Evidence map›Paper›PMID 38769904›Full record

ArticlePharmaceutical statistics

A model-assisted design for partially or completely ordered groups.

Connor Celum, Mark Conaway

Abstract read
In one paragraph

Article in Pharmaceutical statistics. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

2 authors.

Connor CelumDepartment of Statistics, University of Virginia, Charlottesville, Virginia, USA.ORCID 0009-0005-5105-6578
Mark ConawayDepartment of Statistics, University of Virginia, Charlottesville, Virginia, USA.

Funding

The integrated Translational Health Research Institute of Virginia (iTHRIV): Using Data to Improve HealthUL1TR003015 · NCATS · UNIVERSITY OF VIRGINIA · PI BROWN, DONALD E, JOHNSTON, KAREN C. · 2019 to 2023
$20.3M
NCATS NIH HHS UL1 TR003015
6 · The paper itself

Abstract

This paper proposes a trial design for locating group-specific doses when groups are partially or completely ordered by dose sensitivity. Previous trial designs for partially ordered groups are model-based, whereas the proposed method is model-assisted, providing clinicians with a design that is simpler. The proposed method performs similarly to model-based methods, providing simplicity without losing accuracy. Additionally, to the best of our knowledge, the proposed method is the first paper on dose-finding for partially ordered groups with convergence results. To generalize the proposed method, a framework is introduced that allows partial orders to be transferred to a grid format with a known ordering across rows but an unknown ordering within rows.

Indexed as

Research DesignClinical Trials as TopicComputer SimulationDose-Response Relationship, DrugHumansModels, StatisticalBOINclinical trialdose‐findinggroupstoxicity

Identifiers

PMID38769904
PMCPMC11602961

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.