20 世纪 60 年代，通过基于实验室的外周血研究并结合详细的临床注释，Waldenström 博士描述了一种他称之为“良性单克隆丙种球蛋白病”的病症。这些患者无症状，可检测到单克隆蛋白，并且不符合多发性骨髓瘤的影像学和实验室标准。 1978 年，通过对病历进行观察性回顾性审查，凯尔博士观察到并非所有单克隆丙种球蛋白病病例都是良性的。他引入了意义未定的单克隆丙种球蛋白病 (MGUS) 一词来描述可能进展为多发性骨髓瘤 (MM) 的病症，强调临床无法预测哪些患者可能会进展。 1980 年，博士。 Kyle 和 Greipp 描述了 6 例不符合 MGUS 或 MM 定义的病例，并且在至少 5 年随访后仍无症状；他们被诊断患有冒烟型多发性骨髓瘤（SMM）。随着时间的推移，SMM 由任意数值定义（骨髓中浆细胞≥10%，血清 M 蛋白浓度≥3 g/dL）。已经开发出许多临床评分来定义进展为 MM 的高风险群体。目前的进展统计模型仅提供平均风险评分，由于个体水平的进展风险仍然未知，因此临床实用性有限。医生科学家们正在关注新兴技术，例如全基因组测序、肿瘤微环境分析和单细胞 RNA 测序，以在分子水平上了解前体状态。这些技术的首要目标是更好地表征单克隆丙种球蛋白病和其他骨髓瘤前体状态。这将使临床医生能够提供更精确、个性化的风险评估，并最终改善患者的治疗结果。本综述概述了 MM 前体状态的历史、当前定义、风险分层模型的挑战以及新兴技术在增强预测和结果方面的作用。版权所有 © 2024。由 Elsevier Ltd 出版。

In the 1960s, through laboratory-based investigations of peripheral blood partnered with detailed clinical annotations, Dr. Waldenström described a condition he called "benign monoclonal gammopathy". These patients were asymptomatic with a detectable monoclonal protein, and did not meet imaging and laboratory criteria for multiple myeloma. In 1978, through observational retrospective review of medical records, Dr. Kyle observed that not all cases of monoclonal gammopathy were benign. He introduced the term monoclonal gammopathy of undetermined significance (MGUS) to describe a condition that may potentially progress to multiple myeloma (MM), highlighting clinical inability in predicting which patients might progress. In 1980, Drs. Kyle and Greipp described 6 cases which did not fit the definitions of MGUS or MM, and they remained asymptomatic after at least 5 years of follow-up; they were proposed to have smoldering multiple myeloma (SMM). Over time, SMM was defined by arbitrary numerical values (≥10 % plasma cells in the bone marrow and serum M-protein concentration ≥ 3 g/dL). Numerous clinical scores have been developed to define high-risk groups for progression to MM. Current statistical models for progression provide only average risk scores, offering limited clinical utility since the risk of progression at an individual level remains unknown. Physician-scientists are focusing on emerging technologies, such as whole genome sequencing, tumor microenvironment analysis, and single-cell RNA sequencing, to understand precursor states at a molecular level. The overarching goal of these technologies is to better characterize monoclonal gammopathy and other myeloma precursor states. This will enable clinicians to provide more precise, individualized risk assessments and ultimately improve patient outcomes. This review outlines the history of MM precursor states, current definitions, challenges in risk stratification models, and the role of emerging technologies in enhancing predictions and outcomes.Copyright © 2024. Published by Elsevier Ltd.