使用扩展算法来估计美国和英国肌缩侧面硬化症的患病率
Ali Abbasi1, Henrik Fryk2, Jan Rudnik2
1UCB Pharma Ltd., 208 Bath Road, Slough, SL1 3WE, UK. ali.abbasi@ucb.com.
概括
这项研究开发了一种改进的算法,用于在真实世界的数据中识别肌缩性侧面硬化症 (ALS) 病例. 改进的方法准确地估计了不同数据库中大量患者群体的ALS患病率.
科学领域:
- 神经学 神经学
- 流行病学 流行病学
- 医疗信息学 医疗信息学
背景情况:
- 了解肌缩性侧面硬化症 (ALS) 的负担至关重要,但使用真实世界数据 (RWD) 具有挑战性.
- 由于ALS的罕见性和编码系统的变化,在RWD中准确识别病例构成了重大障碍.
- 现有的方法需要改进,以捕捉ALS流行情况的全面图像.
研究的目的:
- 在现实世界的数据库中开发和验证一种增强的算法,用于识别肌缩性侧面硬化症 (ALS) 病例.
- 通过扩展识别标准估计ALS的患病率和可能的ALS病例.
- 在大规模的医疗保健索赔和临床数据库中评估算法的实用性.
主要方法:
- 使用MarketScan和英国临床实践研究数据链接 (CPRD) 数据库,搜索ALS/MND诊断代码和批准的治疗方法 (riluzole,edaravone).
- 采用了一个主要算法,需要≥1个ALS代码加上处方或临床访问,以及一个扩展的算法,用于可能的ALS病例 (MND代码+ALS药物).
- 分析了从2011年1月1日到2020年12月31日的数据,重点是2011年1月1日之前12个月入学的患者.
主要成果:
- 在MarketScan中确定了9,433名ALS患者 (患病率为4.5-6.2 / 100,000) 和在CPRD中2,785名潜在ALS患者中的47.9%,接受了riluzole.
- 根据MND代码和ALS药物处方,MarketScan的分析显示了3,658个可能的ALS病例 (每10万人中有4.3例).
- 英国CPRD根据MND代码和riluzole处方确定了每10万可能的ALS病例中的6.3.
结论:
- 扩展的算法成功地识别了更多的ALS患者和可能的ALS病例.
- 这种增强的方法使得在真实世界的数据库中,比如MarketScan和CPRD,可以更准确地估计ALS患病率.
- 这项研究证明了使用RWD与精细算法的可行性,以了解像ALS这样的罕见疾病的负担.
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