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Archetype Analysis Identifies Distinct Profiles in Renal Transplant Recipients with Transplant Glomerulopathy Associated with Allograft Survival
- Source :
- Clinical journal of the American Society of Nephrology, 30(4), 625-639. American Society of Nephrology
- Publication Year :
- 2019
- Publisher :
- Ovid Technologies (Wolters Kluwer Health), 2019.
-
Abstract
- Background Transplant glomerulopathy, a common glomerular lesion observed after kidney transplant that is associated with poor prognosis, is not a specific entity but rather the end stage of overlapping disease pathways. Its heterogeneity has not been precisely characterized to date. Methods Our study included consecutive kidney transplant recipients from three centers in France and one in Canada who presented with a diagnosis of transplant glomerulopathy (Banff cg score ≥1 by light microscopy), on the basis of biopsies performed from January of 2004 through December of 2014. We used an unsupervised archetype analysis of comprehensive pathology findings and clinical, immunologic, and outcome data to identify distinct groups of patients. Results Among the 8207 post-transplant allograft biopsies performed during the inclusion period, we identified 552 biopsy samples (from 385 patients) with transplant glomerulopathy (incidence of 6.7%). The median time from transplant to transplant glomerulopathy diagnosis was 33.18 months. Kidney allograft survival rates at 3, 5, 7, and 10 years after diagnosis were 69.4%, 57.1%, 43.3%, and 25.5%, respectively. An unsupervised learning method integrating clinical, functional, immunologic, and histologic parameters revealed five transplant glomerulopathy archetypes characterized by distinct functional, immunologic, and histologic features and associated causes and distinct allograft survival profiles. These archetypes showed significant differences in allograft outcomes, with allograft survival rates 5 years after diagnosis ranging from 88% to 22%. Based on those results, we built an online application, which can be used in clinical practice on the basis of real patients. Conclusions A probabilistic data-driven archetype analysis approach applied in a large, well defined multicenter cohort refines the diagnostic and prognostic features associated with cases of transplant glomerulopathy. Reducing heterogeneity among such cases can improve disease characterization, enable patient-specific risk stratification, and open new avenues for archetype-based treatment strategies and clinical trials optimization.
- Subjects :
- Adult
Graft Rejection
Male
medicine.medical_specialty
Time Factors
Biopsy
030232 urology & nephrology
Disease
030230 surgery
Kidney
Risk Assessment
Severity of Illness Index
Young Adult
03 medical and health sciences
Glomerulonephritis
0302 clinical medicine
Clinical Research
Internal medicine
Humans
Medicine
Stage (cooking)
Kidney transplantation
medicine.diagnostic_test
business.industry
Incidence (epidemiology)
Graft Survival
Transplant glomerulopathy
Complement System Proteins
General Medicine
Middle Aged
Allografts
medicine.disease
Kidney Transplantation
Survival Rate
Clinical trial
Phenotype
Nephrology
Cohort
Kidney Failure, Chronic
Female
business
Software
Unsupervised Machine Learning
Subjects
Details
- ISSN :
- 15333450 and 10466673
- Volume :
- 30
- Database :
- OpenAIRE
- Journal :
- Journal of the American Society of Nephrology
- Accession number :
- edsair.doi.dedup.....5134ff2e421202d2ed500dae5227ac64