Although venous thromboembolism (VTE) is an important treatment and disease-related complication in myeloma, a validated risk prediction model including disease-specific variables such as cytogenetics or tumor burden is lacking. The aim of this study was to develop a new risk prediction model for VTE in the context of modern antimyeloma therapy. All consecutive patients diagnosed at the Cleveland Clinic between 2008 and 2018 and with available data on baseline candidate risk factors constituted the derivation cohort. The primary outcome was VTE (deep venous thrombosis/pulmonary embolism) within 1 year of treatment initiation. A multivariable model was used, and weights were derived from subdistribution hazard ratios to construct a risk score. The model was validated both by internal bootstrap validation and in an external validation cohort. The derivation cohort consisted of 783 patients. A 5-component risk prediction tool, named the PRISM score, was developed, including the following variables: prior VTE, prior surgery, immunomodulatory drug use, abnormal metaphase cytogenetics, and Black race. The c-statistic of the model was 0.622 (95% confidence interval [CI], 0.567-0.674). The model stratified patients into low, intermediate, and high risk, with 12-month cumulative VTE incidence of 2.7%, 10.8%, and 36.5%, respectively. Risk of VTE increased significantly with increasing score in both the derivation and the external validation data sets, with a subdistribution hazard ratio per 1-point increase of 1.28 (95% CI, 1.19-1.39; P < .001) and 1.23 (95% CI, 1.07-1.41; P = .004) respectively. Although the PRISM score can guide clinicians in identifying patients at a high risk of VTE, additional external validation is necessary for incorporation into routine clinical practice.

中文翻译：

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异常中期细胞遗传学预测骨髓瘤中的静脉血栓栓塞：PRISM 评分的推导和验证。

尽管静脉血栓栓塞 (VTE) 是骨髓瘤的重要治疗和疾病相关并发症，但缺乏经过验证的风险预测模型，包括细胞遗传学或肿瘤负荷等疾病特异性变量。本研究的目的是在现代抗骨髓瘤治疗的背景下开发一种新的 VTE 风险预测模型。2008 年至 2018 年期间在克利夫兰诊所诊断出的所有连续患者以及关于基线候选风险因素的可用数据构成了推导队列。主要结果是治疗开始后 1 年内的 VTE（深静脉血栓形成/肺栓塞）。使用多变量模型，并从子分布风险比中得出权重以构建风险评分。该模型通过内部引导程序验证和外部验证队列进行了验证。推导队列由 783 名患者组成。开发了一个名为 PRISM 评分的 5 分量风险预测工具，包括以下变量：既往 VTE、既往手术、免疫调节药物使用、异常中期细胞遗传学和黑人种族。该模型的 c 统计量为 0.622（95% 置信区间 [CI]，0.567-0.674）。该模型将患者分为低风险、中风险和高风险，12 个月累计 VTE 发生率分别为 2.7%、10.8% 和 36.5%。VTE 的风险随着推导和外部验证数据集中得分的增加而显着增加，每增加 1 点的子分布风险比为 1.28（95% CI，1.19-1.39；P <.001）和 1.23（95% CI，1.07-1.41；P = .004)。尽管 PRISM 评分可以指导临床医生识别 VTE 高危患者，