Risk of progression of monoclonal gammopathy of undetermined significance (MGUS) into multiple myeloma and related plasma cell disorders can be determined by three major risk stratification models, namely Mayo2005, Sweden2014, and NCI2019. This retrospective study of 427 patients with MGUS diagnosed according to the 2014 International Myeloma Working Group criteria aimed to describe and analyze the longitudinal applicability of these risk models. In all three models, the majority of patients remained at their baseline risk group, whereas small numbers of patients migrated to a different risk group. Proportions of patients among risk groups remained stable over time (e.g. Mayo2005 model, low-risk group, at baseline: 43%, after 1, 2, 3, 4, 5, and 8 years: 40%, 37%, 37%, 43%, 44%, and 43%). All three risk models reliably distinguished risk of progression at baseline, upon yearly reassessment (e.g. 1 year from diagnosis) and in time-dependent analyses. Upstaging to a high-risk category was associated with an increased risk of progression in all three models (Mayo2005: hazard ratio [HR] = 5.43, 95% confidence interval [95% CI] 1.21–24.39, p = 0.027; Sweden2014: HR = 13.02, 95% CI 5.25–32.28, p < 0.001; NCI2019: HR = 5.85, 95% CI 2.49–13.74, p < 0.001). Our study shows that MGUS risk stratification models can be applied longitudinally to repeatedly determine and improve individual risk of progression. Patient migration to higher risk categories during follow up should prompt more frequent monitoring in clinical routine.

意义未明的单克隆丙种球蛋白病 （MGUS） 进展为多发性骨髓瘤和相关浆细胞疾病的风险可以通过三个主要的风险分层模型来确定，即 Mayo2005、Sweden2014 和 NCI2019。这项回顾性研究对 427 名根据 2014 年国际骨髓瘤工作组标准诊断的 MGUS 患者进行，旨在描述和分析这些风险模型的纵向适用性。在所有三个模型中，大多数患者保持在基线风险组，而少数患者迁移到不同的风险组。风险组患者比例随着时间的推移保持稳定 （例如 Mayo2005 模型，低风险组，基线时：43%，1、2、3、4、5 和 8 年后：40%、37%、37%、43%、44% 和 43%）。所有三种风险模型都可靠地区分了基线、年度重新评估 （例如诊断后 1 年） 和时间依赖性分析的进展风险。在所有三个模型中，升级到高风险类别与进展风险增加相关 （Mayo2005：风险比 [HR] = 5.43,95% 置信区间 [95% CI] 1.21-24.39，p = 0.027 ;瑞典 2014： HR = 13.02,95% CI 5.25–32.28，p < 0.001; NCI2019：HR = 5.85,95% CI 2.49–13.74，p < 0.001）。 我们的研究表明，MGUS 风险分层模型可以纵向应用，以反复确定和改善个体进展风险。患者在随访期间迁移到高风险类别时，应促使在临床常规中进行更频繁的监测。