A nomogram integrating DCE-MRI imaging features and clinicopathological parameters for predicting pathological complete response in HER2-positive breast cancer - Report - MDSpire

A nomogram integrating DCE-MRI imaging features and clinicopathological parameters for predicting pathological complete response in HER2-positive breast cancer

  • By

  • Jianlong Wu

  • Bo Gao

  • Jingna Wu

  • Zhongsheng Peng

  • Min Ye

  • Changyou Zhong

  • Mengxia Zhuang

  • Jinfeng Zhang

  • June 24, 2026

  • 0 min

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Clinical Report: Predictive Nomogram for pCR in HER2-Positive Breast Cancer

Overview

This study developed and validated a nomogram that combines DCE-MRI imaging characteristics and clinicopathological factors to predict pathological complete response (pCR) in HER2-positive breast cancer patients undergoing neoadjuvant chemotherapy. The nomogram showed an AUC of 0.823 in the training cohort and 0.795 in the validation cohort.

Background

HER2-positive breast cancer accounts for 15-20% of all breast cancer cases and is associated with aggressive behavior and poorer prognosis. Neoadjuvant chemotherapy (NAC) is standard treatment, with pCR serving as a key prognostic indicator.

Data Highlights

ParameterValue
Overall pCR Rate44.6% (74/166)
pCR Rate HR-/HER2+52.2%
pCR Rate HR+/HER2+38.5%
AUC Training Cohort0.823 (95% CI: 0.754-0.892)
AUC Validation Cohort0.795 (95% CI: 0.691-0.899)

Key Findings

  • The overall pCR rate was 44.6% among evaluable patients.
  • HR-/HER2+ patients had a significantly higher pCR rate (52.2%) compared to HR+/HER2+ patients (38.5%, P = 0.048).
  • Independent predictors of pCR included ADCmin value, Ki-67 index, tumor size, clinical N stage, and HR status.
  • The nomogram showed excellent discrimination with AUC values of 0.823 and 0.795 in training and validation cohorts, respectively.
  • Calibration plots indicated good agreement (Hosmer-Lemeshow P = 0.412).

Clinical Implications

The nomogram developed in this study can assist clinicians in predicting pCR in HER2-positive breast cancer patients receiving NAC.

Conclusion

The integration of DCE-MRI features with clinicopathological parameters in a nomogram provides a predictive tool for assessing pCR in HER2-positive breast cancer patients.

Related Resources & Content

  1. Frontiers in Oncology, 2026 -- Multiparametric MRI-based nomogram integrating clinicopathological factors for predicting HER2 expression status in breast cancer
  2. European Radiology, 2024 -- The Role of Diffusion-Weighted Imaging Combined with Contrast-Enhanced MRI in Assessing Complete Response in HER2-Positive Breast Cancer
  3. Archives of Gynecology and Obstetrics, 2026 -- The predictive role of Ki67 in pathological complete response (pCR) and invasive disease-free survival (IDFS) in HER2-positive breast cancer: a bi-centric retrospective cohort study of 244 cases
  4. ASCO Selection of Optimal Adjuvant Chemotherapy and Targeted Therapy for Early Breast Cancer Guideline Summary - Guideline Central
  5. Assessing Predictive Factors for Pathological Complete Response Following Neoadjuvant Chemoradiotherapy in Rectal Cancer: Insights Beyond Morphological MRI Analysis
  6. ASCO Selection of Optimal Adjuvant Chemotherapy and Targeted Therapy for Early Breast Cancer Guideline Summary - Guideline Central
  7. Biomarker analysis of the NeoSphere study: pertuzumab, trastuzumab, and docetaxel versus trastuzumab plus docetaxel, pertuzumab plus trastuzumab, or pertuzumab plus docetaxel for the neoadjuvant treatment of HER2-positive breast cancer - PMC
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