Division of Rheumatology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea.
Front Immunol. 2022 Jun 17;13:925341. doi: 10.3389/fimmu.2022.925341. eCollection 2022.
To develop a new disease activity assessment tool with high accuracy for Takayasu arteritis.
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).
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.
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.
开发一种新的大动脉炎疾病活动评估工具，具有较高的准确性。
从国立卫生研究院（NIH）标准和印度大动脉炎临床活动评分（ITAS2010）中选择个体项目作为候选变量，在推导队列（N=100）中开发一种新的疾病活动评估工具。医生对疾病活动的整体评估被用作金标准。构建多变量逻辑回归模型，并确定准确性最高的模型。使用简化的β系数（四舍五入到小数点后一位）生成评估疾病活动的公式。通过估计曲线下面积（AUC）来评估诊断性能。随后在验证队列（N=46）中验证新的评估工具。
产生最高准确性的多变量模型由高红细胞沉降率（ESR）、NIH 标准 1 和 4 以及颈动脉痛组成。使用简化的β系数，开发了以下疾病活动评估工具：高 ESR（3 分）、NIH 标准 1（2 分）、NIH 标准 4（4 分）和颈动脉痛（3 分）（总分≥5 分，活动；总分<5 分，不活动）。新的疾病活动评估工具在区分活动和不活动疾病方面的 AUC（89.37）高于 NIH 标准（AUC 77.96）、ITAS2010（AUC 66.12）、ITAS-ESR（AUC 75.58）和 ITAS-C 反应蛋白（AUC 71.34）。新评估工具在验证队列中的 AUC（85.23）相似。
一种新的疾病活动评估工具，由高 ESR、NIH 标准 1 和 4 以及颈动脉痛组成，在区分活动和不活动疾病方面的准确性高于目前使用的临床评估工具。
