Construction and effect evaluation of risk prediction model for grades 3-4 myeloma bone disease in newly diagnosed multiple myeloma patients

Corresponding author: Le Jing, nblejing@aliyun.com

DOI: 10.12201/bmr.202410.00057

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  Abstract: Objective To investigate the influencing factors of developing Grade 3-4 myeloma bone disease (MBD) in newly diagnosed multiple myeloma (NDMM) patients and establish a Nomogram risk prediction model. Methods We selected NDMM patients from January 2015 to December 2021 at Ningbo Li Huili Hospital. Patients were divided into group A (MBD grades 0-2, 110 cases) and group B (MBD grades 3-4, 151 cases) based on the presence of Grade 3-4 MBD at diagnosis. Logistic regression analysis was used to determine the risk factors for the occurrence of Grade 3-4 MBD at diagnosis and construct a risk prediction model. To ensure the effectiveness of the model, we used the and receiver operating characteristic (ROC) curve for comprehensive evaluation. Results A total of 261 NDMM patients were included, with 150 cases with Grade 3-4 MBD, and the incidence rate was 56.39%. According to the results of the logistic multivariate regression analysis, we found that age, serum phosphorus, C-reactive protein (CRP), serum globulin (GLB), and bone marrow plasma cell proportion (BMPCp) were independent risk factors for the occurrence of Grade 3-4 MBD in NDMM patients (all P<0.05). Based on these findings, we established a risk prediction model for Grade 3-4 MBD: logit(P)=-15.092+0.107(age)+1.150(serum phosphorus)+0.057(CRP)+0.040(GLB)+0.212(BMPCp). The Hosmer-Lemeshow goodness-of-fit test showed no significant difference (P=0.770) between the predicted probability of developing Grade 3-4 MBD and the actual incidence rate. In addition, the accuracy of the model was verified, and the result showed that the accuracy rate of the model reached 90.40%. Finally, we measured the predictive ability of the model using the area under the ROC curve (AUC), and the result showed that the AUC was 0.957 (95% CI 0.932-0.981), indicating that the model had good predictive reliability. Conclusion Age, serum phosphorus, CRP, GLB, and BMPCp are independent risk factors for the occurrence of Grade 3-4 MBD in NDMM patients. The risk prediction model constructed using logistic regression analysis is effective for predicting the occurrence of Grade 3-4 MBD in NDMM patients.

  Key words: Multiple myeloma bone; myeloma bone disease; logistic regression analysis; risk prediction model

  Submit time: 20 October 2024

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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