MRI-Based Bone Marrow Radiomics Nomogram for Prediction of Overall Survival in Patients With Multiple Myeloma.

Yang Li,Lei Chen,Yang Liu,Ping Yin,Chuanxi Hao,Sicong Wang,Nan Hong,Chao Sun

doi:10.3389/fonc.2021.709813

Abstract

PurposeTo develop and validate a radiomics nomogram for predicting overall survival (OS) in multiple myeloma (MM) patients.Material and MethodsA total of 121 MM patients was enrolled and divided into training (n=84) and validation (n=37) sets. The radiomics signature was established by the selected radiomics features from lumbar MRI. The radiomics signature and clinical risk factors were integrated in multivariate Cox regression model for constructing radiomics nomogram to predict MM OS. The predictive ability and accuracy of the nomogram were evaluated by the index of concordance (C-index) and calibration curves, and compared with other four models including the clinical model, radiomics signature model, the Durie-Salmon staging system (D-S) and the International Staging System (ISS). The potential association between the radiomics signature and progression-free survival (PFS) was also explored.ResultsThe radiomics signature, 1q21 gain, del (17p), and β2-MG≥5.5 mg/L showed significant association with MM OS. The predictive ability of radiomics nomogram was better than the clinical model, radiomics signature model, the D-S and the ISS (C-index: 0.793 vs. 0.733 vs. 0.742 vs. 0.554 vs. 0.671 in training set, and 0.812 vs. 0.799 vs.0.717 vs. 0.512 vs. 0.761 in validation set). The radiomics signature lacked the predictive ability for PFS (log-rank P=0.001 in training set and log-rank P=0.103 in validation set), whereas the 1-, 2- and 3-year PFS rates all showed significant difference between the high and low risk groups (P ≤ 0.05).ConclusionThe MRI-based bone marrow radiomics may be an additional useful tool for MM OS prediction.

Highlights

Multiple myeloma (MM) is the second most common hematologic malignancy, characterized by anemia, hypercalcemia, renal failure, and lytic bone lesions [1]
Several risk stratification models were routinely used in clinical practice, such as Durie-Salmon staging system (D-S) [5], the International Staging System (ISS) [6], the Revised-International Staging System (R-ISS) [7]. and the Mayo Stratification of Myeloma and Risk-Adapted Therapy [8]
Our study evaluated the potential association between the OSbased rad-score and the progression-free survival (PFS)

Summary

Introduction

Multiple myeloma (MM) is the second most common hematologic malignancy, characterized by anemia, hypercalcemia, renal failure, and lytic bone lesions [1]. Despite the more effective therapies were introduced, this incurable disease remains highly heterogeneous in clinical outcome due to the patient characteristics and features intrinsic to the MM [2, 3]. Many factors including patient characteristics, disease biology and genetic lesions had the prognostic value that should be considered for patient assessment [4]. The Mayo Stratification of Myeloma and Risk-Adapted Therapy (mSMART) [8]. Several risk stratification models were routinely used in clinical practice, such as Durie-Salmon staging system (D-S) [5], the International Staging System (ISS) [6], the Revised-International Staging System (R-ISS) [7]. These models should be further analyzed and refined, and the accurate prognostic stratification is still under research

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Results

Conclusion