Evidence map›Paper›PMID 30533550›Full record

ArticleContemporary clinical trials communications2018

Interactive calculator for operating characteristics of phase I cancer clinical trials using standard 3+3 designs.

Zhengjia Chen, Youyun Zheng, Zhibo Wang, Michael Kutner, Walter J Curran, Jeanne Kowalski

Abstract read
In one paragraph

Article in Contemporary clinical trials communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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.

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

6 authors.

Zhengjia ChenDepartment of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, United States.
Youyun ZhengDepartment of Computer Science, Emory University, Atlanta, GA, United States.
Zhibo WangBiostatistics and Bioinformatics Shared Resource, Winship Cancer Institute, Emory University, Atlanta, GA, United States.
Michael KutnerDepartment of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, United States.
Walter J CurranDepartment of Radiation Oncology, Emory University, Atlanta, GA, United States.
Jeanne KowalskiDepartment of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, United States.

Funding

Winship Cancer Institute Cancer Center Support GrantP30CA138292 · NCI · EMORY UNIVERSITY · PI Suresh S Ramalingam · 2009 to 2026
$47.5M
NCI NIH HHS P30 CA138292
6 · The paper itself

Abstract

Among various Phase I clinical trial designs, rule-based standard 3 + 3 designs are the most widely utilized for their simplicity and robustness. It is necessary to define crucial operating characteristics of a Phase I clinical trial before it starts. Based on the assumed probability of dose limiting toxicity (DLT) at each tested dose level, Lin and Shih elaborated formulas to calculate the five key operating characteristics of Phase I clinical trials using the two subtypes of standard 3 + 3 designs (with vs without dose de-escalation): probability of each dose level being chosen as the maximum tolerated dose (MTD); expected number of patients treated at each dose level; expected number of patients experiencing DLT at each dose level; target toxicity level (TTL) (expected probability of DLT at MTD); expected total number of patients experiencing DLT. Understanding these formulas requires advanced statistical knowledge and the formulas are too complicated to be used directly. To facilitate their application, we have developed stand-alone interactive software for convenient calculation of these key operating characteristics. The calculated results are presented in tables and plots that can be saved and easily edited for further use. Some examples of calculation using the software are presented and discussed.

Indexed as

Cancer phase I clinical trialsDose limiting toxicityMaximum tolerated doseOperating characteristicsStandard 3+3 designStatistical software

Identifiers

PMID30533550
PMCPMC6261803

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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.