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Derivation and Validation of a New Disease Activity Assessment Tool With Higher Accuracy for Takayasu Arteritis
OBJECTIVE: To develop a new disease activity assessment tool with high accuracy for Takayasu arteritis. METHODS: Individual items from National Institute of Health (NIH) criteria and the Indian Takayasu Clinical Activity Score (ITAS2010) were tested as candidate variables to develop a new disease ac...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9248800/ https://www.ncbi.nlm.nih.gov/pubmed/35784279 http://dx.doi.org/10.3389/fimmu.2022.925341 |
Sumario: | OBJECTIVE: To develop a new disease activity assessment tool with high accuracy for Takayasu arteritis. METHODS: Individual items from National Institute of Health (NIH) criteria and the Indian Takayasu Clinical Activity Score (ITAS2010) were tested as candidate variables to develop a new disease activity assessment tool in a derivation cohort (N = 100). Physician global assessment on disease activity was used as the gold standard. Multivariable logistic regression models were constructed and the model with the highest accuracy was identified. A formula assessing disease activity was generated using simplified β coefficients (rounded to decimal place). Diagnostic performance was evaluated through estimating the area under the curve (AUC). The new assessment tool was subsequently validated in a validation cohort (N = 46). RESULTS: The multivariable model yielding the highest accuracy consisted of a high erythrocyte sedimentation rate (ESR), NIH criteria 1 and 4, and carotidynia. Using simplified β coefficients, the following disease activity assessment tool was developed: high ESR (3 points), NIH criterion 1 (2 points), NIH criterion 4 (4 points), and carotidynia (3 points) (total score ≥5, active; total score <5, inactive). The new disease activity assessment tool had a higher AUC (89.37) for discriminating active and inactive diseases than NIH criteria (AUC 77.96), ITAS2010 (AUC 66.12), ITAS-ESR (AUC 75.58), and ITAS-C-reactive protein (AUC 71.34). The AUC (85.23) of the new assessment tool was similar in the validation cohort. CONCLUSION: A new disease activity assessment tool that consists of high ESR, NIH criteria 1 and 4, and carotidynia had higher accuracy in discriminating active and inactive disease than currently used clinical assessment tools. |
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