Department of Medicine and Biosystemic Science, Kyushu University Graduate School of Medical Sciences, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan.
Department of Cancer Stem Cell Research, Kyushu University Graduate School of Medical Sciences, Fukuoka, Japan.
Rheumatol Int. 2020 Jul;40(7):1101-1109. doi: 10.1007/s00296-020-04512-9. Epub 2020 Feb 15.
We aimed to identify predictors of inadequate response to glucocorticoid (GC) treatment in patients with polymyalgia rheumatica (PMR). We retrospectively studied 32 patients as a derivation cohort and 24 patients as a validation cohort. The patients were divided into two groups according to the response to GC treatment: GC-responders and GC-inadequate responders (GC-IRs). We compared laboratory data and bilateral shoulder ultrasound findings between the groups. Receiver operating characteristic (ROC) analysis was performed to determine the optimal cutoff value of candidate predictors of treatment response; the predictors were examined using multivariate logistic analysis. Gray-scale ultrasound findings of long head of the biceps (LHB) tenosynovitis and subacromial/subdeltoid (SAD) bursitis were scored semiquantitatively (0-3). A total gray-scale score (TGSS) was calculated as the sum of the gray-scale scores. In the derivation cohort, serum lactate dehydrogenase (LDH) levels and TGSS were significantly higher in GC-IRs than in GC-responders. On ROC analysis, the cutoff values of serum LDH levels ≥ 175 IU/ml and TGSS ≥ 5 were found to be the candidate predictors. Multivariate logistic analysis revealed an independent association of both the predictors with inadequate response to GC treatment. In the validation cohort, patients with one or both predictors exhibited a higher incidence of inadequate response to GC treatment. These findings indicate that the severities of LHB tenosynovitis and SAD bursitis evaluated using ultrasound and serum LDH levels are independent predictors of inadequate response to GC treatment in patients with PMR. Treatment adjustment based on prediction model may allow precise treatment of patients with PMR.
我们旨在确定巨细胞动脉炎（PMR）患者对糖皮质激素（GC）治疗反应不足的预测因素。我们回顾性研究了 32 例患者作为推导队列和 24 例患者作为验证队列。根据 GC 治疗的反应将患者分为两组：GC 反应者和 GC 反应不足者（GC-IR）。我们比较了两组之间的实验室数据和双侧肩部超声检查结果。进行受试者工作特征（ROC）分析以确定治疗反应的候选预测因素的最佳截断值；使用多变量逻辑分析检查预测因素。肱二头肌长头腱鞘炎和肩峰下/三角肌下（SAD）囊炎的灰阶超声表现进行半定量评分（0-3）。总灰阶评分（TGSS）为灰阶评分的总和。在推导队列中，GC-IR 患者的血清乳酸脱氢酶（LDH）水平和 TGSS 明显高于 GC 反应者。在 ROC 分析中，发现血清 LDH 水平≥175 IU/ml 和 TGSS≥5 的截断值是候选预测因素。多变量逻辑分析显示，两种预测因素均与 GC 治疗反应不足独立相关。在验证队列中，具有一个或两个预测因素的患者对 GC 治疗的反应不足发生率更高。这些发现表明，超声和血清 LDH 水平评估的肱二头肌长头腱鞘炎和 SAD 囊炎的严重程度是 PMR 患者对 GC 治疗反应不足的独立预测因素。基于预测模型的治疗调整可能允许对 PMR 患者进行精确治疗。
