Association of Age With Risk of Kidney Failure in Adults With Stage IV Chronic Kidney Disease in Canada

This cohort study examines the competing risks of death and kidney failure in an aging population with or without age-related comorbid conditions.


Study design and data sources
We conducted a population-based cohort study, using linked administrative and laboratory provincial data from Alberta, Canada (Alberta Health database). [1][2][3][4][5] The Alberta Health database contains information on demographic data, vital statistics, and diagnostic and procedural information for inpatient and outpatient physician services. All data were available from May 1, 2002until March 31, 2017. Information about the receipt of renal replacement was available from April 1, 1994. Over 99% of Alberta residents are registered with Alberta Health and have universal access to hospital care, laboratory testing and physician services. The institutional review boards at the Universities of Alberta (Pro00053469) and Calgary (REB16-1575) approved this study and waived the requirement for participants to provide consent.

Methods to calculate eGFR to define cohort entry and kidney failure
Cohort entry.
Moving average: Starting on the date of the first eGFR <30 ml/min/1.73 m 2 , we determined the average eGFR over a period of >90 days provided that there were at least 2 outpatient measurements to calculate the mean. 6 Individuals with only one eGFR <30 ml/min/1.73 m 2 or with two values of eGFR <30 ml/min/1.73 m 2 recorded within 90 days were excluded. We used the minimum value of eGFR when there were multiple measurements on the same day. Participants met the criterion for stage 4 CKD when the average eGFR during this period was between 15 and <30 ml/min/1.73 m 2 . We used the date of the last eGFR measurement included in the calculation of the average (index eGFR) to define cohort entry (index date).

Kidney failure.
Moving average (main analyses): Starting on the date of the first eGFR <10 ml/min/1.73 m 2 , we determined the average of at least two inpatient or outpatient eGFR measurements made over a period of >90 days, using the minimum value of eGFR when there were multiple measurements on the same day. We used the date of the last eGFR measured during this period to define the event date.
Individuals with only one eGFR <10 ml/min/1.73 m 2 or with two values of eGFR <10 ml/min/1.73 m 2 recorded within 90 days remained event-free (at risk); if they died after a single eGFR <10 ml/min/1.73 m 2 they were classified as dead.

Sustained reduction (sensitivity analyses):
We defined sustained eGFR<10 ml/min/1.73 m 2 by the occurrence of ≥2 consecutive eGFR values <10 ml/min/1.73m 2 over a period of >90 days. We used the ©2020 Ravani P et al. JAMA Network Open date of the last eGFR in the first episode of sustained eGFR measurements <10 ml/min/1.73 m 2 as the event date. Individuals with only one eGFR <10 ml/min/1.73 m 2 or with two values of eGFR <10 ml/min/1.73 m 2 recorded within 90 days remained event-free (at risk); if they died after a single eGFR <10 ml/min/1.73 m 2 they were classified as dead.
The threshold of <10 ml/min/1.73 m 2 allows for separation of the value defining cohort entry and the value defining the outcome. According to the Canadian registry of organ replacement, the mean eGFR at dialysis start has been between 9.5 and 10 ml/min/1.73 m 2 between 2002 and 2012. 7

Independent variables, exposure and outcomes
We considered demographics and other characteristics that are associated with death or kidney failure: lower index eGFR, more severe albuminuria, diabetes and cardiovascular disease. The latter was defined as one or more of congestive heart failure, myocardial infarction, stroke or transient ischemic attack, or peripheral vascular disease (amputation or peripheral revascularization). We used validated coding algorithms applied to physician claims and hospitalization data to define comorbidities based on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) and International Statistical Classification of Diseases, Tenth Revision (ICD-10). 8 We used the most recent albuminuria values (on or within the two years preceding the index date), with the following types of measurement in descending order of preference: albumin-to-creatinine ratio, protein-to-creatinine ratio, and urine dipstick. We categorized albuminuria as normal, moderate, severe, or unmeasured. 9

Statistical analysis details
We used standard methods for qualitative data (frequencies) and quantitative data (mean/standard deviation) to summarize baseline information and competing risk analysis to estimate risks. 10 Cumulative incidence functions. We estimated the crude and adjusted cumulative incidence functions of kidney failure and death without kidney failure and their 95% confidence intervals (CI) across age categories. 11 The cumulative incidence function (CIF) is the probability of failing from a specific cause k at time t. We obtained adjusted cumulative incidence functions for each event indirectly from a cause-specific hazard model of both kidney failure and death. 11 We used plots to summarize the crude and model-based cumulative incidence functions. 10,12 Model building and checking. We used cause-specific Cox regression to model both cause-specific hazard functions simultaneously and derive cause-specific CIFs indirectly. We adjusted all models for ©2020 Ravani P et al. JAMA Network Open sex, eGFR, albuminuria category, diabetes and presence of cardiovascular disease, and tested all possible first-order interactions among these variables. We used fractional polynomials, spline functions and martingale residuals analyses to assess the form of the relationship between continuous covariates and outcome. We used residual analyses to identify deviations from proportionality assumption, influential observations and outliers, and for assessment of goodness-of-fit. During model building we checked that results were consistent across study time.
Second, we defined kidney failure solely by initiation of renal replacement, defined as receipt of a kidney transplant or registration in the provincial database of chronic dialysis. Third, we restricted the analyses to complete cases for albuminuria (excluding those with unmeasured values