Zhongguo shi yan xue ye xue za zhi · 2025
[Analysis of Risk Factors for Early Relapse/Progression in Patients with Multiple Myeloma and Development of a Nomogram Prediction Model].
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Huang Mei-Jiao, Liu Yu, Wang Hong-Yan, Chen Tai-Ran, Zou Xing-Li
Аннотация
OBJECTIVE: To analyze the potential risk factors for early relapse/progression in patients with multiple myeloma (MM) and develop a risk prediction model based on these factors.
METHODS: A retrospective analysis was conducted on 187 newly diagnosed multiple myeloma (NDMM) patients who treated at the Affiliated Hospital of North Sichuan Medical College from February 2014 to December 2020. The clinical, laboratory examination, and follow-up data of patients experiencing relapse/progression within 24 months after treatment (ER/EP24) were analyzed using univariate and multivariate analyses, and a nomogram prediction model was established.
RESULTS: Among the 187 patients, 58 (31.0%) experienced ER/EP24, with a median survival time of only 24 months. The results of multivariate logistic regression analysis showed that failure to achieve partial response (PR) or better after 3-4 cycles of chemotherapy and albumin (ALB) levels <35 g/L were independent risk factors for ER/EP24 (P < 0.05). These factors, along with other clinically relevant variables, were further incorporated into the nomogram prediction model. The model demonstrated a concordance index (C-index) of 0.784, indicating strong predictive accuracy.
CONCLUSION: MM patients experiencing ER/EP24 exhibit poor outcome, and the nomogram model developed in this study effectively predicts the risk of ER/EP24 in NDMM patients, providing a valuable tool for clinical risk assessment.
METHODS: A retrospective analysis was conducted on 187 newly diagnosed multiple myeloma (NDMM) patients who treated at the Affiliated Hospital of North Sichuan Medical College from February 2014 to December 2020. The clinical, laboratory examination, and follow-up data of patients experiencing relapse/progression within 24 months after treatment (ER/EP24) were analyzed using univariate and multivariate analyses, and a nomogram prediction model was established.
RESULTS: Among the 187 patients, 58 (31.0%) experienced ER/EP24, with a median survival time of only 24 months. The results of multivariate logistic regression analysis showed that failure to achieve partial response (PR) or better after 3-4 cycles of chemotherapy and albumin (ALB) levels <35 g/L were independent risk factors for ER/EP24 (P < 0.05). These factors, along with other clinically relevant variables, were further incorporated into the nomogram prediction model. The model demonstrated a concordance index (C-index) of 0.784, indicating strong predictive accuracy.
CONCLUSION: MM patients experiencing ER/EP24 exhibit poor outcome, and the nomogram model developed in this study effectively predicts the risk of ER/EP24 in NDMM patients, providing a valuable tool for clinical risk assessment.