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Defining estimands for efficacy assessment in single arm phase 1b or phase 2 clinical trials in oncology early development
Authors:Stefan Englert  François Mercier  Elizabeth A. Pilling  Victoria Homer  Christina Habermehl  Stefan Zimmermann  Natalia Kan-Dobrosky
Affiliation:1. Statistical Modeling & Methodology, Janssen R&D, Janssen-Cilag GmbH, Neuss, Germany;2. Biostatistics, Roche Innovation Center Basel, F Hoffmann-La Roche AG, Basel, Switzerland;3. Early Biometrics, AstraZeneca, Cambridge, UK;4. Cancer Research (UK) Clinical Trials Unit, University of Birmingham, Birmingham, UK;5. Global Biostatistics, The healthcare Business of Merck KgaA, Darmstadt, Germany;6. Early Clinical Development Oncology, Roche Innovation Center Zurich, F. Hoffmann-La Roche AG, Basel, Switzerland;7. Statistical Science, PPD, Part of Thermo Fisher Scientific, Wilmington, North Carolina, USA
Abstract:The addendum of the ICH E9 guideline on the statistical principles for clinical trials introduced the estimand framework. The framework is designed to strengthen the dialog between different stakeholders, to introduce greater clarity in the clinical trial objectives and to provide alignment between the estimand and statistical analysis. Estimand framework related publications thus far have mainly focused on randomized clinical trials. The intention of the Early Development Estimand Nexus (EDEN), a task force of the cross-industry Oncology Estimand Working Group ( www.oncoestimand.org ), is to apply it to single arms Phase 1b or Phase 2 trials designed to detect a treatment-related efficacy signal, typically measured by objective response rate. Key recommendations regarding the estimand attributes include that in a single arm early clinical trial, the treatment attribute should start when the first dose is received by the participant. Focusing on the estimation of an absolute effect, the population-level summary measure should reflect only the property used for the estimation. Another major component introduced in the ICH E9 addendum is the definition of intercurrent events and the associated possible ways to handle them. Different strategies reflect different clinical questions of interest that can be answered based on the journeys an individual subject can take during a trial. We provide detailed strategy recommendations for intercurrent events typically seen in early-stage oncology. We highlight where implicit assumptions should be made transparent as whenever follow-up is suspended, a while-on-treatment strategy is implied.
Keywords:early oncology  estimator  non-randomized  ORR  response
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