Evidence map›Paper›PMID 42317098›Full record

ArticleEuropean journal of breast health2026

Interim Breast MRI for Predicting Pathologic Complete Response After Neoadjuvant Chemotherapy in Early Breast Cancer.

Eri Kato, Hideo Shigematsu, Ai Amioka, Shinsuke Sasada, Takayuki Kadoya, Morihito Okada

Abstract read
In one paragraph

Article in European journal of breast health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Eri KatoDepartment of Surgical Oncology, Hiroshima University, Research Institute for Radiation Biology and Medicine, Hiroshima, Japan.ORCID 0009-0006-7628-2886
Hideo ShigematsuDepartment of Surgical Oncology, Hiroshima University, Research Institute for Radiation Biology and Medicine, Hiroshima, Japan.ORCID 0009-0005-5568-2330
Ai AmiokaDepartment of Surgical Oncology, Hiroshima University, Research Institute for Radiation Biology and Medicine, Hiroshima, Japan.ORCID 0009-0009-0840-8282
Shinsuke SasadaDepartment of Surgical Oncology, Hiroshima University, Research Institute for Radiation Biology and Medicine, Hiroshima, Japan.ORCID 0009-0000-4867-7123
Takayuki KadoyaDepartment of Surgical Oncology, Hiroshima University, Research Institute for Radiation Biology and Medicine, Hiroshima, Japan.ORCID 0000-0003-1532-174X
Morihito OkadaDepartment of Surgical Oncology, Hiroshima University, Research Institute for Radiation Biology and Medicine, Hiroshima, Japan.ORCID 0000-0001-7383-6763

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Accurate prediction of pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) is essential for treatment decision-making in breast cancer. The value of integrated prediction models combining interim magnetic resonance imaging (MRI) findings with clinicopathological factors remains uncertain. This study aimed to compare interim and post-NAC MRI in predicting pCR and to assess the performance of prediction models integrating MRI and clinicopathological variables. Materials and Methods: We retrospectively analyzed 249 patients with early-stage breast cancer who underwent MRI before, during (interim), and after NAC. Clinicopathological variables were selected via stepwise regression based on the minimum Akaike information criterion. Four predictive models were developed: Model A used clinicopathological variables alone; Model B added interim MRI; Model C added post-NAC MRI; and Model D incorporated both interim and post-NAC MRI. Model performance was assessed using receiver operating characteristic curve analysis, calibration plots, and decision curve analysis. Results: Sixty-two (25%) patients achieved pCR. Independent predictors in Model A included hormone receptor status, human epidermal growth factor receptor 2 status, and clinical tumor size. The areas under the curves were 0.721 (Model A), 0.819 (Model B), 0.847 (Model C), and 0.848 (Model D). Model B (interim MRI) demonstrated the highest sensitivity (0.99) and negative predictive value (0.97), enabling early identification of pCR, while Models C and D showed only modest improvements. In decision curve analysis, calibration and clinical utility were superior in models incorporating MRI compared with Model A. Conclusion: Interim MRI demonstrated pCR-predictive performance comparable to that of post-NAC MRI, supporting its potential utility as a clinically meaningful tool for early treatment decision-making. However, its relatively high false-positive rate suggests that caution is warranted when applying it to guide surgical de-escalation.

Indexed as

Breast neoplasmsmagnetic resonance imagingneoadjuvant therapypathologic complete responsepredictive value of tests

Identifiers

PMID42317098
PMCPMC13280616

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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.