Evidence map›Paper›PMID 39877140›Full record

ArticleStatistics in biopharmaceutical research2024

MT-Keyboard: A Bayesian Model-assisted Interval Design to Account for Toxicity Grades and Types for Phase I Trials.

Kai Chen, Li Wang, Ying Yuan

Abstract read
In one paragraph

Article in Statistics in biopharmaceutical research, 2024. 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

3 authors.

Kai ChenDepartment of Biostatistics and Data Science, The University of Texas Health Science Center, Houston, TX, USA.
Li WangAbbVie Inc., North Chicago, IL, USA.
Ying YuanDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Funding

Tropism Enhanced Oncolytic Adenovirus for the Treatment of Brain TumorsP50CA127001 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Juan Fueyo · 2008 to 2026
$41.2M
Consortium for the Study of Chronic Pancreatitis, Diabetes and Pancreatic Cancer: Coordinating and Data Management Center (CSCPDPC-CDMC)U01DK108328 · NIDDK · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Liang Li, Suyu Liu · 2015 to 2026
$32.8M
The University of Texas MD Anderson Cancer Center SPORE in Ovarian CancerP50CA281701 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Ying Yuan · 2023 to 2026
$11.5M
Project 3: Inhibiting Oxidative Phosphorylation in Pancreatic CancerP50CA221707 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI KOPETZ, SCOTT, MAITRA, ANIRBAN · 2019 to 2023
$11.0M
NCI NIH HHS P50 CA127001NCI NIH HHS P50 CA221707NCI NIH HHS P50 CA281701NIDDK NIH HHS U01 DK108328
6 · The paper itself

Abstract

Conventionally, dose finding trials are based on dose-limiting toxicity (DLT) that only captures the most severe toxicities, e.g., treatment related grade 3 or higher toxicity according to the NCI Common Terminology Criteria for Adverse Events. However, this approach is often problematic for certain novel targeted therapies and immunotherapies, which may not induce DLT within a clinically active dose range and are often characterized by low grade toxicities. This important issue has been highlighted and discussed in the American Statistical Association (ASA) Biopharmaceutical (BIOP) Section Open Forums, and is also an important consideration of the Project Optimus initiated by FDA to "reform the dose optimization and dose selection paradigm in oncology drug development." In this paper, we propose an easy-to-implement model-assisted Bayesian design, known as multiple toxicity keyboard (MT-Keyboard) design, to incorporate toxicity grades and types into dose finding. The MT-Keyboard design is able to accommodate binary, quasi-binary and continuous toxicity endpoints that are constructed to account for toxicity grades and types. We further extend the MT-Keyboard design, referred to as TITE-MT-Keyboard, to accommodate late-onset toxicity using the approximated likelihood approach. Simulation shows that the MT-Keyboard and TITE-MT-Keyboard designs have desirable operating characteristics, comparable to or better than some existing designs. A web-based software to implement the design will be freely available at www.trialdesign.org.

Indexed as

Bayesian designLate-onset toxicityModel-assisted designPhase I trialsToxicity gradesToxicity types

Identifiers

PMID39877140
PMCPMC11774480

What OpenQuestion holds

Textmetadata
LicenceTDM
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.