Evidence map›Paper›PMID 38706611›Full record

ArticleFrontiers in oncology2024

Quantitative ultrasound radiomics guided adaptive neoadjuvant chemotherapy in breast cancer: early results from a randomized feasibility study.

Archya Dasgupta, Daniel DiCenzo, Lakshmanan Sannachi, Sonal Gandhi, Rossana C Pezo, Andrea Eisen, Ellen Warner, Frances C Wright, Nicole Look-Hong, Ali Sadeghi-Naini and 4 more

Registry-linked trialAbstract read
In one paragraph

Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04050228 (A Phase II Study of Quantitative Ultrasound to Guide Adaptive Chemotherapy Among Women With Locally Advanced Breast Cancer), which is not on this map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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.

NCT04050228 narecruitingnot on this map

A Phase II Study of Quantitative Ultrasound to Guide Adaptive Chemotherapy Among Women With Locally Advanced Breast Cancer (LABC)

TypeinterventionalSponsorSunnybrook Health Sciences CentreRan2018 to 2029Enrolled240ConditionsBreast CancerArmsQuantitative ultrasound to guide adaptive chemotherapy
3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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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

14 authors.

Archya DasguptaDepartment of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
Daniel DiCenzoPhysical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada.
Lakshmanan SannachiPhysical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada.
Sonal GandhiDivision of Medical Oncology, Department of Medicine, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
Rossana C PezoDivision of Medical Oncology, Department of Medicine, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
Andrea EisenDivision of Medical Oncology, Department of Medicine, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
Ellen WarnerDivision of Medical Oncology, Department of Medicine, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
Frances C WrightDepartment of Surgical Oncology, Department of Surgery, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
Nicole Look-HongDepartment of Surgical Oncology, Department of Surgery, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
Ali Sadeghi-NainiDepartment of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
Belinda CurpenDepartment of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
Michael C KoliosDepartment of Physics, Ryerson University, Toronto, ON, Canada.
Maureen TrudeauDivision of Medical Oncology, Department of Medicine, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
Gregory J CzarnotaDepartment of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In patients with locally advanced breast cancer (LABC) receiving neoadjuvant chemotherapy (NAC), quantitative ultrasound (QUS) radiomics can predict final responses early within 4 of 16-18 weeks of treatment. The current study was planned to study the feasibility of a QUS-radiomics model-guided adaptive chemotherapy. Methods: The phase 2 open-label randomized controlled trial included patients with LABC planned for NAC. Patients were randomly allocated in 1:1 ratio to a standard arm or experimental arm stratified by hormonal receptor status. All patients were planned for standard anthracycline and taxane-based NAC as decided by their medical oncologist. Patients underwent QUS imaging using a clinical ultrasound device before the initiation of NAC and after the 1 Results: Between June 2018 and July 2021, 60 patients were accrued in the study arm, with 28 patients in each arm available for final analysis. In patients without a change in chemotherapy regimen (53 of 56 patients total), the QUS-radiomics model at week 4 of NAC that was used demonstrated an accuracy of 97%, respectively, in predicting the final treatment response. Seven patients were predicted to be non-responders (observational arm (n=2), experimental arm (n=5)). Three of 5 non-responders in the experimental arm had chemotherapy regimens adapted with an early initiation of taxane therapy or chemotherapy intensification, or early surgery and ended up as responders on final evaluation. Conclusion: The study demonstrates the feasibility of QUS-radiomics adapted guided NAC for patients with breast cancer. The ability of a QUS-based model in the early prediction of treatment response was prospectively validated in the current study. Clinical trial registration: clinicaltrials.gov, ID NCT04050228.

Indexed as

adaptive chemotherapyartificial intelligencebreast cancerneoadjuvant chemotherapyquantitative ultrasound (QUS)radiomics

Identifiers

PMID38706611
PMCPMC11066296

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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.