Evidence map›Paper›PMID 34181760›Full record

ArticleBiometrics2022

Flexible use of copula-type model for dose-finding in drug combination clinical trials.

Koichi Hashizume, Jun Tshuchida, Takashi Sozu

Open access · hybridAbstract read
In one paragraph

Article in Biometrics, 2022. 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
1.2field-weighted citation impact, top 19% of its field
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, 6 citations in OpenAlex.

  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

3 authors at 3 institutions in 1 country.

Koichi HashizumeDepartment of Information and Computer Technology, Graduate School of Engineering, Tokyo University of Science, Tokyo, Japan.ORCID 0000-0001-7493-3485
Jun TshuchidaDepartment of Culture and Information Science, Faculty of Culture and Information Science, Doshisha University, Kyoto, Japan.ORCID 0000-0003-2349-2709
Takashi SozuDepartment of Information and Computer Technology, Faculty of Engineering, Tokyo University of Science, Tokyo, Japan.ORCID 0000-0002-9857-5819
Doshisha University · JPTokyo University of Science · JPTokyo University of Technology · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identification of the maximum tolerated dose combination (MTDC) of cancer drugs is an important objective in phase I oncology trials. Numerous dose-finding designs for drug combination have been proposed over the years. Copula-type models exhibit distinctive advantages in this task over other models used in existing competitive designs. For example, their application enables the consideration of dose-limiting toxicities attributable to one of two agents. However, if a particular combination therapy demonstrates extremely synergistic toxicity, copula-type models are liable to induce biases in toxicity probability estimators due to the associated Fréchet-Hoeffding bounds. Consequently, the dose-finding performance may be worse than those of other competitive designs. The objective of this study is to improve the performance of dose-finding designs based on copula-type models while maintaining their advantageous properties. We propose an extension of the parameter space of the interaction term in copula-type models. This releases the Fréchet-Hoeffding bounds, making the estimation of toxicity probabilities more flexible. Numerical examples in various scenarios demonstrate that the performance (e.g., the percentage of correct MTDC selection) of the proposed method is better than those exhibited by existing copula-type models and comparable with those of other competitive designs, irrespective of the existence of extreme synergistic toxicity. The results obtained in this study could motivate the real-world application of the proposed method in cases requiring the utilization of the properties of copula-type models.

Indexed as

Antineoplastic AgentsNeoplasmsBayes TheoremComputer SimulationDose-Response Relationship, DrugDrug CombinationsHumansMaximum Tolerated DoseResearch DesignAntineoplastic AgentsDrug Combinationscombining drugscopula regressionmaximum tolerated doseoncologyphase I trialsynergistic toxicity

Identifiers

PMID34181760
PMCPMC10393268
OpenAlexW3176453700

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.