Evidence map›Paper›PMID 29430043›Full record

ArticleBiometrika2017

Optimal designs for active controlled dose-finding trials with efficacy-toxicity outcomes.

K Schorning, H Dette, K Kettelhake, W K Wong, F Bretz

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biometrika, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

K SchorningFakultät für Mathematik, Ruhr-Universität Bochum, 44780 Bochum, GermanyKirsten.Schorning@rub.deholger.dette@rub.deKatrin.Kettelhake@rub.de.
H DetteFakultät für Mathematik, Ruhr-Universität Bochum, 44780 Bochum, GermanyKirsten.Schorning@rub.deholger.dette@rub.deKatrin.Kettelhake@rub.de.
K KettelhakeFakultät für Mathematik, Ruhr-Universität Bochum, 44780 Bochum, GermanyKirsten.Schorning@rub.deholger.dette@rub.deKatrin.Kettelhake@rub.de.
W K WongDepartment of Biostatistics, University of California at Los Angeles, 650 Charles E. Young Dr. South, Los Angeles, California 90095, U.S.A.wkwong@ucla.edu.
F BretzStatistical Methodology, Novartis Pharma AG, 4002 Basel, Switzerlandfrank.bretz@novartis.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We derive optimal designs to estimate efficacy and toxicity in active controlled dose-finding trials when the bivariate continuous outcomes are described using nonlinear regression models. We determine upper bounds on the required number of different doses and provide conditions under which the boundary points of the design space are included in the optimal design. We provide an analytical description of minimally supported optimal designs and show that they do not depend on the correlation between the bivariate outcomes.

Indexed as

Admissible designEquivalence theoremParticle swarm optimizationTchebycheff system

Identifiers

PMID29430043
PMCPMC5793717

What OpenQuestion holds

Textmetadata
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.