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A Bayesian non-inferiority approach using experts’ margin elicitation – application to the monitoring of safety events

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  • معلومة اضافية
    • Contributors:
      Epidémiologie Clinique et Evaluation Economique Appliquées aux Populations Vulnérables (ECEVE (U1123 / UMR_S_1123)); Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM)-AP-HP Hôpital universitaire Robert-Debré Paris; Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP); Centre d'Investigation Clinique 1426 (CIC 1426); Institut National de la Santé et de la Recherche Médicale (INSERM)-AP-HP Hôpital universitaire Robert-Debré Paris; Centre de Recherche des Cordeliers (CRC (UMR_S_1138 / U1138)); École Pratique des Hautes Études (EPHE); Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPCité); AP-HP Hôpital universitaire Robert-Debré Paris; Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP); 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); Maladies neurodéveloppementales et neurovasculaires (NeuroDiderot (UMR_S_1141 / U1141)); Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM); F-CRIN PARTNERS Platform AP-HP
    • بيانات النشر:
      HAL CCSD
      BioMed Central
    • الموضوع:
      2019
    • Collection:
      EPHE (Ecole pratique des hautes études, Paris): HAL
    • نبذة مختصرة :
      International audience ; Background: When conducing Phase-III trial, regulatory agencies and investigators might want to get reliable information about rare but serious safety outcomes during the trial. Bayesian non-inferiority approaches have been developed, but commonly utilize historical placebo-controlled data to define the margin, depend on a single final analysis, and no recommendation is provided to define the prespecified decision threshold. In this study, we propose a non-inferiority Bayesian approach for sequential monitoring of rare dichotomous safety events incorporating experts' opinions on margins.Methods: A Bayesian decision criterion was constructed to monitor four safety events during a non-inferiority trial conducted on pregnant women at risk for premature delivery. Based on experts' elicitation, margins were built using mixtures of beta distributions that preserve experts' variability. Non-informative and informative prior distributions and several decision thresholds were evaluated through an extensive sensitivity analysis. The parameters were selected in order to maintain two rates of misclassifications under prespecified rates, that is, trials that wrongly concluded an unacceptable excess in the experimental arm, or otherwise.Results: The opinions of 44 experts were elicited about each event non-inferiority margins and its relative severity. In the illustrative trial, the maximal misclassification rates were adapted to events' severity. Using those maximal rates, several priors gave good results and one of them was retained for all events. Each event was associated with a specific decision threshold choice, allowing for the consideration of some differences in their prevalence, margins and severity. Our decision rule has been applied to a simulated dataset.Conclusions: In settings where evidence is lacking and where some rare but serious safety events have to be monitored during non-inferiority trials, we propose a methodology that avoids an arbitrary margin choice and helps in the decision ...
    • Relation:
      info:eu-repo/semantics/altIdentifier/pmid/31533631; inserm-02456619; https://inserm.hal.science/inserm-02456619; https://inserm.hal.science/inserm-02456619/document; https://inserm.hal.science/inserm-02456619/file/s12874-019-0826-5.pdf; PUBMED: 31533631; PUBMEDCENTRAL: PMC6751616
    • الرقم المعرف:
      10.1186/s12874-019-0826-5
    • الدخول الالكتروني :
      https://inserm.hal.science/inserm-02456619
      https://inserm.hal.science/inserm-02456619/document
      https://inserm.hal.science/inserm-02456619/file/s12874-019-0826-5.pdf
      https://doi.org/10.1186/s12874-019-0826-5
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.1A08FDD8