Evidence map›Paper›PMID 38273261›Full record

ArticleBMC medical research methodology2024

Comparison of Pocock and Simon's covariate-adaptive randomization procedures in clinical trials.

Guogen Shan, Yulin Li, Xinlin Lu, Yahui Zhang, Samuel S Wu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medical research methodology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. BayCAR: A Bayesian based Covariate-Adaptive Randomization method for multi-arm trials.Communications in statistics: Simulation and computation · 2024
    Article
  4. 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

5 authors.

Guogen ShanDepartment of Biostatistics, University of Florida, Gainesville, 32610, FL, USA. gshan@ufl.edu.
Yulin LiDepartment of Biostatistics, University of Florida, Gainesville, 32610, FL, USA.
Xinlin LuDepartment of Biostatistics, University of Florida, Gainesville, 32610, FL, USA.
Yahui ZhangDepartment of Biostatistics, University of Florida, Gainesville, 32610, FL, USA.
Samuel S WuDepartment of Biostatistics, University of Florida, Gainesville, 32610, FL, USA.

Funding

Alzheimer's Disease: New Trial Designs for Emerging ChallengesR01AG070849 · NIA · UNIVERSITY OF NEVADA LAS VEGAS · PI SHAN, GUOGEN · 2021 to 2025
$1.5M
Application of deep learning and novel survival models to predict MCI-to-AD dementia progressionR03AG083207 · NIA · UNIVERSITY OF FLORIDA · PI SHAN, GUOGEN · 2023 to 2024
$164k
Adaptive randomized designs for cancer clinical trials by using integer algorithms and exact Monte Carlo methodsR03CA248006 · NCI · UNIVERSITY OF FLORIDA · PI SHAN, GUOGEN · 2021 to 2022
$153k
NCI NIH HHS R03 CA248006NIA NIH HHS R01 AG070849NIA NIH HHS R03 AG083207NIH HHS R01AG070849
6 · The paper itself

Abstract

When multiple influential covariates need to be balanced during a clinical trial, stratified blocked randomization and covariate-adaptive randomization procedures are frequently used in trials to prevent bias and enhance the validity of data analysis results. The latter approach is increasingly used in practice for a study with multiple covariates and limited sample sizes. Among a group of these approaches, the covariate-adaptive procedures proposed by Pocock and Simon are straightforward to be utilized in practice. We aim to investigate the optimal design parameters for the patient treatment assignment probability of their developed three methods. In addition, we seek to answer the question related to the randomization performance when additional covariates are added to the existing randomization procedure. We conducted extensive simulation studies to address these practically important questions.

Indexed as

Research DesignClinical Trials as TopicComputer SimulationHumansProbabilityRandom AllocationSample SizeAdditional covariatesAllocation predictabilityCovariate adaptive randomizationImbalance scorePocock and SimonStatistical power

Identifiers

PMID38273261
PMCPMC10809571

What OpenQuestion holds

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Registered trials

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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.