在多文化布朗克斯队列中评估冰岛筛查、治疗或预防多发性骨髓瘤(iStopMM)模型的性能:对未确定显著性风险分层的单克隆γ病的影响

IF 11.6 1区 医学 Q1 HEMATOLOGY
Rajvi Gor, Jeevan Shivakumar, Pallavi Surana, John Wei, Irina Murakhovskaya, Mendel Goldfinger, Noah Kornblum, Lauren Shapiro, Aditi Shastri, Ridhi Gupta, David Levitz, Marina Konopleva, Eric Feldman, Kira Gritsman, R. Alejandro Sica, Ioannis Mantzaris, Amit Verma, Dennis Cooper, Murali Janakiram, Nishi Shah
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引用次数: 0

摘要

冰岛筛查、治疗或预防多发性骨髓瘤(iStopMM)风险分层模型,用于预测未确定意义单克隆γ病(MGUS)患者骨髓中≥10%的异常浆细胞,该模型在主要为白人和遗传同质的冰岛人群中开发,缺乏外部验证。我们的研究旨在外部验证这一模型在种族和民族多样化的布朗克斯人口。检索了Montefiore医疗中心2002-2023年患者的医疗记录,以确定接受骨髓活检的MGUS患者。对于每位患者,将iStopMM变量输入iStopMM预测模型,进行预测,并记录实际浆细胞百分比。以受试者工作特征曲线下面积(AUROC)评估iStopMM模型预测≥10%浆细胞的性能,并计算敏感性、特异性、阳性预测值(PPV)和阴性预测值(NPV)。在最初的663例患者中,有190例纳入最终队列,其中52.6%为非洲裔美国人,23.2%为西班牙裔/拉丁裔,与iStopMM研究的同质人群有显著不同。iStopMM预测模型能够预测大于或等于10%的骨髓活检浆细胞,AUROC为0.78 (CI 0.71, 0.85)。当设定为10%的阈值预测SMM或更差时,iStopMM模型的敏感性为93.3%,特异性为33.7%,PPV为55.3%,NPV为85.0%。这个AUROC值为0.778,表明该模型在我们的种族和民族多样化的布朗克斯人口中具有合理的歧视性表现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Assessing the performance of the Iceland screens, treats, or prevents multiple myeloma (iStopMM) model in a multicultural Bronx cohort: implications for monoclonal gammopathy of undetermined significance risk stratification

Assessing the performance of the Iceland screens, treats, or prevents multiple myeloma (iStopMM) model in a multicultural Bronx cohort: implications for monoclonal gammopathy of undetermined significance risk stratification

The Iceland Screens, Treats, or Prevents Multiple Myeloma (iStopMM) risk stratification model, developed to predict ≥10% abnormal plasma cells in the bone marrow in monoclonal gammopathy of undetermined significance (MGUS) patients, was developed in a predominantly White and genetically homogeneous Icelandic population, lacking external validation. Our study aimed to externally validate this model in a racially and ethnically diverse Bronx population. The medical records of patients at Montefiore Medical Center (2002–2023) were searched to identify patients with MGUS who had undergone a bone marrow biopsy. For each patient, the iStopMM variables were entered into the iStopMM prediction model, and predicted, and actual plasma cell percentages were recorded. The area under the receiver operating characteristic (AUROC) curve assessed the iStopMM model’s performance in predicting ≥10% plasma cells, and sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Of the initial 663 patients, 190 were included in the final cohort, of whom 52.6% were African-Americans, and 23.2% identified themselves as Hispanic/Latino, remarkably different from the homogenous population of the iStopMM study. The iStopMM predictive model was able to predict greater than or equal to 10% plasma cells on bone marrow biopsy with an AUROC of 0.78 (CI 0.71, 0.85). When set at a 10% threshold for predicting SMM or worse, the iStopMM model had a 93.3% sensitivity, 33.7% specificity, 55.3% PPV, and 85.0% NPV. This AUROC value of 0.778 suggests a reasonable discriminatory performance of the model in our racially and ethnically diverse Bronx population.

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来源期刊
CiteScore
16.70
自引率
2.30%
发文量
153
审稿时长
>12 weeks
期刊介绍: Blood Cancer Journal is dedicated to publishing high-quality articles related to hematologic malignancies and related disorders. The journal welcomes submissions of original research, reviews, guidelines, and letters that are deemed to have a significant impact in the field. While the journal covers a wide range of topics, it particularly focuses on areas such as: Preclinical studies of new compounds, especially those that provide mechanistic insights Clinical trials and observations Reviews related to new drugs and current management of hematologic malignancies Novel observations related to new mutations, molecular pathways, and tumor genomics Blood Cancer Journal offers a forum for expedited publication of novel observations regarding new mutations or altered pathways.
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