Literature DB >> 34857075

Estimands-A Basic Element for Clinical Trials.

Moritz Pohl1, Lukas Baumann, Rouven Behnisch, Marietta Kirchner, Johannes Krisam, Anja Sander.   

Abstract

BACKGROUND: Clinical trials are of central importance for the evaluation and comparison of treatments. The transparency and intelligibility of the treatment effect under investigation is an essential matter for physicians, patients, and health-care authorities. The estimand framework has been introduced because many trials are deficient in this respect.
METHODS: Introduction, definition, and application of the estimand framework on the basis of an example and a selective review of the literature.
RESULTS: The estimand framework provides a systematic approach to the definition of the treatment effect under investigation in a clinical trial. An estimand consists of five attributes: treatment, population, variable, population-level summary, and handling of intercurrent events. Each of these attributes is defined in an interdisciplinary discussion during the trial planning phase, based on the clinical question being asked. Special attention is given to the handling of intercurrent events (ICEs): these are events-e.g., discontinuation or modification of treatment or the use of emergency medication-that can occur once the treatment has begun and might affect the possibility of observing the endpoints or their interpretability. There are various strategies for the handling of ICEs; these can, for example, also reflect the existing intention-to-treat (ITT) principle. Per-protocol analyses, in contrast, are prone to bias and cannot be represented in a sensible manner by an estimand, although they may be performed as a supplementary analysis. The discussion of potential intercurrent events and how they should appropriately be handled in view of the aim of the trial must already take place in the planning phase.
CONCLUSION: Use of the estimand framework should make it easier for both physicians and patients to understand what trials reveal about the efficacy of treatment, and to compare the results of different trials.

Entities:  

Mesh:

Year:  2021        PMID: 34857075      PMCID: PMC8962508          DOI: 10.3238/arztebl.m2021.0373

Source DB:  PubMed          Journal:  Dtsch Arztebl Int        ISSN: 1866-0452            Impact factor:   5.594


  23 in total

Review 1.  Randomized controlled trials: part 17 of a series on evaluation of scientific publications.

Authors:  Maria Kabisch; Christian Ruckes; Monika Seibert-Grafe; Maria Blettner
Journal:  Dtsch Arztebl Int       Date:  2011-09-30       Impact factor: 5.594

2.  The Adaptive designs CONSORT Extension (ACE) statement: a checklist with explanation and elaboration guideline for reporting randomised trials that use an adaptive design.

Authors:  Munyaradzi Dimairo; Philip Pallmann; James Wason; Susan Todd; Thomas Jaki; Steven A Julious; Adrian P Mander; Christopher J Weir; Franz Koenig; Marc K Walton; Jon P Nicholl; Elizabeth Coates; Katie Biggs; Toshimitsu Hamasaki; Michael A Proschan; John A Scott; Yuki Ando; Daniel Hind; Douglas G Altman
Journal:  BMJ       Date:  2020-06-17

3.  A novel estimand to adjust for rescue treatment in randomized clinical trials.

Authors:  Hege Michiels; Cristina Sotto; An Vandebosch; Stijn Vansteelandt
Journal:  Stat Med       Date:  2021-02-10       Impact factor: 2.373

4.  PIONEER 1: Randomized Clinical Trial of the Efficacy and Safety of Oral Semaglutide Monotherapy in Comparison With Placebo in Patients With Type 2 Diabetes.

Authors:  Vanita R Aroda; Julio Rosenstock; Yasuo Terauchi; Yuksel Altuntas; Nebojsa M Lalic; Enrique C Morales Villegas; Ole K Jeppesen; Erik Christiansen; Christin L Hertz; Martin Haluzík
Journal:  Diabetes Care       Date:  2019-06-11       Impact factor: 19.112

5.  Disentangling estimands and the intention-to-treat principle.

Authors:  Ann-Kristin Leuchs; Andreas Brandt; Jörg Zinserling; Norbert Benda
Journal:  Pharm Stat       Date:  2016-12-02       Impact factor: 1.894

6.  Dapagliflozin monotherapy in type 2 diabetic patients with inadequate glycemic control by diet and exercise: a randomized, double-blind, placebo-controlled, phase 3 trial.

Authors:  Ele Ferrannini; Silvia Jimenez Ramos; Afshin Salsali; Weihua Tang; James F List
Journal:  Diabetes Care       Date:  2010-06-21       Impact factor: 19.112

7.  The attributable estimand: A new approach to account for intercurrent events.

Authors:  Patrick Darken; Jack Nyberg; Shaila Ballal; David Wright
Journal:  Pharm Stat       Date:  2020-03-21       Impact factor: 1.894

Review 8.  Estimating and reporting treatment effects in clinical trials for weight management: using estimands to interpret effects of intercurrent events and missing data.

Authors:  Sean Wharton; Arne Astrup; Lars Endahl; Michael E J Lean; Altynai Satylganova; Dorthe Skovgaard; Thomas A Wadden; John P H Wilding
Journal:  Int J Obes (Lond)       Date:  2021-01-18       Impact factor: 5.095

9.  Why most published research findings are false.

Authors:  John P A Ioannidis
Journal:  PLoS Med       Date:  2005-08-30       Impact factor: 11.613

10.  Common pitfalls in statistical analysis: Intention-to-treat versus per-protocol analysis.

Authors:  Priya Ranganathan; C S Pramesh; Rakesh Aggarwal
Journal:  Perspect Clin Res       Date:  2016 Jul-Sep
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