Evidence map›Paper›PMID 29606891›Full record

ReviewClinical epidemiology2018

Critical concepts in adaptive clinical trials.

Jay Jh Park, Kristian Thorlund, Edward J Mills

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Clinical epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 6 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

44 citing papers in PubMed, 6 syntheses or guidelines pooled it.

  1. Pooled it
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  12. Real-World Data and Causal Machine Learning to Enhance Drug Development.Therapeutic innovation & regulatory science · 2025
    Review
  13. Replicable Bandits for Digital Health Interventions.Statistical science : a review journal of the Institute of Mathematical Statistics · 2025
    Article
  14. Article
  15. Review
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  17. Article
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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.

Jay Jh ParkDepartment of Medicine, University of British Columbia, Vancouver, BC, Canada.
Kristian ThorlundDepartment of Health Research Methods, Evidence, and Impact (HEI), McMaster University, Hamilton, ON, Canada.
Edward J MillsDepartment of Health Research Methods, Evidence, and Impact (HEI), McMaster University, Hamilton, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adaptive clinical trials are an innovative trial design aimed at reducing resources, decreasing time to completion and number of patients exposed to inferior interventions, and improving the likelihood of detecting treatment effects. The last decade has seen an increasing use of adaptive designs, particularly in drug development. They frequently differ importantly from conventional clinical trials as they allow modifications to key trial design components during the trial, as data is being collected, using preplanned decision rules. Adaptive designs have increased likelihood of complexity and also potential bias, so it is important to understand the common types of adaptive designs. Many clinicians and investigators may be unfamiliar with the design considerations for adaptive designs. Given their complexities, adaptive trials require an understanding of design features and sources of bias. Herein, we introduce some common adaptive design elements and biases and specifically address response adaptive randomization, sample size reassessment, Bayesian methods for adaptive trials, seamless trials, and adaptive enrichment using real examples.

Indexed as

adaptive designsadaptive enrichmentBayesian adaptive trialsresponse adaptive randomizationsample size reassessmentseamless trials

Identifiers

PMID29606891
PMCPMC5868584

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.