Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Orphanet J Rare Dis. 2021 May 10;16(1):210. doi: 10.1186/s13023-021-01825-1.
Although clinician, researcher, and patient resources for matchmaking exist, finding similar patients remains an obstacle for rare disease diagnosis. The goals of this study were to develop and test the effectiveness of an Internet case-finding strategy and identify factors associated with increased matching within a rare disease population.
Public web pages were created for consented participants. Matches made, time to each inquiry and match, and outcomes were recorded and analyzed using descriptive statistics. A Poisson regression model was run to identify characteristics associated with matches.
385 participants were referred to the project and 158 had pages posted. 579 inquiries were received; 89.0% were from the general public and 24.7% resulted in a match. 81.6% of pages received at least one inquiry and 15.0% had at least one patient match. Primary symptom category of neurology, diagnosis, gene page, and photo were associated with increased matches (p ≤ 0.05).
This Internet case-finding strategy was of interest to patients, families, and clinicians, and similar patients were identified using this approach. Extending matchmaking efforts to the general public resulted in matches and suggests including this population in matchmaking activities can improve identification of similar patients.
尽管存在为匹配患者而设立的临床医生、研究人员和患者资源，但寻找相似患者仍然是罕见病诊断的一个障碍。本研究的目的是开发并测试一种互联网病例发现策略的有效性，并确定与罕见病患者群体中匹配增加相关的因素。
为同意参与的参与者创建了公共网页。使用描述性统计记录和分析匹配情况、每次查询和匹配的时间以及结果。运行泊松回归模型以确定与匹配相关的特征。
向该项目推荐了 385 名参与者，其中有 158 名参与者的网页被发布。共收到 579 次查询；其中 89.0%来自公众，24.7%促成了匹配。81.6%的网页至少收到一次查询，15.0%的网页至少有一次患者匹配。主要症状类别为神经病学、诊断、基因网页和照片与增加匹配有关（p≤0.05）。
这种互联网病例发现策略引起了患者、家属和临床医生的兴趣，并通过这种方法找到了相似的患者。将匹配工作扩展到公众中，促成了匹配，并表明将这一人群纳入匹配活动可以提高相似患者的识别率。
