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单克隆丙种球蛋白病进展为多发性骨髓瘤的潜在疾病状况的定量风险:一项全国性队列研究。

Quantitative risk of underlying disease conditions for progression from monoclonal gammopathy to multiple myeloma: a nationwide cohort study.

作者信息

Ko H, Choi S, Park S-S, Jung S, Lee C H, Han S, Min C-K

机构信息

Department of Pharmacology, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.

Department of Pharmacology, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea; Division of Data Science, PIPET, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.

出版信息

ESMO Open. 2025 Jul;10(7):105327. doi: 10.1016/j.esmoop.2025.105327. Epub 2025 Jul 9.

Abstract

BACKGROUND

This nationwide real-world data cohort study developed a risk-scoring model to predict the progression of monoclonal gammopathy of undetermined significance (MGUS) to symptomatic multiple myeloma (MM) using prior disease conditions.

MATERIALS AND METHODS

The Health Insurance Review and Assessment Service database, which covers nearly the entire Korean population, was utilized in this study. Out of 5361 MGUS patients, 345 (6.4%) were diagnosed with MM, with 253 (73.3%) of them progressing to symptomatic MM.

RESULTS

We identified female sex, chronic pulmonary disease, peptic ulcer disease, diabetes, and non-malignant hematologic disorder as significant risk factors and integrated these into the risk-scoring model. MGUS patients can be stratified into low-, intermediate-, and high-risk groups for progression to symptomatic MM using this model. The high-risk group showed a hazard ratio (HR) of 2.53 [95% confidence interval (CI) 1.70-3.75] compared with the low-risk group, and the intermediate-risk group showed an HR of 1.38 (95% CI 1.02-1.86) compared with the low-risk group.

CONCLUSION

This scoring model will help in the early detection of MGUS patients at high risk for symptomatic MM and allow for a more efficient allocation of health care resources to those patients who require intensive monitoring.

摘要

背景

这项全国性的真实世界数据队列研究开发了一种风险评分模型,以利用既往疾病状况预测意义未明的单克隆丙种球蛋白病(MGUS)进展为有症状的多发性骨髓瘤(MM)。

材料与方法

本研究使用了涵盖几乎全体韩国人口的健康保险审查与评估服务数据库。在5361例MGUS患者中,345例(6.4%)被诊断为MM,其中253例(73.3%)进展为有症状的MM。

结果

我们确定女性、慢性肺病、消化性溃疡病、糖尿病和非恶性血液系统疾病为显著风险因素,并将这些因素纳入风险评分模型。使用该模型,MGUS患者可被分为进展为有症状MM的低风险、中风险和高风险组。与低风险组相比,高风险组的风险比(HR)为2.53[95%置信区间(CI)1.70 - 3.75],中风险组与低风险组相比的HR为1.38(95%CI 1.02 - 1.86)。

结论

该评分模型将有助于早期发现有症状MM高风险的MGUS患者,并能更有效地将医疗资源分配给那些需要密切监测的患者。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a5d/12308365/55e0c6b69074/gr1.jpg

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