Evidence map›Paper›PMID 38346971›Full record

ArticleScientific reports2024

A new function for drug combination dose finding trials.

Jiacheng Xiao, Weijia Zhang

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.7field-weighted citation impact, top 33% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 1 institution in 1 country.

Jiacheng XiaoDepartment of Financial and Actuarial Mathematics, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, Jiangsu, China.
Weijia ZhangDepartment of Financial and Actuarial Mathematics, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, Jiangsu, China. vivian_wzhang@163.com.
Xi’an Jiaotong-Liverpool University · CN

Funding

Science and Technology Project of Chongqing Education Commission No. KJQN202100804Xi'an Jiaotong-Liverpool University School Research Grant
6 · The paper itself

Abstract

Combination drugs play an essential role in treating cancers. The challenging part of the combination drugs are to specify the dose-toxicity ordering, which means the sequences of dose escalation and de-escalation in process of dose findings should be pre-determined. In the paper, we extend a novel function of the continual reassessment method based on the combination of the normal distribution for drug-combination dose-finding trials and systematically evaluate its performance using a template of four performance measures EARS (Efficiency, Accuracy, Reliability, Selection). Dose escalation and deescalation rules are based on the nearest neighborhood continual reassessment method for a combination drug, and we specify all possible dose-toxicity orderings in the trial. Simulation demonstrates that the new design is efficient, accurate and reasonably reliable.

Indexed as

Research DesignBayes TheoremComputer SimulationDose-Response Relationship, DrugMaximum Tolerated DoseReproducibility of Results

Identifiers

PMID38346971
PMCPMC10861533
OpenAlexW4391752525

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.