Kidney disease progression and the factors influencing progressive loss of kidney function in a primary care population. A retrospective database analysis

Conference:

SAPC ASM 2019 - Exeter

Talk Code:

2B.4c

Presenter:

Jason Oke

Twitter:

@oke_jason

Co-authors:

Jason Oke, Benjamin Feakins, Iryna Schlackow, Borislava Mihaylova, Claire Simons, Chris O’Callaghan, Daniel Lasserson, Richard Hobbs, Richard Stevens, Rafael Perera.

Author institutions:

Nuffield Department of Primary Care Health Sciences University of Oxford, Nuffield Department of Population Health University of Oxford, Nuffield Department of Medicine University of Oxford, Institute of Applied Health Research University of Birmingham

Problem

Monitoring kidney function using estimated glomerular filtration rate (eGFR) is recommended in people with, or at risk of, chronic kidney disease (CKD). Current guidelines suggest increasing the intensity of monitoring according to eGFR, urine albumin levels, comorbidities and changes in therapy, but the evidence base is weak. To inform recommendations for the timing of eGFR monitoring in primary care, we set out to create a statistical model for kidney disease progression and the factors influencing this progressive loss of kidney function in a primary care population.

Approach

We used the Clinical Practice Research Practice Datalink (CPRD) to construct an open cohort study of all adult patient records from April 2005 to March 2014. Patients were eligible for inclusion if they had three or more serum creatinine tests on record. We excluded patients who, in the 12 months before study entry, were pregnant, had a renal transplant, were receiving dialysis, or were living kidney donors. Follow-up ended at the study end date, unless preceded by death, transfer out of CPRD, pregnancy, renal transplantation/donation, or dialysis. To model kidney function over time, a hidden Markov model (HMM) was fitted to four cohorts of patients based on their baseline albuminuria status. The HMM estimates the relationship between observed values of eGFR and the unobserved values of GFR over time. Models were adjusted for annually updated age, sex, read codes for chronic heart failure or cancer at baseline. The average time spent in stage 3b (the sojourn time) and five and ten year risks of renal failure (eGFR < 15 ml/min/1.73^2) and all-cause death are presented.

Findings

Of 1,973,064 patients, 1,921,949 had no recorded urine albumin at baseline, 37,946 had tested and normal urine albumin levels (< 3 mg/mmol), 10,247 had microalbuminuria (3 – 30 mg/mmol) and 2,922 had macroalbuminuria (> 30 mg/mmol) at baseline. The sojourn time (95% C.I.) in stage 3b CKD was 25.1 (22.3 to 27.1) years for patients with untested urine albumin, 15.7 (14.6 to 16.8) years in patients with normal urine albumin, 7.3 (6.7 to 8.1) years for patients with microalbuminuria and 4.5 (3.9 to 5.3) years in patients with macroalbuminuria. For a male, age 60, with eGFR 45-59 ml/min/1.73^2 the five-year risk (95% CI) of end-stage renal failure is 0.017 (0.012 to 0.026)% and the 10 year risk 0.1 (0.07 to 0.15)%, whereas the 5 and 10 year risk of death is 6.8 (6.1 to 7.6)% and 13.5 (12.3 to 14.8)%.

Consequences

Our findings have implications for scheduling appointments for monitoring eGFR. As true change in kidney function is slow, monitoring intervals should be extended for low-risk groups. This model will combine with a cost-effectiveness analysis to provide evidence-based recommendations for monitoring eGFR in primary care.

Submitted by:

Jason Oke

Funding acknowledgement:

This article presents independent research funded by the National Institute for Health Research (NIHR) under the programme grants for applied research programme (RP-PG-1210-12003). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health and Social Care.