Phinyo Phichayut, Jarupanich Nutcha, Lumkul Lalita, Phanphaisarn Areerak, Poosiripinyo Thanate, Sukpanichyingyong Sermsak, Thanindratarn Pichaya, Pornmeechai Yodsawee, Wisanuyotin Taweechok, Phimolsarnti Rapin, Rattarittamrong Ekarat, Pruksakorn Dumnoensun
Department of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Center for Clinical Epidemiology and Clinical Statistics, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Clin Epidemiol. 2023 Jul 24;15:881-890. doi: 10.2147/CLEP.S416028. eCollection 2023.
A diagnostic model to differentiate multiple myeloma (MM) from bone metastasis (BM) in patients with destructive bone lesions (MM-BM DDx) was developed to promote timely and appropriate referral of patients with MM to hematologists. External validation has never been conducted. This study aims to externally validate the performance of the MM-BM DDx model.
This multi-center external validation study was conducted using retrospective data of patients over 45 years old diagnosed with MM or BM at six university-affiliated hospitals in Thailand from 2016 to 2022. The MM-BM DDx development dataset, including patients from 2012 to 2015, was utilized during external validation. Diagnostic indicators for MM included in the MM-BM DDx model are serum creatinine, serum globulin, and serum alkaline phosphatase (ALP). MM and BM diagnosis was based on the documented International Classification of Diseases 10th Revision codes. Model performance was evaluated in terms of discrimination, calibration, and accuracy.
A total of 3018 patients were included in the validation dataset (586 with MM and 2432 with BM). Clinical characteristics were similar between the validation and development datasets. The MM-BM DDx model's predictions showed an AUC of 0.89 (95% CI, 0.87, 0.90). The predicted probabilities of MM from the model increased concordantly with the observed proportion of MM within the validation dataset. The estimated sensitivity, specificity, and LR for each odds class in the validation dataset were similar to those of the development dataset.
The discriminative ability and calibration of the MM-BM DDx model were found to be preserved during external validation. These findings provide support for the practical use of the MM-BM DDx model to assist clinicians in identifying patients with destructive bone lesions who are likely to have MM and enable them to arrange timely referrals for further evaluation by hematologists.
开发一种用于鉴别多发性骨髓瘤（MM）与骨转移（BM）患者的诊断模型（MM-BM鉴别诊断模型），以促进MM患者及时、适当地转诊至血液科医生处。此前从未进行过外部验证。本研究旨在对MM-BM鉴别诊断模型的性能进行外部验证。
本多中心外部验证研究使用了2016年至2022年期间在泰国六家大学附属医院诊断为MM或BM的45岁以上患者的回顾性数据。外部验证期间使用了MM-BM鉴别诊断模型开发数据集，其中包括2012年至2015年的患者。MM-BM鉴别诊断模型中纳入的MM诊断指标包括血清肌酐、血清球蛋白和血清碱性磷酸酶（ALP）。MM和BM诊断基于记录的国际疾病分类第10版编码。从区分度、校准度和准确性方面评估模型性能。
验证数据集中共纳入3018例患者（586例MM患者和2432例BM患者）。验证数据集和开发数据集的临床特征相似。MM-BM鉴别诊断模型的预测显示曲线下面积（AUC）为0.89（95%置信区间，0.87，0.90）。模型预测的MM概率与验证数据集中观察到的MM比例一致增加。验证数据集中每个比值类别估计的敏感性、特异性和似然比与开发数据集相似。
发现MM-BM鉴别诊断模型在外部验证期间其区分能力和校准度得以保留。这些发现为MM-BM鉴别诊断模型的实际应用提供了支持，有助于临床医生识别可能患有MM的破坏性骨病变患者，并使他们能够安排及时转诊以便血液科医生进行进一步评估。
