Evidence map›Paper›PMID 34891221›Full record

ArticlePharmaceutical statistics2022

A dose-finding design for dual-agent trials with patient-specific doses for one agent with application to an opiate detoxification trial.

Pavel Mozgunov, Suzie Cro, Anne Lingford-Hughes, Louise M Paterson, Thomas Jaki

Abstract read
In one paragraph

Article in Pharmaceutical statistics, 2022. 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. Trial
  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

5 authors.

Pavel MozgunovMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.ORCID 0000-0001-6810-0284
Suzie CroImperial Clinical Trials Unit, School of Public Health, Imperial College, London, UK.
Anne Lingford-HughesDivision of Psychiatry, Department of Brain Sciences, Imperial College, London, UK.
Louise M PatersonDivision of Psychiatry, Department of Brain Sciences, Imperial College, London, UK.
Thomas JakiMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.ORCID 0000-0002-1096-188X

Funding

Department of Health BRC-1215-20014Department of Health NIHR300576Department of Health NIHR300593Department of Health NIHR-SRF-2015-08-001Medical Research Council MC_UU_00002/14Medical Research Council MR/T025557/1
6 · The paper itself

Abstract

There is a growing interest in early phase dose-finding clinical trials studying combinations of several treatments. While the majority of dose finding designs for such setting were proposed for oncology trials, the corresponding designs are also essential in other therapeutic areas. Furthermore, there is increased recognition of recommending the patient-specific doses/combinations, rather than a single target one that would be recommended to all patients in later phases regardless of their characteristics. In this paper, we propose a dose-finding design for a dual-agent combination trial motivated by an opiate detoxification trial. The distinguishing feature of the trial is that the (continuous) dose of one compound is defined externally by the clinicians and is individual for every patient. The objective of the trial is to define the dosing function that for each patient would recommend the optimal dosage of the second compound. Via a simulation study, we have found that the proposed design results in high accuracy of individual dose recommendation and is robust to the model misspecification and assumptions on the distribution of externally defined doses.

Indexed as

NeoplasmsOpiate AlkaloidsComputer SimulationDose-Response Relationship, DrugHumansMaximum Tolerated DoseMedical OncologyResearch DesignOpiate Alkaloidsbaclofencombination trialdose-findingdose individualisationmethadoneopiate detoxification

Identifiers

PMID34891221
PMCPMC7612599

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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.