Sample Size Calculation for Meta-Epidemiological Studies
2016
Giraudeau, Bruno | Higgins, Julian P. T. | Tavernier, Elsa | Trinquart, Ludovic | Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)) ; Institut National de la Recherche Agronomique (INRA)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM) | Centre d’Investigation Clinique [Tours] CIC 1415 (CIC) ; Centre Hospitalier Régional Universitaire de Tours (CHRU Tours)-Institut National de la Santé et de la Recherche Médicale (INSERM) | Université de Tours (UT) | PRES Centre-Val de Loire Université | Centre Hospitalier Régional Universitaire de Tours (CHRU Tours) | MethodS in Patients-centered outcomes and HEalth ResEarch (SPHERE) ; Université de Tours (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR des Sciences Pharmaceutiques et Biologiques (UFR SPB) ; Université de Nantes (UN)-Université de Nantes (UN) | Biostatistique, Recherche Clinique et Mesures Subjectives en Santé (EA 4275) ; Université de Nantes - UFR des Sciences Pharmaceutiques et Biologiques (UFR SPB) ; Université de Nantes (UN)-Université de Nantes (UN) | Centre d'Epidémiologie Clinique ; Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Hôtel Dieu | Université Paris Descartes - Faculté de Médecine (UPD5 Médecine) ; Université Paris Descartes - Paris 5 (UPD5) | Equipe 5 : METHODS - Méthodes de l’évaluation thérapeutique des maladies chroniques (CRESS - U1153) ; Université Paris Descartes - Paris 5 (UPD5)-Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)) ; Institut National de la Recherche Agronomique (INRA)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de la Recherche Agronomique (INRA)-Université Paris Diderot - Paris 7 (UPD7)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)
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Show more [+] Less [-]English. Meta-epidemiological studies are used to compare treatment effect estimates between randomized clinical trials with and without a characteristic of interest. To our knowledge, there is presently nothing to help researchers to a priori specify the required number of meta-analyses to be included in a meta-epidemiological study. We derived a theoretical power function and sample size formula in the framework of a hierarchical model that allows for variation in the impact of the characteristic between trials within a meta-analysis and between meta-analyses. A simulation study revealed that the theoretical function overestimated power (because of the assumption of equal weights for each trial within and between meta-analyses). We also propose a simulation approach that allows for relaxing the constraints used in the theoretical approach and is more accurate. We illustrate that the two variables that mostly influence power are the number of trials per meta-analysis and the proportion of trials with the characteristic of interest. We derived a closed-form power function and sample size formula for estimating the impact of trial characteristics in meta-epidemiological studies. Our analytical results can be used as a 'rule of thumb' for sample size calculation for a meta-epidemiologic study. A more accurate sample size can be derived with a simulation study.
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