Evidence map›Paper›PMID 37725573›Full record

ReviewClinical cancer research : an official journal of the American Association for Cancer Research2023

Novel Clinical Trial Designs with Dose Optimization to Improve Long-term Outcomes.

Peter F Thall, Yong Zang, Andrew G Chapple, Ying Yuan, Ruitao Lin, David Marin, Pavlos Msaouel

Abstract readReview
In one paragraph

Review in Clinical cancer research : an official journal of the American Association for Cancer Research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Panitumumab-Based EGFR Blockade in SMARCB1-Deficient Renal Medullary Carcinoma: Preclinical Basis and Prospective Clinical Activity.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026
    Article
  3. AI-based augmentation of oncology clinical trials.Nature reviews. Clinical oncology · 2026
    Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. 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

7 authors.

Peter F ThallDepartment of Biostatistics, MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0002-7293-529X
Yong ZangDepartment of Biostatistics and Health Data Science, Center for Computational Biology, and Bioinformatics, School of Medicine, Indiana University, Indianapolis, Indiana.ORCID 0000-0003-0572-4756
Andrew G ChappleDepartment of Interdisciplinary Oncology, School of Medicine, LSU Health Sciences Center, New Orleans.ORCID 0000-0001-5332-2730
Ying YuanDepartment of Biostatistics, MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0003-3163-480X
Ruitao LinDepartment of Biostatistics, MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0003-2244-131X
David MarinDepartment of Stem Cell Transplantation and Cellular Therapy, MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0003-0812-9346
Pavlos MsaouelDepartment of Genitourinary Medical Oncology, MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0001-6505-8308

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Fabien Delerue · 1985 to 2026
$290.8M
THE THERAPY OF AMLP01CA055164 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI BERRY, DONALD A · 1992 to 2011
$25.3M
Bayesian Methods for Complex Precision Biotherapy Trials in OncologyR01CA261978 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LIN, RUITAO, THALL, PETER F · 2021 to 2024
$1.4M
NCI NIH HHS P01 CA055164NCI NIH HHS P30 CA016672NCI NIH HHS R01 CA261978
6 · The paper itself

Abstract

Conventional designs for choosing a dose for a new therapy may select doses that are unsafe or ineffective and fail to optimize progression-free survival time, overall survival time, or response/remission duration. We explain and illustrate limitations of conventional dose-finding designs and make four recommendations to address these problems. When feasible, a dose-finding design should account for long-term outcomes, include screening rules that drop unsafe or ineffective doses, enroll an adequate sample size, and randomize patients among doses. As illustrations, we review three designs that include one or more of these features. The first illustration is a trial that randomized patients among two cell therapy doses and standard of care in a setting where it was assumed on biological grounds that dose toxicity and dose-response curves did not necessarily increase with cell dose. The second design generalizes phase I-II by first identifying a set of candidate doses, rather than one dose, randomizing additional patients among the candidates, and selecting an optimal dose to maximize progression-free survival over a longer follow-up period. The third design combines a phase I-II trial and a group sequential randomized phase III trial by using survival time data available after the first stage of phase III to reoptimize the dose selected in phase I-II. By incorporating one or more of the recommended features, these designs improve the likelihood that a selected dose or schedule will be optimal, and thus will benefit future patients and obtain regulatory approval.

Indexed as

Research DesignClinical Trials as TopicClinical Trials, Phase III as TopicHumansProbabilityRandomized Controlled Trials as Topic

Identifiers

PMID37725573
PMCPMC10841062

What OpenQuestion holds

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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.