Evidence map›Paper›PMID 36494872›Full record

ArticleCancer imaging : the official publication of the International Cancer Imaging Society2022

Evaluation of pretreatment ADC values as predictors of treatment response to neoadjuvant chemotherapy in patients with breast cancer - a multicenter study.

Alexey Surov, Maciej Pech, Hans-Jonas Meyer, Almir G V Bitencourt, Hiroshi Fujimoto, Gabrielle C Baxter, Gorane Santamaría, Fiona J Gilbert, Andreas Wienke

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.3field-weighted citation impact, top 21% 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.

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

10 citing papers in PubMed, 12 citations in OpenAlex.

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  9. Histogram analysis of multiple diffusion models for predicting advanced non-small cell lung cancer response to chemoimmunotherapy.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024
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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 7 institutions in 5 countries.

Alexey SurovDepartment of Radiology and Nuclear Medicine, Otto von Guericke University, Magdeburg, Germany.
Maciej PechDepartment of Radiology and Nuclear Medicine, Otto von Guericke University, Magdeburg, Germany.
Hans-Jonas MeyerDepartment of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany. hans-jonas.meyer@medizin.uni-leipzig.de.ORCID http://orcid.org/0000-0001-8489-706X
Almir G V BitencourtDepartment of Imaging - A.C.Camargo Cancer Center, São Paulo, Brazil.
Hiroshi FujimotoDepartment of General Surgery, Chiba University Graduate, School of Medicine, 1-8-1 Inohana, Chuo-ku, Japan.
Gabrielle C BaxterDepartment of Radiology, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
Gorane SantamaríaDepartments of Radiology, Hospital Clínic de Barcelona, University of Barcelona Medical School, Barcelona, Spain.
Fiona J Gilbert *Department of Radiology, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
Andreas Wienke *Institute of Medical Epidemiology, Biostatistics, and Informatics, Martin-Luther-University Halle-Wittenberg, Halle, Germany.
Otto-von-Guericke-Universität Magdeburg · DEUniversity of Cambridge · GBAC Camargo Hospital · BRChiba University · JPHospital Clínic de Barcelona · ESMartin Luther University Halle-Wittenberg · DEUniversity Hospital Leipzig · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMagnetic resonance imaging (MRI) can be used to diagnose breast cancer. Diffusion weighted imaging (DWI) and the apparent diffusion coefficient (ADC) can reflect tumor microstructure in a non-invasive manner. The correct prediction of response of neoadjuvant chemotherapy (NAC) is crucial for clinical routine. Our aim was to compare ADC values between patients with pathological complete response (pCR) and non-responders based upon a multi-center design to improve the correct patient selection, which patient would more benefit from NAC and which patient would not.

methodsFor this study, data from 4 centers (from Japan, Brazil, Spain and United Kingdom) were retrospectively acquired. The time period was overall 2003-2019. The patient sample comprises 250 patients (all female; median age, 50.5). In every case, pretreatment breast MRI with DWI was performed. pCR was assessed by experienced pathologists in every center using the surgical specimen in the clinical routine work up. pCR was defined as no residual invasive disease in either breast or axillary lymph nodes after NAC. ADC values between the group with pCR and those with no pCR were compared using the Mann-Whitney U test (two-group comparisons). Univariable and multivariabe logistic regression analysis was performed to predict pCR status.

resultsOverall, 83 patients (33.2%) achieved pCR. The ADC values of the patient group with pCR were lower compared with patients without pCR (0.98 ± 0.23 × 10

conclusionsThe pretreatment ADC-value is associated with pathological complete response after NAC in breast cancer patients. This could aid in clinical routine to reduce treatment toxicity for patients, who would not benefit from NAC. However, this must be tested in further studies, as the overlap of the ADC values in both groups is too high for clinical prediction.

Indexed as

Breast NeoplasmsNeoadjuvant TherapyDiffusion Magnetic Resonance ImagingFemaleHumansMiddle AgedRetrospective StudiesTreatment OutcomeADCBreast cancerDWINeoadjuvant treatment

Identifiers

PMID36494872
PMCPMC9733082
OpenAlexW4311664375

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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.