The challenges of trials in reproductive medicine: can a Bayesian approach help?

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The challenges of trials in reproductive medicine : can a Bayesian approach help? / Odendaal, Joshua; Ryan, Elizabeth G; Quenby, Siobhan; Gates, Simon.

In: Reproductive BioMedicine Online, 24.12.2020.

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@article{579624981ebb41f7989ab3b439eec3fb,
title = "The challenges of trials in reproductive medicine: can a Bayesian approach help?",
abstract = "Reproductive medicine is imbued with debates over the results of key trials. This has resulted in heterogeneity in clinical practice and a disconnect between researchers and the patient group they aim to treat. The criticisms of trials originate from the nature of reproductive health conditions and limitations imposed in designing trials to assess effect in a patient group with heterogenous pathologies leading to the same condition. This leads to challenges in balancing the difficulties of recruiting an enriched patient cohort versus the dilutionary effect and need for subgroup analysis from wider recruitment. These challenges manifest as a failure to achieve traditional statistical significance. One potential solution to overcoming these inherent challenges is that of a Bayesian statistical approach. Using examples from the literature we demonstrate the benefits of a Bayesian approach. Taking published data and using a flat prior (no background information used), a Bayesian re-analysis of the PRISM and EAGeR trials is presented. This demonstrated a 94.7% chance of progesterone and a 95.3% probability of aspirin preventing miscarriage, in contrast to the original trial conclusions. These highlight the role a Bayesian approach can play in overcoming the challenges of trials within reproductive health.",
author = "Joshua Odendaal and Ryan, {Elizabeth G} and Siobhan Quenby and Simon Gates",
note = "Copyright {\textcopyright} 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.",
year = "2020",
month = dec,
day = "24",
doi = "10.1016/j.rbmo.2020.12.009",
language = "English",
journal = "Reproductive BioMedicine Online",
issn = "1472-6483",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - The challenges of trials in reproductive medicine

T2 - can a Bayesian approach help?

AU - Odendaal, Joshua

AU - Ryan, Elizabeth G

AU - Quenby, Siobhan

AU - Gates, Simon

N1 - Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.

PY - 2020/12/24

Y1 - 2020/12/24

N2 - Reproductive medicine is imbued with debates over the results of key trials. This has resulted in heterogeneity in clinical practice and a disconnect between researchers and the patient group they aim to treat. The criticisms of trials originate from the nature of reproductive health conditions and limitations imposed in designing trials to assess effect in a patient group with heterogenous pathologies leading to the same condition. This leads to challenges in balancing the difficulties of recruiting an enriched patient cohort versus the dilutionary effect and need for subgroup analysis from wider recruitment. These challenges manifest as a failure to achieve traditional statistical significance. One potential solution to overcoming these inherent challenges is that of a Bayesian statistical approach. Using examples from the literature we demonstrate the benefits of a Bayesian approach. Taking published data and using a flat prior (no background information used), a Bayesian re-analysis of the PRISM and EAGeR trials is presented. This demonstrated a 94.7% chance of progesterone and a 95.3% probability of aspirin preventing miscarriage, in contrast to the original trial conclusions. These highlight the role a Bayesian approach can play in overcoming the challenges of trials within reproductive health.

AB - Reproductive medicine is imbued with debates over the results of key trials. This has resulted in heterogeneity in clinical practice and a disconnect between researchers and the patient group they aim to treat. The criticisms of trials originate from the nature of reproductive health conditions and limitations imposed in designing trials to assess effect in a patient group with heterogenous pathologies leading to the same condition. This leads to challenges in balancing the difficulties of recruiting an enriched patient cohort versus the dilutionary effect and need for subgroup analysis from wider recruitment. These challenges manifest as a failure to achieve traditional statistical significance. One potential solution to overcoming these inherent challenges is that of a Bayesian statistical approach. Using examples from the literature we demonstrate the benefits of a Bayesian approach. Taking published data and using a flat prior (no background information used), a Bayesian re-analysis of the PRISM and EAGeR trials is presented. This demonstrated a 94.7% chance of progesterone and a 95.3% probability of aspirin preventing miscarriage, in contrast to the original trial conclusions. These highlight the role a Bayesian approach can play in overcoming the challenges of trials within reproductive health.

U2 - 10.1016/j.rbmo.2020.12.009

DO - 10.1016/j.rbmo.2020.12.009

M3 - Article

C2 - 33468401

JO - Reproductive BioMedicine Online

JF - Reproductive BioMedicine Online

SN - 1472-6483

ER -