4.6 Article

Elicitation of Expert Prior Opinion: Application to the MYPAN Trial in Childhood Polyarteritis Nodosa

Journal

PLOS ONE
Volume 10, Issue 3, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0120981

Keywords

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Funding

  1. Arthritis Research UK [20094]
  2. Medical Research Council North-West Hub for Trials Methodology Research [G0800792]
  3. Medical Research Council [MR/J014079/1]
  4. MRC [MR/J014079/1, G0800792] Funding Source: UKRI
  5. Medical Research Council [G0800792, MR/J014079/1] Funding Source: researchfish
  6. Rosetrees Trust [M8-F1-CD1, M465] Funding Source: researchfish
  7. Versus Arthritis [20094] Funding Source: researchfish

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Objectives Definitive sample sizes for clinical trials in rare diseases are usually infeasible. Bayesian methodology can be used to maximise what is learnt from clinical trials in these circumstances. We elicited expert prior opinion for a future Bayesian randomised controlled trial for a rare inflammatory paediatric disease, polyarteritis nodosa (MYPAN, Mycophenolate mofetil for polyarteritis nodosa). Methods A Bayesian prior elicitation meeting was convened. Opinion was sought on the probability that a patient in the MYPAN trial treated with cyclophosphamide would achieve disease remission within 6-months, and on the relative efficacies of mycophenolate mofetil and cyclophosphamide. Expert opinion was combined with previously unseen data from a recently completed randomised controlled trial in ANCA associated vasculitis. Results A pan-European group of fifteen experts participated in the elicitation meeting. Consensus expert prior opinion was that the most likely rates of disease remission within 6 months on cyclophosphamide or mycophenolate mofetil were 74% and 71%, respectively. This prior opinion will now be taken forward and will be modified to formulate a Bayesian posterior opinion once the MYPAN trial data from 40 patients randomised 1: 1 to either CYC or MMF become available. Conclusions We suggest that the methodological template we propose could be applied to trial design for other rare diseases.

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