Evidence map›Paper›PMID 32395663›Full record

ArticleContemporary clinical trials communications2020

A model-based approach for simulating adaptive clinical studies with surrogate endpoints used for interim decision-making.

Xiaotian Chen, Alan Hartford, Jun Zhao

Abstract read
In one paragraph

Article in Contemporary clinical trials communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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. Article
  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

3 authors.

Xiaotian ChenData and Statistical Sciences, AbbVie Inc, North Chicago, IL, United States.
Alan HartfordStatistical and Quantitative Sciences, Takeda Pharmaceuticals Inc, Cambridge, MA, United States.
Jun ZhaoData Science, Astellas Pharma Global Development, Northbrook, IL, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In clinical trials, when exploring multiple dose groups to establish efficacy and safety on one or more selected doses, adaptive designs with interim dose selection are often used for dropping less effective dose groups. When it takes a long time to observe primary outcomes, utilizing information on a surrogate endpoint available at an earlier interim may be preferred for selecting which dose to continue. We propose a Bayesian model-based approach where historical data can be leveraged to incorporate a correlation model for investigating the design's operating characteristics. Simulation studies were conducted and the method can be readily applied for power and sample size calculations.

Indexed as

Adaptive designBayesian modelCombination testHistorical dataSurrogate markerSurvival analysis

Identifiers

PMID32395663
PMCPMC7205753

What OpenQuestion holds

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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.