Combining information from multiple bone turnover markers as diagnostic indices for osteoporosis using support vector machines.
Biomarkers
; 24(2): 120-126, 2019 Mar.
Article
em En
| MEDLINE
| ID: mdl-30442069
ABSTRACT
CONTEXT Osteoporosis (OP) is a progressive systemic bone disease. Dual-energy X-ray absorptiometry (DXA) is routinely employed and is considered the gold standard method for the diagnosis of OP. OBJECTIVE:
We aimed to investigate the potential use of combined information from multiple bone turnover markers (BTMs) as a clinical diagnostic tool for OP. MATERIALS ANDMETHODS:
A total of 9053 Chinese postmenopausal women (2464 primary OP patients and 6589 healthy controls) were recruited. Serum levels of six common BTMs, including BAP, BSP, CTX, OPG, OST and sRANKL were assayed. Models based on support vector machine (SVM) were constructed to explore the efficiency of different combinations of multiple BTMs for OP diagnosis.RESULTS:
Increasing the number of BTMs used in generating the models increased the predictive power of the SVM models for determining the disease status of study subjects. The highest kappa coefficient for the model with one BTM (BAP) compared to DXA was 0.7783. The full model incorporating all six BTMs resulted in a high kappa coefficient of 0.9786.CONCLUSION:
Our findings showed that although single BTMs were not sufficient for OP diagnosis, appropriate combinations of multiple BTMs incorporated into the SVM models showed almost perfect agreement with the DXA.Palavras-chave
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Base de dados:
MEDLINE
Assunto principal:
Osteoporose
/
Biomarcadores
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Remodelação Óssea
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Limite:
Aged
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Female
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Humans
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Middle aged
País como assunto:
Asia
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article