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Scleroderma prevalence: demographic variations in a population-based sample.

S Bernatsky1, L Joseph, C A Pineau

  • 1Division of Clinical Epidemiology, McGill University Health Centre, Montreal, Quebec, Canada. sasha.bernatsky@mail.mcgill.ca

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PubMed
Summary
This summary is machine-generated.

Systemic sclerosis (SSc) prevalence varies by age, sex, and region. Combining multiple data sources with statistical adjustments is crucial for accurate population-based SSc studies, as individual case ascertainment methods lack sensitivity.

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Area of Science:

  • Epidemiology
  • Rheumatology
  • Health Informatics

Background:

  • Systemic sclerosis (SSc) is a complex autoimmune disease with poorly understood population prevalence.
  • Accurate estimation of SSc prevalence is essential for public health planning and resource allocation.
  • Existing administrative data may have limitations in comprehensively identifying SSc cases.

Purpose of the Study:

  • To estimate the population prevalence of systemic sclerosis (SSc) in Quebec using administrative health databases.
  • To evaluate the sensitivity and effectiveness of different case ascertainment algorithms for identifying SSc cases.
  • To identify demographic and geographic factors influencing SSc prevalence.

Main Methods:

  • Utilized physician billing and hospitalization databases covering approximately 7.5 million individuals in Quebec.
  • Compared three distinct case definition algorithms for SSc ascertainment.
  • Employed a hierarchical Bayesian latent class regression model to account for imperfect case ascertainment and estimate prevalence, adjusting for data source dependencies and patient characteristics.

Main Results:

  • Estimated SSc prevalence in 2003 at 74.4 per 100,000 women and 13.3 per 100,000 men, with higher rates in older individuals and urban women.
  • Observed significant variations in prevalence by age, sex, and geographic region (e.g., lowest in young men in rural areas).
  • Found that individual case ascertainment algorithms had limited sensitivity, with point estimates ranging from 20-73%.

Conclusions:

  • Systemic sclerosis prevalence differs significantly across demographic and geographic subgroups.
  • No single administrative data-based ascertainment method is sufficiently sensitive for accurate SSc case identification.
  • Multi-source data utilization combined with statistical adjustments for ascertainment error is vital for robust population-based SSc research.