I F Godsland1, B V North, D G Johnston. 1. Endocrinology and Metabolic Medicine, Imperial College London, St Mary's Campus, Mint Wing, Praed Street, London W2 1PG, UK. i.godsland@imperial.ac.uk
Abstract
BACKGROUND: Previous studies have identified sub-clinical inflammation as a potential factor in the pathogenesis of cancer and cardiovascular disease (CVD) but the possibility that simple, readily measured indices of sub-clinical inflammation might predict both CVD and cancer has not been tested in the context of a single, prospective analysis. AIM: To evaluate simply measured indices of inflammation as long-term predictors of death from either cancer or CVD. DESIGN: Prospective open cohort study. METHODS: A total of 1192 white males received measurements of a range of risk markers including the inflammation indices white blood cell count (WBC), erythrocyte sedimentation rate (ESR) and serum globulin concentrations. Inflammation marker clustering was quantified as a factor-analysis-derived inflammation score and survival time to death from any cancer or CVD was modeled on baseline measures using the Cox proportional hazards model. RESULTS: A total of 1010 participants met inclusion criteria, of whom 94 died of cancer and 67 of CVD. Mean follow-up times among cases and survivors ranged from 18.2-21.9 years. Independently of established risk factors [age, body mass index (BMI), smoking, alcohol and exercise], WBC, ESR and globulin levels were all individually predictive of both cancer (hazard ratio 1.43, P = 0.002; 1.27, P = 0.02; 1.26, P = 0.02, respectively) and CVD mortality (1.29, P = 0.06; 1.43, P = 0.007; 1.50, P = 0.001). The inflammation score predicted both cancer mortality (1.35, P = 0.003) and CVD mortality (1.46, P = 0.002). Risks associated with high inflammation score were equivalent to and independent of smoking cigarettes for cancer or, for CVD, having a serum cholesterol concentration ≥6.2 mmol/l. CONCLUSIONS: Simple indices of inflammation predict death from cancer or CVD two decades later as strongly as smoking predicts cancer or cholesterol predicts CVD. Their measurement could contribute to evaluation of both cancer and CVD risk.
BACKGROUND: Previous studies have identified sub-clinical inflammation as a potential factor in the pathogenesis of cancer and cardiovascular disease (CVD) but the possibility that simple, readily measured indices of sub-clinical inflammation might predict both CVD and cancer has not been tested in the context of a single, prospective analysis. AIM: To evaluate simply measured indices of inflammation as long-term predictors of death from either cancer or CVD. DESIGN: Prospective open cohort study. METHODS: A total of 1192 white males received measurements of a range of risk markers including the inflammation indices white blood cell count (WBC), erythrocyte sedimentation rate (ESR) and serum globulin concentrations. Inflammation marker clustering was quantified as a factor-analysis-derived inflammation score and survival time to death from any cancer or CVD was modeled on baseline measures using the Cox proportional hazards model. RESULTS: A total of 1010 participants met inclusion criteria, of whom 94 died of cancer and 67 of CVD. Mean follow-up times among cases and survivors ranged from 18.2-21.9 years. Independently of established risk factors [age, body mass index (BMI), smoking, alcohol and exercise], WBC, ESR and globulin levels were all individually predictive of both cancer (hazard ratio 1.43, P = 0.002; 1.27, P = 0.02; 1.26, P = 0.02, respectively) and CVD mortality (1.29, P = 0.06; 1.43, P = 0.007; 1.50, P = 0.001). The inflammation score predicted both cancer mortality (1.35, P = 0.003) and CVD mortality (1.46, P = 0.002). Risks associated with high inflammation score were equivalent to and independent of smoking cigarettes for cancer or, for CVD, having a serum cholesterol concentration ≥6.2 mmol/l. CONCLUSIONS: Simple indices of inflammation predict death from cancer or CVD two decades later as strongly as smoking predicts cancer or cholesterol predicts CVD. Their measurement could contribute to evaluation of both cancer and CVD risk.
Authors: Stephen Kaptoge; Emanuele Di Angelantonio; Lisa Pennells; Angela M Wood; Ian R White; Pei Gao; Matthew Walker; Alexander Thompson; Nadeem Sarwar; Muriel Caslake; Adam S Butterworth; Philippe Amouyel; Gerd Assmann; Stephan J L Bakker; Elizabeth L M Barr; Elizabeth Barrett-Connor; Emelia J Benjamin; Cecilia Björkelund; Hermann Brenner; Eric Brunner; Robert Clarke; Jackie A Cooper; Peter Cremer; Mary Cushman; Gilles R Dagenais; Ralph B D'Agostino; Rachel Dankner; George Davey-Smith; Dorly Deeg; Jacqueline M Dekker; Gunnar Engström; Aaron R Folsom; F Gerry R Fowkes; John Gallacher; J Michael Gaziano; Simona Giampaoli; Richard F Gillum; Albert Hofman; Barbara V Howard; Erik Ingelsson; Hiroyasu Iso; Torben Jørgensen; Stefan Kiechl; Akihiko Kitamura; Yutaka Kiyohara; Wolfgang Koenig; Daan Kromhout; Lewis H Kuller; Debbie A Lawlor; Tom W Meade; Aulikki Nissinen; Børge G Nordestgaard; Altan Onat; Demosthenes B Panagiotakos; Bruce M Psaty; Beatriz Rodriguez; Annika Rosengren; Veikko Salomaa; Jussi Kauhanen; Jukka T Salonen; Jonathan A Shaffer; Steven Shea; Ian Ford; Coen D A Stehouwer; Timo E Strandberg; Robert W Tipping; Alberto Tosetto; Sylvia Wassertheil-Smoller; Patrik Wennberg; Rudi G Westendorp; Peter H Whincup; Lars Wilhelmsen; Mark Woodward; Gordon D O Lowe; Nicholas J Wareham; Kay-Tee Khaw; Naveed Sattar; Chris J Packard; Vilmundur Gudnason; Paul M Ridker; Mark B Pepys; Simon G Thompson; John Danesh Journal: N Engl J Med Date: 2012-10-04 Impact factor: 91.245
Authors: Ahmad A Hariri; Nicholas S Oliver; Desmond G Johnston; John C Stevenson; Ian F Godsland Journal: Dis Markers Date: 2013-11-18 Impact factor: 3.434