Mowang Wang,1– 4,* Xiaoyan Yue,5,* Yingying Ding,5,* Zhen Cai,1,4 Haowen Xiao,5 He Huang,1– 4 Jingsong He1,4 

1Bone Marrow Transplantation Center, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, People’s Republic of China; 2Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, Zhejiang Province, People’s Republic of China; 3Institute of Hematology, Zhejiang University, Hangzhou, Zhejiang Province, People’s Republic of China; 4Zhejiang Province Engineering Laboratory for Stem Cell and Immunity Therapy, Hangzhou, Zhejiang Province, People’s Republic of China; 5Department of Hematology and Cell Therapy, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, People’s Republic of China

*These authors contributed equally to this work

Correspondence: He Huang; Jingsong He, Bone Marrow Transplantation Center, the First Affiliated Hospital, Zhejiang University School of Medicine, No. 79 Qingchun Road, Hangzhou, Zhejiang Province, 310006, People’s Republic of China, Email huanghe@zju.edu.cn; hejingsong@zju.edu.cn

Purpose: The growth and survival of multiple myeloma (MM) cells depend heavily on bone marrow microenvironment, where inflammation emerges as a significant feature and is commonly associated with unfavorable prognosis in MM. Our previous study and other published studies have shown that MM patients with higher neutrophil-to-lymphocyte ratio (NLR) or interleukin (IL)-10 (IL-10), lower lymphocyte-to-monocyte ratio (LMR) or platelet-to-lymphocyte ratio (PLR) frequently have inferior overall survival (OS) independent of current risk- stratification markers. Nevertheless, whether specific inflammation-related markers have prognostic value for MM patients remains elusive.
Patients and methods: We retrospectively analyzed the clinical data of 452 newly diagnosed MM (NDMM) patients treated in our center from May 2013 to June 2022. Cox regression analysis and least absolute shrinkage and selector operation (LASSO) were performed to establish the predictive nomograms for survival outcomes in the training cohort, and the nomograms were validated by calibration curves in the validation cohort.
Results: The best cutoff values of NLR, LMR, PLR, and IL-10 were 4.44, 4.0, 100, and 1.42pg/mL, respectively. We established a nomogram model after LASSO Cox and multivariate Cox regression analysis. The nomogram model exhibited acceptable discrimination, with C-index values of 0.777, 0.714, and 0.71 in the training cohort, validation cohort, and entire cohort, respectively, which was significantly higher than the C-indices of the three most extensively used staging systems for NDMM (D-S, ISS, and R-ISS). All calibration curves revealed good consistency between the predictive and actual survival outcomes. Patients were divided into high-risk and low-risk groups based on their total nomogram scores, with a threshold of 106.2, where the median OS of patients in the high-risk group was significantly shorter than that of patients in the low-risk group.
Conclusion: The proposed nomogram based on circulating inflammatory factors is an inexpensive, widely available, and easily interpretable risk-stratification tool for NDMM patients.

Keywords: multiple myeloma, neutrophil to lymphocyte ratio, platelet to lymphocyte ratio, lymphocyte to monocyte ratio, IL-10, nomogram