Evidence map›Paper›PMID 34716780›Full record

ArticleEuropean radiology2022

Pre-treatment MRI tumor features and post-treatment mammographic findings: may they contribute to refining the prediction of pathologic complete response in post-neoadjuvant breast cancer patients with radiologic complete response on MRI?

Bruna M Thompson, Luciano F Chala, Carlos Shimizu, Max S Mano, José R Filassi, Felipe C Geyer, Ulysses S Torres, Giselle Guedes Netto de Mello, Cláudia da Costa Leite

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Article in European radiology, 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
1.0field-weighted citation impact, top 27% 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, 16 citations in OpenAlex.

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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 4 institutions in 1 country.

Bruna M ThompsonInstitute of Radiology, Clinics Hospital, School of Medicine, University of São Paulo, São Paulo, Brazil.
Luciano F ChalaFleury Group, Rua Cincinato Braga, 282, Bela Vista, São Paulo, SP, 01333-010, Brazil.
Carlos ShimizuInstitute of Radiology, Clinics Hospital, School of Medicine, University of São Paulo, São Paulo, Brazil.
Max S ManoDepartment of Oncology, Hospital Sírio Libanês, São Paulo, Brazil.
José R FilassiDepartment of Gynecology and Obstetrics, Mastology Section, Instituto Do Câncer Do Estado de São Paulo, São Paulo, Brazil.
Felipe C GeyerDepartment of Pathology, Instituto Do Câncer Do Estado de São Paulo, São Paulo, Brazil.
Ulysses S TorresFleury Group, Rua Cincinato Braga, 282, Bela Vista, São Paulo, SP, 01333-010, Brazil. ulysses.torres@grupofleury.com.br.ORCID http://orcid.org/0000-0002-1911-9090
Giselle Guedes Netto de MelloFleury Group, Rua Cincinato Braga, 282, Bela Vista, São Paulo, SP, 01333-010, Brazil.
Cláudia da Costa LeiteInstitute of Radiology, Clinics Hospital, School of Medicine, University of São Paulo, São Paulo, Brazil.
Fleury S.A. (Brazil) · BRUniversidade de São Paulo · BRInstituto do Câncer do Estado de São Paulo · BRHospital Sírio-Libanês · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeRadiologic complete response (rCR) in breast cancer patients after neoadjuvant chemotherapy (NAC) does not necessarily correlate with pathologic complete response (pCR), a marker traditionally associated with better outcomes. We sought to verify if data extracted from two important steps of the imaging workup (tumor features at pre-treatment MRI and post-treatment mammographic findings) might assist in refining the prediction of pCR in post-NAC patients showing rCR.

methodsA total of 115 post-NAC women with rCR on MRI (2010-2016) were retrospectively assessed. Pre-treatment MRI (lesion morphology, size, and distribution) and post-treatment mammographic findings (calcification, asymmetry, mass, architectural distortion) were assessed, as well as clinical and molecular variables. Bivariate and multivariate analyses evaluated correlation between such variables and pCR. Post-NAC mammographic findings and their correlation with ductal in situ carcinoma (DCIS) were evaluated using Pearson's correlation.

resultsTumor distribution at pre-treatment MRI was the only significant predictive imaging feature on multivariate analysis, with multicentric lesions having lower odds of pCR (p = 0.035). There was no significant association between tumor size and morphology with pCR. Mammographic residual calcifications were associated with DCIS (p = 0.009). The receptor subtype remained as a significant predictor, with HR-HER2 + and triple-negative status demonstrating higher odds of pCR on multivariate analyses.

conclusionsMulticentric lesions on pre-NAC MRI were associated with a lower chance of pCR in post-NAC rCR patients. The receptor subtype remained a reliable predictor of pCR. Residual mammographic calcifications correlated with higher odds of malignancy, making the correlation between mammography and MRI essential for surgical planning. Key Points • The presence of a multicentric lesion on pre-NAC MRI, even though the patient reaches a radiologic complete response on MRI, is associated with a lower chance of pCR. • Molecular status of the tumor remained the only significant predictor of pathologic complete response in such patients in the present study. • Post-neoadjuvant residual calcifications found on mammography were related to higher odds of residual malignancy, making the correlation between mammography and MRI essential for surgical planning.

Indexed as

Breast NeoplasmsNeoadjuvant TherapyChemotherapy, AdjuvantFemaleHumansMagnetic Resonance ImagingMammographyRetrospective StudiesBreast cancerMagnetic resonance imagingMammographyPathologic complete responseRadiologic complete response

Identifiers

PMID34716780
OpenAlexW3210574527

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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.