The value of a nomogram based on multi-parameter MRI for predicting the risk of postoperative recurrence in hormone receptor positive breast cancer
10.3760/cma.j.cn112149-20250228-00105
- VernacularTitle:基于多参数MRI列线图评估激素受体阳性型乳腺癌术后复发风险的价值
- Author:
Di KANG
1
;
Lihua ZHANG
;
Weixia TANG
;
Jinfeng QIAN
;
Tianle WANG
;
Meihong SHENG
Author Information
1. 南通大学第二附属医院 南通市第一人民医院影像科，南通 226001
- Publication Type:Journal Article
- Keywords:
Breast neoplasms;
Magnetic resonance imaging;
Recurrence;
Nomogram
- From:
Chinese Journal of Radiology
2025;59(10):1155-1162
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the value of a multi-parameter MRI nomogram model in evaluating the recurrence risk of hormone receptor (HR)-positive breast cancer.Methods:This study was a retrospective cross-sectional study. A retrospective analysis was conducted on the clinicopathological data (age, menopausal status, axillary lymph node metastasis, etc.) and imaging data of 220 patients with HR-positive breast cancer who underwent breast MRI examination and were pathologically confirmed at the Second Affiliated Hospital of Nantong University from January 2018 to December 2023. All patients underwent preoperative MRI examinations. Their MRI features were analyzed, and the maximum diameter of the lesion and the apparent diffusion coefficient (ADC) value were measured. Finally, the clinical treatment score (CTS5 score) after 5 years was calculated, and all patients were divided into a low recurrence risk (CTS5 score 3.13 points) and a medium to high recurrence risk (CTS5 score≥3.13 points) group. The patients were followed up through the electronic medical record system or by phone until December 31, 2024 to determine recurrence status. The patients were divided into the recurrence group and the non-recurrence group. The differences in clinicopathological data, MRI features and CTS5 scores between the recurrence group and the non-recurrence group were compared using independent sample t-tests, Mann-Whitney U tests or χ2 tests. Indicators with P0.05 in the univariate analysis were included in the multivariate logistic regression to screen the independent risk factors for predicting the recurrence of HR receptor-positive breast cancer, and a nomogram was constructed to establish the nomogram model. The receiver operating characteristic curves and the area under the curve (AUC) were used to evaluate the efficacy of the nomogram model in predicting the postoperative recurrence risk of patients with HR-positive breast cancer. The variance inflation factor (VIF) was used to evaluate the multicollinearity among independent variables. Calibration curves and decision curve analysis (DCA) were used to assess the fit and net clinical benefit of the nomogram model. Results:Among 220 patients with HR-positive breast cancer, 196 cases were in the non-recurrence group and 24 cases were in the recurrence group. There were statistically significant differences in the maximum diameter of the lesion, axillary lymph node metastasis, ADC value, CTS5 grouping, and CTS5 score between the recurrence group and the non-recurrence group ( P0.05). Multivariate logistic regression analysis showed that the maximum diameter of the lesion ( OR=1.110, 95% CI 1.169-1.503, P0.001), ADC value ( OR=0.993, 95% CI 0.993?0.989, P0.001), and axillary lymph node metastasis ( OR=8.842; 95% CI 2.120?36.884, P=0.003) were independent factors influencing postoperative recurrence in patients with HR-positive breast cancer, and a nomogram model was constructed based on this. VIF analysis showed that no significant multicollinearity was detected among the variables (VIF5). The AUC value of the nomogram model for predicting postoperative recurrence in patients with HR-positive breast cancer was 0.868 (95% CI 0.794-0.942), the sensitivity was 0.875, and the specificity was 0.781. The calibration curve showed that the prediction curve of this model for predicting postoperative recurrence in HR-positive breast cancer patients was basically consistent with the ideal curve trend. DCA showed that this model had a relatively high clinical benefit within the threshold probability range of 0.01% to 90.00%. Conclusion:The nomogram constructed based on multi-parameter MRI features can predict the postoperative recurrence risk of HR-positive breast cancer patients, with good consistency and predictive ability.
