Systematically missing confounders in individual participant data meta-analysis of observational cohort studies

D. Jackson; I. White; J.B. Kostis; A.C. Wilson; A.R. Folsom; K. Wu; L. Chambless; M. Benderly; U. Goldbourt; J. Willeit; S. Kiechl; J.W. Yarnell; P.M. Sweetnam; P.C. Elwood; M. Cushman; B.M. Psaty; R.P. Tracy; A. Tybjaerg-Hansen; F. Haverkate; M.P. de Maat; S.G. Thompson; F.G. 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. 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. Nyyssonen; T.P. Tuomainen; B. Hedblad; G. Engstrom; 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. 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. Lowe; I. Ford; M. Robertson; E. Brunner; M. Shipley; E.J. Feskens; E. Di Angelantonio; S. Kaptoge; S. Lewington; G.D. Lowe; N. Sarwar; S.G. Thompson; M. Walker; S. Watson; I.R. White; A.M. Wood; J. Danesh

Systematically missing confounders in individual participant data meta-analysis of observational cohort studies

D. Jackson, I. White, J.B. Kostis, A.C. Wilson, A.R. Folsom, K. Wu, L. Chambless, M. Benderly, U. Goldbourt, J. Willeit, S. Kiechl, J.W. Yarnell, P.M. Sweetnam, P.C. Elwood, M. Cushman, B.M. Psaty, R.P. Tracy, A. Tybjaerg-Hansen, F. Haverkate, M.P. de MaatS.G. Thompson, F.G. 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. 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. Nyyssonen, T.P. Tuomainen, B. Hedblad, G. Engstrom, 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. 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. Lowe, I. Ford, M. Robertson, E. Brunner, M. Shipley, E.J. Feskens, E. Di Angelantonio, S. Kaptoge, S. Lewington, G.D. Lowe, N. Sarwar, S.G. Thompson, M. Walker, S. Watson, I.R. White, A.M. Wood, J. Danesh

34 Citations (Scopus)

Abstract

One difficulty in performing meta-analyses of observational cohort studies is that the availability of confounders may vary between cohorts, so that some cohorts provide fully adjusted analyses while others only provide partially adjusted analyses. Commonly, analyses of the association between an exposure and disease either are restricted to cohorts with full confounder information, or use all cohorts but do not fully adjust for confounding. We propose using a bivariate random-effects meta-analysis model to use information from all available cohorts while still adjusting for all the potential confounders. Our method uses both the fully adjusted and the partially adjusted estimated effects in the cohorts with full confounder information, together with an estimate of their within-cohort correlation. The method is applied to estimate the association between fibrinogen level and coronary heart disease incidence using data from 154,012 participants in 31 cohorts
Udgivelsesdato: 2009/4/15

Original language	English
Journal	Statistics in Medicine
Volume	28
Issue number	8
Pages (from-to)	1218-1237
Number of pages	19
ISSN	0277-6715
Publication status	Published - 2009

Cite this

Jackson, D., White, I., Kostis, J. B., Wilson, A. C., Folsom, A. R., Wu, K., Chambless, L., Benderly, M., Goldbourt, U., Willeit, J., Kiechl, S., Yarnell, J. W., Sweetnam, P. M., Elwood, P. C., Cushman, M., Psaty, B. M., Tracy, R. P., Tybjaerg-Hansen, A., Haverkate, F., ... Danesh, J. (2009). Systematically missing confounders in individual participant data meta-analysis of observational cohort studies. Statistics in Medicine, 28(8), 1218-1237.

Jackson, D, White, I, Kostis, JB, Wilson, AC, Folsom, AR, Wu, K, Chambless, L, Benderly, M, Goldbourt, U, Willeit, J, Kiechl, S, Yarnell, JW, Sweetnam, PM, Elwood, PC, Cushman, M, Psaty, BM, Tracy, RP, Tybjaerg-Hansen, A, Haverkate, F, Maat, MPD, Thompson, SG, Fowkes, FG, Lee, AJ, Smith, FB, Salomaa, V, Harald, K, Rasi, V, Vahtera, E, Jousilahti, P, D'Agostino, R, Kannel, WB, Wilson, PW, Tofler, G, Levy, D, Marchioli, R, Valagussa, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Cremer, P, Nagel, D, Curb, JD, Rodriguez, B, Yano, K, Salonen, JT, Nyyssonen, K, Tuomainen, TP, Hedblad, B, Engstrom, G, Berglund, G, Loewel, H, Koenig, W, Hense, HW, Meade, TW, Cooper, JA, Stavola, BD, Knottenbelt, C, Miller, GJ, Cooper, JA, Bauer, KA, Rosenberg, RD, Sato, S, Kitamura, A, Naito, Y, Iso, H, Salomaa, V, Harald, K, Rasi, V, Vahtera, E, Jousilahti, P, Palosuo, T, Ducimetiere, P, Amouyel, P, Arveiler, D, Evans, AE, Ferrieres, J, Juhan-Vague, I, Bingham, A, Schulte, H, Assmann, G, Cantin, B, Lamarche, B, Despres, JP, Dagenais, GR, Tunstall-Pedoe, H, Lowe, GD, Woodward, M, Ben-Shlomo, Y, Smith, GD, Palmieri, V, Yeh, JL, Meade, TW, Rudnicka, A, Brennan, P, Knottenbelt, C, Cooper, JA, Ridker, P, Rodeghiero, F, Tosetto, A, Shepherd, J, Lowe, GD, Ford, I, Robertson, M, Brunner, E, Shipley, M, Feskens, EJ, Angelantonio, ED, Kaptoge, S, Lewington, S, Lowe, GD, Sarwar, N, Thompson, SG, Walker, M, Watson, S, White, IR, Wood, AM & Danesh, J 2009, 'Systematically missing confounders in individual participant data meta-analysis of observational cohort studies', Statistics in Medicine, vol. 28, no. 8, pp. 1218-1237.

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title = "Systematically missing confounders in individual participant data meta-analysis of observational cohort studies",

abstract = "One difficulty in performing meta-analyses of observational cohort studies is that the availability of confounders may vary between cohorts, so that some cohorts provide fully adjusted analyses while others only provide partially adjusted analyses. Commonly, analyses of the association between an exposure and disease either are restricted to cohorts with full confounder information, or use all cohorts but do not fully adjust for confounding. We propose using a bivariate random-effects meta-analysis model to use information from all available cohorts while still adjusting for all the potential confounders. Our method uses both the fully adjusted and the partially adjusted estimated effects in the cohorts with full confounder information, together with an estimate of their within-cohort correlation. The method is applied to estimate the association between fibrinogen level and coronary heart disease incidence using data from 154,012 participants in 31 cohorts Udgivelsesdato: 2009/4/15",

author = "D. Jackson and I. White and J.B. Kostis and A.C. Wilson and A.R. Folsom and K. Wu and L. Chambless and M. Benderly and U. Goldbourt and J. Willeit and S. Kiechl and J.W. Yarnell and P.M. Sweetnam and P.C. Elwood and M. Cushman and B.M. Psaty and R.P. Tracy and A. Tybjaerg-Hansen and F. Haverkate and Maat, {M.P. de} and S.G. Thompson and F.G. Fowkes and A.J. Lee and F.B. Smith and V. Salomaa and K. Harald and V. Rasi and E. Vahtera and P. Jousilahti and R. D'Agostino and W.B. Kannel and P.W. Wilson and G. Tofler and D. Levy and R. Marchioli and F. Valagussa and A. Rosengren and L. Wilhelmsen and G. Lappas and H. Eriksson and P. Cremer and D. Nagel and J.D. Curb and B. Rodriguez and K. Yano and J.T. Salonen and K. Nyyssonen and T.P. Tuomainen and B. Hedblad and G. Engstrom and G. Berglund and H. Loewel and W. Koenig and H.W. Hense and T.W. Meade and J.A. Cooper and Stavola, {B. De} and C. Knottenbelt and G.J. Miller and J.A. Cooper and K.A. Bauer and R.D. Rosenberg and S. Sato and A. Kitamura and Y. Naito and H. Iso and V. Salomaa and K. Harald and V. Rasi and E. Vahtera and P. Jousilahti and T. Palosuo and P. Ducimetiere and P. Amouyel and D. Arveiler and A.E. Evans and J. Ferrieres and I. Juhan-Vague and A. Bingham and H. Schulte and G. Assmann and B. Cantin and B. Lamarche and J.P. Despres and G.R. Dagenais and H. Tunstall-Pedoe and G.D. Lowe and M. Woodward and Y. Ben-Shlomo and Smith, {G. Davey} and V. Palmieri and J.L. Yeh and T.W. Meade and A. Rudnicka and P. Brennan and C. Knottenbelt and J.A. Cooper and P. Ridker and F. Rodeghiero and A. Tosetto and J. Shepherd and G.D. Lowe and I. Ford and M. Robertson and E. Brunner and M. Shipley and E.J. Feskens and Angelantonio, {E. Di} and S. Kaptoge and S. Lewington and G.D. Lowe and N. Sarwar and S.G. Thompson and M. Walker and S. Watson and I.R. White and A.M. Wood and J. Danesh",

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language = "English",

volume = "28",

pages = "1218--1237",

journal = "Statistics in Medicine",

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T1 - Systematically missing confounders in individual participant data meta-analysis of observational cohort studies

AU - Jackson, D.

AU - White, I.

AU - Kostis, J.B.

AU - Wilson, A.C.

AU - Folsom, A.R.

AU - Wu, K.

AU - Chambless, L.

AU - Benderly, M.

AU - Goldbourt, U.

AU - Willeit, J.

AU - Kiechl, S.

AU - Yarnell, J.W.

AU - Sweetnam, P.M.

AU - Elwood, P.C.

AU - Cushman, M.

AU - Psaty, B.M.

AU - Tracy, R.P.

AU - Tybjaerg-Hansen, A.

AU - Haverkate, F.

AU - Maat, M.P. de

AU - Thompson, S.G.

AU - Fowkes, F.G.

AU - Lee, A.J.

AU - Smith, F.B.

AU - Salomaa, V.

AU - Harald, K.

AU - Rasi, V.

AU - Vahtera, E.

AU - Jousilahti, P.

AU - D'Agostino, R.

AU - Kannel, W.B.

AU - Wilson, P.W.

AU - Tofler, G.

AU - Levy, D.

AU - Marchioli, R.

AU - Valagussa, F.

AU - Rosengren, A.

AU - Wilhelmsen, L.

AU - Lappas, G.

AU - Eriksson, H.

AU - Cremer, P.

AU - Nagel, D.

AU - Curb, J.D.

AU - Rodriguez, B.

AU - Yano, K.

AU - Salonen, J.T.

AU - Nyyssonen, K.

AU - Tuomainen, T.P.

AU - Hedblad, B.

AU - Engstrom, G.

AU - Berglund, G.

AU - Loewel, H.

AU - Koenig, W.

AU - Hense, H.W.

AU - Meade, T.W.

AU - Cooper, J.A.

AU - Stavola, B. De

AU - Knottenbelt, C.

AU - Miller, G.J.

AU - Cooper, J.A.

AU - Bauer, K.A.

AU - Rosenberg, R.D.

AU - Sato, S.

AU - Kitamura, A.

AU - Naito, Y.

AU - Iso, H.

AU - Salomaa, V.

AU - Harald, K.

AU - Rasi, V.

AU - Vahtera, E.

AU - Jousilahti, P.

AU - Palosuo, T.

AU - Ducimetiere, P.

AU - Amouyel, P.

AU - Arveiler, D.

AU - Evans, A.E.

AU - Ferrieres, J.

AU - Juhan-Vague, I.

AU - Bingham, A.

AU - Schulte, H.

AU - Assmann, G.

AU - Cantin, B.

AU - Lamarche, B.

AU - Despres, J.P.

AU - Dagenais, G.R.

AU - Tunstall-Pedoe, H.

AU - Lowe, G.D.

AU - Woodward, M.

AU - Ben-Shlomo, Y.

AU - Smith, G. Davey

AU - Palmieri, V.

AU - Yeh, J.L.

AU - Meade, T.W.

AU - Rudnicka, A.

AU - Brennan, P.

AU - Knottenbelt, C.

AU - Cooper, J.A.

AU - Ridker, P.

AU - Rodeghiero, F.

AU - Tosetto, A.

AU - Shepherd, J.

AU - Lowe, G.D.

AU - Ford, I.

AU - Robertson, M.

AU - Brunner, E.

AU - Shipley, M.

AU - Feskens, E.J.

AU - Angelantonio, E. Di

AU - Kaptoge, S.

AU - Lewington, S.

AU - Lowe, G.D.

AU - Sarwar, N.

AU - Thompson, S.G.

AU - Walker, M.

AU - Watson, S.

AU - White, I.R.

AU - Wood, A.M.

AU - Danesh, J.

PY - 2009

Y1 - 2009

N2 - One difficulty in performing meta-analyses of observational cohort studies is that the availability of confounders may vary between cohorts, so that some cohorts provide fully adjusted analyses while others only provide partially adjusted analyses. Commonly, analyses of the association between an exposure and disease either are restricted to cohorts with full confounder information, or use all cohorts but do not fully adjust for confounding. We propose using a bivariate random-effects meta-analysis model to use information from all available cohorts while still adjusting for all the potential confounders. Our method uses both the fully adjusted and the partially adjusted estimated effects in the cohorts with full confounder information, together with an estimate of their within-cohort correlation. The method is applied to estimate the association between fibrinogen level and coronary heart disease incidence using data from 154,012 participants in 31 cohorts Udgivelsesdato: 2009/4/15

AB - One difficulty in performing meta-analyses of observational cohort studies is that the availability of confounders may vary between cohorts, so that some cohorts provide fully adjusted analyses while others only provide partially adjusted analyses. Commonly, analyses of the association between an exposure and disease either are restricted to cohorts with full confounder information, or use all cohorts but do not fully adjust for confounding. We propose using a bivariate random-effects meta-analysis model to use information from all available cohorts while still adjusting for all the potential confounders. Our method uses both the fully adjusted and the partially adjusted estimated effects in the cohorts with full confounder information, together with an estimate of their within-cohort correlation. The method is applied to estimate the association between fibrinogen level and coronary heart disease incidence using data from 154,012 participants in 31 cohorts Udgivelsesdato: 2009/4/15

M3 - Journal article

SN - 0277-6715

VL - 28

SP - 1218

EP - 1237

JO - Statistics in Medicine

JF - Statistics in Medicine

IS - 8

ER -