National Clinical Research Center for Blood Diseases, State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.
Tianjin Institutes of Health Science, Tianjin, China.
Am J Hematol. 2024 Apr;99(4):523-533. doi: 10.1002/ajh.27207. Epub 2024 Jan 21.
Current standard predictive models of disease risk do not adequately account for the heterogeneity of survival outcomes in patients with new-diagnosed multiple myeloma (NDMM). In this retrospective, multicohort study, we collected clinical and genetic data from 1792 NDMM patients and identified the prognostic impact of all features. Using the top-ranked predictive features, a weighted Myeloma Prognostic Score System (MPSS) risk model was formulated and validated to predict overall survival (OS). In the training cohort, elevated lactate dehydrogenase level (LDH), International Staging System (ISS) Stage III, thrombocytopenia, and cumulative high-risk cytogenetic aberration (HRA) numbers were found to have independent prognostic significance. Each risk factor was defined as its weighted value respectively according to their hazard ratio for OS (thrombocytopenia 2, elevated LDH 1, ISS III 2, one HRA 1, and ≥2 HRA 2, points). Patients were further stratified into four risk groups: MPSS I (22.5%, 0 points), II (17.6%, 1 points), III (38.6%, 2-3 points), and IV (21.3%, 4-7 points). MPSS risk stratification showed optimal discrimination, as well as calibration, of four risk groups with median OS of 91.0, 69.8, 45.0, and 28.0 months, for patients in MPSS I to IV groups (p < .001), respectively. Importantly, the MPSS model retained its prognostic value in the internal validation cohort and an independent external validation cohort, and exhibited significant risk distribution compared with conventional prognostic models (R-ISS, R2-ISS, and MASS). Utilization of the MPSS model in clinical practice could improve risk estimation in NDMM patients, thus prompting individualized treatment strategies.
目前,疾病风险的预测模型并不能充分考虑新诊断多发性骨髓瘤(NDMM)患者生存结局的异质性。在这项回顾性、多队列研究中,我们从 1792 名 NDMM 患者中收集了临床和遗传数据,并确定了所有特征的预后影响。使用排名最高的预测特征,制定并验证了加权多发性骨髓瘤预后评分系统(MPSS)风险模型,以预测总生存期(OS)。在训练队列中,发现乳酸脱氢酶水平升高(LDH)、国际分期系统(ISS)分期 III 期、血小板减少症和累积高危细胞遗传学异常(HRA)数量具有独立的预后意义。每个危险因素根据其对 OS 的风险比(血小板减少症 2 分、LDH 升高 1 分、ISS III 期 2 分、一个 HRA 1 分和≥2 个 HRA 2 分)分别定义为其加权值。患者进一步分为四个风险组:MPSS I(22.5%,0 分)、II(17.6%,1 分)、III(38.6%,2-3 分)和 IV(21.3%,4-7 分)。MPSS 风险分层显示了四个风险组的最佳区分度和校准度,中位 OS 分别为 91.0、69.8、45.0 和 28.0 个月,分别为 MPSS I 至 IV 组的患者(p<0.001)。重要的是,MPSS 模型在内部验证队列和独立外部验证队列中保留了其预后价值,与传统预后模型(R-ISS、R2-ISS 和 MASS)相比,显示出显著的风险分布。在临床实践中使用 MPSS 模型可以改善 NDMM 患者的风险估计,从而促使个体化治疗策略的制定。