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Clinical Features of Patients With Progressive Supranuclear Palsy in an US Insurance Claims Database
Emma Viscidi1, Irene Litvan2, Tien Dam1
1Biogen, Cambridge, MA, United States.
Frontiers in Neurology
|July 5, 2021
Summary
The prevalence of diagnosed progressive supranuclear palsy (PSP) is 2.95 per 100,000 people. Many patients show suggestive symptoms years before diagnosis, indicating a potential delay in identifying this rare neurodegenerative movement disorder.
Area of Science:
- Neurology
- Epidemiology
- Public Health
Background:
- Progressive supranuclear palsy (PSP) is a rare neurodegenerative movement disorder with limited epidemiological data.
- Understanding PSP epidemiology is crucial for public health planning and resource allocation.
Purpose of the Study:
- To estimate the age-adjusted prevalence of progressive supranuclear palsy (PSP) in the US.
- To describe antecedent diagnoses and clinical features in PSP patients up to five years prior to their first diagnostic code.
Main Methods:
- A nested case-control study utilized large US insurance databases (IBM MarketScan).
- Progressive supranuclear palsy (PSP) cases were identified using ICD-9/10 codes; controls were matched by demographics and enrollment.
- Prevalence was estimated for 2016, and antecedent diagnoses were analyzed within five years before the index date.
Main Results:
- The age-adjusted prevalence of diagnosed progressive supranuclear palsy (PSP) was 2.95 per 100,000 in 2016.
- Common pre-index diagnoses in PSP cases included gait abnormalities (79.3%), joint pain (54.9%), Parkinson's disease (54.6%), fatigue (49.8%), and cerebrovascular disease (45.6%).
- These symptoms were significantly more prevalent in PSP cases compared to controls.
Conclusions:
- The diagnosed prevalence of progressive supranuclear palsy (PSP) is lower than previously reported in some studies.
- Suggestive clinical features often appear years before a PSP diagnosis, highlighting a significant diagnostic delay.
- Identifying early clinical indicators could enable predictive models for earlier progressive supranuclear palsy (PSP) detection and intervention.
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