Evidence map›Paper›PMID 36998163›Full record

ArticleStatistical methods in medical research2023

Promising zone two-stage design for a single-arm study with binary outcome.

Guogen Shan

Abstract read
In one paragraph

Article in Statistical methods in medical research, 2023. 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. Continuity corrected Wilson interval for the difference of two independent proportions.Journal of statistical theory and applications : JSTA · 2023
    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

1 author.

Guogen ShanDepartment of Biostatistics, University of Florida, Gainesville, FL, USA.ORCID 0000-0001-8690-6599

Funding

Alzheimer's Disease: New Trial Designs for Emerging ChallengesR01AG070849 · NIA · UNIVERSITY OF NEVADA LAS VEGAS · PI SHAN, GUOGEN · 2021 to 2025
$1.5M
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 AG070849
6 · The paper itself

Abstract

Adaptive designs are increasingly used in clinical trials to assess the effectiveness of new drugs. For a single-arm study with a binary outcome, several adaptive designs were developed by using numerical search algorithms and the conditional power approach. The design based on numerical search algorithms is able to identify the global optimal design, but the computational intensity limits the usage of these designs. The conditional power approach searches for the optimal design without expensive computing time. In addition, promising zone strategy was proposed to move on drug development to the follow-up stages when the interim results are promising. We propose to develop two adaptive designs: One based on the conditional power approach, and the other based on the promising zone strategy. These two designs preserve types I and II error rates. It is preferable to satisfy the monotonic property for adaptive designs: The second stage sample size decreases as the first stage responses go up. We theoretically prove this important property for the two proposed designs. The proposed designs can be easily applied to real trials with limited computing resources.

Indexed as

AlgorithmsResearch DesignSample SizeAdaptive designbinary responseconditional poweroptimal two-stage designpromising zone designsingle-arm study

Identifiers

PMID36998163
PMCPMC10641844

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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.