Seasonal Exacerbation of Rheumatoid Arthritis Detected by Big Claims Data Anal ysis: A Retrospective Population Study
Seasonal Exacerbation of Rheumatoid Arthritis Detected by Big Claims Data Anal ysis: A Retrospective Population Study
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通过大额索赔数据分析检测类风湿性关节炎的季节性恶化：一项回顾性人群研究
DOI：
10.1093/mr/roab122
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Takahiro Suzuki
中科院分区：
文献类型：
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作者：
Fumihiko Ando;Katsuhiko Takabayashi ;Shinsuke Fujita;Hiroshi Nakajima;Hideki Hanaoka;Takahiro Suzuki
该研究的目的是利用大数据确定生物疾病缓解抗风湿药物（bDMARDs）和甲氨蝶呤（MTX）开始使用的季节变化。方法统计2010年4月至2017年3月类风湿关节炎（RA）患者每月首次使用bDMARD和MTX的次数。数据收集自日本国家健康保险索赔和特定健康检查数据库。这个数据库覆盖了95%以上的日本公民。确定了入会数量的季节变化。患者索赔也根据药物、地区、性别和年龄进行分类。结果甲氨蝶呤起始剂量和甲氨蝶呤给药剂量随季节呈正弦曲线变化，5 ~ 7月最多，11 ~ 1月最少；在每个bDMARD，地区，性别和年龄组中观察到相同的变化模式，特别是当数字较高时。结论：我们注意到bdmard发病数量有明显的季节变化，春季达到高峰，提示日本春季RA病情加重。这些变化在日常实践中被忽视，只有使用大数据才能看到。
ObjectivesThe objective of the study was to determine the seasonal changes in the initiation of biological disease-modifying antirheumatic drugs (bDMARDs) and methotrexate (MTX) using big claims data.MethodsWe counted the monthly number of initial administrations of each bDMARD and MTX in patients with rheumatoid arthritis (RA) between April 2010 and March 2017. Data were collected from the National Database of Health Insurance Claims and Specific Health Checkups of Japan. This database covers more than 95% of Japanese citizens. Seasonal changes in the number of initiations were determined. Patient claims were also classified according to drugs, districts, gender, and ages.ResultsThe initiation of bDMARDs and MTX administration varied according to the season in a sine curve shape, with the highest numbers in May to July and the lowest numbers in November to January. The same changing pattern was observed among each bDMARD, district, gender, and age groups particularly when the number was on the higher side.ConclusionWe noted an apparent seasonal change in the number of bDMARDs initiated, with a peak during spring, suggesting an exacerbation of RA in the spring in Japan. These changes are overlooked in daily practice and are only visible using big data.