OBJECTIVE: Limited evidence suggests NT-proBNP improves prediction of coronary heart disease (CHD) events but further data are needed, especially in people without pre-existing CHD and in women. METHODS: We measured NT-proBNP in serum from 162 women with incident CHD events and 1226 controls (60-79 years) in a case-control study nested within the prospective British Women's Heart and Health Study. All cases and controls were free from CHD at baseline. We related NT-proBNP to CHD event risk, and determined to what extent NT-proBNP enhanced CHD risk prediction beyond established risk factors. RESULTS: The odds ratio for CHD per 1 standard deviation increase in log(e)NT-proBNP was 1.37 (95% CI: 1.13-1.68) in analyses adjusted for established CHD risk factors, social class, CRP and insulin. However, addition of log(e)NT-proBNP did not improve the discrimination of a prediction model including age, social class, smoking, physical activity, lipids, fasting glucose, waist:hip ratio, hypertension, statin and aspirin use, nor a standard Framingham risk score model; area under the receiver operator curve for the former model increased from 0.676 to 0.687 on inclusion of NT-proBNP (p=0.3). Furthermore, adding NT-proBNP did not improve calibration of a prediction model containing established risk factors, nor did inclusion more appropriately re-classify participants in relation to their final outcome. Findings were similar (independent associations, but no prediction improvement) for fasting insulin and CRP. CONCLUSION: These results caution against use of NT-proBNP for CHD risk prediction in healthy women and suggest a need for larger studies in both genders to resolve outstanding uncertainties.
OBJECTIVE: Limited evidence suggests NT-proBNP improves prediction of coronary heart disease (CHD) events but further data are needed, especially in people without pre-existing CHD and in women. METHODS: We measured NT-proBNP in serum from 162 women with incident CHD events and 1226 controls (60-79 years) in a case-control study nested within the prospective British Women's Heart and Health Study. All cases and controls were free from CHD at baseline. We related NT-proBNP to CHD event risk, and determined to what extent NT-proBNP enhanced CHD risk prediction beyond established risk factors. RESULTS: The odds ratio for CHD per 1 standard deviation increase in log(e)NT-proBNP was 1.37 (95% CI: 1.13-1.68) in analyses adjusted for established CHD risk factors, social class, CRP and insulin. However, addition of log(e)NT-proBNP did not improve the discrimination of a prediction model including age, social class, smoking, physical activity, lipids, fasting glucose, waist:hip ratio, hypertension, statin and aspirin use, nor a standard Framingham risk score model; area under the receiver operator curve for the former model increased from 0.676 to 0.687 on inclusion of NT-proBNP (p=0.3). Furthermore, adding NT-proBNP did not improve calibration of a prediction model containing established risk factors, nor did inclusion more appropriately re-classify participants in relation to their final outcome. Findings were similar (independent associations, but no prediction improvement) for fasting insulin and CRP. CONCLUSION: These results caution against use of NT-proBNP for CHD risk prediction in healthy women and suggest a need for larger studies in both genders to resolve outstanding uncertainties.
Authors: Keith Colaco; Ker-Ai Lee; Shadi Akhtari; Raz Winer; Paul Welsh; Naveed Sattar; Iain B McInnes; Vinod Chandran; Paula Harvey; Richard J Cook; Dafna D Gladman; Vincent Piguet; Lihi Eder Journal: Arthritis Rheumatol Date: 2022-05-16 Impact factor: 15.483
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Authors: Peter Willeit; Stephen Kaptoge; Paul Welsh; Adam Butterworth; Rajiv Chowdhury; Sarah Spackman; Lisa Pennells; Pei Gao; Stephen Burgess; Daniel Freitag; Michael Sweeting; Angela Wood; Nancy Cook; Suzanne Judd; Stella Trompet; Vijay Nambi; Michael Olsen; Brendan Everett; Frank Kee; Johan Ärnlöv; Veikko Salomaa; Daniel Levy; Jussi Kauhanen; Jari Laukkanen; Maryam Kavousi; Toshiharu Ninomiya; Juan-Pablo Casas; Lori Daniels; Lars Lind; Caroline Kistorp; Jens Rosenberg; Thomas Mueller; Speranza Rubattu; Demosthenes Panagiotakos; Oscar Franco; James de Lemos; Andreas Luchner; Jorge Kizer; Stefan Kiechl; Jukka Salonen; S Goya Wannamethee; Rudolf de Boer; Børge Nordestgaard; Jonas Andersson; Torben Jørgensen; Olle Melander; Christie Ballantyne; Christopher DeFilippi; Paul Ridker; Mary Cushman; Wayne Rosamond; Simon Thompson; Vilmundur Gudnason; Naveed Sattar; John Danesh; Emanuele Di Angelantonio Journal: Lancet Diabetes Endocrinol Date: 2016-09-03 Impact factor: 44.867