Renal Interstitial Fibrosis: An Imperfect Predictor of Kidney Disease Progression in Some Patient Cohorts

Abstract

Background: The extent of interstitial fibrosis on kidney biopsy is regarded as a prognostic indicator and guide to treatment. Patients with extensive fibrosis are assigned to supportive treatments with the expectation that they have advanced beyond the point at which immunosuppressive or other disease-modifying therapies would be of benefit. Our study highlights some of the limitations of using interstitial fibrosis to predict who will develop end-stage renal disease (ESRD).

Methods: Analysis of 434 consecutive renal biopsies performed between 2001 and 2012 at a single center. We assessed the influence of various clinical factors along with fibrosis as predictors of ESRD and dialysis-free survival in various patient groups.

Results: Interstitial fibrosis performed well overall as a predictor of progression to dialysis. On average, patients with >50% fibrosis progressed more rapidly than those with either 25-49 or 0-24% fibrosis with a median time to dialysis of 1.2, 6.5 and >10 years, respectively. In contrast, interstitial fibrosis was of less value as a predictor of disease progression in a subset of cases that included patients over the age of 70 and those with diabetic nephropathy on biopsy. Surprisingly, 13.9% of patients with normal renal function had 25-49% fibrosis and 5% had more than 50% fibrosis on biopsy, and 5 years after undergoing biopsy 21% of patients with >50% fibrosis still remained dialysis free.

Conclusion: Renal fibrosis is an imperfect prognostic indicator for the development of ESRD and caution should be exercised in applying it too rigidly, especially in elderly or diabetic patients.

Figure 1. Correlation between GFR and degree of fibrosis

A. Percentage of fibrosis according to GFR levels. B. A scatter plot of the overall cohort mapping the association of GFR with percent fibrosis. Each dot represents a single patient. (GFR, Glomerular Filtration Rate).

Figure 2. Dialysis prediction model

Parsimonious prediction model for reaching dialysis. See Methods for a detailed description of the prediction model development. 2A: Dialysis prediction model using 6 variables: parsimonious 0.2 level (left panel) and receiver operator curve for 6 variable model predicting dialysis (right panel) (variables included: BMI, percentage of interstitial fibrosis, creatinine, proteinuria, HTN, IDDM). (AUC, area under the curve; BMI, Body Mass Index; GFR, Glomerular Filtration Rate; HTN, hypertension; IDDM, insulin dependent diabetes; CAD, coronary artery disease; DM, diabetes mellitus; IgA, Immunoglobulin A; DM, diabetes mellitus; IgA, Immunoglobulin A). 2B. Interstitial fibrosis alone dialysis prediction model (left panel) and receiver operator curve (ROC) for dialysis prediction model using interstitial fibrosis only.

Fig 3

Kaplan-Meier analysis of time-to-dialysis according to the level of interstitial fibrosis.

Fig 4. Correlation between fibrosis and time to dialysis

A scatter plot of the overall cohort mapping the association of percentage fibrosis and time to dialysis. Each dot represents a single patient.