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Arriving at a diagnosis: Effective strategies used by the Undiagnosed Diseases Network
Somin Hwang1, Rachel M Brown2, Dustin Baldridge3
1MGH Institute of Health Professions, Boston, MA; Harvard Medical School, Boston, MA.
Purpose:
Despite the increasing use of exome sequencing (ES) and genome sequencing (GS) in clinical settings, many individuals remain undiagnosed. This study examined the Undiagnosed Diseases Network (UDN)'s approach to establishing diagnoses for participants.
Methods:
As a continuation of the first UDN cohort (9/16/2015-5/23/2017), this study reviewed diagnostic strategies and outcomes in the second UDN cohort (5/24/2017-6/30/2023).
Results:
Over the study period, the proportion of UDN participants with prior ES/GS increased from 40.2% to 75.0%. The diagnostic rate for the UDN was 22.1% (379/1,713). Reanalysis/reinterpretation of sequencing data (prior ES: 21.4%, prior GS: 2.6%, UDN ES: 4.8%, UDN GS: 17.3%) yielded the greatest number of diagnoses, and the most frequent supporting strategy was case matching (25.6%). Aggregation of clinical information (57.7%) and clinical testing (42.3%) were the primary strategies used to identify non-genetic diagnoses (n=26). Notably, 235 diagnoses (59.9%) required research efforts beyond current standard clinical approaches.
Conclusion:
The UDN addresses challenging undiagnosed cases by integrating clinical expertise with research strategies that go beyond standard care. By employing these advanced approaches, the UDN resolves cases that remain unsolved in routine clinical settings, demonstrating the power of connecting research and clinical care.
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