Qianwen Cheng1, Li Cai1, Yuyang Zhang1, Lei Chen1, Yu Hu1,2, Chunyan Sun1,2. 1. Institute of Hematology, Wuhan Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. 2. Collaborative Innovation Center of Hematology, Huazhong University of Science and Technology, Wuhan, China.
Abstract
Background: To investigate the prognostic value of circulating plasma cells (CPC) and establish novel nomograms to predict individual progression-free survival (PFS) as well as overall survival (OS) of patients with newly diagnosed multiple myeloma (NDMM). Methods: One hundred ninetyone NDMM patients in Wuhan Union Hospital from 2017.10 to 2020.8 were included in the study. The entire cohort was randomly divided into a training (n = 130) and a validation cohort (n = 61). Univariate and multivariate analyses were performed on the training cohort to establish nomograms for the prediction of survival outcomes, and the nomograms were validated by calibration curves. Results: When the cut-off value was 0.038%, CPC could well distinguish patients with higher tumor burden and lower response rates (P < 0.05), and could be used as an independent predictor of PFS and OS. Nomograms predicting PFS and OS were developed according to CPC, lactate dehydrogenase (LDH) and creatinine. The C-index and the area under receiver operating characteristic curves (AUC) of the nomograms showed excellent individually predictive effects in training cohort, validation cohort or entire cohort. Patients with total points of the nomograms ≤ 60.7 for PFS and 75.8 for OS could be defined as low-risk group and the remaining as high-risk group. The 2-year PFS and OS rates of patients in low-risk group was significantly higher than those in high-risk group (p < 0.001). Conclusions: CPC is an independent prognostic factor for NDMM patients. The proposed nomograms could provide individualized PFS and OS prediction and risk stratification.
Background: To investigate the prognostic value of circulating plasma cells (CPC) and establish novel nomograms to predict individual progression-free survival (PFS) as well as overall survival (OS) of patients with newly diagnosed multiple myeloma (NDMM). Methods: One hundred ninetyone NDMMpatients in Wuhan Union Hospital from 2017.10 to 2020.8 were included in the study. The entire cohort was randomly divided into a training (n = 130) and a validation cohort (n = 61). Univariate and multivariate analyses were performed on the training cohort to establish nomograms for the prediction of survival outcomes, and the nomograms were validated by calibration curves. Results: When the cut-off value was 0.038%, CPC could well distinguish patients with higher tumor burden and lower response rates (P < 0.05), and could be used as an independent predictor of PFS and OS. Nomograms predicting PFS and OS were developed according to CPC, lactate dehydrogenase (LDH) and creatinine. The C-index and the area under receiver operating characteristic curves (AUC) of the nomograms showed excellent individually predictive effects in training cohort, validation cohort or entire cohort. Patients with total points of the nomograms ≤ 60.7 for PFS and 75.8 for OS could be defined as low-risk group and the remaining as high-risk group. The 2-year PFS and OS rates of patients in low-risk group was significantly higher than those in high-risk group (p < 0.001). Conclusions: CPC is an independent prognostic factor for NDMMpatients. The proposed nomograms could provide individualized PFS and OS prediction and risk stratification.