Evidence map›Paper›PMID 40842959›Full record

ArticleStatistics in biopharmaceutical research2025

Isotonic Phase I cancer clinical trial design utilizing patient-reported outcomes.

Nolan A Wages, Ruitao Lin

Abstract read
In one paragraph

Article in Statistics in biopharmaceutical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
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  5. Review
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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.

Nolan A WagesDepartment of Biostatistics, Virginia Commonwealth University, Richmond, Virginia, U.S.A.
Ruitao LinDepartment of Biostatistics, MD Anderson Cancer Center, Houston, Texas, U.S.A.

Funding

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
Dose finding designs for late-onset toxicitiesR01CA247932 · NCI · VIRGINIA COMMONWEALTH UNIVERSITY · PI WAGES, NOLAN · 2021 to 2023
$1.0M
NCI NIH HHS R01 CA247932NCI NIH HHS R01 CA261978
6 · The paper itself

Abstract

This article considers the concept of designing Phase I clinical trials using both clinician- and patient-reported outcomes to adaptively allocate study participants to tolerable doses and determine the maximum tolerated dose (MTD) at the study conclusion. We describe a new isotonic patient-reported outcome (PRO-ISO) Phase I design with the flexibility of allocating patients to lower, more tolerable regimens if a large number of PRO-DLT events are seen at higher doses. We conduct simulation studies of the operating characteristics of the design and compared them to the patient-reported outcomes continual reassessment method (PRO-CRM). We illustrate that the PRO-ISO makes appropriate dose assignments during the study to give investigators and reviewers an idea of how the method behaves. In simulation studies, the PRO-ISO demonstrates comparable performance to the PRO-CRM in terms of recommending target doses and allocating patients to these doses. It also performs well relative to a nonparametric optimal benchmark applied to the PRO setting. Finally, we extend our methodology to account for the problem of late-onset toxicities.

Indexed as

dose-findingisotonic regressionlate-onset toxicitypatient-reported outcomes

Identifiers

PMID40842959
PMCPMC12365655

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.