Model selection versus model averaging in dose finding studies

Abstract

A key objective of Phase II dose finding studies in clinical drug development is to adequately characterize the dose response relationship of a new drug. An important decision is then on the choice of a suitable dose response function to support dose selection for the subsequent Phase III studies. In this paper, we compare different approaches for model selection and model averaging using mathematical properties as well as simulations. We review and illustrate asymptotic properties of model selection criteria and investigate their behavior when changing the sample size but keeping the effect size constant. In a simulation study, we investigate how the various approaches perform in realistically chosen settings. Finally, the different methods are illustrated with a recently conducted Phase II dose finding study in patients with chronic obstructive pulmonary disease. Copyright © 2016 John Wiley & Sons, Ltd.

Fevipiprant, an oral prostaglandin DP2receptor (CRTh2) antagonist, in allergic asthma uncontrolled on low-dose inhaled corticosteroids

“…For the modelling part of MCP-Mod, uncertainty was reflected by generating 10 000 parametric bootstrap samples and using the generalised Akaike information criterion to select the best fitting model from a set of monotonic candidate models for each bootstrap sample [9,10]. Each model included a model parameter that describes what multiple of the same total daily dose given once daily corresponds to the same total daily dose given twice daily.…”

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ABSTRACT Dose-related efficacy and safety of fevipiprant (QAW039), an oral DP 2 (CRTh2) receptor antagonist, was assessed in patients with allergic asthma uncontrolled by low-dose inhaled corticosteroids (ICS).Adult patients were randomised to 12 weeks' treatment with once-daily (1,3,10, 30, 50, 75, 150, 300 Montelukast also demonstrated a significant improvement in this end-point. No impact on other efficacy end-points was observed.

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“…Adult patients were randomised to 12 weeks' treatment with once-daily (1,3,10, 30, 50, 75, 150, 300 Montelukast also demonstrated a significant improvement in this end-point. No impact on other efficacy end-points was observed.…”

Advanced Methods for Dose and Regimen Finding During Drug Development: Summary of the EMA/EFPIA Workshop on Dose Finding (London 4–5 December 2014)

“…These effects from each model should be evaluated in such a way as to account for parameter uncertainty. Other methods of model averaging that utilize bootstrapped model selection techniques to average over model predictions have also shown promise 30, 31, 32, 33, 34…”

“…However, single model informed predictions may be overoptimistic or biased (if the “wrong” model is used). As more examples of the dangers of ignoring model uncertainty are publicized, as computing power continues to expand, and as the size of databases, the numbers of variables, and hence the numbers of possible models increase, accounting for model uncertainty (e.g., application through model sensitivity analysis) will become an integral part of statistical modeling 28, 29, 34, 35…”