Ascertainment of chronic diseases in the Canadian longitudinal study on aging (CLSA), systematic review

Area of Science:

• Epidemiology
• Biostatistics
• Gerontology

Background:

• Standard clinical diagnostic procedures are often infeasible for large-scale population studies.
• Accurate disease status ascertainment is critical for epidemiological research and health surveillance.
• The Canadian Longitudinal Study on Aging (CLSA) requires robust methods for chronic disease assessment.

Purpose of the Study:

• To systematically review algorithms, criteria, and tools for ascertaining 17 chronic diseases.
• To assess the feasibility of developing disease ascertainment algorithms for the CLSA.
• To identify necessary tools for creating reliable disease ascertainment algorithms.

Main Methods:

• Conducted a systematic literature review of 29,616 citations.
• Included 668 papers that met all inclusion criteria for disease ascertainment methods.
• Analyzed the types of data required for different chronic disease categories.

Main Results:

• Disease ascertainment information varies significantly by condition type.
• Symptomatic conditions (e.g., osteoarthritis, arthritis) require clinical substantiation (e.g., imaging).
• Asymptomatic conditions (e.g., hypertension) necessitate physiologic and laboratory measures, while others (e.g., depression) may rely on self-report.

Conclusions:

• Disease ascertainment algorithms must be tailored to specific chronic conditions.
• A combination of self-report, clinical criteria, physiologic measures, and laboratory data is often required.
• This study identified essential tools and approaches for developing effective disease ascertainment algorithms for population studies like the CLSA.