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Validation of a Diagnostic Model to Differentiate Multiple Myeloma from Bone Metastasis

PURPOSE: 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 a...

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Autores principales: Phinyo, Phichayut, Jarupanich, Nutcha, Lumkul, Lalita, Phanphaisarn, Areerak, Poosiripinyo, Thanate, Sukpanichyingyong, Sermsak, Thanindratarn, Pichaya, Pornmeechai, Yodsawee, Wisanuyotin, Taweechok, Phimolsarnti, Rapin, Rattarittamrong, Ekarat, Pruksakorn, Dumnoensun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10377591/
https://www.ncbi.nlm.nih.gov/pubmed/37522153
http://dx.doi.org/10.2147/CLEP.S416028
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author Phinyo, Phichayut
Jarupanich, Nutcha
Lumkul, Lalita
Phanphaisarn, Areerak
Poosiripinyo, Thanate
Sukpanichyingyong, Sermsak
Thanindratarn, Pichaya
Pornmeechai, Yodsawee
Wisanuyotin, Taweechok
Phimolsarnti, Rapin
Rattarittamrong, Ekarat
Pruksakorn, Dumnoensun
author_facet Phinyo, Phichayut
Jarupanich, Nutcha
Lumkul, Lalita
Phanphaisarn, Areerak
Poosiripinyo, Thanate
Sukpanichyingyong, Sermsak
Thanindratarn, Pichaya
Pornmeechai, Yodsawee
Wisanuyotin, Taweechok
Phimolsarnti, Rapin
Rattarittamrong, Ekarat
Pruksakorn, Dumnoensun
author_sort Phinyo, Phichayut
collection PubMed
description PURPOSE: 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. PATIENTS AND METHODS: 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. RESULTS: 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. CONCLUSION: 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.
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spelling pubmed-103775912023-07-29 Validation of a Diagnostic Model to Differentiate Multiple Myeloma from Bone Metastasis Phinyo, Phichayut Jarupanich, Nutcha Lumkul, Lalita Phanphaisarn, Areerak Poosiripinyo, Thanate Sukpanichyingyong, Sermsak Thanindratarn, Pichaya Pornmeechai, Yodsawee Wisanuyotin, Taweechok Phimolsarnti, Rapin Rattarittamrong, Ekarat Pruksakorn, Dumnoensun Clin Epidemiol Original Research PURPOSE: 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. PATIENTS AND METHODS: 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. RESULTS: 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. CONCLUSION: 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. Dove 2023-07-24 /pmc/articles/PMC10377591/ /pubmed/37522153 http://dx.doi.org/10.2147/CLEP.S416028 Text en © 2023 Phinyo et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Phinyo, Phichayut
Jarupanich, Nutcha
Lumkul, Lalita
Phanphaisarn, Areerak
Poosiripinyo, Thanate
Sukpanichyingyong, Sermsak
Thanindratarn, Pichaya
Pornmeechai, Yodsawee
Wisanuyotin, Taweechok
Phimolsarnti, Rapin
Rattarittamrong, Ekarat
Pruksakorn, Dumnoensun
Validation of a Diagnostic Model to Differentiate Multiple Myeloma from Bone Metastasis
title Validation of a Diagnostic Model to Differentiate Multiple Myeloma from Bone Metastasis
title_full Validation of a Diagnostic Model to Differentiate Multiple Myeloma from Bone Metastasis
title_fullStr Validation of a Diagnostic Model to Differentiate Multiple Myeloma from Bone Metastasis
title_full_unstemmed Validation of a Diagnostic Model to Differentiate Multiple Myeloma from Bone Metastasis
title_short Validation of a Diagnostic Model to Differentiate Multiple Myeloma from Bone Metastasis
title_sort validation of a diagnostic model to differentiate multiple myeloma from bone metastasis
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10377591/
https://www.ncbi.nlm.nih.gov/pubmed/37522153
http://dx.doi.org/10.2147/CLEP.S416028
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