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Predicting Pathological Complete Response in Breast Cancer After Two Cycles of Neoadjuvant Chemotherapy by Tumor Reduction Rate: A Retrospective Case-Control Study.
Journal of Breast Cancer 2023 April
PURPOSE: We aimed to identify effectiveness-associated indicators and evaluate the optimal tumor reduction rate (TRR) after two cycles of neoadjuvant chemotherapy (NAC) in patients with invasive breast cancer.
METHODS: This retrospective case-control study included patients who underwent at least four cycles of NAC at the Department of Breast Surgery between February 2013 and February 2020. A regression nomogram model for predicting pathological responses was constructed based on potential indicators.
RESULTS: A total of 784 patients were included, of whom 170 (21.68%) reported pathological complete response (pCR) after NAC and 614 (78.32%) had residual invasive tumors. The clinical T stage, clinical N stage, molecular subtype, and TRR were identified as independent predictors of pCR. Patients with a TRR > 35% were more likely to achieve pCR (odds ratio, 5.396; 95% confidence interval [CI], 3.299-8.825). The receiver operating characteristic (ROC) curve was plotted using the probability value, and the area under the ROC curve was 0.892 (95% CI, 0.863-0.922).
CONCLUSION: TRR > 35% is predictive of pCR after two cycles of NAC, and an early evaluation model using a nomogram based on five indicators, age, clinical T stage, clinical N stage, molecular subtype, and TRR, is applicable in patients with invasive breast cancer.
METHODS: This retrospective case-control study included patients who underwent at least four cycles of NAC at the Department of Breast Surgery between February 2013 and February 2020. A regression nomogram model for predicting pathological responses was constructed based on potential indicators.
RESULTS: A total of 784 patients were included, of whom 170 (21.68%) reported pathological complete response (pCR) after NAC and 614 (78.32%) had residual invasive tumors. The clinical T stage, clinical N stage, molecular subtype, and TRR were identified as independent predictors of pCR. Patients with a TRR > 35% were more likely to achieve pCR (odds ratio, 5.396; 95% confidence interval [CI], 3.299-8.825). The receiver operating characteristic (ROC) curve was plotted using the probability value, and the area under the ROC curve was 0.892 (95% CI, 0.863-0.922).
CONCLUSION: TRR > 35% is predictive of pCR after two cycles of NAC, and an early evaluation model using a nomogram based on five indicators, age, clinical T stage, clinical N stage, molecular subtype, and TRR, is applicable in patients with invasive breast cancer.
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