BMC cancer · 2025
Prediction of the 70-gene signature (MammaPrint) high versus low risk by nomograms among axillary lymph node positive (LN+) and negative (LN-) Chinese breast cancer patients, a retrospective study.
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Lian Jie, Yao Ru, Xu Ying, Tan Linjuan, Chen Fangyuan, Zhang Jiahui, Qu Yang, Gao Lu, Zhang Yanna, Shen Songjie, Zhu Qingli, Ren Xinyu, Kong Lingyan, Pan Bo, Sun Qiang, Zhou Yidong
Аннотация
BACKGROUND: Luminal-type breast cancer (BC) was characterized as hormonal receptor positive human epidermal receptor 2 negative (HR+/HER2-). The 70-gene signature (70-GS, MammaPrint) test is recommended for assessing recurrence risk and guiding adjuvant chemotherapy decisions for Luminal-type BC. This study updates previously established nomogram models to predict binary 70-GS risk for lymph node positive (LN+) and lymph node negative (LN-) luminal-type BC patients.
METHODS: This retrospective study included 301 consecutive female patients with HR+/HER2- BC treated at Peking Union Medical College Hospital from November 2019 to December 2023. Patients' medical history, imaging reports, and clinicopathological features were reviewed. Forty risk parameters were compared between 70-GS high and low-risk patients among LN + and LN- groups. High risk stratification criterion in MonarchE and Natalee were compared between low and high 70-GS risk for the first time. Logistic regression was utilized to establish nomogram models predicting binary 70-GS risk for LN + and LN- patients. The models' prediction performance was evaluated utilizing accuracy, AUC of ROC curves, C-index, calibration curves, and decision curve analysis.
RESULTS: Significant differences were found between 70-GS high and low-risk patients in both LN + and LN- groups. Among LN + patients, parameters including childbirth number (p = 0.024), cardiovascular diseases (p = 0.037), US min. diameter of tumor (p = 0.034), Ki67 index (p < 0.001) and PR positivity (p = 0.007) were significant predictors. Among LN- patients, micro-calcifications (p = 0.011), PR positivity (p = 0.021), and Ki67 index (p < 0.001) were significant. The nomogram models showed high predictive accuracy, with AUC of 0.948 in the training set (C-index 0.948, 0.914-0.982, accuracy 0.907) and 0.923 in the testing set (C-index 0.923, 0.919-0.927, accuracy 0.828) for LN + patients and 0.917 in the training set (C-index 0917, 0.861-0.972, accuracy 0.870) and 0.917 in the testing sets (C-index 0917, 0.912-0.922, accuracy 0.808) among LN- patients. Calibration and decision curve analyses confirmed model reliability and clinical utility.
CONCLUSIONS: The updated nomogram models for predicting 70-GS risk in LN + and LN- luminal-type BC patients demonstrated improved prediction performance. The models facilitate individualized risk assessment and treatment decision-making, emphasizing tailored approaches based on lymph node status.
METHODS: This retrospective study included 301 consecutive female patients with HR+/HER2- BC treated at Peking Union Medical College Hospital from November 2019 to December 2023. Patients' medical history, imaging reports, and clinicopathological features were reviewed. Forty risk parameters were compared between 70-GS high and low-risk patients among LN + and LN- groups. High risk stratification criterion in MonarchE and Natalee were compared between low and high 70-GS risk for the first time. Logistic regression was utilized to establish nomogram models predicting binary 70-GS risk for LN + and LN- patients. The models' prediction performance was evaluated utilizing accuracy, AUC of ROC curves, C-index, calibration curves, and decision curve analysis.
RESULTS: Significant differences were found between 70-GS high and low-risk patients in both LN + and LN- groups. Among LN + patients, parameters including childbirth number (p = 0.024), cardiovascular diseases (p = 0.037), US min. diameter of tumor (p = 0.034), Ki67 index (p < 0.001) and PR positivity (p = 0.007) were significant predictors. Among LN- patients, micro-calcifications (p = 0.011), PR positivity (p = 0.021), and Ki67 index (p < 0.001) were significant. The nomogram models showed high predictive accuracy, with AUC of 0.948 in the training set (C-index 0.948, 0.914-0.982, accuracy 0.907) and 0.923 in the testing set (C-index 0.923, 0.919-0.927, accuracy 0.828) for LN + patients and 0.917 in the training set (C-index 0917, 0.861-0.972, accuracy 0.870) and 0.917 in the testing sets (C-index 0917, 0.912-0.922, accuracy 0.808) among LN- patients. Calibration and decision curve analyses confirmed model reliability and clinical utility.
CONCLUSIONS: The updated nomogram models for predicting 70-GS risk in LN + and LN- luminal-type BC patients demonstrated improved prediction performance. The models facilitate individualized risk assessment and treatment decision-making, emphasizing tailored approaches based on lymph node status.