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Updated: May 3, 2026
An Organotypic High Throughput System for Characterization of Drug Sensitivity of Primary Multiple Myeloma Cells
Published on: July 15, 2015
A Nomogram Based on Circulating Inflammatory Factors for Predicting Prognosis of Newly Diagnosed Multiple Myeloma
Mowang Wang1,2,3,4, Xiaoyan Yue5, Yingying Ding5
1Bone Marrow Transplantation Center, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, People's Republic of China.
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.
