 2.28]), the endometrial cancer incidence was statistically significant. In the subgroup of Asians (RR = 0.55 [0.44; 0.68]) and the multiparous population (RR = 0.31, [0.21; 0.46]), them can be the statistically protective factor for the cervical cancer.
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Affiliation(s)
- Chuanju Chen
- Center for Reproductive Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; Henan Key Laboratory of Reproduction and Cenetics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; Henan Provincial Obstetrical and Gynecological Diseases (Reproductive Medicine) Clinical Research Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; Henan Engineering Laboratory of Preimplantation Genetic Diagnosis and Screening, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Hao Shi
- Center for Reproductive Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; Henan Key Laboratory of Reproduction and Cenetics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; Henan Provincial Obstetrical and Gynecological Diseases (Reproductive Medicine) Clinical Research Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; Henan Engineering Laboratory of Preimplantation Genetic Diagnosis and Screening, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Jingya Yang
- Center for Reproductive Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; Henan Key Laboratory of Reproduction and Cenetics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; Henan Provincial Obstetrical and Gynecological Diseases (Reproductive Medicine) Clinical Research Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; Henan Engineering Laboratory of Preimplantation Genetic Diagnosis and Screening, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Xiao Bao
- Center for Reproductive Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; Henan Key Laboratory of Reproduction and Cenetics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; Henan Provincial Obstetrical and Gynecological Diseases (Reproductive Medicine) Clinical Research Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; Henan Engineering Laboratory of Preimplantation Genetic Diagnosis and Screening, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Yingpu Sun
- Center for Reproductive Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; Henan Key Laboratory of Reproduction and Cenetics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; Henan Provincial Obstetrical and Gynecological Diseases (Reproductive Medicine) Clinical Research Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; Henan Engineering Laboratory of Preimplantation Genetic Diagnosis and Screening, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China.
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Alba AC, Buchan TA, Saha S, Fan S, Poon S, Mak S, Al-Hesayen A, Toma M, Zieroth S, Anderson K, Demers C, Amin F, Porepa L, Chih S, Giannetti N, Rac V, Ross HJ, Guyatt GH. Factors Impacting Physician Prognostic Accuracy in Heart Failure Patients With Reduced Left Ventricular Ejection Fraction. JACC. HEART FAILURE 2024; 12:878-889. [PMID: 38551522 DOI: 10.1016/j.jchf.2024.02.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 01/23/2024] [Accepted: 02/02/2024] [Indexed: 06/09/2024]
Abstract
BACKGROUND A recent study showed that the accuracy of heart failure (HF) cardiologists and family doctors to predict mortality in outpatients with HF proved suboptimal, performing less well than models. OBJECTIVES The authors sought to evaluate patient and physician factors associated with physician accuracy. METHODS The authors included outpatients with HF from 11 HF clinics. Family doctors and HF cardiologists estimated patient 1-year mortality. They calculated predicted mortality using the Seattle HF Model and followed patients for 1 year to record mortality (or urgent heart transplant or ventricular assist device implant as mortality-equivalent events). Using multivariable logistic regression, the authors evaluated associations among physician experience and confidence in estimates, duration of patient-physician relationship, patient-physician sex concordance, patient race, and predicted risk, with concordant results between physician and model predictions. RESULTS Among 1,643 patients, 1-year event rate was 10% (95% CI: 8%-12%). One-half of the estimates showed discrepant results between model and physician predictions, mainly owing to physician risk overestimation. Discrepancies were more frequent with increasing patient risk from 38% in low-risk to ∼75% in high-risk patients. When making predictions on male patients, female HF cardiologists were 26% more likely to have discrepant predictions (OR: 0.74; 95% CI: 0.58-0.94). HF cardiologist estimates in Black patients were 33% more likely to be discrepant (OR: 0.67; 95% CI: 0.45-0.99). Low confidence in predictions was associated with discrepancy. Analyses restricted to high-confidence estimates showed inferior calibration to the model, with risk overestimation across risk groups. CONCLUSIONS Discrepant physician and model predictions were more frequent in cases with perceived increased risk. Model predictions outperform physicians even when they are confident in their predictions. (Predicted Prognosis in Heart Failure [INTUITION]; NCT04009798).
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Affiliation(s)
- Ana C Alba
- Peter Munk Cardiac Centre, Ted Rogers Center for Heart Research, University Health Network, Toronto, Ontario, Canada; Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada.
| | - Tayler A Buchan
- Peter Munk Cardiac Centre, Ted Rogers Center for Heart Research, University Health Network, Toronto, Ontario, Canada; Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Sudipta Saha
- Peter Munk Cardiac Centre, Ted Rogers Center for Heart Research, University Health Network, Toronto, Ontario, Canada
| | - Steve Fan
- Peter Munk Cardiac Centre, Ted Rogers Center for Heart Research, University Health Network, Toronto, Ontario, Canada
| | - Stephanie Poon
- Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Susanna Mak
- Mount Sinai Hospital, Toronto, Ontario, Canada
| | | | - Mustafa Toma
- Providence Health Care, Vancouver, British Columbia, Canada
| | | | - Kim Anderson
- Nova Scotia health Authority, Halifax, Nova Scotia, Canada
| | | | - Faizan Amin
- Hamilton Health Sciences, Hamilton, Ontario, Canada
| | - Liane Porepa
- Southlake Regional Health Centre, Newmarket, Ontario, Canada
| | - Sharon Chih
- Ottawa Heart Institute, Ottawa, Ontario, Canada
| | | | - Valeria Rac
- Peter Munk Cardiac Centre, Ted Rogers Center for Heart Research, University Health Network, Toronto, Ontario, Canada; Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Heather J Ross
- Peter Munk Cardiac Centre, Ted Rogers Center for Heart Research, University Health Network, Toronto, Ontario, Canada
| | - Gordon H Guyatt
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
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12
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Beaudoin JR, Curran J, Alexander GC. Impact of Race on Classification of Atherosclerotic Risk Using a National Cardiovascular Risk Prediction Tool. AJPM FOCUS 2024; 3:100200. [PMID: 38440670 PMCID: PMC10910235 DOI: 10.1016/j.focus.2024.100200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 03/06/2024]
Abstract
Introduction The use of race in clinical risk prediction tools may exacerbate racial disparities in healthcare access and outcomes. This study quantified the number of individuals reclassified for primary prevention of cardiovascular disease owing to a change in their race alone on the basis of a commonly used risk prediction tool. Methods This is a cross-sectional analysis of individuals aged 40-75 years without a history of cardiovascular events, diabetes, or other high-risk features using the 2005-2018 National Health and Nutritional Examination Survey. Authors compared atherosclerotic cardiovascular disease risk scores using the American Heart Association/American College of Cardiology equation recommended for White individuals or individuals of other races with that recommended for Black individuals. Results A total of 2,946 White individuals; 1,361 Black individuals; and 2,495 individuals of other races were included in the analysis. Using the American Heart Association/American College of Cardiology equation, the mean 10-year atherosclerotic cardiovascular disease risk was 5.80% (95% CI=5.54, 6.06) for White individuals, 7.04% (956% CI=6.69, 7.39) for Black individuals, and 4.93% (95% CI=4.61, 5.24) for individuals of other races. When using the American Heart Association/American College of Cardiology equation designated for the opposite race (White/other race versus Black), the mean atherosclerotic cardiovascular disease risk score increased by 1.02% (95% CI=0.90, 1.13) for White individuals, decreased by 1.82% (95% CI= -1.67, -1.96) for Black individuals, and increased by 0.98% (95% CI=0.85, 1.10) for individuals of other races. When using clinical atherosclerotic cardiovascular disease categories of <7.5%, 7.5%-10%, and >10%, 16.93% of all individuals were reclassified when using the American Heart Association/American College of Cardiology's equation designated for the opposite race. Conclusions Changing race within a commonly used cardiovascular risk prediction tool results in significant changes in risk classification among eligible White and Black individuals in the U.S.
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Affiliation(s)
- Jarett R. Beaudoin
- Department of Family and Community Medicine, University of California, Davis, California
| | - Jill Curran
- Center for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - G. Caleb Alexander
- Center for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Division of General Internal Medicine, Johns Hopkins Medicine, Baltimore, Maryland
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13
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Giuliani M, Santagostino Baldi G, Capra N, Bonomi A, Marzorati C, Sebri V, Guiddi P, Montorsi P, Pravettoni G, Trabattoni D. The heart-mind relationship in women cardiovascular primary prevention: the role of depression, anxiety, distress and Type-D personality in the 10-years cardiovascular risk evaluation. Front Cardiovasc Med 2024; 11:1308337. [PMID: 38516002 PMCID: PMC10955135 DOI: 10.3389/fcvm.2024.1308337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 02/22/2024] [Indexed: 03/23/2024] Open
Abstract
Introduction Cardiovascular diseases are the leading cause of death among women. Prevention programmes underscore the need to address women-specific risk factors. Additionally, mental well-being is a significant aspect to consider when grappling with cardiovascular disease in women, particularly depression, anxiety, distress, and personality traits. This study aimed to create "at-risk" psychological profiles for women without prior cardiovascular disease history and to evaluate the association between anxiety, depression, distress, and Type-D personality traits with increased cardiovascular risk over 10 years. Methods 219 women voluntarily participated in the "Monzino Women's Heart Centre" project for primary prevention and early diagnosis of cardiovascular diseases. Psychological profiles were developed utilising cluster analysis. Results The primary finding indicating that belonging to the "at-risk" psychological cluster was associated with a surge in the 10-year cardiovascular risk prediction score, despite the number of comorbid risk factors (Psychological "at-risk" cluster: β = .0674; p = .006; Risk factors: β = .0199; p = .242). Conclusions This finding suggests that psychological well-being of women should be assessed from the very beginning of cardiovascular prevention programmes.
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Affiliation(s)
- Mattia Giuliani
- Psychology Division, Centro Cardiologico Monzino, IRCCS, Milan, Italy
| | - Giulia Santagostino Baldi
- Department of Interventional Cardiology and Women Heart Center, Centro Cardiologico Monzino, IRCCS, Milan, Italy
| | - Nicolò Capra
- Biostatistic Unit, Centro Cardiologico Monzino, IRCCS, Milan, Italy
| | - Alice Bonomi
- Biostatistic Unit, Centro Cardiologico Monzino, IRCCS, Milan, Italy
| | - Chiara Marzorati
- Applied Research Division for Cognitive and Psychological Science, Istituto Europeo di Oncologia (IEO), European Institute of Oncology IRCCS, Milan, Italy
| | - Valeria Sebri
- Applied Research Division for Cognitive and Psychological Science, Istituto Europeo di Oncologia (IEO), European Institute of Oncology IRCCS, Milan, Italy
| | - Paolo Guiddi
- Psychology Division, Centro Cardiologico Monzino, IRCCS, Milan, Italy
- Applied Research Division for Cognitive and Psychological Science, Istituto Europeo di Oncologia (IEO), European Institute of Oncology IRCCS, Milan, Italy
| | - Piero Montorsi
- Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy
| | - Gabriella Pravettoni
- Applied Research Division for Cognitive and Psychological Science, Istituto Europeo di Oncologia (IEO), European Institute of Oncology IRCCS, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Daniela Trabattoni
- Department of Interventional Cardiology and Women Heart Center, Centro Cardiologico Monzino, IRCCS, Milan, Italy
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14
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Ghosh AK, Venkatraman S, Nanna MG, Safford MM, Colantonio LD, Brown TM, Pinheiro LC, Peterson ED, Navar AM, Sterling MR, Soroka O, Nahid M, Banerjee S, Goyal P. Risk Prediction for Atherosclerotic Cardiovascular Disease With and Without Race Stratification. JAMA Cardiol 2024; 9:55-62. [PMID: 38055247 PMCID: PMC10701663 DOI: 10.1001/jamacardio.2023.4520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 10/03/2023] [Indexed: 12/07/2023]
Abstract
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.
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Affiliation(s)
- Arnab K. Ghosh
- Department of Medicine, Weill Cornell Medical College, Cornell University, New York, New York
| | - Sara Venkatraman
- Department of Medicine, Weill Cornell Medical College, Cornell University, New York, New York
- Department of Statistics and Data Science, Cornell University, New York, New York
| | - Michael G. Nanna
- Department of Internal Medicine, Section of Cardiovascular Medicine, Yale University School of Medicine, New Haven, Connecticut
| | - Monika M. Safford
- Department of Medicine, Weill Cornell Medical College, Cornell University, New York, New York
| | | | - Todd M. Brown
- Division of Cardiovascular Disease, University of Alabama at Birmingham, Birmingham
| | - Laura C. Pinheiro
- Department of Medicine, Weill Cornell Medical College, Cornell University, New York, New York
| | - Eric D. Peterson
- Division of Cardiology, UT Southwestern Medical Center, Dallas, Texas
| | - Ann Marie Navar
- Division of Cardiology, UT Southwestern Medical Center, Dallas, Texas
| | - Madeline R. Sterling
- Department of Medicine, Weill Cornell Medical College, Cornell University, New York, New York
| | - Orysya Soroka
- Department of Medicine, Weill Cornell Medical College, Cornell University, New York, New York
| | - Musarrat Nahid
- Department of Medicine, Weill Cornell Medical College, Cornell University, New York, New York
| | - Samprit Banerjee
- Department of Population Health Sciences, Weill Cornell Medical College, Cornell University, New York, New York
| | - Parag Goyal
- Department of Medicine, Weill Cornell Medical College, Cornell University, New York, New York
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Mazhindu T, Ndlovu N, Borok MZ, Meki S, Nyamhunga A, Havranek EP, Kessler ER, Campbell TB, Flaig TW. Metabolic and cardiovascular disease risk for Zimbabwean men with prostate cancer receiving long-term androgen deprivation therapy. RESEARCH SQUARE 2023:rs.3.rs-3723949. [PMID: 38168443 PMCID: PMC10760221 DOI: 10.21203/rs.3.rs-3723949/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Introduction Prostate cancer is a leading cause of cancer-related mortality in the majority of sub-Saharan Africa region countries. Androgen deprivation therapy (ADT) is effective treatment, however ADT is associated with complications including metabolic syndrome and cardiovascular disease. Although cardiovascular disease is a leading cause of mortality among prostate cancer patients, there is limited information on ADT impact on metabolic syndrome and cardiovascular disease risk among Africans. An observational prospective cohort study was carried out in Harare, Zimbabwe. Prostate cancer patients due to be initiated on ADT (medical or surgical) were assessed for metabolic syndrome and a 10-year Atherosclerotic Cardiovascular Disease (ASCVD) 10-year risk probability score was done before ADT and followed up to 9 months. Results 17 black Zimbabwean men were enrolled with a median age 72 years. Most participants (59%) had stage IV disease and 75% opted for surgical castration. At enrolment 23.5% had metabolic syndrome and this increased to 33% after 9 months of ADT. Baseline ASCVD risk was in the high risk category for 68.8% of participants and remained above 50% after 9 months of ADT. In this cohort, there is a 10% absolute increase in metabolic syndrome prevalence amongst African men with prostate cancer within 9 months of ADT initiation.
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Vasan RS, Rao S, van den Heuvel E. Race as a Component of Cardiovascular Disease Risk Prediction Algorithms. Curr Cardiol Rep 2023; 25:1131-1138. [PMID: 37581773 DOI: 10.1007/s11886-023-01938-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/07/2023] [Indexed: 08/16/2023]
Abstract
PURPOSE OF REVIEW Several prediction algorithms include race as a component to account for race-associated variations in disease frequencies. This practice has been questioned recently because of the risk of perpetuating race as a biological construct and diverting attention away from the social determinants of health (SDoH) for which race might be a proxy. We evaluated the appropriateness of including race in cardiovascular disease (CVD) prediction algorithms, notably the pooled cohort equations (PCE). RECENT FINDINGS In a recent investigation, we reported substantial and biologically implausible differences in absolute CVD risk estimates upon using PCE for predicting CVD risk in Black and White persons with identical risk factor profiles, which might result in differential treatment decisions based solely on their race. We recommend the development of raceless CVD risk prediction algorithms that obviate race-associated risk misestimation and racializing treatment practices, and instead incorporate measures of SDoH that mediate race-associated risk differences.
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Affiliation(s)
- Ramachandran S Vasan
- University of Texas School of Public Health and University of Texas Health Sciences Center, 8403 Floyd Curl Drive, Mail Code 7992, San Antonio, TX 78229, USA.
- Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA.
| | - Shreya Rao
- University of Texas School of Public Health and University of Texas Health Sciences Center, 8403 Floyd Curl Drive, Mail Code 7992, San Antonio, TX 78229, USA
| | - Edwin van den Heuvel
- Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, the Netherlands
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Frank DA, Johnson AE, Hausmann LRM, Gellad WF, Roberts ET, Vajravelu RK. Disparities in Guideline-Recommended Statin Use for Prevention of Atherosclerotic Cardiovascular Disease by Race, Ethnicity, and Gender : A Nationally Representative Cross-Sectional Analysis of Adults in the United States. Ann Intern Med 2023; 176:1057-1066. [PMID: 37487210 PMCID: PMC10804313 DOI: 10.7326/m23-0720] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/26/2023] Open
Abstract
BACKGROUND Although statins are a class I recommendation for prevention of atherosclerotic cardiovascular disease and its complications, their use is suboptimal. Differential underuse may mediate disparities in cardiovascular health for systematically marginalized persons. OBJECTIVE To estimate disparities in statin use by race-ethnicity-gender and to determine whether these potential disparities are explained by medical appropriateness of therapy and structural factors. DESIGN Cross-sectional analysis. SETTING National Health and Nutrition Examination Survey from 2015 to 2020. PARTICIPANTS Persons eligible for statin therapy based on 2013 and 2018 American College of Cardiology/American Heart Association blood cholesterol guidelines. MEASUREMENTS The independent variable was race-ethnicity-gender. The outcome of interest was use of a statin. Using the Institute of Medicine framework for examining unequal treatment, we calculated adjusted prevalence ratios (aPRs) to estimate disparities in statin use adjusted for age, disease severity, access to health care, and socioeconomic status relative to non-Hispanic White men. RESULTS For primary prevention, we identified a lower prevalence of statin use that was not explained by measurable differences in disease severity or structural factors among non-Hispanic Black men (aPR, 0.73 [95% CI, 0.59 to 0.88]) and non-Mexican Hispanic women (aPR, 0.74 [CI, 0.53 to 0.95]). For secondary prevention, we identified a lower prevalence of statin use that was not explained by measurable differences in disease severity or structural factors for non-Hispanic Black men (aPR, 0.81 [CI, 0.64 to 0.97]), other/multiracial men (aPR, 0.58 [CI, 0.20 to 0.97]), Mexican American women (aPR, 0.36 [CI, 0.10 to 0.61]), non-Mexican Hispanic women (aPR, 0.57 [CI, 0.33 to 0.82), non-Hispanic White women (aPR, 0.69 [CI, 0.56 to 0.83]), and non-Hispanic Black women (aPR, 0.75 [CI, 0.57 to 0.92]). LIMITATION Cross-sectional data; lack of geographic, language, or statin-dose data. CONCLUSION Statin use disparities for several race-ethnicity-gender groups are not explained by measurable differences in medical appropriateness of therapy, access to health care, and socioeconomic status. These residual disparities may be partially mediated by unobserved processes that contribute to health inequity, including bias, stereotyping, and mistrust. PRIMARY FUNDING SOURCE National Institutes of Health.
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Affiliation(s)
- David A. Frank
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System
- Department of Epidemiology, University of Pittsburgh School of Public Health
| | - Amber E. Johnson
- Division of Cardiology, Department of Medicine, University of Pittsburgh School of Medicine
| | - Leslie R. M. Hausmann
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System
- Division of General Internal Medicine, Department of Medicine, University of Pittsburgh School of Medicine
| | - Walid F. Gellad
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System
- Division of General Internal Medicine, Department of Medicine, University of Pittsburgh School of Medicine
| | - Eric T. Roberts
- Department of Health Policy and Management, University of Pittsburgh School of Public Health
| | - Ravy K. Vajravelu
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh School of Medicine
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Brotzman LE, Zikmund-Fisher BJ. Perceived Barriers Among Clinicians and Older Adults Aged 65 and Older Regarding Use of Life Expectancy to Inform Cancer Screening: A Narrative Review and Comparison. Med Care Res Rev 2023; 80:372-385. [PMID: 36800914 DOI: 10.1177/10775587231153269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/20/2023]
Abstract
While cancer screening guidelines increasingly recommend incorporating life expectancy estimates to inform screening decisions for older adults, little is known about how this happens in practice. This review summarizes current knowledge about primary care clinician and older adult (65+) perspectives about use of life expectancy to guide cancer screening decisions. Clinicians report operational barriers, uncertainty, and hesitation around use of life expectancy in screening decisions. They recognize it may help them more accurately weigh benefits and harms but are unsure how to estimate life expectancy for individual patients. Older adults face conceptual barriers and are generally unconvinced of the benefits of considering their life expectancy when making screening decisions. Life expectancy will always be a difficult topic for clinicians and patients, but there are advantages to incorporating it in cancer screening decisions. We highlight key takeaways from both clinician and older adult perspectives to guide future research.
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Schmidt IM, Shohet M, Serrano M, Yadati P, Menn-Josephy H, Ilori T, Eneanya ND, Cleveland Manchanda EC, Waikar SS. Patients' Perspectives on Race and the Use of Race-Based Algorithms in Clinical Decision-Making: a Qualitative Study. J Gen Intern Med 2023; 38:2045-2051. [PMID: 36811702 PMCID: PMC9945816 DOI: 10.1007/s11606-023-08035-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 12/30/2022] [Indexed: 02/24/2023]
Abstract
BACKGROUND Clinical algorithms that incorporate race as a modifying factor to guide clinical decision-making have recently been criticized for propagating racial bias in medicine. Equations used to calculate lung or kidney function are examples of clinical algorithms that have different diagnostic parameters depending on an individual's race. While these clinical measures have multiple implications for clinical care, patients' awareness of and their perspectives on the application of such algorithms are unknown. OBJECTIVE To examine patients' perspectives on race and the use of race-based algorithms in clinical decision-making. DESIGN Qualitative study using semi-structured interviews. PARTICIPANTS Twenty-three adult patients recruited at a safety-net hospital in Boston, MA. APPROACH Interviews were analyzed using thematic content analysis and modified grounded theory. KEY RESULTS Among the 23 study participants, 11 were women and 15 self-identified as Black or African American. Three categories of themes emerged: The first theme described definitions and the individual meanings participants ascribed to the term race. The second theme described perspectives on the role and consideration of race in clinical decision-making. Most study participants were unaware that race has been used as a modifying factor in clinical equations and rejected the incorporation of race in these equations. The third theme related to exposure to and experience of racism in healthcare settings. Experiences described by non-White participants ranged from microaggressions to overt acts of racism, including perceived racist encounters with healthcare providers. In addition, patients alluded to a deep mistrust in the healthcare system as a major barrier to equitable care. CONCLUSIONS Our findings suggest that most patients are unaware of how race has been used to make risk assessments and guide clinical care. Further research on patients' perspectives is needed to inform the development of anti-racist policies and regulatory agendas as we move forward to combat systemic racism in medicine.
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Affiliation(s)
- Insa M Schmidt
- Section of Nephrology, Boston University Chobanian & Avedisian School of Medicine and Boston Medical Center, Evans Biomedical Research Center, 5th Floor, 650 Albany Street, Boston, MA, 02118, USA.
| | - Merav Shohet
- Department of Anthropology, Boston University College of Arts and Sciences, Boston, MA, USA
| | - Mariana Serrano
- UMass Memorial Health's Office for Diversity, Equity, Inclusion and Belonging, Boston, MA, USA
| | - Pranav Yadati
- Section of Nephrology, Boston University Chobanian & Avedisian School of Medicine and Boston Medical Center, Evans Biomedical Research Center, 5th Floor, 650 Albany Street, Boston, MA, 02118, USA
| | - Hanni Menn-Josephy
- Section of Nephrology, Boston University Chobanian & Avedisian School of Medicine and Boston Medical Center, Evans Biomedical Research Center, 5th Floor, 650 Albany Street, Boston, MA, 02118, USA
| | - Titilayo Ilori
- Section of Nephrology, Boston University Chobanian & Avedisian School of Medicine and Boston Medical Center, Evans Biomedical Research Center, 5th Floor, 650 Albany Street, Boston, MA, 02118, USA
| | - Nwamaka D Eneanya
- Division of Renal-Electrolyte and Hypertension, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Global Medical Office Fresenius Medical Care, Waltham, MA, USA
| | - Emily C Cleveland Manchanda
- Department of Emergency Medicine, Boston University Chobanian & Avedisian School of Medicine and Boston Medical Center, Boston, MA, USA
| | - Sushrut S Waikar
- Section of Nephrology, Boston University Chobanian & Avedisian School of Medicine and Boston Medical Center, Evans Biomedical Research Center, 5th Floor, 650 Albany Street, Boston, MA, 02118, USA
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20
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Abstract
Dyslipidemia is an important risk factor for coronary artery disease and stroke. All persons with dyslipidemia should be advised to focus on lifestyle interventions, including regular aerobic exercise, a healthy diet, maintenance of a healthy weight, and abstinence from smoking. In addition to lifestyle interventions, lipid-lowering therapy should be considered for persons at moderate to high risk for atherosclerotic cardiovascular disease based on validated risk equations. Statin therapy is the first-line medical treatment for dyslipidemia due to its effectiveness and favorable adverse effect profile, but newer treatments provide additional tools for clinicians to effectively treat dyslipidemia.
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Affiliation(s)
- Marios Arvanitis
- Johns Hopkins University School of Medicine, Baltimore, Maryland (M.A., C.J.L.)
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21
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Brandt EJ. Social determinants of racial health inequities. Lancet Public Health 2023; 8:e396-e397. [PMID: 37244668 PMCID: PMC11104490 DOI: 10.1016/s2468-2667(23)00100-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 05/08/2023] [Indexed: 05/29/2023]
Affiliation(s)
- Eric J Brandt
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI 48109, USA; Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.
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22
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Vassy JL, Posner DC, Ho YL, Gagnon DR, Galloway A, Tanukonda V, Houghton SC, Madduri RK, McMahon BH, Tsao PS, Damrauer SM, O’Donnell CJ, Assimes TL, Casas JP, Gaziano JM, Pencina MJ, Sun YV, Cho K, Wilson PW. Cardiovascular Disease Risk Assessment Using Traditional Risk Factors and Polygenic Risk Scores in the Million Veteran Program. JAMA Cardiol 2023; 8:564-574. [PMID: 37133828 PMCID: PMC10157509 DOI: 10.1001/jamacardio.2023.0857] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 03/09/2023] [Indexed: 05/04/2023]
Abstract
Importance Primary prevention of atherosclerotic cardiovascular disease (ASCVD) relies on risk stratification. Genome-wide polygenic risk scores (PRSs) are proposed to improve ASCVD risk estimation. Objective To determine whether genome-wide PRSs for coronary artery disease (CAD) and acute ischemic stroke improve ASCVD risk estimation with traditional clinical risk factors in an ancestrally diverse midlife population. Design, Setting, and Participants This was a prognostic analysis of incident events in a retrospectively defined longitudinal cohort conducted from January 1, 2011, to December 31, 2018. Included in the study were adults free of ASCVD and statin naive at baseline from the Million Veteran Program (MVP), a mega biobank with genetic, survey, and electronic health record data from a large US health care system. Data were analyzed from March 15, 2021, to January 5, 2023. Exposures PRSs for CAD and ischemic stroke derived from cohorts of largely European descent and risk factors, including age, sex, systolic blood pressure, total cholesterol, high-density lipoprotein (HDL) cholesterol, smoking, and diabetes status. Main Outcomes and Measures Incident nonfatal myocardial infarction (MI), ischemic stroke, ASCVD death, and composite ASCVD events. Results A total of 79 151 participants (mean [SD] age, 57.8 [13.7] years; 68 503 male [86.5%]) were included in the study. The cohort included participants from the following harmonized genetic ancestry and race and ethnicity categories: 18 505 non-Hispanic Black (23.4%), 6785 Hispanic (8.6%), and 53 861 non-Hispanic White (68.0%) with a median (5th-95th percentile) follow-up of 4.3 (0.7-6.9) years. From 2011 to 2018, 3186 MIs (4.0%), 1933 ischemic strokes (2.4%), 867 ASCVD deaths (1.1%), and 5485 composite ASCVD events (6.9%) were observed. CAD PRS was associated with incident MI in non-Hispanic Black (hazard ratio [HR], 1.10; 95% CI, 1.02-1.19), Hispanic (HR, 1.26; 95% CI, 1.09-1.46), and non-Hispanic White (HR, 1.23; 95% CI, 1.18-1.29) participants. Stroke PRS was associated with incident stroke in non-Hispanic White participants (HR, 1.15; 95% CI, 1.08-1.21). A combined CAD plus stroke PRS was associated with ASCVD deaths among non-Hispanic Black (HR, 1.19; 95% CI, 1.03-1.17) and non-Hispanic (HR, 1.11; 95% CI, 1.03-1.21) participants. The combined PRS was also associated with composite ASCVD across all ancestry groups but greater among non-Hispanic White (HR, 1.20; 95% CI, 1.16-1.24) than non-Hispanic Black (HR, 1.11; 95% CI, 1.05-1.17) and Hispanic (HR, 1.12; 95% CI, 1.00-1.25) participants. Net reclassification improvement from adding PRS to a traditional risk model was modest for the intermediate risk group for composite CVD among men (5-year risk >3.75%, 0.38%; 95% CI, 0.07%-0.68%), among women, (6.79%; 95% CI, 3.01%-10.58%), for age older than 55 years (0.25%; 95% CI, 0.03%-0.47%), and for ages 40 to 55 years (1.61%; 95% CI, -0.07% to 3.30%). Conclusions and Relevance Study results suggest that PRSs derived predominantly in European samples were statistically significantly associated with ASCVD in the multiancestry midlife and older-age MVP cohort. Overall, modest improvement in discrimination metrics were observed with addition of PRSs to traditional risk factors with greater magnitude in women and younger age groups.
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Affiliation(s)
- Jason L. Vassy
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts
- Department of Medicine, Brigham & Women’s Hospital and Harvard Medical School, Boston, Massachusetts
| | - Daniel C. Posner
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts
| | - Yuk-Lam Ho
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts
| | - David R. Gagnon
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Ashley Galloway
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts
| | | | | | - Ravi K. Madduri
- Data Science and Learning Division, Argonne National Laboratory, Lemont, Illinois
- University of Chicago Consortium for Advanced Science and Engineering, The University of Chicago, Chicago, Illinois
| | - Benjamin H. McMahon
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico
| | - Philip S. Tsao
- Palo Alto VA Healthcare System, Palo Alto, California
- Stanford Cardiovascular Institute, Stanford University, Stanford, California
| | - Scott M. Damrauer
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | | | - Themistocles L. Assimes
- Palo Alto VA Healthcare System, Palo Alto, California
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, California
- Stanford Cardiovascular Institute, Stanford University, Stanford, California
| | - Juan P. Casas
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts
- Department of Medicine, Brigham & Women’s Hospital and Harvard Medical School, Boston, Massachusetts
| | - J. Michael Gaziano
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts
- Division of Aging, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Michael J. Pencina
- Department of Biostatistics, Duke University Medical Center, Durham, North Carolina
| | - Yan V. Sun
- Veterans Affairs Atlanta Healthcare System, Decatur, Georgia
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia
| | - Kelly Cho
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts
- Department of Medicine, Brigham & Women’s Hospital and Harvard Medical School, Boston, Massachusetts
| | - Peter W.F. Wilson
- Veterans Affairs Atlanta Healthcare System, Decatur, Georgia
- Division of Cardiology, Emory University School of Medicine, Atlanta, Georgia
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia
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23
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Jacobs JA, Addo DK, Zheutlin AR, Derington CG, Essien UR, Navar AM, Hernandez I, Lloyd-Jones DM, King JB, Rao S, Herrick JS, Bress AP, Pandey A. Prevalence of Statin Use for Primary Prevention of Atherosclerotic Cardiovascular Disease by Race, Ethnicity, and 10-Year Disease Risk in the US: National Health and Nutrition Examination Surveys, 2013 to March 2020. JAMA Cardiol 2023; 8:443-452. [PMID: 36947031 PMCID: PMC10034667 DOI: 10.1001/jamacardio.2023.0228] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 01/25/2023] [Indexed: 03/23/2023]
Abstract
Importance The burden of atherosclerotic cardiovascular disease (ASCVD) in the US is higher among Black and Hispanic vs White adults. Inclusion of race in guidance for statin indication may lead to decreased disparities in statin use. Objective To evaluate prevalence of primary prevention statin use by race and ethnicity according to 10-year ASCVD risk. Design, Setting, and Participants This serial, cross-sectional analysis performed in May 2022 used data from the National Health and Nutrition Examination Survey, a nationally representative sample of health status in the US, from 2013 to March 2020 (limited cycle due to the COVID-19 pandemic), to evaluate statin use for primary prevention of ASCVD and to estimate 10-year ASCVD risk. Participants aged 40 to 75 years without ASCVD, diabetes, low-density lipoprotein cholesterol levels 190 mg/dL or greater, and with data on medication use were included. Exposures Self-identified race and ethnicity (Asian, Black, Hispanic, and White) and 10-year ASCVD risk category (5%-<7.5%, 7.5%-<20%, ≥20%). Main Outcomes and Measures Prevalence of statin use, defined as identification of statin use on pill bottle review. Results A total of 3417 participants representing 39.4 million US adults after applying sampling weights (mean [SD] age, 61.8 [8.0] years; 1289 women [weighted percentage, 37.8%] and 2128 men [weighted percentage, 62.2%]; 329 Asian [weighted percentage, 4.2%], 1032 Black [weighted percentage, 12.7%], 786 Hispanic [weighted percentage, 10.1%], and 1270 White [weighted percentage, 73.0%]) were included. Compared with White participants, statin use was lower in Black and Hispanic participants and comparable among Asian participants in the overall cohort (Asian, 25.5%; Black, 20.0%; Hispanic, 15.4%; White, 27.9%) and within ASCVD risk strata. Within each race and ethnicity group, a graded increase in statin use was observed across increasing ASCVD risk strata. Statin use was low in the highest risk stratum overall with significantly lower rates of use among Black (23.8%; prevalence ratio [PR], 0.90; 95% CI, 0.82-0.98 vs White) and Hispanic participants (23.9%; PR, 0.90; 95% CI, 0.81-0.99 vs White). Among other factors, routine health care access and health insurance were significantly associated with higher statin use in Black, Hispanic, and White adults. Prevalence of statin use did not meaningfully change over time by race and ethnicity or by ASCVD risk stratum. Conclusions and Relevance In this study, statin use for primary prevention of ASCVD was low among all race and ethnicity groups regardless of ASCVD risk, with the lowest use occurring among Black and Hispanic adults. Improvements in access to care may promote equitable use of primary prevention statins in Black and Hispanic adults.
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Affiliation(s)
- Joshua A. Jacobs
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Daniel K. Addo
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Alexander R. Zheutlin
- Department of Internal Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Catherine G. Derington
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Utibe R. Essien
- Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine at the University of California, Los Angeles
- Center for the Study of Healthcare Innovation, Implementation & Policy, Greater Los Angeles VA Healthcare System, Los Angeles, California
| | - Ann Marie Navar
- Division of Cardiology, University of Texas Southwestern Medical Center, Dallas
- Deputy Editor, Diversity, Equity, and Inclusion, JAMA Cardiology
| | | | - Donald M. Lloyd-Jones
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Jordan B. King
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
- Institute for Health Research, Kaiser Permanente Colorado, Aurora
| | - Shreya Rao
- Division of Cardiology, University of Texas Southwestern Medical Center, Dallas
| | - Jennifer S. Herrick
- Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City
| | - Adam P. Bress
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Ambarish Pandey
- Division of Cardiology, University of Texas Southwestern Medical Center, Dallas
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24
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Vallée A. Association between cannabis use and ten-year estimated atherosclerotic cardiovascular disease risk in a middle-aged population survey. Eur J Intern Med 2023; 111:69-76. [PMID: 36858942 DOI: 10.1016/j.ejim.2023.02.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 02/05/2023] [Accepted: 02/23/2023] [Indexed: 03/02/2023]
Abstract
BACKGROUND The association between cardiovascular (CV) risk and cannabis use remains inconsistent. The purpose of this study was to examine sex stratified associations of the different lifetime aspects of cannabis use and estimated 10-year atherosclerotic cardiovascular disease (ASCVD) risk levels among the general UK Biobank population. METHODS Among 104,092 volunteers of the UK Biobank population, cannabis use status was assessed by questionnaire and range as heavy, moderate, low, and never users. Associations between cannabis use and ASCVD risk were estimated using multiple regressions. RESULTS Males presented a higher estimated 10-year ASCVD risk compared to females (7.96% vs. 2.24%, p < 0.001) and a higher proportion of heavy lifetime cannabis users (4.00% vs 2.01%, p < 0.001). In all covariate adjusted models, lifetime heavy cannabis use was associated with an increase in estimated 10-year ASCVD risk in both males and females, but with a higher effect among males (in males, B = 0.51 (0.34; 068), in females, B = 0.14 (0.05; 0.23)). When considering high estimated 10-year ASCVD risk (superior to 7.5%), similar results were observed, in males, OR=2.14 [1.82-2.51] and in females: OR=2.07 [1.35-3.17]). The current consumption of cannabis was associated with increased ASCVD risk in both males and females (p < 0.001). When considering the overall population, a significant interaction was observed between sex and cannabis use (p < 0.001). CONCLUSION A positive association between estimated 10-year ASCVD risk and heavy lifetime cannabis use was observed but this was higher in males. Longitudinal studies are needed in general populations to highlight the causal effects of cannabis on the atherosclerosis process.
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Affiliation(s)
- Alexandre Vallée
- Department of Epidemiology-Data-Biostatistics, Delegation of Clinical Research and Innovation (DRCI), Foch hospital, Suresnes 92150, France.
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25
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Wright JL, Davis WS, Joseph MM, Ellison AM, Heard-Garris NJ, Johnson TL. Eliminating Race-Based Medicine. Pediatrics 2022; 150:186963. [PMID: 35491483 DOI: 10.1542/peds.2022-057998] [Citation(s) in RCA: 51] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/29/2022] [Indexed: 02/03/2023] Open
Affiliation(s)
- Joseph L Wright
- Department of Pediatrics, University of Maryland School of Medicine, Baltimore, Maryland.,Department of Health Policy and Management, University of Maryland School of Public Health, College Park, Maryland
| | - Wendy S Davis
- Department of Pediatrics, Robert Larner, MD, College of Medicine, University of Vermont, Burlington, Vermont
| | - Madeline M Joseph
- Departments of Emergency Medicine and Pediatrics, University of Florida College of Medicine - Jacksonville, Jacksonville, Florida
| | - Angela M Ellison
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.,Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Nia J Heard-Garris
- Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Tiffani L Johnson
- Department of Emergency Medicine, University of California, Davis, Sacramento, California
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26
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McElroy L, Fridell JA. Impact of race on pancreas transplant outcomes in the current era: it is not all black and white. Clin Transplant 2022; 36:e14615. [PMID: 35171509 PMCID: PMC8989646 DOI: 10.1111/ctr.14615] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Accepted: 02/09/2022] [Indexed: 12/01/2022]
Abstract
The growth in pancreas transplant is driven in part by expansion of indications to include an increasing number of select patients with type II diabetes. Two papers in this month's issue of Clinical transplantation specifically investigate this association, and in parallel illustrate the complexity of defining the association of race with pancreas transplant outcomes from different perspectives and illustrate several important concepts related to health equity in organ transplantation. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Lisa McElroy
- Department of Surgery, Duke University School of Medicine, Durham, North Carolina
| | - Jonathan A Fridell
- Indiana University School of Medicine, Department of Surgery, Indianapolis, USA
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27
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Vyas DA, James A, Kormos W, Essien UR. Revising the atherosclerotic cardiovascular disease calculator without race. Lancet Digit Health 2021; 4:e4-e5. [PMID: 34952675 DOI: 10.1016/s2589-7500(21)00258-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 11/08/2021] [Indexed: 11/17/2022]
Affiliation(s)
- Darshali A Vyas
- Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA.
| | - Aisha James
- Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - William Kormos
- Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Utibe R Essien
- Department of Medicine, University of Pittsburgh Hospital, Pittsburgh, PA, USA
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