Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/71567
Title: Development of a clinical diagnostic tool to differentiate multiple myeloma from bone metastasis in patients with destructive bone lesions (MM-BM DDx)
Authors: Phichayut Phinyo
Titinat Maihom
Areerak Phanphaisarn
Pakorn Kerdsinchai
Ekarat Rattarittamrong
Jayanton Patumanond
Dumnoensun Pruksakorn
Keywords: Medicine
Issue Date: 1-Dec-2020
Abstract: © 2020, The Author(s). Background: Most patients with destructive bone lesions undergo a comprehensive diagnostic procedure to ensure that proper treatment decisions are pursued. For patients with multiple myeloma, this can lead to delays in diagnosis and treatment initiation. This study was conducted to develop a diagnostic rule that could serve as a tool for early identification of multiple myeloma and promote timely referral of patients to haematologists. Methods: The clinical prediction rule was developed using a retrospective case-series of patients with multiple myeloma (MM) and those with bone metastasis (BM) at Chiang Mai University Hospital from 2012 to 2015. Multivariable fractional polynomial logistic regression was used to derive a diagnostic model to differentiate between MM and BM patients (MM-BM DDx). Results: A total of 586 patients (136 MM patients and 450 BM patients) were included. Serum creatinine, serum globulin, and serum alkaline phosphatase were identified as significant indicators for the differentiation of MM and BM patients. The MM-BM DDx model showed excellent discriminative ability [AuROC of 0.90 (95%CI 0.86 to 0.93)] and good calibration. Conclusions: This MM-BM DDx model could potentially allow for early myeloma diagnosis and improvement of overall prognosis. A prospective validation study is needed to confirm the accuracy of the MM-BM DDx model prior to its application in clinical practice.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85093871539&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/71567
ISSN: 14712296
Appears in Collections:CMUL: Journal Articles

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