Evidence map›Paper›PMID 33130879›Full record

ReviewNeuro-oncology2021

Radiographic read paradigms and the roles of the central imaging laboratory in neuro-oncology clinical trials.

Benjamin M Ellingson, Matthew S Brown, Jerrold L Boxerman, Elizabeth R Gerstner, Timothy J Kaufmann, Patricia E Cole, Jeffrey A Bacha, David Leung, Amy Barone, Howard Colman and 5 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Neuro-oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

15 authors.

Benjamin M EllingsonUCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California, USA.
Matthew S BrownUCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California, USA.
Jerrold L BoxermanDepartment of Diagnostic Imaging, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.
Elizabeth R GerstnerDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Timothy J KaufmannDepartment of Radiology, Mayo Clinic, Rochester, Minnesota, USA.
Patricia E ColeBayer Pharmaceuticals, Whippany, New Jersey, USA.
Jeffrey A BachaEdison Oncology Holding Corp, London, UK.
David LeungBristol Myers Squibb, New York, New York, USA.
Amy BaroneUS Food and Drug Administration, Silver Spring, Maryland, USA.
Howard ColmanHuntsman Cancer Institute, University of Utah, Salt Lake City, Utah, USA.
Martin J van den BentDepartment of Neuro-Oncology, Erasmus Medical Center Cancer Institute, Rotterdam, Netherlands.
Patrick Y WenCenter for Neuro-Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, USA.
W K Alfred YungThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Timothy F CloughesyUCLA Neuro-Oncology Program, University of California Los Angeles, Los Angeles, California, USA.
Jonathan G GoldinUCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California, USA.

Funding

Targeting the Vasular SystemP50CA165962 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI WENDY Beth LONDON · 2013 to 2026
$33.5M
UCLA SPORE in Brain CancerP50CA211015 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Yvonne Yu-Hsuan Chen · 2017 to 2026
$25.2M
EPA EP-C-15-003NCI NIH HHS P50 CA165962NCI NIH HHS P50 CA211015
6 · The paper itself

Abstract

Determination of therapeutic benefit in intracranial tumors is intimately dependent on serial assessment of radiographic images. The Response Assessment in Neuro-Oncology (RANO) criteria were established in 2010 to provide an updated framework to better characterize tumor response to contemporary treatments. Since this initial update a number of RANO criteria have provided some basic principles for the interpretation of changes on MR images; however, the details of how to operationalize RANO and other criteria for use in clinical trials are ambiguous and not standardized. In this review article designed for the neuro-oncologist or treating clinician, we outline essential steps for performing radiographic assessments by highlighting primary features of the Imaging Charter (referred to as the Charter for the remainder of this article), a document that describes the clinical trial imaging methodology and methods to ensure operationalization of the Charter into the workings of a clinical trial. Lastly, we provide recommendations for specific changes to optimize this methodology for neuro-oncology, including image registration, requirement of growing tumor for eligibility in trials of recurrent tumor, standardized image acquisition guidelines, and hybrid reader paradigms that allow for both unbiased measurements and more comprehensive interpretation.

Indexed as

Brain NeoplasmsLaboratoriesDiagnostic ImagingHumansclinical trialsImaging Charterimaging endpointsneuro-oncologyRANO

Identifiers

PMID33130879
PMCPMC7906061

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.