Trends in Incidence of ESKD in People With Type 1 and Type 2 Diabetes in Australia, 2002-2013

Original Investigation

Trends in Incidence of ESKD in People With Type 1 and Type 2 Diabetes in Australia, 2002-2013 Digsu N. Koye, Dianna J. Magliano, Christopher M. Reid, Meda E. Pavkov, Steven J. Chadban, Stephen P. McDonald, Kevan R. Polkinghorne, Sarah White, Christine Paul, and Jonathan E. Shaw Rationale & Objective: The number of people with diabetes and end-stage kidney disease (ESKD) is increasing worldwide, but it is unknown whether this indicates an increasing risk for ESKD in people with diabetes. We examined temporal trends in the incidence of ESKD within the Australian population with diabetes from 2002 to 2013. Study Design: Follow-up study using a national health care services registry. Setting & Participants: Registrants with type 1 or type 2 diabetes in Australia’s National Diabetes Services Scheme (NDSS). Predictors: Age, sex, indigenous status, diabetes type, and calendar year. Outcome: Incidence of ESKD (dialysis or kidney transplantation) or death ascertained using the Australian and New Zealand Dialysis and Transplant Registry and the Australian national death index. Analytical Approach: NDSS registrants were followed up from 2002 or date of registration until onset of ESKD, death, or December 31, 2013. The incidence of ESKD in type 1 diabetes was calculated only in those younger than 55 years.

I

Results: Among 1,375,877 registrants between 2002 and 2013, a total of 9,977 experienced incident ESKD, representing an overall incidence of ESKD in people with diabetes of 10.0 (95% CI, 9.8-10.2) per 10,000 person-years. Among those with type 1 diabetes, the age-standardized annual incidence was stable during the study period. Among those with type 2 diabetes, the incidence increased in nonindigenous people (annual percentage change, 2.2%; 95% CI, 0.4%-4.1%) with the greatest increases in those younger than 50 and those older than 80 years. No significant change over time was observed in indigenous people, although the adjusted incident rate ratio for indigenous versus nonindigenous was 4.03 (95% CI, 3.68-4.41).

Correspondence to D.N. Koye (digsu.koye@ baker.edu.au) Am J Kidney Dis. XX(XX): 1-9. Published online Month X, XXXX. doi: 10.1053/ j.ajkd.2018.10.005

© 2018 by the National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

Limitations: Lack of covariates such as comorbid conditions, medication use, measures of quality of care, and baseline kidney function. Conclusions: The age-standardized annual incidence of ESKD increased in Australia from 2002 to 2013 for nonindigenous people with type 2 diabetes but was stable for people with type 1 diabetes. Efforts to prevent the development of ESKD, especially among indigenous Australians and those with earlyonset type 2 diabetes, are warranted.

n most developed countries, diabetes is now the leading cause of end-stage kidney disease (ESKD) and is often responsible for >40% of new cases of ESKD.1 There have been significant declines in age-standardized rates of cardiovascular events, mortality, and amputations in people with diabetes.2-6 However, a US study found that declines in the incidence of ESKD have been far more modest.7 It is probable that improvements in diabetes management for the secondary prevention of ESKD have been offset by the reduction in competing risks for mortality; that is, persons with diabetes are living longer, increasing their chance of developing ESKD during their life course. At the same time, early-onset type 2 diabetes mellitus (T2DM) has become more common (also increasing the lead time for developing ESKD),8 while willingness to treat diabetesrelated ESKD with dialysis and transplantation has increased.9 Standalone kidney disease registries report the annual incidence of ESKD with an underlying diagnosis of diabetic nephropathy.10,11 However, because registries report incidence relative to the general population, incidence trends cannot be distinguished from the AJKD Vol XX | Iss XX | Month 2018

Complete author and article information provided before references.

underlying dynamics of the diabetes population. To properly understand temporal trends in renal outcomes in the diabetes population, it is necessary to calculate ESKD incidence in a population-representative diabetes cohort. For this analysis, we linked the National Diabetes Services Scheme (NDSS), a near-complete registry of diagnosed diabetes cases in Australia, with the Australian and New Zealand Dialysis and Transplant Registry (ANZDATA) and identified all incident ESKD cases from 2002 to 2013. Our aim was to examine temporal trends in the incidence of ESKD among the Australian diabetes population, looking for any variation in incidence by age group, sex, diabetes type, socioeconomic disadvantage, or geographic remoteness. Methods Data Sources The NDSS was established in 1987 by the Australian government to provide testing strips, syringes, and needles at subsidized prices to people with diabetes; 80% to 90% of all people with diabetes in Australia are 1

Original Investigation listed on the registry.12 Registration of patients is completed by a medical practitioner or accredited diabetes nurse educator. In this study, we included people with T1DM and T2DM who were listed on the NDSS between 2002 (data quality was a problem before 2002) and 2013, including all listed cases as of January 1, 2002, and all cases newly listed between January 1, 2002, and December 31, 2013. In the NDSS database, diabetes type is classified by the health practitioner at the time of registration. However, for the current analysis, T1DM status was assigned to all registrants who were recorded as having T1DM on the NDSS registry and were also taking insulin within 1 year of diagnosis. If time to insulin use was missing, those who were given the diagnosis before the age of 30 years and were taking insulin at registration were classified as having T1DM. If date of diagnosis was missing, those who were registered at age younger than 45 years and were taking insulin at registration were classified as having T1DM. Additionally, registrants who were recorded as having T2DM on the registry and were given the diagnosis before the age of 30 years and were taking insulin within 1 year of diagnosis were reclassified as T1DM. All others were classified as T2DM.2 In a sensitivity analysis, we used the original health practitioner classification. All registrants were mapped to area-based disadvantage indexes, the Accessibility/Remoteness Index of Australia (ARIA) and the Socio-Economic Indexes for Areas (SEIFA), based on postcode at NDSS registration. ARIA categorizes residential postcode into major urban, inner regional, outer regional, remote, and very remote areas according to distance from major service centers. For these analyses, remote and very remote categories (collectively, 2% of the population) were collapsed into 1 category. The SEIFA Index of Relative Socio-Economic Advantage Disadvantage (IRSAD) is calculated for more than 33,000 census collection districts in Australia, using census data on a range of socioeconomic variables, including income, education, employment, occupation, and housing. For this analysis, scores were divided into quintiles.13 Registrants of the NDSS from 2002 to 2013 were matched to ANZDATA and the National Death Index (NDI) for ESKD incidence (dialysis or preemptive kidney transplantation) and mortality outcomes, respectively. ANZDATA records incidence of and outcomes for patients in Australia and New Zealand treated with dialysis or kidney transplantation. All renal units in Australia contribute to ANZDATA, which is essentially 100% complete. The primary cause of kidney disease is recorded by the treating hospitals according to the modified European Renal Association–European Dialysis and Transplant Association (ERA-EDTA) coding system.14 ANZDATA data beyond 2013 were not available at the time of linkage. We only had access to Australian data in the registry. The NDI contains records of all deaths registered in Australia since 1980. Linkages to collect vital status use 2

probabilistic matching elsewhere.15,16

techniques

as

described

Data Analysis NDSS registrants were followed up from January 1, 2002, or date of registration, if later, until onset of ESKD, death, or end of follow-up on December 31, 2013. After we split the data into 10-year age bands and calendar year using the stsplit command in Stata 14 (StataCorp), we used the strate command to estimate crude incidence rates. Crude incidence rates of ESKD were calculated by dividing the total number of new cases of ESKD, irrespective of ESKD cause, registered in ANZDATA in a given year by total personyears of follow-up with diabetes at risk. Calculated incidence rates were expressed per 10,000 person-years at risk with 95% confidence intervals (CIs). Rates were reported for T1DM, T2DM, and all diabetes, separately by calendar year. Standardized rates were derived by applying the agespecific rates observed in the NDSS population to the 2008 Australian population (using dstdize command). Because of the way we defined diabetes, the number of people with T1DM older than 55 years (current age at a given year that we studied) was very small (n = 7,203) in the early years of the period analyzed in this study. Therefore, in the main analysis, the incidence of ESKD in T1DM was reported only in those younger than 55 years (n = 85,800). Those who had T1DM were censored when they reached age 55 years. Age groups were categorized as younger than 40 and 40 to 54 years in T1DM. For T2DM, age groups were categorized as younger than 50, 50 to 59, 60 to 69, 70 to 79, and 80 years or older. For reporting age-specific rates or age-standardized rates, current age at a given year was used. Registrants with missing age, sex, or type of diabetes (n = 115) were excluded from all analyses. Those with missing SEIFA (0.6%), ARIA (0.5%), and indigenous status (8.3%) were excluded only from analyses using the missing variable. Poisson regression models (adjusted for age, sex, indigenous status, SEIFA, and ARIA) were used to calculate incidence rate ratios by diabetes type, sex, indigenous status, ARIA, and SEIFA. To examine annual ESKD incidence trends over time, we used Joinpoint Regression software, version 4.5.0.1 (National Cancer Institute). This determines the number of linear segments needed to describe a trend, identifies points at which linear trends change, and computes annual percentage changes.17 To determine whether there were changes over time in estimated glomerular filtration rates (eGFRs) at dialysis therapy commencement, eGFR was calculated from ANZDATA registration details using a 4-variable variant of the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) creatinine equation, without considering the race/ethnicity of participants. In secondary analyses, we also included deaths with kidney failure–related cause of death from the NDI as cases to partially account for people who developed kidney AJKD Vol XX | Iss XX | Month 2018

Original Investigation failure but did not undergo dialysis or transplantation. A kidney failure–related death was defined as a person who died with chronic kidney failure (International Classification of Diseases, Tenth Revision [ICD-10] codes N18.0, N18.5, N18.8, and N18.9), hypertensive kidney failure (ICD-10 codes I12.0, I13.1, and I13.2), or unspecified kidney failure (ICD-10 code N19) as the underlying cause of death or who had chronic kidney failure, end-stage (ICD-10 codes N18.0 and N18.5) as an associated cause of death.18,19 This study was approved by the Alfred Hospital Ethics Committee (Project No: 15/15) and the Australian Institute of Health and Welfare (AIHW) Ethics Committee (EO 2015/1/148). We received a waiver of consent for this project from the respective ethics committees. Results Participant Characteristics A total of 93,003 individuals with T1DM and 1,282,874 individuals with T2DM were included in this analysis. Their characteristics are described in Table 1. Incidence of ESKD in People With Diabetes Between 2002 and 2013, a total of 9,977 incident ESKD cases (who underwent either dialysis therapy or preemptive kidney transplantation) occurred during 10,017,538 person-years of follow-up. The overall crude

incidence of ESKD in people with diabetes was 10.0 (95% CI, 9.8-10.2) per 10,000 person-years. Crude incidence rates were 16.4 and 9.1 (95% CI, 8.9-9.3) per 10,000 person-years in the T1DM and T2DM groups, respectively (Table 2). ESKD incidence was higher in T1DM than T2DM, in males than females, in indigenous than nonindigenous people, in those living in the most disadvantaged quintile of areas than those in the least disadvantaged, and in those who live in remote and very remote areas of Australia than those living in major cities (Table 3). Temporal Trends in Incidence of ESKD The annual number of ESKD cases in people with diabetes doubled from 528 in 2002 to 1,084 in 2013. However, the age-standardized annual incidence rate of ESKD during this period was stable (annual percentage change, 1.5%; 95% CI, −0.3% to 3.3%). In T1DM, the age-standardized annual incidence rate was stable (annual percentage change, −0.5%; 95% CI, −2.9% to 1.9%). In contrast, in T2DM, the annual incidence of ESKD increased during the 12 years (annual percentage change, 4.5%; 95% CI, 1.9%7.1%; Table S1). Trends in incidence of ESKD by diabetes type, age group, sex, and indigenous status are shown in Figure 1A to E. When we further stratified the incidence of ESKD in T1DM by age group, the rate of ESKD was fairly stable in

Table 1. Characteristics of the NDSS Population Between 2002 and 2013 by Diabetes Type T1DM a

No. of patients Male sex Median age at diagnosis, y Median age at registration, y Median follow-up, y Insulin use Indigenous people Country of birth by IDF region Australia/New Zealand Europe Other Western Pacific Middle East and North Africa South East Asia Others ARIA Major cities Inner regional Outer regional Remote and very remote SEIFA Most disadvantaged Least disadvantaged

Age < 55 y 85,800 (6.2%) 45,901 (53.5%) 17.9 [10.4-28.3] 24.7 [13.3-34.0] 9.8 [4.6-12.0] 85,800 (100%) 1,037 (1.3%)

Total 93,003 (6.8%) 49,987 (53.8%) 19.8 [11.0-30.9] 26.4 [14.1-36.7] 12.0 [6.4-12.0] 93,003 (100%) 1,086 (1.2%)

T2DM 1,282,874 (93.2%) 694,593 (54.1%) 58.3 [48.9-67.6] 60.7 [51.2-69.9] 7.3 [3.3-12.0] 409,353 (31.9%) 24,620 (2.1%)

Total 1,375,877 744,580 (54.1%) 57.5 [47.3-67.1] 59.5 [48.8-69.2] 7.5 [3.4-12.0] 502,356 (36.5%) 25,706 (2.0%)

22,515 (76.1%) 3,525 (11.9%) 1,122 (3.8%) 646 (2.2%) 620 (2.1%) 1,164 (3.9%)

24,333 (74.4%) 4,464 (13.7%) 1,268 (3.9%) 715 (2.2%) 668 (2.0%) 1,245 (3.8%)

398,706 (51.9%) 216,604 (28.2%) 72,236 (9.4%) 29,802 (3.9%) 29,865 (3.9%) 20,521 (2.7%)

423,039 (52.9%) 221,068 (27.6%) 73,504 (9.2%) 30,517 (3.8%) 30,533 (3.8%) 21,766 (2.7%)

59,088 (69.2%) 17,433 (20.4%) 7,450 (8.7%) 1,431 (1.7%)

63,795 (68.9%) 18,999 (20.5%) 8,247 (8.9%) 1,514 (1.6%)

846,682 (66.4%) 272,499 (21.4%) 130,526 (10.2%) 26,121 (2.1%)

910,477 (66.5%) 291,498 (21.3%) 138,773 (10.1%) 27,635 (2.0%)

13,507 (15.8%) 21,472 (25.2%)

14,970 (16.2%) 23,099 (25.0%)

267,873 (21.0%) 247,018 (19.4%)

282,843 (20.7%) 270,117 (19.8%)

Note: Unless otherwise indicated, data for continuous variables are median [interquartile range]; for categorical data, count (column percentage). Abbreviations: ARIA, Accessibility/Remoteness Index of Australia; IDF, International Diabetes Federation; NDSS, National Diabetes Services Scheme; SEIFA, Index of Relative Socioeconomic Advantage/Disadvantage; T1(2)DM, type 1 (2) diabetes melitus. a Percentage is of the 1,375,877 total.

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3

Original Investigation Table 2. Crude Incidence Rate of ESKD and Death in T1DM and T2DM Patients Between 2002 and 2013 ESKD

T1DM <55 y Total T2DM Total

Deaths

No. of Cases

Person-y

Incidence Rate per 10,000 Person-y (95% CI)

1,163 1,621 8,356 9,977

707,141 860,295 9,157,243 10,017,538

16.4 18.8 9.1 10.0

(15.5-17.4) (17.9-19.8) (8.9-9.3) (9.8-10.2)

No. of Cases

Person-y

Incidence Rate per 10,000 Person-y (95% CI)

2,965 6,399 233,980 240,379

711,515 866,796 9,182,961 10,049,757

41.7 73.8 254.8 239.2

(40.2-43.2) (72.0-75.7) (253.8-255.8) (238.2-240.2)

Abbreviations: CI, confidence interval; ESKD, end-stage kidney disease; T1(2)DM, type 1 (2) diabetes mellitus.

those younger than 40 years and those aged 40 to 54 years. The small number of ESKD events in some of the age categories precluded further stratification by sex and indigenous status. In T2DM, incidence was stable in indigenous people but increased in nonindigenous people (Table 4; Fig 1C). The annual percentage change was higher in the total T2DM population than in the nonindigenous T2DM population (4.5 vs 2.2). This is because of the 4-fold increase in number of indigenous people registered on the NDSS over time, and as reported, indigenous people had a higher risk for ESKD compared with nonindigenous people. Therefore, further subgroup analyses for T2DM were performed for the nonindigenous population, rather than for whole T2DM population. In nonindigenous T2DM, ESKD incidence increased in those younger than 50 years and those older than 80 years, but not in those aged 50 to 69 years (Table 4). As shown in Table S2, diabetic kidney disease was listed as the primary cause of kidney failure in 92% and 73% of ESKD cases in persons with T1DM and T2DM, respectively.

Table 3. Incidence Rate Ratios in Subgroups Subgroups T1DM, vs T2DM Current age, per 1 y older Male sex, vs female sex Indigenous vs nonindigenous SEIFA Group 1 (most disadvantaged) Group 2 Group 3 Group 4 Group 5 (least disadvantaged) ARIA Major urban Inner regional Outer regional Remote and very remote

IRR (95% CI) 1.37 (1.29-1.47) 0.98 (0.98-0.98) 1.51 (1.45-1.57) 4.03 (3.68-4.41) 1.43 1.21 1.24 1.20 1.00

(1.34-1.53) (1.13-1.53) (1.16-1.32) (1.13-1.29) (reference)

1.00 0.73 0.88 1.56

(reference) (0.69-0.78) (0.82-0.94) (1.41-1.72)

Abbreviations: ARIA, Accessibility/Remoteness Index of Australia; CI, confidence interval; IRR, incidence rate ratio; SEIFA, Index of Relative Socio-Economic Advantage/Disadvantage; T1(2)DM, type 1 (2) diabetes mellitus.

4

Timing of Renal Replacement Therapy Initiation In T1DM, the median eGFR at the commencement of renal replacement therapy (RRT) was 6.9 mL/min/1.73 m2 in 2002, increased to 9.0 mL/min/1.73 m2 in 2009, and then declined to 7.8 mL/min/1.73 m2 by 2013. The pattern was similar in T2DM. There was no significant change in median age at commencement of RRT over time (Fig S1). In a sensitivity analysis in which we used diabetes type as defined by health care professionals at registration into the NDSS, we observed similar patterns as were seen using the derived diabetes type (Fig S2; Table S3). Crude incidence rates were 15.8 (95% CI, 14.9-16.8) and 7.7 (95% CI, 7.5-7.9) per 10,000 person-years in nonindigenous persons with T1DM and T2DM, respectively. Secondary Analyses In a secondary analysis, we also included kidney failure–related deaths as cases, increasing the number of cases from 9,977 to 15,515. We observed similar trends to the primary analysis (Fig 2), the only exception being that in T2DM, the increases in incidence in nonindigenous individuals became statistically significant in men and women when analyzed separately and in the combined population (Table S4).

Discussion In this national registry–based study, we showed that for T1DM, the age-standardized annual incidence of ESKD was stable between 2002 and 2013, but increased in T2DM during the 12 years, driven mainly by those younger than 50 and older than 80 years. Further, we showed that ESKD incidence was higher in males than females, indigenous people than nonindigenous people, most disadvantaged individuals, and those who live in remote and very remote areas of Australia. The increasing incidence of ESKD in T2DM had 3 components. First, there was a marked increase in number of indigenous people registered on the NDSS during the study period. NDSS registration among indigenous people was low before 2002 because access to supplies for diabetes was available through other mechanisms. However, this changed with efforts to maximize the coverage of the AJKD Vol XX | Iss XX | Month 2018

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Type 1 Type 2

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Men Women

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15

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3 20 1

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1 20 1

9

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E

Incidence rate, per 10,000 person years (95%CI)

8

20 0

6

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20 0

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20 0

20 0

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0

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0-39 40-54

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Indigenous Non-indigenous

6

20 0

Incidence rate, per 10,000 person years (95%CI)

100 90 80 70 60 50 40 30 20 10 8

30

Year

D

Incidence rate, per 10,000 person years (95%CI)

Year

C

40

20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13

0

50

20 0

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Incidence rate, per 10,000 person years (95%CI)

B 25

20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13

A

Incidence rate, per 10,000 person years (95%CI)

Original Investigation

Year 20

15

0-49 50-59 60-69 70-79 80+

10

5

20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13

0

Year

Figure 1. Trends in age-standardized annual incidence rate of end-stage kidney disease per 10,000 person-years (95% confidence interval [CI]) in people with diabetes according to: (A) diabetes type, (B) age group in type 1 diabetes, (C) indigenous status in type 2 diabetes, (D) sex in nonindigenous type 2 diabetes, and (E) age group in nonindigenous type 2 diabetes.

NDSS. Increasing numbers of indigenous NDSS registrants, despite a stable ESKD incidence among indigenous people, influenced the overall incidence of ESKD because of the markedly elevated risk for ESKD in this population.20 Second, there was an increase in ESKD incidence among nonindigenous people older than 80 years. This likely reflects an increasing willingness to actively treat elderly people with kidney failure.9 Third, there was an increase in incidence of ESKD in nonindigenous adults younger than 50 years. This is the most concerning trend because it likely reflects less aggressive therapy or a more aggressive AJKD Vol XX | Iss XX | Month 2018

disease phenotype,8 with the latter possibly being related to the earlier age of onset of T2DM in this group.21 Although our data are reported in terms of incidence among people with diabetes, the total burden of diabetesrelated ESKD is also related to the numbers of people with diabetes. The numbers of people with T2DM increased markedly during the study period (Table S1) due to a combination of decreasing mortality and increasing incidence of diabetes. This will magnify the impact of increasing incidence on overall burden. Although the increase in numbers for T1DM was much more modest, this 5

Original Investigation Table 4. Trends in Incidence of ESKD in People With Diabetes Mellitus in Australia, 2002-2013 ESKD Cases All DM Crude Standardized Type of DM Type 1 Type 2 T1DM Age 0-39 y

Incidence Rates per 10,000 PY (95% CI)a

PY

P

10.0 (9.8 to 10.2) 9.3 (8.9 to 9.6)

2002-2013 2002-2013

0.3% (−1.2% to 1.8%) 1.5% (−0.3% to 3.3%)

14.1 (13.3 to 15.0) 7.0 (6.6 to 7.5)

2002-2013 2002-2013

−0.5% (−2.9% to 1.9%) 4.5% (1.9% to 7.1%)

0.6 0.003

437,148

10.2 (9.3 to 11.2)

269,993

26.6 (24.7 to 28.6)

2002-2005 2005-2013 2002-2013

10.8% (−6.2% to 31.0%) −2.3% (−5.5% to 0.9%) −0.4% (−2.8% to 2.1%)

0.2 0.1 0.7

134,720 9,022,522

45.4 (40.6 to 50.2) 6.1 (5.8 to 6.4)

2002-2013 2002-2013

1.3% (−2.4% to 5.2%) 2.2% (0.4% to 4.1%)

0.5 0.02

1,135,436 1,647,542 2,356,765 2,175,801

4.7 8.5 10.5 11.7

9,997 —

10,0175,338 —

1,163 8,356

707,141 9,157,243

445

Age 40-54 y 718 T2DM Indigenous 746 Nonindigenous 7,610 Nonindigenous T2DM Age 0-49 y 538 50-59 y 1,403 60-69 y 2,466 70-79 y 2,549 ≥80 y Sex Men Women

APC (95% CI)

Period

(4.4 to 5.2) (8.1 to 9.0) (10.1 to 10.9) (11.3 to 12.2)

654

1,706,884

3.8 (3.5 to 4.1)

2002-2013 2002-2013 2002-2013 2002-2006 2006-2013 2002-2013

4,877 2,733

4,768,998 4,253,494

7.9 (7.4 to 8.4) 4.5 (4.2 to 4.9)

2002-2013 2002-2013

4.2% 0.1% −1.7% 9.6% −2.8% 4.2%

(1.4% to 7.2%) (−1.4% to 1.5%) (−3.5% to 0.1%) (−1.2% to 21.6%) (−6.3% to 0.7%) (0.6% to 7.9%)

1.6% (−0.4% to 3.7%) 2.3% (−0.1% to 4.8%)

0.7 0.1

0.007 0.9 0.06 0.08 0.1 0.03 0.1 0.06

Abbreviations: APC, annual percentage change; CI, confidence interval; DM, diabetes mellitus; ESKD, end-stage kidney disease; PY, person-years; T1(2)DM, type 1 (2) diabetes mellitus. a Age-standardized to the 2008 Australian population.

6

25

20

15 Type 1

10

Type 2

5

8

9 20 10 20 11 20 12 20 13

20 0

6

5

4

3

7

20 0

20 0

20 0

20 0

20 0

2

0

20 0

Incidence rate, per 10,000 person years (95%CI)

do not have good national data for target achievement.23 Furthermore, the overall number of CKD due to diabetes in Australia rose to 497,000 in 2016.24

20 0

will still mean that the stable incidence translates into an increasing number of cases of ESKD. Should the numbers of people with diabetes continue to increase, this will significantly offset any population-level gains that could derive from a decreasing incidence within the diabetic population. A nominal decrease in ESKD incidence in those with T2DM aged 60 to 79 years is encouraging, although the finding was not statistically significant. A recent study of the NDSS population showed that age-standardized all-cause and cardiovascular disease mortality rates declined significantly overall between 2000 and 2011.2 The reduction in these competing risks may allow people with diabetes to live long enough to progress to ESKD, which may have limited the decrease in incidence of ESKD in T2DM. However, it is noteworthy that there was no change in age at initiation of ESKD over time. Other factors limiting improvements in ESKD incidence include poor risk factor control. The 2011/ 2012 Australian Health Survey data showed that among those with diabetes, only 55% achieved the target glycated hemoglobin (hemoglobin A1c) levels of <7%, and 29% achieved LDL cholesterol targets.22 According to the 2016 Australian National Diabetes Audit (ANDA), there was no change in mean hemoglobin A1c levels in people with diabetes attending specialist centers from 2010 to 2014 (8.1% in 2010, 8.3% in 2012, and 8.2% in 2014). However, we

Year

Figure 2. Trends in age-standardized annual incidence rate of end-stage kidney disease (including those with kidney failure–related deaths as cases) per 10,000 person-years (95% confidence interval [CI]) in nonindigenous people with diabetes according to diabetes type.

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Original Investigation It is noteworthy that during this period, blood pressure targets for people with diabetes have been changed from <130/80 to <140/90 mm Hg. In 2010, two trials were published that influenced blood pressure treatment: ACCORD25 and INVEST.26 Both trials failed to show a cardiovascular benefit for tight blood pressure control. In line with this, the 2011 American Diabetes Association Standards of Care27 expressed uncertainty in the evidence for the benefit of tight blood pressure target (<130/ 80 mm Hg). The difference in ESKD incidence trends that we observed between T1DM and T2DM is also supported by other studies. A French study28 found that age- and sexadjusted ESKD incidence rates decreased significantly by 10.4% per year for patients with T1DM between 2007 and 2011. In contrast, after a steep increase of 6.9% per year until 2009, the incidence of T2DM-related ESKD appeared to stabilize. Similar to other studies,29-33 we showed that men had a 51% higher incidence of ESKD compared with women. This could be because of a higher prevalence of smoking, comorbid conditions, overweight and obesity, and higher blood pressure among men. Furthermore, there may be sex differences in health-seeking behavior that may affect the development of long-term complications or the propensity to accept RRT. Women may use the available health care system more frequently and may adhere better to the recommended treatment regimens compared with men.34 The incidence rate of ESKD among indigenous people was 4 times higher than in the nonindigenous population. Indigenous Australians are known to have a higher burden of ESKD risk factors than the nonindigenous population, including tobacco smoking, poor nutrition, high blood pressure, obesity, and infections, as well as a higher prevalence of poor glycemic control.20,35,36 Furthermore, many indigenous people live in remote areas with limited access to health care. However, the coverage of the NDSS is lower in remote and very remote areas of Australia and for indigenous people, given the availability of other programs in these areas to assist with the purchase of diabetesrelated products. This may bias our findings toward severe and more advanced cases being registered on the NDSS, which may inflate the incidence. Thus, the incidence rate ratio for indigenous people here may be an overestimate. However, this is unlikely to explain the entire 4-fold increase, and steps to improve blood pressure and glycemic control in indigenous people with diabetes are urgently needed. The incidence of ESKD depends not only on CKD progression, but also on decisions that physicians make about whether and when to start RRT, and this may change over time. Our analysis showed that the level of kidney function at RRT commencement increased from 2002 to 2009 and then declined to 2013, in both T1DM and T2DM. Thus, there does not appear to be a progressively increasing eGFR at the time of RRT to explain the AJKD Vol XX | Iss XX | Month 2018

progressive increase in ESKD from 2002 to 2013 among persons with T2DM. The decline in median eGFR at RRT after 2009 is likely to be due to the results of the IDEAL Study37 that came out in 2010 and showed that early initiation of dialysis therapy had no significant effect on outcomes. There have been some changes during the last 12 years with regard to management of kidney disease in Australia.19 In 2005, there was standardization of creatinine measurement38 and automatic eGFR reporting,39 which increased awareness of CKD among clinicians. This may have prompted increased screening and improved management. All of these may have had an impact on the trends in incidence of ESKD and we are not able to disentangle these possible effects. Not all people with kidney failure receive RRT. Similar to other studies,18 we found that there was a slightly larger number of kidney failure–related deaths during the study period than cases of ESKD. When we accounted for kidney failure not treated by RRT, the trends in incidence of kidney failure were similar to the primary analysis of ESKD incidence trends. Our study has a number of strengths. First, this is a national and population-based cohort. Second, this is a whole population analysis with a long follow-up time and the ability to distinguish between T1DM and T2DM. However, these results should be interpreted in the context of some of the study’s limitations. First, we are limited to those who use NDSS services. It is possible that people who manage their diabetes with diet and physical activity alone may not have a need for the NDSS and therefore are under-represented. However, a previous study showed that of those with known diabetes, the capture of T1DM is nearly 100% and is 80% to 90% for T2DM.12 We also cross-checked the number of ESKD cases reported by ANZDATA. Between 2002 and 2013, ANZDATA reported 12,213 incident cases of ESKD with diabetes as a comorbid condition.10 We captured 9,977 (82%) of these cases, indicating that the NDSS has good coverage of people with diagnosed diabetes. Second, those with undiagnosed diabetes are not covered by the NDSS. It is estimated that for every 3 to 4 people with diagnosed diabetes, 1 person is likely to have undiagnosed diabetes in Australia.22,40 Third, NDSS use is lower in indigenous populations. Fourth, the definition of type of diabetes is not 100% accurate and misclassification may exist. However, because our population characteristics are similar to other known populations of T1DM and T2DM, we believe the proportion of misclassification is likely to be very small. Last, changes in quality and intensity of care over time for people with diabetes could have influenced the findings. However, because of the nature of this administrative database, we do not have data for other factors that contribute to ESKD and mortality, such as smoking, physical activity, duration of diabetes, comorbid conditions, medication use, and measures of quality of care. 7

Original Investigation Our analysis has shown that the age-standardized annual incidence of ESKD in T1DM was stable from 2002 to 2013. In contrast, the annual incidence of ESKD increased progressively in T2DM during this interval, driven by increases among those younger than 50 and older than 80 years. Identification of ways of reducing progression to ESKD both in indigenous and nonindigenous people with T2DM is urgently needed. The findings of this study also emphasize the importance of aggressive risk factor treatment, especially in those with younger-onset T2DM. This should include blood pressure and other cardiovascular risk factors and not just glycemic control. Further, there is a need for more research understanding the reasons for the increasing incidence of ESKD in younger adults with T2DM. Finally, the increasing prevalence of diabetes coupled with the increasing risk for ESKD in T2DM suggest that the future demand for RRT will increase in Australia, which has major implications for our health system. Supplementary Material Figure S1: eGFR and age in years at commencement of RRT. Figure S2: Trends in age-standardized annual incidence rate of ESKD per 10,000 person-years in nonindigenous people with diabetes, using NDSS diabetes type. Table S1: Crude and age-standardized ESKD incidence rate per 10,000 person-years, by year and diabetes type. Table S2: Proportion of primary cause of kidney disease by diabetes type. Table S3: Crude and age-standardized ESKD incidence rate per 10,000 person-years in nonindigenous people with diabetes, using the NDSS diabetes type. Table S4: Trends in incidence of ESKD (including those with kidney failure–related deaths as cases) in people with diabetes in Australia, 2002-2013.

Article Information Authors’ Full Names and Academic Degrees: Digsu N. Koye, PhD, Dianna J. Magliano, PhD, Christopher M. Reid, PhD, Meda E. Pavkov, PhD, Steven J. Chadban, PhD, Stephen P. McDonald, PhD, Kevan R. Polkinghorne, PhD, Sarah White, PhD, Christine Paul, PhD, and Jonathan E. Shaw, MD. Authors’ Affiliations: Department of Clinical Diabetes and Epidemiology, Baker Heart and Diabetes Institute (DNK, DJM, JES); Department of Epidemiology and Preventive Medicine, Monash University, Melbourne (DNK, DJM, CMR, KRP, JES); School of Public Health, Curtin University, Perth, Australia (CMR); Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, GA (MEP); Charles Perkins Centre, University of Sydney, Sydney (SJC, SW); ANZDATA (SPM); University of Adelaide, Adelaide (SPM); Department of Nephrology, Monash Medical Centre, Monash Health, Melbourne (KRP); School of Medicine and Public Health, University of Newcastle (CP); and Hunter Medical Research Institute, Newcastle, Australia (CP). Address for Correspondence: Digsu N. Koye, PhD, Baker Heart and Diabetes Institute, 99 Commercial Road, Melbourne, VIC 3004, Australia. E-mail: [email protected] Authors’ Contributions: Research idea and study design: DNK, DJM, JES; data acquisition: DNK, DJM, JES; data analysis/ 8

interpretation: DNK, DJM, CMR, MEP, SJC, SPM, KRP, SW, CP, JES; statistical analysis: DNK, DJM; supervision or mentorship: DJM, CMR, JES. Each author contributed important intellectual content during manuscript drafting or revision and accepts accountability for the overall work by ensuring that questions pertaining to the accuracy or integrity of any portion of the work are appropriately investigated and resolved. Support: Dr Koye is supported by a Monash University Postgraduate Research Scholarship and a Baker IDI Bright Sparks Scholarship. Drs Magliano, Reid, and Shaw are supported by National Health and Medical Research Council Senior Research Fellowships. This work is partially supported by the Victorian Government’s OIS Program. Funders of this study had no role in study design; collection, analysis, and interpretation of data; writing the report; and the decision to submit the report for publication. Financial Disclosure: The authors declare that they have no relevant financial interests. Acknowledgements: Data for this project were sourced from the NDSS, ANZDATA, and the NDI. NDSS is an initiative of the Australian government that has been administered by Diabetes Australia since 1987. We thank the AIHW for linking the NDSS to ANZDATA and the NDI. ANZDATA is funded by the Australian Organ and Tissue Donation and Transplantation Authority, the New Zealand Ministry of Health, and Kidney Health Australia. Disclaimer: The interpretation and conclusions from this study are those of the authors and in no way should be seen as an official policy or interpretation of ANZDATA. Peer Review: Received May 29, 2018. Evaluated by 3 external peer reviewers, with direct editorial input from a Statistics/Methods Editor, an Associate Editor, and the Editor-in-Chief. Accepted in revised form October 11, 2018.

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