Evidence map›Paper›PMID 40781756›Full record

ReviewStatistics in medicine2025

Confidence Intervals for Adaptive Trial Designs II: Case Study and Practical Guidance.

David S Robertson, Thomas Burnett, Babak Choodari-Oskooei, Munya Dimairo, Michael Grayling, Philip Pallmann, Thomas Jaki

Abstract readReview
In one paragraph

Review in Statistics in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

David S RobertsonMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.ORCID https://orcid.org/0000-0001-6207-0416
Thomas BurnettUniversity of Bath, Bath, UK.ORCID https://orcid.org/0000-0001-8912-2554
Babak Choodari-OskooeiMRC Clinical Trials Unit at UCL, London, UK.ORCID https://orcid.org/0000-0001-7679-5899
Munya DimairoSheffield Centre for Health and Related Research (SCHARR), University of Sheffield, Sheffield, UK.
Michael GraylingStatistics and Decision Sciences, Janssen R&D, High Wycombe, UK.
Philip PallmannCentre for Trials Research, Cardiff University, Cardiff, UK.
Thomas JakiMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.

Funding

Cancer Research UKHCRW_Medical Research Council MC_UU_00002/14Medical Research Council MC_UU_00004_09Medical Research Council MC_UU_0040_03
6 · The paper itself

Abstract

In adaptive clinical trials, the conventional confidence interval (CI) for a treatment effect is prone to undesirable properties such as undercoverage and potential inconsistency with the final hypothesis testing decision. Accordingly, as is stated in recent regulatory guidance on adaptive designs, there is the need for caution in the interpretation of CIs constructed during and after an adaptive clinical trial. However, it may be unclear which of the available CIs in the literature are preferable. This paper is the second in a two-part series that explores CIs for adaptive trials. Part I provided a methodological review of approaches to construct CIs for adaptive designs. In this paper (Part II), we present an extended case study based around a two-stage group sequential trial, including a comprehensive simulation study of the proposed CIs for this setting. This facilitates an expanded description of considerations around what makes for an effective CI procedure following an adaptive trial. We show that the CIs can have notably different properties. Finally, we propose a set of guidelines for researchers around the choice of CIs and the reporting of CIs following an adaptive design.

Indexed as

Adaptive Clinical Trials as TopicResearch DesignComputer SimulationConfidence IntervalsData Interpretation, StatisticalHumansModels, Statisticaladaptive designbootstrapconditional inferencecoverageestimationgroup sequentialinterim analyses

Identifiers

PMID40781756
PMCPMC12334836

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.