Nomogram for Predicting Pathological Complete Response after Neoadjuvant Chemotherapy in Operable Primary Breast Cancer

Yanli Lv; Weimin Mu; Qingzhong Yang; Huiying Xu; Baochen Jin; Yi Li

doi:10.29271/jcpsp.2025.03.324

Author(s)

Yanli Lv Breast Centre, Shunyi District Health Care Hospital for Women and Children of Beijing,Beijing,China

Weimin Mu Breast Centre, Shunyi District Health Care Hospital for Women and Children of Beijing,Beijing,China

Qingzhong Yang Breast Centre, Shunyi District Health Care Hospital for Women and Children of Beijing,Beijing,China

Huiying Xu Breast Centre, Shunyi District Health Care Hospital for Women and Children of Beijing,Beijing,China

Baochen Jin Breast Centre, Shunyi District Health Care Hospital for Women and Children of Beijing,Beijing,China

Yi Li Breast Centre, Shunyi District Health Care Hospital for Women and Children of Beijing,Beijing,China

Abstract

Objective: To establish a predictive model for pathological complete response (pCR) in operable primary breast cancer after neoadjuvant chemotherapy (NAC). Study Design: Observational study. Place and Duration of the Study: Breast Centre, Shunyi District Health Care Hospital for Women and Children of Beijing, Beijing, China, from January 2010 to June 2023. Methodology: Four hundred and fourteen operable invasive breast cancer patients who received NAC were included in this study. After a random assignment at a ratio of 7:3, 289 patients in the training set were analysed for model building, and the remaining 125 patients in the test set were used for validation. The de nition of pCR was the absence of residual invasive disease in either the breasts or the axillary lymph nodes (ypT0 / is ypN0). After multivariate logistic regression analysis, a nomogram was drawn. In the validation phase, the receiver operating characteristic (ROC) curve and AUC were used for evaluation of discrimination, while the calibration plot and Hosmer-Lemeshow test for calibration. Additionally, a decision curve was drawn. Results: A model containing 8 variables, including BMI, tumour size, histological grade, HR, HER2, axilla status, chemotherapy cycles, and regimens was built. After validation, the model had moderate discriminatory power [AUC, 0.831; 95% CI (0.733, 0.928)]. Calibration curve and Hosmer-Lemeshow goodness of t (GOF) test (p = 0.1645) demonstrated that the model tted well. Meanwhile, the decision curve analysis revealed that the model was bene cial to patients. Conclusion: Model containing BMI, tumour size, histological grade, HR, HER2, axilla status, chemotherapy cycles, and regimens showed moderate discrimination and calibration abilities in predicting pCR.

Publication Details

Page(s) 324-330

DOI 10.29271/jcpsp.2025.03.324

Published Journal: Journal of College of Physicians and Surgeons--Pakistan : JCPSP, Volume: 35, Issue: 3, Year: 2025

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Keywords

Surgery, Neoadjuvant therapy, Pathology, Breast neoplasms, Nomogram

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