BACKGROUND: Within-person variability in measured values of a risk factor can bias its association with disease. The extent of this regression dilution bias for plasma fibrinogen was investigated using repeat measurement data collected at varying time intervals on 27 247 adults in 15 prospective studies. METHODS: Regression dilution ratios (RDRs) were estimated from a linear regression of repeat measurements on baseline values in each study and for each time interval, and pooled allowing for within- and between-study heterogeneity. RDRs were estimated both without and with adjustment for confounders, and factors were investigated that might influence the RDRs. RESULTS: The unadjusted overall RDR was 0.51 (95% CI: 0.47, 0.55), which decreased to 0.46 (95% CI: 0.42, 0.49) after adjustment for age, sex and measured values of other established vascular risk factors. The RDR did not vary materially by assay method, age, sex or smoking status, but decreased at higher levels of baseline fibrinogen. CONCLUSION: It is appropriate to use an RDR of 0.5 to correct approximately for regression dilution bias in plasma fibrinogen values; however, this correction factor may produce somewhat conservative hazard ratios in adjusted analyses, at higher fibrinogen concentrations and in follow-up beyond a decade. More generally, the methods described in this report have widespread applicability to quantifying regression dilution bias in repeatability data from multiple prospective studies.
BACKGROUND: Within-person variability in measured values of a risk factor can bias its association with disease. The extent of this regression dilution bias for plasma fibrinogen was investigated using repeat measurement data collected at varying time intervals on 27 247 adults in 15 prospective studies. METHODS: Regression dilution ratios (RDRs) were estimated from a linear regression of repeat measurements on baseline values in each study and for each time interval, and pooled allowing for within- and between-study heterogeneity. RDRs were estimated both without and with adjustment for confounders, and factors were investigated that might influence the RDRs. RESULTS: The unadjusted overall RDR was 0.51 (95% CI: 0.47, 0.55), which decreased to 0.46 (95% CI: 0.42, 0.49) after adjustment for age, sex and measured values of other established vascular risk factors. The RDR did not vary materially by assay method, age, sex or smoking status, but decreased at higher levels of baseline fibrinogen. CONCLUSION: It is appropriate to use an RDR of 0.5 to correct approximately for regression dilution bias in plasma fibrinogen values; however, this correction factor may produce somewhat conservative hazard ratios in adjusted analyses, at higher fibrinogen concentrations and in follow-up beyond a decade. More generally, the methods described in this report have widespread applicability to quantifying regression dilution bias in repeatability data from multiple prospective studies.
Authors: Shelly-Ann M Love; Kari E North; Donglin Zeng; Natalia Petruski-Ivleva; Anna Kucharska-Newton; Priya Palta; Mariaelisa Graff; Laura Loehr; Sarah B Jones; Gerardo Heiss Journal: Am J Epidemiol Date: 2020-08-01 Impact factor: 4.897
Authors: Emanuele Di Angelantonio; Nadeem Sarwar; Philip Perry; Stephen Kaptoge; Kausik K Ray; Alexander Thompson; Angela M Wood; Sarah Lewington; Naveed Sattar; Chris J Packard; Rory Collins; Simon G Thompson; John Danesh Journal: JAMA Date: 2009-11-11 Impact factor: 56.272
Authors: Alexander Thompson; Pei Gao; Lia Orfei; Sarah Watson; Emanuele Di Angelantonio; Stephen Kaptoge; Christie Ballantyne; Christopher P Cannon; Michael Criqui; Mary Cushman; Albert Hofman; Chris Packard; Simon G Thompson; Rory Collins; John Danesh Journal: Lancet Date: 2010-05-01 Impact factor: 79.321
Authors: Sebhat Erqou; Stephen Kaptoge; Philip L Perry; Emanuele Di Angelantonio; Alexander Thompson; Ian R White; Santica M Marcovina; Rory Collins; Simon G Thompson; John Danesh Journal: JAMA Date: 2009-07-22 Impact factor: 56.272
Authors: Dan Jackson; Ian White; J B Kostis; A C Wilson; A R Folsom; K Wu; L Chambless; M Benderly; U Goldbourt; J Willeit; S Kiechl; J W G Yarnell; P M Sweetnam; P C Elwood; M Cushman; B M Psaty; R P Tracy; A Tybjaerg-Hansen; F Haverkate; M P M de Maat; S G Thompson; F G R Fowkes; A J Lee; F B Smith; V Salomaa; K Harald; V Rasi; E Vahtera; P Jousilahti; R D'Agostino; W B Kannel; P W F Wilson; G Tofler; D Levy; R Marchioli; F Valagussa; A Rosengren; L Wilhelmsen; G Lappas; H Eriksson; P Cremer; D Nagel; J D Curb; B Rodriguez; K Yano; J T Salonen; K Nyyssönen; T-P Tuomainen; B Hedblad; G Engström; G Berglund; H Loewel; W Koenig; H W Hense; T W Meade; J A Cooper; B De Stavola; C Knottenbelt; G J Miller; J A Cooper; K A Bauer; R D Rosenberg; S Sato; A Kitamura; Y Naito; H Iso; V Salomaa; K Harald; V Rasi; E Vahtera; P Jousilahti; T Palosuo; P Ducimetiere; P Amouyel; D Arveiler; A E Evans; J Ferrieres; I Juhan-Vague; A Bingham; H Schulte; G Assmann; B Cantin; B Lamarche; J-P Despres; G R Dagenais; H Tunstall-Pedoe; G D O Lowe; M Woodward; Y Ben-Shlomo; G Davey Smith; V Palmieri; J L Yeh; T W Meade; A Rudnicka; P Brennan; C Knottenbelt; J A Cooper; P Ridker; F Rodeghiero; A Tosetto; J Shepherd; G D O Lowe; I Ford; M Robertson; E Brunner; M Shipley; E J M Feskens; E Di Angelantonio; S Kaptoge; S Lewington; G D O Lowe; N Sarwar; S G Thompson; M Walker; S Watson; I R White; A M Wood; J Danesh Journal: Stat Med Date: 2009-04-15 Impact factor: 2.373