Evidence map›Paper›PMID 37243720›Full record

ArticleJournal of the National Cancer Institute2023

Seamless phase II/III design: a useful strategy to reduce the sample size for dose optimization.

Liyun Jiang, Ying Yuan

Open access · greenAbstract read
In one paragraph

Article in Journal of the National Cancer Institute, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
4.4field-weighted citation impact, top 5% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. 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

2 authors at 2 institutions in 2 countries.

Liyun JiangResearch Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, China.
Ying YuanDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.ORCID 0000-0003-3163-480X
China Pharmaceutical University · CNThe University of Texas MD Anderson Cancer Center · US

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
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
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 P30 CA016672NCI NIH HHS P50 CA127001NCI NIH HHS P50 CA221707
6 · The paper itself

Abstract

backgroundThe traditional more-is-better dose selection paradigm, originally developed for cytotoxic chemotherapeutics, can be problematic when applied to the development of novel molecularly targeted agents. Recognizing this issue, the US Food and Drug Administration initiated Project Optimus to reform the dose optimization and selection paradigm in oncology drug development, emphasizing the need for greater attention to benefit-risk considerations.

methodsWe identify different types of phase II/III dose-optimization designs, classified according to trial objectives and endpoint types. Through computer simulations, we examine their operating characteristics and discuss the relevant statistical and design considerations for effective dose optimization.

resultsPhase II/III dose-optimization designs are capable of controlling family-wise type I error rates and achieving appropriate statistical power with substantially smaller sample sizes than the conventional approach while also reducing the number of patients who experience toxicity. Depending on the design and scenario, the sample size savings range from 16.6% to 27.3%, with a mean savings of 22.1%.

conclusionsPhase II/III dose-optimization designs offer an efficient way to reduce sample sizes for dose optimization and accelerate the development of targeted agents. However, because of interim dose selection, the phase II/III dose-optimization design presents logistical and operational challenges and requires careful planning and implementation to ensure trial integrity.

Indexed as

Clinical Trials, Phase II as TopicClinical Trials, Phase III as TopicResearch DesignAntineoplastic AgentsComputer SimulationDrug DevelopmentHumansSample SizeAntineoplastic Agents

Identifiers

PMID37243720
PMCPMC10483325
OpenAlexW4378530354

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.