The Canadian Glomerulonephritis Registry (CGNR) and Translational Research Initiative: Rationale and Clinical Research Protocol

Evaluating Progression Risk in Patients With Immunoglobulin A Nephropathy

The highly variable rate of decline in kidney function in patients with immunoglobulin A nephropathy (IgAN) provides a major clinical challenge. Predicting which patients will progress to kidney failure, and how quickly, is difficult. Multiple novel therapies are likely to be approved in the short-term, but clinicians lack the tools to identify patients most likely to benefit from specific treatments at the right time. Noninvasive and validated markers for selecting at-risk patients and longitudinal monitoring are urgently needed. This review summarizes what is known about demographic, clinical, and histopathologic prognostic markers in the clinician's toolkit, including the International IgAN Prediction Tool. We also briefly review what is known on these topics in children and adolescents with IgAN. Although helpful, currently used markers leave clinicians heavily reliant on histologic features from the diagnostic kidney biopsy and standard clinical data to guide treatment choice, and very few noninvasive markers reflect treatment efficacy over time. Novel prognostic and predictive markers are under clinical investigation, with considerable progress being made in markers of complement activation. Other areas of research are the interplay between gut microbiota and galactose-deficient IgA1 expression; microRNAs; imaging; artificial intelligence; and markers of fibrosis. Given the rate of therapeutic advancement, the remaining gaps in biomarker research need to be addressed. We finish by describing our route to clinical utility of predictive and prognostic markers in IgAN. This route will provide us with the chance to improve IgAN prognosis by using robust, clinically practical markers to inform patient care.

Knowledge Translation in Glomerulonephritis: Successes in Translational Research From the Bench to Bedside

Purpose of review

Glomerulonephritis refers to a rare group of diseases characterized by glomerular inflammation, which collectively are a common cause of kidney failure. Until recently, there was a lack of high-quality clinical trials to inform the care of patients with glomerulonephritides. We identified examples of successful translational research spanning from basic science to clinical applications, and highlight gaps in implementation science.

Sources of information

The focus of our review was derived from discussions between health care professionals, researchers, and patient partners. We also performed literature searches pertaining to the treatment of glomerulonephritis in PubMed and Google Scholar.

Methods

Examples of successful knowledge translation were generated through review of new evidence in the past 5 years and by iterative discussions by the authors. We then conducted a narrative review of several themes related to knowledge translation in glomerulonephritis. This was complemented by an interview with a patient partner to provide an example of a patient's perspective living with glomerulonephritis.

Key findings

We summarized selected recent advances in glomerulonephritis and its knowledge translation in the following domains: (1) identification of auto-antibodies in membranous nephropathy and minimal change disease; (2) clinical trials of novel targeted therapies for IgA nephropathy and lupus nephritis, which have led to approval of new treatments; (3) developments in research networks and clinical trials in glomerulonephritis; (4) recognition of the importance in developing standardized patient reported outcome measures in clinical trials; and (5) barriers in knowledge translation including access to medication.

Limitations

A systematic search of the literature and formal assessment of quality of evidence were beyond the scope of this review.

Indian TrANslational GlomerulonephrItis BioLogy nEtwork (I-TANGIBLE): Design and Methods

Background and Aim

Primary glomerular disease accounts for one-sixth of all chronic kidney diseases (CKDs) in India. We remain limited in our ability to effectively treat these conditions because of lack of understanding of the disease mechanisms and lack of predictors to identify the clinical course and therapeutic responsiveness. We propose to develop a network of investigators in glomerular diseases, collect information in a systematic fashion to understand the clinical outcomes, answer translational research questions better, and identify and recruit patients for clinical trials.

Materials and Methods

This is a prospective, observational study. The Indian TrANslational GlomerulonephrItis BioLogy nEtwork (I-TANGIBLE) cohort will enroll patients (>18 years) with biopsy-proven minimal change disease (MCD), focal segmental glomerulonephritis (FSGS), membranous nephropathy (MN), IgA nephropathy (IgAN), or membranoproliferative glomerulonephritis (MPGN) (immune complex- and complement-mediated), with first biopsy taken within 2 years of enrollment. Patients with estimated glomerular filtration (eGFR) rate <15 ml/min/1.73 m2 for >3 months at the time of screening, kidney transplant or bone marrow transplant recipients, patients with active malignancy, and patients with active hepatitis B/C replication or human immunodeficiency virus (HIV)-I/II will be excluded. Clinical details including history, medication history and details, and family history will be obtained. Consenting patient's blood and urine samples will be collected and stored, aligned to their clinical follow-up.

Expected Outcomes

The network will allow accurate ascertainment of disease burden of glomerular diseases across study sites, establishment of the treatment pattern of common glomerular diseases, investigation of medium- and long-term outcomes (remission, relapse, rate of eGFR decline), and building a suitable infrastructure to carry out clinical trials in primary glomerular disease.

The Development of a Comprehensive Clinicopathologic Registry for Glomerular Diseases Using Natural Language Processing

Background

Glomerulonephritis (GN) represents a common cause of chronic kidney disease, and treatment to slow or prevent progression of GN is associated with significant morbidity. Large patient registries have improved the understanding of risk stratification, treatment selection, and definitions of treatment response in GN, but can be resource-intensive, with incomplete patient capture.

Objective

To describe the creation of a comprehensive clinicopathologic registry for all patients undergoing kidney biopsy in Manitoba, using natural language processing software for data extraction from pathology reports, as well as to describe cohort characteristics and outcomes.

Design

Retrospective population-based cohort study.

Setting

Tertiary care center in the province of Manitoba.

Patients

All patients undergoing a kidney biopsy in the province of Manitoba from 2002 to 2019.

Measurements

Descriptive statistics are presented for the most common glomerular diseases, along with outcomes of kidney failure and mortality for the individual diseases.

Methods

Data from native kidney biopsy reports from January 2002 to December 2019 were extracted into a structured database using a natural language processing algorithm employing regular expressions. The pathology database was then linked with population-level clinical, laboratory, and medication data, creating a comprehensive clinicopathologic registry. Kaplan-Meier curves and Cox models were constructed to assess the relationship between type of GN and outcomes of kidney failure and mortality.

Results

Of 2421 available biopsies, 2103 individuals were linked to administrative data, of which 1292 had a common glomerular disease. The incidence of yearly biopsies increased almost 3-fold over the study period. Among common glomerular diseases, immunoglobulin A (IgA) nephropathy was the most common (28.6%), whereas infection-related GN had the highest proportions of kidney failure (70.3%) and all-cause mortality (42.3%). Predictors of kidney failure included urine albumin-to-creatinine ratio at the time of biopsy (adjusted hazard ratio [HR] = 1.43, 95% confidence interval [CI] = 1.24-1.65), whereas predictors of mortality included age at the time of biopsy (adjusted HR = 1.05, 95% CI = 1.04-1.06) and infection-related GN (adjusted HR = 1.85, 95% CI = 1.14-2.99, compared with the reference category of IgA nephropathy).

Limitations

Retrospective, single-center study with a relatively small number of biopsies.

Conclusions

Creation of a comprehensive glomerular diseases registry is feasible and can be facilitated through the use of novel data extraction methods. This registry will facilitate further epidemiological research in GN.