QJM Advance Access originally published online on August 6, 2007
QJM 2007 100(9):551-560; doi:10.1093/qjmed/hcm062
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Patients with diabetic nephropathy on renal replacement therapy in England and Wales
From the 1Department of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, 2Renal Unit, Nottingham City Hospital, Nottingham, 3UK Renal Registry and 4Renal Unit, Southmead Hospital, Bristol, and 5Applied Epidemiology Group, University of Southampton, Southampton General Hospital, Southampton, UK
Address correspondence to Dr D. Nitsch, Department of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT, UK. email: dorothea.nitsch{at}lshtm.ac.uk
Received 1 March 2007 and in revised form 30 April 2007
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Background: The incidence of patients with diabetic nephropathy (DN) who start renal replacement therapy (RRT) is increasing.
Aim: To describe the characteristics and survival of patients with DN starting RRT in the UK
Design: Retrospective cohort study.
Methods: We analysed data for incident patients on RRT in centres participating in the Renal Association UK Renal Registry (UKRR), 1997 –2004, comparing DN vs. non-DN patients with regard to survival, social deprivation, ethnicity, gender, and age, using Cox regression models.
Results: DN was the most common renal disease (19%) in the 20 532 patients starting RRT. The majority of patients with DN (77%) were Caucasian. Within the Caucasian population, DN patients were more likely to be from a socially deprived area (p < 0.0001). About 20% were referred <3 months before starting RRT. The difference in crude survival was greatest in younger patients (5-year survival was 56% (DN) vs. 85% (non-DN) in patients aged 18–54 years, and 17% (DN) vs. 28% (non-DN) in patients aged 
65 years). Despite adjusting for gender, age, treatment modality, social deprivation, referral and co-morbidities, the long-term prognosis for DN patients aged 18–54 years was worse (adjusted hazard ratio 2.13, 95%CI 1.23–3.67) than for older age groups.
Discussion: Patients with DN starting RRT are more likely to come from socially deprived areas. Relative risk of death is greatest in working-age DN patients and is not fully explained by recorded co-morbidity. This emphasizes the need for focused diabetes care in poorer areas, and assessment of quality of care of diabetic patients on RRT.
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Introduction |
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Diabetic nephropathy (DN) is now the most common disease leading to renal replacement therapy (RRT) in developed countries.1–3 In the UK, the number of DN patients accepted for RRT rose steadily in the 1990s,4 especially in the Black and South Asian populations,4,5 although the overall rise has slowed in the last 4 years.6 International comparisons have confirmed the large proportion of DN patients among those on RRT in non-Caucasian populations, but there is substantial international variation in levels of DN even among Caucasians;7 for example, the number of Caucasian patients with DN on RRT in the UK is relatively low when compared to that in Germany.8 The English National Service Frameworks for Diabetes9 and Renal Services10 have highlighted the importance of prevention of DN by early detection and aggressive management of blood pressure, glucose control and cardiovascular risk factors, and of referral at least 1 year before the anticipated start of RRT for those with progressive chronic kidney disease (CKD).
The increasing incidence of patients with DN on RRT is the result of the increased prevalence of type 2 diabetes in the general population, the ageing population, and the greater acceptance of RRT among older people.4,11 DN patients starting RRT are likely to have more co-morbidity than other patients, in particular cardiovascular disease (CVD), and consequently to have poorer survival on RRT.12–14
There is a key policy drive to reduce health inequalities in England.15 In the UK, there is evidence that patients with diabetes in more socially deprived areas have higher all-cause mortality even after adjustment for smoking and blood pressure,16 and lower rates of attendance at primary-care and hospital clinics.17 There are few data on the relationship of social deprivation to the incidence and outcomes of established renal failure (ERF) from DN.5,6 A recent meta-analysis suggested a worse outcome for women with diabetes when compared to men.18
Our objective was to re-assess the characteristics and survival of patients with DN, relative to other patients who start RRT in England and Wales, with a particular focus on gender, age and social deprivation, by analysing data from the Renal Association UK Renal Registry (UKRR).
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Patient population
At the time of analysis, data from renal units in Scotland and Northern Ireland were not available to the Registry, so this study is confined to data from units in England and Wales. All patients commencing RRT between 1997 and 2004 were included. Follow-up was continued until 31 December 2004. Information was extracted on primary cause of ERF, time of referral, modality of treatment, co-morbidities, and date and cause of death. Patients with diabetes as the primary cause of ERF were defined as the DN group. It was not possible to separate patients accurately between diabetes type 1 and 2; however most will have been type 2. The UKRR has approval from the Secretary of State through the Patient Information Advisory Group to collect patient data without individual patient consent. Details of how data are collected have been published elsewhere.6
Measure of social deprivation
All patient postcodes were validated against the full address using a commercial software package (QAS Systems). The Townsend index, a composite measure of social deprivation, was calculated from the 2001 UK Census. This index is based in each area on the percentages of unemployed people, and percentages of households without a car, that are overcrowded and are not owner-occupied;19 a higher Townsend score indicates greater social deprivation. The Census output area for each patient's postcode of residence was identified, and scores were allocated into general population postcode quintiles of deprivation. For the 5% of postcodes that cross a Census output area boundary, and therefore have more than one Townsend score, the mean value was taken.
Measures of ethnicity, co-morbidity and referral
Ethnicity was recorded largely by self-description. Our analysis was limited to Afro-Caribbean, South Asian and Caucasian patients, as other groups were too small, and the analysis was confined to centres which returned information on ethnicity for 85% of patients. Within this restricted group of patients, there was a high proportion of missing data on co-morbidity at start of RRT, and on date of referral to nephrologists; thus, striking a balance between data quality and quantity for these items, slightly less stringent cut-offs were chosen: only centres returning >75% referral data and >80% co-morbidity data were included. For analysis of co-morbidities, ‘cardiac disease’ included those patients recorded as having angina, previous myocardial infarction, coronary artery bypass grafts or angioplasty, and ‘peripheral vascular disease’ included claudication, ischaemic and neuropathic ulcers, non-cardiac angioplasty and amputations due to ischaemia. According to the comorbidity data, there were another 270 patients with other causes of ERF (9.3% of 2908 patients) who also had diabetes, but these were not included with the DN patients in these analyses. Late referral was defined as referral to nephrologists within 90 days of starting RRT; referral within 1 year of RRT was also examined.
Statistical analyses
To identify associations between different potential predictors of survival at baseline, a range of statistical tests was used where appropriate. For binary and categorical associations, 
2 tests were used. Graded categorical associations were examined with 2 tests for trend. For non-normal data across several categories, Kruskal-Wallis tests were used. Continuous normal data were examined with linear regression, and crude associations adjusted for age and sex. Mantel-Haenszel tests were used when categorical associations were adjusted for age and sex. Before collapsing results across different strata of age and sex, appropriate heterogeneity tests were conducted.
Our aim was to assess overall survival on RRT. Hence, patients were not censored at time of renal transplant, as this would have introduced selection towards a sicker population. For descriptive analyses of survival in incident DN patients, Kaplan-Meier graphs, and corresponding log-rank tests were used where appropriate. Some renal units may have included patients with acute renal failure, which affects early death rates. Therefore, survival up to 90 days of RRT was assessed separately from survival after 90 days. Cox's proportional hazards model was then used to explore the independent effect of variables on survival. All Cox models assessing survival after 90 days excluded all the patients who had started RRT in the last quarter of 2004.
Age was entered as a linear variable, social deprivation as a categorical variable using the aforementioned quintiles, late referral, DN and gender as binary variables. Because a cohort effect up to 90 days on RRT had been observed, all models were adjusted for year of onset of RRT, although this variable had no significant effect on survival after 90 days RRT. We used a robust sandwich estimate for the covariance matrix, which results in a robust standard error for the parameter estimates to account for clustering within centres.
Four different cohorts were used in the analysis (Figure 1). Cohort 1, patients with available baseline information on Townsend Scores, treatment modality at start, gender, age, and primary renal disease (n = 20 532, from 49 centres). Cohort 2, as 1, but restricted to Caucasians (n = 9810, 24 centres), to assess the effect of DN adjusting for social deprivation independent of ethnicity. Cohort 3, as 1, but restricted to those with data on co-morbidities at start of RRT, irrespective of ethnicity (n = 3656, 16 centres), to examine whether these were the main mediators of worse outcome of DN patients while adjusting for social deprivation and all other variables. Cohort 4, as 3, but restricted to Caucasians (n = 2760, 10 centres).
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Prior knowledge20 and both crude and adjusted analyses suggested the presence of an multiplicative interaction between DN and age in models after 90 days RRT, both on a continuous age-scale as well as when using age categories. For simplicity, the effect is reported in age categories (18–54, 55–64,
65 years of age). However, because of remaining residual confounding due to age, adjustment for age within each category was necessary. We also tested for differences in effects of DN by gender. Other interactions were only assessed in the final model if both predictors had significant independent effects. The assumption of proportionality was investigated using graphical methods (complementary log-log plots) and in the final model using Schoenfeld tests. All analyses used SAS statistical software. |
Results |
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Characteristics of incident patients on RRT (Tables 1 and 2)
Of new patients starting RRT, 19% had DN; just over 60% of these (and of all new RRT patients) were male. DN patients were younger at the start of RRT than other RRT patients, slightly more likely to receive peritoneal dialysis (PD) and half as likely to be transplanted in the first year of RRT, both in the full and in the Caucasian-only cohort, even after adjusting for age and gender.
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Incident DN patients had higher Townsend scores (greater social deprivation). Given the strong association between social deprivation and ethnicity, with ethnic minorities being more deprived (OR 3.15, 95%CI 2.81–3.53, p < 0.0001), Caucasian patients alone were analysed: a significantly higher proportion of DN patients were still from a more socially deprived background (p < 0.0001) (Figure 2). Within Caucasian DN patients, there was no evidence for an association between gender and increasing deprivation quintiles (
2 test for trend, p = 0.41).
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Late referral (< 90 days before starting RRT) occurred in 20% of DN patients, and only half were referred within 1 year (Table 2). Across the continuous range of Townsend scores, socially deprived patients were more often referred late, both in crude and in age- and sex-adjusted analyses (crude association with three referral categories, p < 0.0001; age-, sex-adjusted, p = 0.0026).
Roughly half of the DN patients had manifest CVD. Malignancy was much less common in DN patients than in non-DN patients. About a fifth of both DN patients and non-DN patients smoked (Table 2). When adjusted for age and gender, social deprivation was associated with increased CVD within all DN patients (Mantel-Haenszel, p = 0.023).
Survival in the first 90 days of RRT
Up to day 90, 1527 patients died, corresponding to a mortality rate of 30.6 deaths/100 person-years. Even after adjustments for age, gender, modality and deprivation, DN patients had similar or better survival than others at 90 days of RRT. The slight crude survival advantage was due to confounding from earlier referral, and less malignancy at start of RRT (Table 3). Accordingly, the proportion of deaths due to malignancy was significantly higher in non-DN than DN patients in the first 90 days (6% vs. 0.5%, p < 0.001). There was no difference in survival between men and women with DN in the first 90 days of RRT (p for interaction 0.93).
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Survival after 90 days of RRT
After 90 days, the Kaplan-Meier curves showed lower crude survival for DN vs. non-DN patients, in all age groups (Figure 3). Estimated crude mortality rate in DN patients was 19.3 deaths/100 person-years in the full cohort, and 13.3 deaths/100 person-years in the non-DN patients. However, the difference varied by age in all cohorts examined. Although older patients had a higher mortality, the difference between DN patients and others was greatest in the young, with a tripling of crude hazards in those aged <55 years (p for interaction by age <0.0001). At one year after 90 days RRT, the proportion of 18–54-year-old DN patients surviving dropped to 87%, with only 56% alive at 5 years after commencing RRT, compared with 96% and 85% respectively of non-DN patients in the same age group (log-rank p < 0.0001).
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For those under 65 years, DN remained a significant predictor of death, with up to a doubling of hazard compared to others on RRT, even when adjusted for all the manifest co-morbidities and time of referral (Tables 4 and 5). In contrast, in Caucasians aged
65 years, the effect of DN seemed to be due to manifest co-morbidities.
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The slightly elevated hazard ratio (HR) of 1.20 for the highest vs. the lowest quintile of social deprivation in Caucasian patients (gender-, age- and modality-adjusted, 95%CI 1.09–1.32, p = 0.0002) disappeared in all above models as soon as DN and associated co-morbidities were added as predictors (HR 1.01, 95%CI 0.85–1.19, p = 0.94), suggesting that DN and co-morbidities may explain the effect of social deprivation in Caucasians on RRT.
Across all four cohorts, the crude and adjusted effects of covariates (including age and gender) were similar (data not shown). In particular, there was no evidence for a difference in survival between men and women with DN (in all models, p for interaction >0.1).
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Discussion |
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This study confirms that DN is now the most common cause of ERF in the UK: nearly 1 in 5 of those starting RRT. However, the annual incidence of nearly 20 pmp is rather low, when compared to that of other Western countries.6 DN patients were more likely than non-DN patients to come from deprived areas. Younger patients had an especially poor long-term survival on RRT, which was not fully explained by co-morbidity. There was no evidence of inequity in survival amongst DN by gender or social deprivation.
Although South Asian and Afro-Caribbean ethnic minorities are approximately four times more likely to have dialysis-dependent DN, compared with Caucasians, within the UK, Caucasians were the largest ethnic group among DN patients starting RRT. DN patients were younger than others at the start of RRT, even after correcting for ethnicity, which may reflect bias against older patients with DN (and associated co-morbidities), or competing risks: older patients with diabetes may be more likely than younger ones to die of CVD before starting RRT.21 In addition, there is evidence that younger patients with diabetes may receive care at a lower quality and impact level than older patients do.22 In theory, this could increase the likelihood of developing end organ disease earlier in life, and therefore explain the younger age on RRT.
The direction of the association between social deprivation and DN at baseline cannot be elucidated with cross-sectional data at start of RRT. Patients with DN may be socially deprived secondary to ill health. However, it seems more plausible that the observed differences in social deprivation in DN and non-DN patients are due to the increased incidence of obesity and metabolic syndrome, and consequently of type 2 diabetes, in more socially deprived groups.23 Quality of health care might contribute to the development of co-morbidity, as poorer diabetes control, poor CVD risk management and a higher rate of smoking in patients with diabetes have all been found in deprived areas.16,17, 24–27 The new General Practice contract in England includes financial incentives for achieving 18 targets relating to diabetes.28 Very recent studies performed after introduction of this contract show that it is less successful in socially deprived areas.29,30
CKD is now recognized as a marker of increased CVD risk,31 and DN patients starting RRT are a high-risk group, with half suffering from CVD. Even after adjusting for manifest co-morbidity and smoking at start of RRT, young and middle-aged patients with DN have higher relative mortality than older patients. This may be due to the fact that diabetes itself is an independent prognostic factor: a similar increased risk for the young patients with diabetes has been described in the INTERHEART study32 and in the US RRT population.20 Studies regarding HbA1c as a prognostic factor in different populations of dialysis patients have been inconclusive.33,34 There might also be residual confounding by unmeasured factors preceding manifest co-morbidities, e.g. left ventricular hypertrophy, or asymptomatic undetected coronary artery disease.35 Anaemia is unlikely to explain the observed differences by age, as further adjustments for haemoglobin levels at 3 months did not alter the coefficients for DN (data not shown). Cardiovascular interventions may have fewer long-term benefits for patients with diabetes compared to patients without diabetes, which may explain some of the relative increase in mortality at younger ages.36
Data from the Netherlands suggest that it is possible to prevent the progression of DN to RRT at younger ages.11 Although the relative impact of having DN on survival in older people seems to be small, the increasing proportion of DN patients with high co-morbidity will present difficult management challenges.
Late referral was less common in DN patients than others, but it was disappointing that nearly a half of DN patients presented less than a year before initiation of RRT. There remains much scope for improving the timeliness of referral to nephrologists, as advocated by the English National Service Framework.10 Use of estimated glomerular filtration rate instead of serum creatinine should improve recognition of CKD in patients with diabetes and reduce late referral.10,28
There was a low rate of transplantation in DN patients, even after adjusting for ethnicity. This is despite the fact that renal transplantation offers the best survival option for DN patients.14,37 Approaches to pre-emptive transplantation, and whether or not DN patients are listed for transplantation, vary widely between renal units.38,39
There was no evidence for an excess mortality in women with DN when compared to men on RRT. This differs from the findings of a recent meta-analysis, where a 50% excess risk for fatal CHD of women with diabetes compared to diabetic men was described.18 The authors postulated that these differences were the result of more adverse cardiovascular disease profiles in these women when compared to men, as well as (possibly) differences in treatment.18 Our results suggest that the prognosis of patients with DN on RRT is determined by their advanced renal disease and associated co-morbidity, irrespective of gender.
A particular strength of this study is that it is based on a cohort of incident patients on RRT, derived from a large national registry with a high degree of quality control, standard definitions and long-term follow-up, and from a country with comprehensive data on social deprivation. The main limitation is incomplete data on co-morbidity, although the cohort represents the largest collection of such information in Europe. There was also no separation between type 1 and type 2 diabetes, and data on vascular access or individual social support were lacking. As data were only analysed from centres with a high data return, and because of the consistency of the findings across different subsets of the data, the results appear robust. Only survival was analysed; more research is needed into morbidity, dialysis-related issues (vascular access,40 biocompatibility of membranes41), health-care use and quality of life/social support.
In conclusion, patients with DN are now widely accepted onto RRT programmes, but have poor long-term survival. In the elderly, this is partly due to a greater burden of manifest co-morbidity. The higher mortality in the younger patients was not explained by this study. However since cardiovascular disease is the principal cause of death, it may well have been present (but asymptomatic) when co-morbidity was recorded at the start of RRT. The outcome of DN may be improved by more systematic assessment and aggressive treatment of CVD risk by all involved in the management of patients with diabetes at every stage; the high rate of smoking (19%) is a particular cause for concern.9,10 To reduce the health inequalities associated with diabetes mellitus, there is a need to target prevention of DN in more socially deprived areas.
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The data were supplied by the UK Renal Registry of the Renal Association. The interpretation and reporting of these data are the responsibility of the authors, and are not the official policy of the UK Renal Registry or the Renal Association. We thank Hannah Jordan of Southampton University for her help on the calculation of the Townsend scores, and Az Ahmad (former Registrar of the UK Renal Registry) for helpful comments. Dorothea Nitsch was sponsored by grant PBBSB-100661 from the Swiss National Science Foundation. The Renal Association (UK Renal Registry) is a Charitable Company. Registered in England No. 2229663.
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References |
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