Evidence map›Paper›PMID 32527022›Full record

ReviewCancers2020

Current Landscape of Breast Cancer Imaging and Potential Quantitative Imaging Markers of Response in ER-Positive Breast Cancers Treated with Neoadjuvant Therapy.

Ella F Jones, Deep K Hathi, Rita Freimanis, Rita A Mukhtar, A Jo Chien, Laura J Esserman, Laura J Van't Veer, Bonnie N Joe, Nola M Hylton

Registry-linked trialOpen access · goldAbstract readReview
In one paragraph

Review in Cancers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04882371 (Comparison of MRI With PET / CT in the Evaluation of Response to Neoadjuvant Therapy Based on the Molecular Subtypes of Breast Cancer), which is not on this map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
0.9field-weighted citation impact, top 31% 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.

NCT04882371 completednot on this map

Comparison of MRI With PET / CT in the Evaluation of Response to Neoadjuvant Therapy Based on the Molecular Subtypes of Breast Cancer

TypeobservationalSponsorCem Ilgin ErolRan2018 to 2020Enrolled88ConditionsBreast Cancer, Chemotherapy EffectArmsChemotherapy, Magnetic Resonance Imaging (MRI), Positron emission tomography - Copmputer Tomography (PET-CT)
3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 17 citations in OpenAlex.

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  10. ZR-75-1 breast cancer models to study the utility ofTranslational cancer research · 2021
    Article
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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

9 authors at 1 institution in 1 country.

Ella F JonesDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94115, USA.ORCID 0000-0001-8700-2129
Deep K HathiDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94115, USA.
Rita FreimanisDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94115, USA.ORCID 0000-0001-5229-8687
Rita A MukhtarDepartment of Surgery, University of California, San Francisco, CA 94115, USA.
A Jo ChienSchool of Medicine, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA 94115, USA.
Laura J EssermanDepartment of Surgery, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA 94115, USA.
Laura J Van't VeerSchool of Medicine, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA 94115, USA.
Bonnie N JoeDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94115, USA.
Nola M HyltonDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94115, USA.
University of California, San Francisco · US

Funding

The I SPY 2.2 TRIAL: Evolving to Imaging and Molecular Biomarker Response Directed Adaptive Sequential Treatment to Optimize Breast Cancer OutcomesP01CA210961 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Nola M. Hylton-Watson · 2017 to 2026
$22.9M
Dedicated breast PET and MRI for characterization of breast cancer and its response to therapyR01CA227763 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Natsuko Onishi Yamashita · 2019 to 2026
$3.6M
Quantitative Imaging for Assessing Breast Cancer Response to TreatmentU01CA225427 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HYLTON-WATSON, NOLA M. · 2018 to 2022
$3.2M
Quantitative Imaging for Assessing Breast Cancer Response to TreatmentU01CA151235 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HYLTON-WATSON, NOLA M. · 2011 to 2015
$2.8M
NCI NIH HHS P01 CA210961NCI NIH HHS R01 CA227763NCI NIH HHS U01 CA151235NCI NIH HHS U01 CA225427NIH HHS R01CA227763U.S. Department of Defense BC17123
6 · The paper itself

Abstract

In recent years, neoadjuvant treatment trials have shown that breast cancer subtypes identified on the basis of genomic and/or molecular signatures exhibit different response rates and recurrence outcomes, with the implication that subtype-specific treatment approaches are needed. Estrogen receptor-positive (ER+) breast cancers present a unique set of challenges for determining optimal neoadjuvant treatment approaches. There is increased recognition that not all ER+ breast cancers benefit from chemotherapy, and that there may be a subset of ER+ breast cancers that can be treated effectively using endocrine therapies alone. With this uncertainty, there is a need to improve the assessment and to optimize the treatment of ER+ breast cancers. While pathology-based markers offer a snapshot of tumor response to neoadjuvant therapy, non-invasive imaging of the ER disease in response to treatment would provide broader insights into tumor heterogeneity, ER biology, and the timing of surrogate endpoint measurements. In this review, we provide an overview of the current landscape of breast imaging in neoadjuvant studies and highlight the technological advances in each imaging modality. We then further examine some potential imaging markers for neoadjuvant treatment response in ER+ breast cancers.

Indexed as

breast cancerestrogen receptor (ER)mammographyMRIneoadjuvant therapyPETquantitative imagingultrasoundX-ray

Identifiers

PMID32527022
PMCPMC7352259
OpenAlexW3035136416

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.