Risk for Incident Heart Failure: A Subject‐Level Meta‐Analysis From the Heart “OMics” in AGEing (HOMAGE) Study

Background To address the need for personalized prevention, we conducted a subject‐level meta‐analysis within the framework of the Heart “OMics” in AGEing (HOMAGE) study to develop a risk prediction model for heart failure (HF) based on routinely available clinical measurements. Methods and Results...

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Vydáno v:Journal of the American Heart Association Ročník 6; číslo 5
Hlavní autoři: Jacobs, Lotte, Efremov, Ljupcho, Ferreira, João Pedro, Thijs, Lutgarde, Yang, Wen‐Yi, Zhang, Zhen‐Yu, Latini, Roberto, Masson, Serge, Agabiti, Nera, Sever, Peter, Delles, Christian, Sattar, Naveed, Butler, Javed, Cleland, John G. F., Kuznetsova, Tatiana, Staessen, Jan A., Zannad, Faiez, Pinet, Florence, Pizard, Anne, Rouet, Philippe, Leenders, Joost, Diez, Javier, Odili, Augustine, Wei, Fang‐Fei, Newman, Anne, Papadimitrious, Lampros, Davoli, Marina, Mureddu, Gian Francesco, Ford, Ian, Jukema, Wouter, Stott, David J., Poulter, Neil
Médium: Journal Article
Jazyk:angličtina
Vydáno: England Wiley-Blackwell 01.05.2017
John Wiley and Sons Inc
Wiley
Témata:
Adult
Age Factors
Aged
Aged, 80 and over
Aging - blood
Area Under Curve
Biomarkers - blood
Blood Pressure
Chi-Square Distribution
Comorbidity
Decision Support Techniques
Female
Geriatric Assessment
heart failure
Heart Failure - blood
Heart Failure - diagnosis
Heart Failure - epidemiology
Heart Failure - physiopathology
Heart Rate
Hospitalization
Human health and pathology
Humans
Incidence
Life Sciences
Life Style
Linear Models
Male
meta‐analysis
Middle Aged
Multivariate Analysis
Predictive Value of Tests
Prognosis
Proportional Hazards Models
Risk Assessment
risk factor
Risk Factors
risk prediction
ROC Curve
Systematic Review and Meta‐Analysis
Time Factors
heart failure
meta‐analysis
risk factor
risk prediction
ISSN:2047-9980, 2047-9980
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Shrnutí:Background To address the need for personalized prevention, we conducted a subject‐level meta‐analysis within the framework of the Heart “OMics” in AGEing (HOMAGE) study to develop a risk prediction model for heart failure (HF) based on routinely available clinical measurements. Methods and Results Three studies with elderly persons (Health Aging and Body Composition [Health ABC], Valutazione della PREvalenza di DIsfunzione Cardiaca asinTOmatica e di scompenso cardiaco [PREDICTOR], and Prospective Study of Pravastatin in the Elderly at Risk [PROSPER]) were included to develop the HF risk function, while a fourth study (Anglo‐Scandinavian Cardiac Outcomes Trial [ASCOT]) was used as a validation cohort. Time‐to‐event analysis was conducted using the Cox proportional hazard model. Incident HF was defined as HF hospitalization. The Cox regression model was evaluated for its discriminatory performance (area under the receiver operating characteristic curve) and calibration (Grønnesby‐Borgan χ2 statistic). During a follow‐up of 3.5 years, 470 of 10 236 elderly persons (mean age, 74.5 years; 51.3% women) developed HF. Higher age, BMI, systolic blood pressure, heart rate, serum creatinine, smoking, diabetes mellitus, history of coronary artery disease, and use of antihypertensive medication were associated with increased HF risk. The area under the receiver operating characteristic curve of the model was 0.71, with a good calibration (χ2 7.9, P=0.54). A web‐based calculator was developed to allow easy calculations of the HF risk. Conclusions Simple measurements allow reliable estimation of the short‐term HF risk in populations and patients. The risk model may aid in risk stratification and future HF prevention strategies.
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PMCID: PMC5524083
Dr Jacobs and Dr Efremov contributed equally to this work and are joint first authors.
A complete list of the Heart “OMics” in AGEing (HOMAGE) investigators can be found in the Appendix at the end of the manuscript.
ISSN:2047-9980
2047-9980
DOI:10.1161/JAHA.116.005231