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期刊来源：Ann Intern Med

原文链接：https://doi.org/10.7326/M23-2540

摘要内容如下：

背景

意义未明的单克隆丙种球蛋白病（MGUS）和闷烧型多发性骨髓瘤（SMM）是多发性骨髓瘤及相关疾病的无症状先兆疾病。闷烧型多发性骨髓瘤与MGUS的区别在于取样时有10%或更多的骨髓浆细胞（BMPC），具有更高的进展风险，需要专科治疗。

客观

开发一种多变量预测模型，该模型可预测假定MGUS患者具有10%或更高BMPC（骨髓标准SMM或更差）的概率，以告知获取骨髓样本的决定，并将其性能与梅奥诊所风险分层模型进行比较。

设计

ISTOPMM（冰岛筛查、治疗或预防多发性骨髓瘤），一项基于人群的MGUS前瞻性筛查研究。（ClinicalTrials.gov：NCT03327597）

设置

冰岛40岁及以上的成年人口。

病人

1043人通过筛查和可解释的骨髓样本检测到IgG、IgA、轻链和双克隆MGUS。

测量

未确定意义的单克隆丙种球蛋白病同种型；单克隆蛋白浓度；游离轻链比例；总IgG、IgM和IgA浓度被用作预测因子。骨髓浆细胞分类为0%至4%、5%至9%、10%至14%或15%或更高。

结果

SMM或更差的C-统计量为0.85（95%CI，0.82至0.88），校准非常好（截距，-0.07；斜率，0.95）。在SMM预测风险为10%或更差的阈值下，敏感性为86%，特异性为67%，阳性预测值为32%，阴性预测值为96%。与梅奥诊所（Mayo Clinic）模型相比，在合理的低风险阈值范围内，决定参考抽样的净效益高出0.13至0.30。

局限性

预测模型需要外部验证。

结论

这一准确的SMM或更差的预测模型是在假定的MGUS人群队列中开发的，可用于推迟骨髓采样和转诊至血液科。

主要资金来源

国际骨髓瘤基金会和欧洲研究理事会。

英文原文如下：

Abstracts

BACKGROUND  Monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM) are asymptomatic precursor conditions to multiple myeloma and related disorders. Smoldering multiple myeloma is distinguished from MGUS by 10% or greater bone marrow plasma cells (BMPC) on sampling, has a higher risk for progression, and requires specialist management.

OBJECTIVE  To develop a multivariable prediction model that predicts the probability that a person with presumed MGUS has 10% or greater BMPC (SMM or worse by bone marrow criteria) to inform the decision to obtain a bone marrow sample and compare its performance to the Mayo Clinic risk stratification model.

DESIGN  iStopMM (Iceland Screens, Treats or Prevents Multiple Myeloma), a prospective population-based screening study of MGUS. (ClinicalTrials.gov: NCT03327597).

SETTING  Icelandic population of adults aged 40 years or older.

PATIENTS  1043 persons with IgG, IgA, light-chain, and biclonal MGUS detected by screening and an interpretable bone marrow sample.

MEASUREMENTS  Monoclonal gammopathy of undetermined significance isotype; monoclonal protein concentration; free light-chain ratio; and total IgG, IgM, and IgA concentrations were used as predictors. Bone marrow plasma cells were categorized as 0% to 4%, 5% to 9%, 10% to 14%, or 15% or greater.

RESULTS  The c-statistic for SMM or worse was 0.85 (95% CI, 0.82 to 0.88), and calibration was excellent (intercept, -0.07; slope, 0.95). At a threshold of 10% predicted risk for SMM or worse, sensitivity was 86%, specificity was 67%, positive predictive value was 32%, and negative predictive value was 96%. Compared with the Mayo Clinic model, the net benefit for the decision to refer for sampling was between 0.13 and 0.30 higher over a range of plausible low-risk thresholds.

LIMITATION  The prediction model will require external validation.

CONCLUSION  This accurate prediction model for SMM or worse was developed in a population-based cohort of persons with presumed MGUS and may be used to defer bone marrow sampling and referral to hematology.

PRIMARY FUNDING SOURCE  International Myeloma Foundation and the European Research Council.

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