Primary IgA nephropathy (IgAN) is the most common form of glomerulonephritis in China and
the world. It is the main reason for Chinese young people's renal failure. The main
difficulties in clinical IgAN and treatment are 1) high clinical and prognostic
heterogeneity, the prognosis cannot be accurately predicted; 2) no clinically available
biomarkers, diagnosis is established by kidney biopsy; 3) The lack of specific treatment
methods. These lead 20-40% of IgAN patients to develop end-stage renal failure (ESRD)
after 10 to 20 years. Therefore, to improve clinical diagnosis, treatment, and scientific
research of IgAN, it is much-needed to establish high-quality long-term cohort study,
multi-center database, biobank, and conduct high-quality clinical research.
The incidence of IgAN in the Asia Pacific region is higher than in other regions, and
China is one of the countries with the highest incidence of IgAN in the world. Although
the number of IgAN patients in our country is vast and the clinical data and patient
sample resources are abundant, the clinical diagnosis and treatment are not standardized,
the follow-up rate is low, and the quality of clinical data is poor, which seriously
affect the development of related clinical research. Therefore, optimization and
integration of health care big data under careful top-level design is urgently needed.
Regarding IgAN, the Nephrology Department of Ruijin Hospital has been active in clinical
database construction and clinical biobank management and has carried out several
clinical and basic research. The world's largest IgAN cohort-CRPIGA cohort has been
established, all patients in the cohort are followed up in a standardized manner by
special personnel, and the data is recorded in a clinical database in real-time. However,
optimization and integration of health care big data under careful top-level design is
urgently needed. It is to establish IgAN specific disease structured data set standard in
a multi-center linkage mode, formulate IgAN diagnosis and treatment specifications and
clinical pathway standards, develop structured clinical case diagnosis and treatment
information collection template, real-time scrape the actual clinical IgAN diagnosis and
treatment data of various hospitals through the big data platform of health care
consortium, clean and structure the acquired data, establish a multi-center structured
database, integrate resources, strengthen advantages, and provide a qualified database
for clinical research in the real world. All diagnosis and treatment data for the same
patient are linked and integrated to offer individual patient-based longitudinal tracking
records and support evidence-based medicine.
This study aims to improve the scale and quality of the IgAN multi-center cohort
database, advance the clinical and basic research of IgAN, standardize and optimize the
clinical diagnosis and treatment path of IgAN, provide more effective and safe treatment
options for more IgAN patients and also provide evidence-based medicine evidence support.