Evidence map›Paper›PMID 34473708›Full record

ArticlePloS one2021

phase1RMD: An R package for repeated measures dose-finding designs with novel toxicity and efficacy endpoints.

Jun Yin, Yu Du, Rui Qin, Shihao Shen, Sumithra Mandrekar

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Trial
  2. Applications of artificial intelligence in nuclear medicine.Zeitschrift fur medizinische Physik · 2026
    Review
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

5 authors.

Jun YinDepartment of Health Sciences Research, Mayo Clinic, Rochester, MN, United States of America.ORCID 0000-0003-3242-9664
Yu DuStatistics-Diabetes/Endocrine, Eli Lilly and Company, Indianapolis, IN, United States of America.
Rui QinClinical Biostatistics, Janssen Research and Development, Raritan, NJ, United States of America.
Shihao ShenData Science & Biostatistics, DermBiont, Boston, MA, United States of America.
Sumithra MandrekarDepartment of Health Sciences Research, Mayo Clinic, Rochester, MN, United States of America.

Funding

Women's Cancer ProgramP30CA015083 · NCI · MAYO CLINIC ROCHESTER · PI Felicity Enders · 1985 to 2026
$151.3M
Methodology for development, validation, and use of novel endpoints in oncologyR01CA174779 · NCI · MAYO CLINIC ROCHESTER · PI MANDREKAR, SUMITHRA JAY · 2014 to 2017
$1.2M
NCI NIH HHS P30 CA015083NCI NIH HHS R01 CA174779
6 · The paper itself

Abstract

Traditional dose-finding designs are substantially inefficient for targeted agents and cancer immunotherapies by failing to incorporate efficacy signals, mild and moderate adverse events, and late, cumulative toxicities. However, the lack of user-friendly software is a barrier to the practical use of the novel phase I designs, despite their demonstrated superiority of traditional 3+3 designs. To overcome these barriers, we present an R package, phase1RMD, which provides a comprehensive implementation of novel designs with repeated toxicity measures and early efficacy. A novel phase I repeated measures design that used a continuous toxicity score from multiple treatment cycles was implemented. Furthermore, in studies where preliminary efficacy is evaluated, an adaptive, multi-stage design to identify the most efficacious dose with acceptable toxicity was demonstrated. Functions are provided to recommend the next dose based on the data collected in a phase I trial, as well as to assess trial characteristics given design parameters via simulations. The repeated measure designs accurately estimated both the magnitude and direction of toxicity trends in late treatment cycles, and allocated more patients at therapeutic doses. The R package for implementing these designs is available from the Comprehensive R Archive Network. To our best knowledge, this is the first software that implement novel phase I dose-finding designs that simultaneously accounts for the multiple-grade toxicity events over multiple treatment cycles and a continuous early efficacy outcome. With the software published on CRAN, we will pursue the implementation of these designs in phase I trials in real-life settings.

Indexed as

Models, StatisticalSoftwareAntineoplastic AgentsClinical Trials as TopicDrug Dosage CalculationsHumansMaximum Tolerated DoseNeoplasmsRandomized Controlled Trials as TopicResearch DesignAntineoplastic Agents

Identifiers

PMID34473708
PMCPMC8412295

What OpenQuestion holds

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Registered trials

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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.