BACKGROUND: Cardiorespiratory fitness (fitness) is associated with cardiovascular disease (CVD) mortality. However, the extent to which fitness improves risk classification when added to traditional risk factors is unclear. METHODS AND RESULTS: Fitness was measured by the Balke protocol in 66 371 subjects without prior CVD enrolled in the Cooper Center Longitudinal Study between 1970 and 2006; follow-up was extended through 2006. Cox proportional hazards models were used to estimate the risk of CVD mortality with a traditional risk factor model (age, sex, systolic blood pressure, diabetes mellitus, total cholesterol, and smoking) with and without the addition of fitness. The net reclassification improvement and integrated discrimination improvement were calculated at 10 and 25 years. Ten-year risk estimates for CVD mortality were categorized as <1%, 1% to <5%, and ≥5%, and 25-year risk estimates were categorized as <8%, 8% to 30%, and ≥30%. During a median follow-up period of 16 years, there were 1621 CVD deaths. The addition of fitness to the traditional risk factor model resulted in reclassification of 10.7% of the men, with significant net reclassification improvement at both 10 years (net reclassification improvement=0.121) and 25 years (net reclassification improvement=0.041) (P<0.001 for both). The integrated discrimination improvement was 0.010 at 10 years (P<0.001), and the relative integrated discrimination improvement was 29%. Similar findings were observed for women at 25 years. CONCLUSIONS: A single measurement of fitness significantly improves classification of both short-term (10-year) and long-term (25-year) risk for CVD mortality when added to traditional risk factors.
BACKGROUND:Cardiorespiratory fitness (fitness) is associated with cardiovascular disease (CVD) mortality. However, the extent to which fitness improves risk classification when added to traditional risk factors is unclear. METHODS AND RESULTS: Fitness was measured by the Balke protocol in 66 371 subjects without prior CVD enrolled in the Cooper Center Longitudinal Study between 1970 and 2006; follow-up was extended through 2006. Cox proportional hazards models were used to estimate the risk of CVD mortality with a traditional risk factor model (age, sex, systolic blood pressure, diabetes mellitus, total cholesterol, and smoking) with and without the addition of fitness. The net reclassification improvement and integrated discrimination improvement were calculated at 10 and 25 years. Ten-year risk estimates for CVD mortality were categorized as <1%, 1% to <5%, and ≥5%, and 25-year risk estimates were categorized as <8%, 8% to 30%, and ≥30%. During a median follow-up period of 16 years, there were 1621 CVD deaths. The addition of fitness to the traditional risk factor model resulted in reclassification of 10.7% of the men, with significant net reclassification improvement at both 10 years (net reclassification improvement=0.121) and 25 years (net reclassification improvement=0.041) (P<0.001 for both). The integrated discrimination improvement was 0.010 at 10 years (P<0.001), and the relative integrated discrimination improvement was 29%. Similar findings were observed for women at 25 years. CONCLUSIONS: A single measurement of fitness significantly improves classification of both short-term (10-year) and long-term (25-year) risk for CVD mortality when added to traditional risk factors.
Authors: Olle Melander; Christopher Newton-Cheh; Peter Almgren; Bo Hedblad; Göran Berglund; Gunnar Engström; Margaretha Persson; J Gustav Smith; Martin Magnusson; Anders Christensson; Joachim Struck; Nils G Morgenthaler; Andreas Bergmann; Michael J Pencina; Thomas J Wang Journal: JAMA Date: 2009-07-01 Impact factor: 56.272
Authors: Tamar S Polonsky; Robyn L McClelland; Neal W Jorgensen; Diane E Bild; Gregory L Burke; Alan D Guerci; Philip Greenland Journal: JAMA Date: 2010-04-28 Impact factor: 56.272
Authors: Vijay Nambi; Lloyd Chambless; Aaron R Folsom; Max He; Yijuan Hu; Tom Mosley; Kelly Volcik; Eric Boerwinkle; Christie M Ballantyne Journal: J Am Coll Cardiol Date: 2010-04-13 Impact factor: 24.094
Authors: Jarett D Berry; Benjamin Willis; Sachin Gupta; Carolyn E Barlow; Susan G Lakoski; Amit Khera; Anand Rohatgi; James A de Lemos; William Haskell; Donald M Lloyd-Jones Journal: J Am Coll Cardiol Date: 2011-04-12 Impact factor: 24.094
Authors: Chia-Yih Wang; William L Haskell; Stephen W Farrell; Michael J Lamonte; Steven N Blair; Lester R Curtin; Jeffery P Hughes; Vicki L Burt Journal: Am J Epidemiol Date: 2010-01-15 Impact factor: 4.897
Authors: Nicholas R Lamoureux; John S Fitzgerald; Kevin I Norton; Todd Sabato; Mark S Tremblay; Grant R Tomkinson Journal: Sports Med Date: 2019-01 Impact factor: 11.136
Authors: Nina P Paynter; Michael J LaMonte; JoAnn E Manson; Lisa W Martin; Lawrence S Phillips; Paul M Ridker; Jennifer G Robinson; Nancy R Cook Journal: Circulation Date: 2014-08-25 Impact factor: 29.690
Authors: Ambarish Pandey; Minesh Patel; Ang Gao; Benjamin L Willis; Sandeep R Das; David Leonard; Mark H Drazner; James A de Lemos; Laura DeFina; Jarett D Berry Journal: Am Heart J Date: 2014-11-12 Impact factor: 4.749
Authors: Jacob P Kelly; Brian J Andonian; Mahesh J Patel; Zhen Huang; Linda K Shaw; Robert W McGarrah; Salvador Borges-Neto; Eric J Velazquez; William E Kraus Journal: Am Heart J Date: 2019-01-16 Impact factor: 4.749
Authors: Jennifer C Gander; Xuemei Sui; James R Hébert; Linda J Hazlett; Bo Cai; Carl J Lavie; Steven N Blair Journal: Mayo Clin Proc Date: 2015-10 Impact factor: 7.616
Authors: Lee W Jones; Whitney E Hornsby; Amy Goetzinger; Lindsay M Forbes; Emily L Sherrard; Morten Quist; Amy T Lane; Miranda West; Neil D Eves; Margaret Gradison; April Coan; James E Herndon; Amy P Abernethy Journal: Lung Cancer Date: 2011-11-22 Impact factor: 5.705
Authors: Michel G Khouri; Whitney E Hornsby; Niels Risum; Eric J Velazquez; Samantha Thomas; Amy Lane; Jessica M Scott; Graeme J Koelwyn; James E Herndon; John R Mackey; Pamela S Douglas; Lee W Jones Journal: Breast Cancer Res Treat Date: 2014-01-04 Impact factor: 4.872