ICH E9 Statistical Principles for Clinical Trials was issued in 1998. In October 2014, an addendum to ICH E9 was proposed relating to estimands and sensitivity analyses. In preparation for the release of the addendum, Statisticians in the Pharmaceutical Industry held a 1-day expert group meeting in February 2015. Topics debated included definition, development, implementation, education and communication challenges associated with estimands and sensitivity analyses. The topic of estimands is an important and relatively new one in clinical development. A clear message from the meeting was that estimands bridge the gap between study objectives and statistical methods. When defining estimands, an iterative process linking trial objectives, estimands, trial design, statistical and sensitivity analysis needs to be established. Each objective should have at least one distinct estimand, supported by sensitivity analyses. Because clinical trials are multi-faceted and expensive, it is unrealistic to restrict a study to a single objective and associated estimand. The actual set of estimands and sensitivity analyses for a study will depend on the study objectives, the disease setting and the needs of the various stakeholders. Copyright © 2016 John Wiley & Sons, Ltd.
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http://dx.doi.org/10.1002/pst.1745 | DOI Listing |
Trials
January 2025
Palliative and Advanced Illness Research (PAIR) Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Background: A key challenge for many critical care clinical trials is that some patients will die before their outcome is fully measured. This is referred to as "truncation due to death" and must be accounted for in both the treatment effect definition (i.e.
View Article and Find Full Text PDFBr J Clin Pharmacol
November 2024
Statistical Innovation, Respiratory and Immunology Biometrics and Statistical Innovation, Biopharmaceuticals R&D, AstraZeneca, Cambridge, UK.
The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use has published an addendum on estimands and sensitivity analysis in clinical trials along with related training materials. These define an estimand as a precise description of the treatment effect that reflects the scientific question of interest. In December 2022, the US Food and Drug Administration released draft guidance recommending estimands of interest be specified in bioequivalence trial protocols.
View Article and Find Full Text PDFBiostatistics
November 2024
Department of Statistics, Ludwig-Maximilians Universität München, Ludwigstraße 33, 80539 München, Germany.
Missing data in multiple variables is a common issue. We investigate the applicability of the framework of graphical models for handling missing data to a complex longitudinal pharmacological study of children with HIV treated with an efavirenz-based regimen as part of the CHAPAS-3 trial. Specifically, we examine whether the causal effects of interest, defined through static interventions on multiple continuous variables, can be recovered (estimated consistently) from the available data only.
View Article and Find Full Text PDFStat Med
December 2024
Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Ontario, Canada.
Regression analyses based on transformations of cumulative incidence functions are often adopted when modeling and testing for treatment effects in clinical trial settings involving competing and semi-competing risks. Common frameworks include the Fine-Gray model and models based on direct binomial regression. Using large sample theory we derive the limiting values of treatment effect estimators based on such models when the data are generated according to multiplicative intensity-based models, and show that the estimand is sensitive to several process features.
View Article and Find Full Text PDFBMC Med Res Methodol
October 2024
Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK.
Background: The ICH E9 (R1) addendum on Estimands and Sensitivity analysis in Clinical trials proposes a framework for the design and analysis of clinical trials aimed at improving clarity around the definition of the targeted treatment effect (the estimand) of a study.
Methods: We adopt the estimand framework in the context of a study using "trial emulation" to estimate the risk of pneumocystis pneumonia, an opportunistic disease contracted by people living with HIV and AIDS having a weakened immune system, when considering two antibiotic treatment regimes for stopping antibiotic prophylaxis treatment against this disease. A "while on treatment" strategy has been implemented for post-randomisation (intercurrent) events.
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