A 10-miRNA risk score-based prediction model for pathological complete response to neoadjuvant chemotherapy in hormone receptor-positive breast cancer

Patients with hormone receptor(HR)-positive tumors breast cancer usually experience a relatively low pathological complete response(p CR)to neoadjuvant chemotherapy(NAC).Here,we derived a 10-micro RNA risk score(10-mi RNA RS)-based model with better performance in the prediction of p CR and validated its relation with the disease-free survival(DFS)in 755 HRpositive breast cancer patients(273,265,and 217 in the training,internal,and external validation sets,respectively).This model,presented as a nomogram,included four parameters:the 10-mi RNA RS found in our previous study,progesterone receptor(PR),human epidermal growth factor receptor 2(HER2)status,and volume transfer constant(K).Favorable calibration and discrimination of 10-mi RNA RS-based model with areas under the curve(AUC)of 0.865,0.811,and 0.804 were shown in the training,internal,and external validation sets,respectively.Patients who have higher nomogram score(>92.2)with NAC treatment would have longer DFS(hazard ratio=0.57;95%CI:0.39–0.83;P=0.004).In summary,our data showed the 10-mi RNA RS-based model could precisely identify more patients who can attain p CR to NAC,which may help clinicians formulate the personalized initial treatment strategy and consequently achieves better clinical prognosis for patients with HRpositive breast cancer.