Research challenge
IgA nephropathy (IgAN) is the most common primary glomerulonephritis worldwide, yet its natural history and treatment impact are poorly understood outside of specialized registries.
In most real-world data sources, diagnosis codes (such as ICD‑10), while useful for standardizing disease classification, often lack the granularity needed to capture the full clinical complexity of certain conditions. Many codes group together diverse subtypes or stages of a disease, which can lead to oversimplification in medical records and research. Because coding relies on documentation and interpretation rather than direct biological evidence, the most definitive way to confirm a diagnosis is through pathological examination which can identify specific cellular changes and disease markers that coding alone cannot capture. This ensures diagnostic accuracy, and thus, reliable cohort selection for observational research.
Our approach
Using the PHARMO Data Network, we conducted a comprehensive IgAN study that:
- Identified IgAN patients using results from pathology records, ensuring high specificity
- Linked laboratory datasets to capture longitudinal estimated glomerular filtration rate (eGFR) and proteinuria measurements—values rarely observed in non-specialist real-world sources
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