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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Published in:	Journal of the American Heart Association Vol. 6; no. 5
Main Authors:	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
Format:	Journal Article
Language:	English
Published:	England Wiley-Blackwell 01.05.2017 John Wiley and Sons Inc Wiley
Subjects:	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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Summary:	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.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 ObjectType-Review-3 content type line 23 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