- Email: [email protected]
Socioeconomic deprivation is independently associated with mortality post kidney transplantation
clinical investigation
http://www.kidney-international.org & 2013 International Society of Nephrology
see commentary on page 647
Socioeconomic deprivation is independently associated with mortality post kidney transplantation Irena Begaj1, Sajan Khosla1, Daniel Ray1 and Adnan Sharif2 1
Department of Medical Informatics, Queen Elizabeth Hospital, Birmingham, UK and 2Department of Nephrology and Transplantation, Renal Institute of Birmingham, Queen Elizabeth Hospital, Birmingham, UK
The association between area socioeconomic deprivation and mortality post kidney transplantation is unclear. To clarify this, we obtained data from 19,103 kidney transplant procedures performed in England from April 2001 to March 2012. Patient demographics included age, gender, donor type (living or deceased), ethnicity, transplant year, allograft failure, medical comorbidities, and area socioeconomic deprivation (Index of Multiple Deprivation (2010)). Primary and secondary outcome measures were 1- and 5-year mortality with Cox proportional hazard models performed to identify independent factors associated with mortality. Data were broken down into quintiles of patients by area socioeconomic deprivation 1 to 5 (most to least deprived, respectively). At 1 year post transplant, 566 deaths were recorded, with infection being the most common cause of death. Compared with the most deprived individuals (reference point), the least deprived recipients had significantly decreased risk of death at 1 and 5 years post kidney transplant (hazard ratio 0.66, 95% CI (0.57–0.76) and hazard ratio 0.65, 95% CI (0.54–0.77), respectively). Thus, socioeconomic deprivation is independently associated with increased mortality post kidney transplantation. Kidney International (2013) 84, 803–809; doi:10.1038/ki.2013.176; published online 29 May 2013 KEYWORDS: area socioeconomic deprivation; kidney transplantation; mortality
Correspondence: Adnan Sharif, Department of Nephrology and Transplantation, Renal Institute of Birmingham, Queen Elizabeth Hospital, Edgbaston, Birmingham B15 2WB, UK. Email: [email protected] Received 17 October 2012; revised 21 February 2013; accepted 1 March 2013; published online 29 May 2013 Kidney International (2013) 84, 803–809
The association between area socioeconomic deprivation and mortality in the general population is well documented,1–5 but its relationship with mortality post kidney transplantation has never been adequately described. Analyses of the association of socioeconomic deprivation (represented at area or individual level) post kidney transplantation have focused predominantly on allograft outcomes, with data reported in the United States demonstrating poorer graft survival for recipients residing in more socially deprived areas.6,7 However, interpretation of area socioeconomic deprivation data from the United States in relation to kidney transplantation is confounded by suboptimal definitions (the use of isolated domains of socioeconomic deprivation assessment) and financial coverage limits regarding immunosuppression (medication affordability),8 which is likely to have an impact on outcome analysis. It is therefore more useful to explore social determinants of mortality post kidney transplantation in the context of robust definition and a health-care system administered by universal health coverage. In the United Kingdom, with universal health coverage through the state-funded National Health Service, this important limitation is eliminated and provides a useful model to analyze the effects of area socioeconomic deprivation post kidney transplantation. The handful of studies reported from the United Kingdom has predominantly focused on the impact of area socioeconomic deprivation and access to transplantation,9–12 with other studies reporting on kidney allograft outcomes.13 In this journal, Caskey et al.14 previously reported area socioeconomic deprivation to be independently associated with mortality after commencing renal replacement therapy (albeit this was a predominant dialysis (96.7%) population). To date, the impact of area socioeconomic deprivation (in the context of universal health coverage) on mortality post kidney transplantation remains unclear. In addition, there are several important limitations in many previous studies; first, they have used loosely defined indices of deprivation; and second, the lack of ethnicity data in many of these studies confounds interpretation of the independent influence of area socioeconomic deprivation. Therefore, the aim of this study was to explore the impact of area socioeconomic deprivation on 1- and 5-year mortality post kidney 803
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transplantation, independent of important confounders, by linking national data sources for all kidney transplant procedures performed in England over the past decade. Our assessment of area socioeconomic deprivation was by the Index of Multiple Deprivation: a composite index of multiple domains epidemiologically weighted to provide a spectrum of local-level assessment of areas of deprivation.
RESULTS
In total, 19,688 kidney transplant procedures were recorded between April 2001 and March 2012 (repeat transplants during this period were excluded from analysis); 584 were excluded owing to the lack of social deprivation information and 1 had no age/gender recorded, leaving us with 19,103 recipients for analysis. These data incorporate every kidney transplant procedure performed at every kidney transplant center in England over the past decade as recorded by Hospital Episode Statistics (HES; excluding any subsequent transplant during this period of analysis). Pediatric recipients constituted a small proportion of the overall number of
kidney transplants performed (4.9% (n ¼ 942) of the overall cohort with only 27 deaths). Data accuracy
To verify the quality of the HES data, we extracted information from the UK Transplant National Transplant database to determine the number of transplants performed during the same time frame. During the time from 1 April 2001 to 31 March 2013, 19,405 kidney transplant procedures were registered (19,241 kidney transplant alone, 49 en-bloc kidneys, and 115 double kidney transplants). This identifies a small discrepancy of 283 kidney transplant alone procedures that have been over-reported in the HES data in comparison to UK National Transplant Database records. Patients and area socioeconomic deprivation
Table 1 highlights the demographic make up of the kidney transplant patient cohort divided by area socioeconomic deprivation quintiles. Non-whites were more likely to reside in areas of high versus low area socioeconomic deprivation (Po0.001). Residents within more socially deprived areas
Table 1 | Summary of variables using area socioeconomic deprivation quintiles Most deprived (1)
(2)
(3)
(4)
Least deprived (5)
Patients, % (N) Age, median (Q1–Q3) Males, % (N)
22.0 (4203) 43 (32–53) 60.6 (2549)
22.0 (4197) 44 (34–55) 61.3 (2571)
19.7 (3765) 46 (35–57) 60.7 (2286)
18.3 (3490) 48 (36–58) 61.1 (2134)
18.0 (3448) 48 (37–58) 61.9 (2133)
Ethnicity, % (N) White Mixed Asian or Asian British Black or Black British Chinese Other ethnic groups Unknown
59.6 (2505) 1.2 (51) 15.1 (636) 10.1 (424) 0.6 (26) 3 (128) 10.3 (433)
67.2 (2822) 1 (42) 11.2 (470) 7 (292) 0.5 (20) 2.1 (90) 11 (461)
74.2 (2795) 0.6 (24) 7.8 (292) 3.4 (129) 0.4 (16) 1.5 (57) 12 (452)
80.7 (2817) 0.7 (25) 4.9 (170) 1.3 (46) 0.2 (6) 1.1 (39) 11.1 (387)
79.9 (2756) 0.7 (24) 3.9 (136) 1.2 (43) 0.4 (13) 1 (36) 12.8 (440)
Medical comorbidities, % (N) None recorded Acute myocardial Infraction Congestive heart failure Peripheral vascular disease Cerebral vascular accident Pulmonary disease Connective tissue disorder Peptic ulcer Cancer Liver disease Diabetes
73.6 (3095) 0.6 (107) 0.1 (28) 0.4 (81) 0.2 (38) 1.2 (220) 0.4 (85) 0.1 (19) 0.1 (15) 0.1 (19) 3.4 (651)
73.0 (3064) 0.6 (108) 0.2 (33) 0.3 (66) 0.2 (45) 1 (200) 0.5 (100) 0.1 (14) 0.1 (12) 0.1 (20) 3.9 (737)
74.2 (2793) 0.6 (112) 0.1 (26) 0.3 (61) 0.2 (34) 0.9 (180) 0.4 (84) 0.1 (15) 0.1 (20) 0.1 (13) 3.1 (590)
74.0 (2581) 0.5 (97) 0.1 (19) 0.2 (42) 0.1 (18) 0.9 (165) 0.3 (64) 0.1 (16) 0.1 (14) 0.1 (10) 2.6 (500)
76.7 (2645) 0.4 (79) 0.1 (14) 0.2 (34) 0.1 (19) 0.8 (161) 0.3 (52) 0.1 (13) 0.1 (16) 0.1 (24) 2.6 (492)
1.2 (33)
1.3 (36)
0.9 (21)
0.9 (20)
0.7 (15)
26.1 (1086)
31.8 (1335)
33.1 (1248)
36.6 (1277)
38.2 (1316)
1-Year mortality % (N)
3.4 (145)
3.1 (132)
2.7 (100)
3.1 (107)
2.4 (82)
5-Year mortality % (N)
8.2 (343)
7.3 (307)
7.5 (283)
7.5 (262)
6.3 (218)
Transplant failurea % (N) Living-donor transplant % (N)
a
Transplant failure defined as X10 dialysis sessions from 90 days post transplant (only transplants from 1 April 2006 to 31 March 2012). In this time period, there were 11,961 transplants in England.
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I Begaj et al.: Area socioeconomic deprivation and mortality post kidney transplantation
were also less likely to receive living-donor kidney transplantation compared with residents in less socially deprived areas (P ¼ 0.009). No other significant differences between the area socioeconomic deprivation quintile groups were observed. Mortality 1 year post kidney transplantation
There were 566 deaths recorded within the first year post kidney transplantation for this study population. One-year risks of mortality post kidney transplantation per Index of Multiple Deprivation (2010) quintile were as follows (from most to least deprived, respectively): 1 (3.6%), 2 (3.0%), 3 (3.2%), 4 (2.9%), and 5 (2.5%). Infection was the most common cause of death, accounting for 30.9% of all deaths within the first year post transplantation. Cardiovascular death was the second most common cause and accounted for 15.9% of all deaths. The remaining causes of death all accounted for o10% of mortality within the first year post kidney transplantation (see Figure 1). There was no significant difference between area socioeconomic deprivation quintile and cause of mortality within the first year post kidney transplantation (P ¼ 0.081). Survival analysis
At 1 year post kidney transplantation, recipients living in the area with the least socioeconomic deprivation had a significantly lower hazard ratio for death post kidney
transplantation compared with those living in the area with most socioeconomic deprivation (hazard ratio 0.66, 95% CI (0.57–0.76). Po0.001). At 5 years post kidney transplantation, recipients living in the area with least socioeconomic deprivation continued to have a lower hazard ratio for death post kidney transplantation compared with those living in the area with the most socioeconomic deprivation (hazard ratio 0.65, 95% CI (0.54–0.77), Po0.001) (see Table 2). Adding allograft failure into additional Cox regression model retained the same result (see Table 3), with individuals residing within areas of least socioeconomic deprivation having lower hazard ratio for death 1 year post kidney transplantation compared with those recipients living in areas with the most socioeconomic deprivation (hazard ratio 0.61, 95% CI (0.47–0.79), Po0.001). Owing to the inability to obtain allograft failure data (using our surrogate definition) preceding 2006, we did not perform any supportive analysis incorporating allograft failure into the statistical model for 5-year mortality risk post kidney transplantation. However, the absence of a major difference including/ excluding allograft failure on the hazard ratio at 1 year post kidney transplantation for area socioeconomic deprivation makes us speculate a similar negligible impact on 5-year mortality. Kaplan–Meier survival curves were performed and showed a constant disparity in the first year and long-term patient Cardiovascular Cerebrovascular Vascular Infection Malignancy Trauma Renal Metabolic Gl/liver Pulmonary Other Unknown
5.8%
3.0%
15.9%
5.5%
5.5% 5.8% 1.4%
6.4%
8.0%
4.6%
7.2%
30.9%
Figure 1 | Pie chart demonstrating the cause of 1-year mortality for all kidney allograft recipients (adult and pediatric) between 2001 and 2012 based upon registered death certificate details submitted to Office for National Statistics. Infection and cardiovascular death were the two most common causes of death at 30.9 and 15.9%, respectively, with all other causes o10% each. There was no significant difference in the cause of death between area socioeconomic deprivation quintiles (P ¼ 0.081). Kidney International (2013) 84, 803–809
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Table 2 | Cox regression output regarding 1- and 5-year mortality post kidney transplantation (assessing short- and medium-term risk of death, respectively) Mortality
Hazard ratio
95% Confidence interval
P-value
1-Year mortality Area socioeconomic deprivation quintile Most deprived (1) 1.00 (2) 0.83 (3) 0.85 (4) 0.80 Least deprived (5) 0.66
0.006 0.019 0.002 o0.001
0.73–0.95 0.75–0.97 0.70–0.92 0.57–0.76
5-Year mortality Area socioeconomic deprivation quintile Most deprived (1) 1.00 (2) 0.85 (3) 0.83 (4) 0.81 Least deprived (5) 0.65
0.035 0.026 0.010 o0.001
0.72–0.99 0.71–0.98 0.68–0.95 0.54–0.77
DISCUSSION
Cox regression model looking at area socioeconomic deprivation and mortality; adjusted for age, gender, ethnicity, living donor versus deceased donor, transplantation year, and selected medical comorbidities (history of myocardial infarction, peripheral vascular disease, cerebrovascular disease, congestive cardiac failure pulmonary disease, liver disease, peptic ulcer, previous cancer, and diabetes).
Table 3 | Cox regression output regarding mortality post kidney transplantation incorporating allograft failure (data from April 2006 onward, n ¼ 11,961) Mortality
Hazard ratio
1-Year mortality Area socioeconomic deprivation quintile Most deprived (1) 1.00 (2) 0.84 (3) 0.86 (4) 0.87 Least deprived (5) 0.61
survival comparing kidney allograft recipients living in the most and the least socially deprived neighborhoods, respectively (see Figure 2).
P-value
95% Confidence interval
0.119 0.198 0.232 o0.001
0.67–1.05 0.69–1.08 0.69–1.09 0.47–0.79
Cox regression model looking at area socioeconomic deprivation and mortality, adjusted for age, gender, ethnicity, living donor versus deceased donor, allograft failure*, transplantation year, and selected medical comorbidities (history of myocardial infarction, peripheral vascular disease, cerebrovascular disease, congestive cardiac failure pulmonary disease, liver disease, peptic ulcer, previous cancer, and diabetes). *Allograft failure surrogate definition: X10 dialysis sessions from 90 days post transplant (only transplants from 1 April 2006 to 31 March 2012). In this time period, there were 11,961 transplants in England.
In this study, we show that kidney transplant recipients who reside in a socially deprived neighborhood have increased mortality post kidney transplantation independent of age, gender, donor type (living vs. deceased), ethnicity, transplant year, allograft failure, medical comorbidities, and financial coverage. To our knowledge, this is the first clear description of an association between area socioeconomic deprivation and mortality post kidney transplantation, introducing an important and hitherto unconfirmed risk factor for posttransplant mortality. Further research is required to investigate this sociological association and the factors contributing to increased mortality for recipients residing in socially deprived environments. The efficacy and/or viability of developing support frameworks for recipients residing in areas of area socioeconomic deprivation post kidney transplantation to attenuate this risk also require further exploration. There is a paucity of literature linking area socioeconomic deprivation and adverse postkidney transplant outcomes, and little is known of social determinants of health in this population in general. Caskey et al.14 showed area socioeconomic deprivation to be associated with mortality post commencement of renal replacement therapy, although the data were skewed toward a dialysis population predominantly. To that effect, our analysis is the first to focus on mortality post kidney transplantation. More recently, Stephens et al.13 reported on the influence of area socioeconomic deprivation on graft outcomes after kidney transplantation in a single-center analysis of 621 consecutive recipients transplanted between 1997 and 2005. By using the Welsh Index of Multiple Deprivation (similar domains to our English index), the authors found that individuals living in the most deprived areas had a significantly greater risk of rejection requiring treatment (most deprived vs. least Long-term Kaplan–Meier survival plot
1-Year Kaplan–Meier survival plot 1.00
1.00
0.95 0.99
0.90 0.85
0.98
0.80
0.97
0.75 0.70
0.96 0
100
200
300
Survival time (days)
400
0
2 4 6 Survival time (years)
The most deprived (1)
The most deprived (1)
The least deprived (5)
The least deprived (5)
8
Figure 2 | Kaplan–Meier survival plots comparing the kidney transplant recipients in the most and the least socioeconomically deprived areas for their risk of death within the first year and in the long term post transplantation in England, respectively (2000–2012). 806
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deprived, 36% vs. 27% respectively, P ¼ 0.01). No association between area socioeconomic deprivation and death-censored graft survival was observed; income deprivation alone was associated with worse death-censored graft survival (hazard ratio 1.48, P ¼ 0.046). This is consistent with data from the United States where recipient employment status (peri- and post-transplantation, respectively) was found to have a strong and independent association with both patient and graft survival in a retrospective registry data analysis.15 Utilizing employment data alone is difficult, as transplantation can be associated with change in employment status. For example, Helantera et al.16 recently demonstrated increased employment opportunity post kidney transplantation compared with in-center hemodialysis, which one would anticipate improves income. This supports the use of more broadly defined assessments of area socioeconomic deprivation rather than reliance on single isolated domains. An important limitation in the analysis from Stephens et al.13 was the lack of ethnicity data, and its subsequent omission as a variable in the multivariate analysis, which could confound the data (although the authors cited very low numbers of non-whites within their transplant program). Regardless of such limitations, this analysis provides valuable insight into adverse outcomes post transplantation associated with broadly defined area socioeconomic deprivation that is independent of financial coverage for immunosuppression. Previous studies have predominantly focused on the association between area socioeconomic deprivation and poor access to transplantation.9–11,17 Two of these analyses11,17 focused on inferior access to living-donor transplantation for residents in areas of socioeconomic deprivation, and this is consistent with our findings. Exploring this link further is vital in the context of the survival advantages of living-donor and/or preemptive kidney transplantation. It is also important to determine why recipients residing in socioeconomically deprived areas have increased mortality post kidney transplantation. It may be that such residents have an inherent risk for higher mortality, and kidney transplantation does not significantly attenuate this risk. These individuals may also have weaker social support networks or negative health behavior that drives the risk for mortality (such as smoking, alcohol consumption, sedentary lifestyle, and poor diet). Our understanding of social epidemiological impact on health inequalities is limited,18 and developing targeting interventions such as support networks lack evidence-base for efficacy. Although such sociological interventions may improve the quality of life for kidney transplant recipients, it remains to be determined whether social support frameworks improve hard clinical end points, such as mortality or graft loss. The advantage of this study is the utilization of the Index of Multiple Deprivation classification,19,20 which attempts to measure a broader concept of area socioeconomic deprivation and is superior to the frequently cited Townsend Index.21 In addition, we have adjusted our data Kidney International (2013) 84, 803–809
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for a variety of important confounders in our Cox regression model. Most important is the adjustment for ethnicity, which our analysis demonstrated has unequal distribution across the area socioeconomic deprivation quintiles. Another strength is the linking of data between HES and Office for National Statistics, ensuring that all mortality events are captured for the study cohort. We are therefore confident that the robust association ascertained between area socioeconomic deprivation and mortality post kidney transplantation in our analysis is valid, although we acknowledge that statistics can never fully adjust for all the effects from observational data. There are several limitations of this analysis that must be appreciated in the interpretation of our results. There are likely to be numerous recipient-related confounders that have an impact on mortality post kidney transplantation that we were unable to factor in (e.g., smoking, lifestyle, dialysis vintage, etc.). Allograft failure within the first year is an important confounder, and the absence of robust data is an important limitation of our analysis, although in the context of our methodology unfortunately unavoidable. In the absence of obtainable data, we incorporated a surrogate for allograft failure in the Cox regression analysis. Although suboptimal, reassuringly, the inclusion/exclusion of the surrogate did not alter the hazard ratio linking area socioeconomic deprivation and 1-year mortality analysis. We can therefore speculate that the impact on 5-year mortality is similarly limited but was not analyzed (owing to the absence of pre-2006 data). Missing data (and misclassification bias) also have an implication on the analyses performed. The inaccuracy of HES data in relation to UK Transplant activity should also be acknowledged as demonstrated in our validation analysis. It should be appreciated that the area socioeconomic deprivation assessment by Index of Multiple Deprivation calculation is an indirect appraisal of the quality of health-care delivery. Determination of deprivation is at the level of postal code area and not the individual; the area socioeconomic deprivation calculation indicates that a particular area has a level of deprivation, and it does not necessitate that a specific individual within that area is socially deprived. The dynamic nature of residence suggests caution in attributing area socioeconomic deprivation to an individual who is newly resided in that local environment. Finally, mortality data are readily available and were the sole analytical end point of this analysis. However, the absence of recorded death may not necessarily translate to an assumption that a recipient remains alive (e.g., lost to follow-up owing to emigration). To conclude, this is the first study showing that area socioeconomic deprivation is independently associated with increased mortality 1 and 5 years post kidney transplantation. Further work is essential to investigate this sociological phenomenon, to aid our inadequate understanding of the social and environmental pressures faced by kidney allograft recipients residing in socially deprived neighborhoods. The ability to perform linkage analyses across different data 807
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registries is currently limited, but if feasible it would significantly enhance our ability to perform and/or enhance epidemiological analyses such as this with significant robustness. In the context of overwhelming health and economic advantages of kidney transplantation, exploring links between area socioeconomic deprivation and mortality is essential and may attenuate the long-term risk of death and allograft attrition rates. MATERIALS AND METHODS Data sources We obtained data on all kidney transplant procedures performed in England between April 2001 and March 2012, with patient demographics obtained at the time of transplant, including age, gender, donor type (living vs. deceased), ethnicity, allograft failure, medical comorbidities, and area socioeconomic deprivation. Data were obtained from HES,22 an administrative data warehouse containing admissions to all National Health Service hospitals in England. It contains detailed records relating to individual patient treatments, with data extraction facilitated using codes on procedural classifications (Office of Population Censuses and Surveys Classification of Interventions and Procedures, 4th revision (OPCS-4))23 and medical classifications (World Health Organization International Classification of Disease, 10th revision (ICD-10)).24 This study included all kidney transplant procedures (OPCS-4 codes; M01-M05, M08, and M09) performed in England between 2001 and 2012. With regard to outcome analysis, HES data alone have the limitation of only capturing deaths occurring in a hospital setting. To obtain the complete mortality list, the study cohort was cross-referenced with mortality data from the Office for National Statistics, which collects information on all registered deaths in the United Kingdom. Combining sources via this data linkage process creates a comprehensive data set with regard to mortality, which was the end point of interest in this analysis. Data regarding allograft failure were defined using a surrogate marker in the absence of specific obtainable data (return to dialysis for X10 dialysis sessions beyond 90 days post kidney transplantation). These data were only obtainable for years from April 2006 onward (11,961 kidney transplant procedures performed during this time period in England) and constituted the supportive analysis for the Cox regression models. This study did not require institutional review board approval owing to the pseudoanonymized nature of the data retrieved—data were linked by NHS Informatics using a special HES ID code and avoided patient-identifiable codes.
a single composite termed the Index of Multiple Deprivation. On the Index of Multiple Deprivation quintile scale, 1 represented the most deprived and 5 the least deprived area, respectively. Statistical analysis The primary outcome measure was mortality 1 year post kidney transplantation (for recipients transplanted between 2001 and 2012), with 5-year mortality (for recipients transplanted between 2001 and 2007) being the secondary outcome measure. These time points were arbitrarily chosen to represent short- and medium-term mortality risk, respectively. Cox’s Proportional Hazards Model was used (Stata 12, StataCorp LP, College Station, TX). The proportionality assumption was checked for each variable and the whole model (using scaled Schoenfeld Residuals). Variables included in the model were age, gender, donor type (living vs. deceased), area socioeconomic deprivation, ethnicity, year of transplant, and selected medical comorbidities (history of myocardial infarction, peripheral vascular disease, cerebrovascular disease, congestive cardiac failure pulmonary disease, liver disease, peptic ulcer, previous cancer, and diabetes). Additional analyses that included allograft failure in the model (defined as X10 dialysis sessions from 90 days of the transplant) were performed to adjust for this important variable— this was only possible for recipients transplanted from April 2006 onward (n ¼ 11,961). Recipients were identified as having allograft failure if they fulfilled the above criteria, and this was added as a covariate in the Cox model. Because of the small numbers of pediatric kidney transplant recipients, they were not analyzed in isolation and were incorporated into the main analyses. Missing data regarding area socioeconomic deprivation was ascertained in only 3% of the data. With the assumption that these data were missing at random, we simply performed list-wise deletion and excluded the missing values from the analysis. Other missing data (e.g., ethnicity) were adjusted for as dummy variables in the models as required. Survival analyses were performed by generation of Kaplan–Meier curve estimates. A P-value o0.05 was considered statistically significant in the analysis. DISCLOSURE
All the authors declared no competing interests. REFERENCES 1. 2.
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see commentary on page 647
Socioeconomic deprivation is independently associated with mortality post kidney transplantation Irena Begaj1, Sajan Khosla1, Daniel Ray1 and Adnan Sharif2 1
Department of Medical Informatics, Queen Elizabeth Hospital, Birmingham, UK and 2Department of Nephrology and Transplantation, Renal Institute of Birmingham, Queen Elizabeth Hospital, Birmingham, UK
The association between area socioeconomic deprivation and mortality post kidney transplantation is unclear. To clarify this, we obtained data from 19,103 kidney transplant procedures performed in England from April 2001 to March 2012. Patient demographics included age, gender, donor type (living or deceased), ethnicity, transplant year, allograft failure, medical comorbidities, and area socioeconomic deprivation (Index of Multiple Deprivation (2010)). Primary and secondary outcome measures were 1- and 5-year mortality with Cox proportional hazard models performed to identify independent factors associated with mortality. Data were broken down into quintiles of patients by area socioeconomic deprivation 1 to 5 (most to least deprived, respectively). At 1 year post transplant, 566 deaths were recorded, with infection being the most common cause of death. Compared with the most deprived individuals (reference point), the least deprived recipients had significantly decreased risk of death at 1 and 5 years post kidney transplant (hazard ratio 0.66, 95% CI (0.57–0.76) and hazard ratio 0.65, 95% CI (0.54–0.77), respectively). Thus, socioeconomic deprivation is independently associated with increased mortality post kidney transplantation. Kidney International (2013) 84, 803–809; doi:10.1038/ki.2013.176; published online 29 May 2013 KEYWORDS: area socioeconomic deprivation; kidney transplantation; mortality
Correspondence: Adnan Sharif, Department of Nephrology and Transplantation, Renal Institute of Birmingham, Queen Elizabeth Hospital, Edgbaston, Birmingham B15 2WB, UK. Email: [email protected] Received 17 October 2012; revised 21 February 2013; accepted 1 March 2013; published online 29 May 2013 Kidney International (2013) 84, 803–809
The association between area socioeconomic deprivation and mortality in the general population is well documented,1–5 but its relationship with mortality post kidney transplantation has never been adequately described. Analyses of the association of socioeconomic deprivation (represented at area or individual level) post kidney transplantation have focused predominantly on allograft outcomes, with data reported in the United States demonstrating poorer graft survival for recipients residing in more socially deprived areas.6,7 However, interpretation of area socioeconomic deprivation data from the United States in relation to kidney transplantation is confounded by suboptimal definitions (the use of isolated domains of socioeconomic deprivation assessment) and financial coverage limits regarding immunosuppression (medication affordability),8 which is likely to have an impact on outcome analysis. It is therefore more useful to explore social determinants of mortality post kidney transplantation in the context of robust definition and a health-care system administered by universal health coverage. In the United Kingdom, with universal health coverage through the state-funded National Health Service, this important limitation is eliminated and provides a useful model to analyze the effects of area socioeconomic deprivation post kidney transplantation. The handful of studies reported from the United Kingdom has predominantly focused on the impact of area socioeconomic deprivation and access to transplantation,9–12 with other studies reporting on kidney allograft outcomes.13 In this journal, Caskey et al.14 previously reported area socioeconomic deprivation to be independently associated with mortality after commencing renal replacement therapy (albeit this was a predominant dialysis (96.7%) population). To date, the impact of area socioeconomic deprivation (in the context of universal health coverage) on mortality post kidney transplantation remains unclear. In addition, there are several important limitations in many previous studies; first, they have used loosely defined indices of deprivation; and second, the lack of ethnicity data in many of these studies confounds interpretation of the independent influence of area socioeconomic deprivation. Therefore, the aim of this study was to explore the impact of area socioeconomic deprivation on 1- and 5-year mortality post kidney 803
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transplantation, independent of important confounders, by linking national data sources for all kidney transplant procedures performed in England over the past decade. Our assessment of area socioeconomic deprivation was by the Index of Multiple Deprivation: a composite index of multiple domains epidemiologically weighted to provide a spectrum of local-level assessment of areas of deprivation.
RESULTS
In total, 19,688 kidney transplant procedures were recorded between April 2001 and March 2012 (repeat transplants during this period were excluded from analysis); 584 were excluded owing to the lack of social deprivation information and 1 had no age/gender recorded, leaving us with 19,103 recipients for analysis. These data incorporate every kidney transplant procedure performed at every kidney transplant center in England over the past decade as recorded by Hospital Episode Statistics (HES; excluding any subsequent transplant during this period of analysis). Pediatric recipients constituted a small proportion of the overall number of
kidney transplants performed (4.9% (n ¼ 942) of the overall cohort with only 27 deaths). Data accuracy
To verify the quality of the HES data, we extracted information from the UK Transplant National Transplant database to determine the number of transplants performed during the same time frame. During the time from 1 April 2001 to 31 March 2013, 19,405 kidney transplant procedures were registered (19,241 kidney transplant alone, 49 en-bloc kidneys, and 115 double kidney transplants). This identifies a small discrepancy of 283 kidney transplant alone procedures that have been over-reported in the HES data in comparison to UK National Transplant Database records. Patients and area socioeconomic deprivation
Table 1 highlights the demographic make up of the kidney transplant patient cohort divided by area socioeconomic deprivation quintiles. Non-whites were more likely to reside in areas of high versus low area socioeconomic deprivation (Po0.001). Residents within more socially deprived areas
Table 1 | Summary of variables using area socioeconomic deprivation quintiles Most deprived (1)
(2)
(3)
(4)
Least deprived (5)
Patients, % (N) Age, median (Q1–Q3) Males, % (N)
22.0 (4203) 43 (32–53) 60.6 (2549)
22.0 (4197) 44 (34–55) 61.3 (2571)
19.7 (3765) 46 (35–57) 60.7 (2286)
18.3 (3490) 48 (36–58) 61.1 (2134)
18.0 (3448) 48 (37–58) 61.9 (2133)
Ethnicity, % (N) White Mixed Asian or Asian British Black or Black British Chinese Other ethnic groups Unknown
59.6 (2505) 1.2 (51) 15.1 (636) 10.1 (424) 0.6 (26) 3 (128) 10.3 (433)
67.2 (2822) 1 (42) 11.2 (470) 7 (292) 0.5 (20) 2.1 (90) 11 (461)
74.2 (2795) 0.6 (24) 7.8 (292) 3.4 (129) 0.4 (16) 1.5 (57) 12 (452)
80.7 (2817) 0.7 (25) 4.9 (170) 1.3 (46) 0.2 (6) 1.1 (39) 11.1 (387)
79.9 (2756) 0.7 (24) 3.9 (136) 1.2 (43) 0.4 (13) 1 (36) 12.8 (440)
Medical comorbidities, % (N) None recorded Acute myocardial Infraction Congestive heart failure Peripheral vascular disease Cerebral vascular accident Pulmonary disease Connective tissue disorder Peptic ulcer Cancer Liver disease Diabetes
73.6 (3095) 0.6 (107) 0.1 (28) 0.4 (81) 0.2 (38) 1.2 (220) 0.4 (85) 0.1 (19) 0.1 (15) 0.1 (19) 3.4 (651)
73.0 (3064) 0.6 (108) 0.2 (33) 0.3 (66) 0.2 (45) 1 (200) 0.5 (100) 0.1 (14) 0.1 (12) 0.1 (20) 3.9 (737)
74.2 (2793) 0.6 (112) 0.1 (26) 0.3 (61) 0.2 (34) 0.9 (180) 0.4 (84) 0.1 (15) 0.1 (20) 0.1 (13) 3.1 (590)
74.0 (2581) 0.5 (97) 0.1 (19) 0.2 (42) 0.1 (18) 0.9 (165) 0.3 (64) 0.1 (16) 0.1 (14) 0.1 (10) 2.6 (500)
76.7 (2645) 0.4 (79) 0.1 (14) 0.2 (34) 0.1 (19) 0.8 (161) 0.3 (52) 0.1 (13) 0.1 (16) 0.1 (24) 2.6 (492)
1.2 (33)
1.3 (36)
0.9 (21)
0.9 (20)
0.7 (15)
26.1 (1086)
31.8 (1335)
33.1 (1248)
36.6 (1277)
38.2 (1316)
1-Year mortality % (N)
3.4 (145)
3.1 (132)
2.7 (100)
3.1 (107)
2.4 (82)
5-Year mortality % (N)
8.2 (343)
7.3 (307)
7.5 (283)
7.5 (262)
6.3 (218)
Transplant failurea % (N) Living-donor transplant % (N)
a
Transplant failure defined as X10 dialysis sessions from 90 days post transplant (only transplants from 1 April 2006 to 31 March 2012). In this time period, there were 11,961 transplants in England.
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I Begaj et al.: Area socioeconomic deprivation and mortality post kidney transplantation
were also less likely to receive living-donor kidney transplantation compared with residents in less socially deprived areas (P ¼ 0.009). No other significant differences between the area socioeconomic deprivation quintile groups were observed. Mortality 1 year post kidney transplantation
There were 566 deaths recorded within the first year post kidney transplantation for this study population. One-year risks of mortality post kidney transplantation per Index of Multiple Deprivation (2010) quintile were as follows (from most to least deprived, respectively): 1 (3.6%), 2 (3.0%), 3 (3.2%), 4 (2.9%), and 5 (2.5%). Infection was the most common cause of death, accounting for 30.9% of all deaths within the first year post transplantation. Cardiovascular death was the second most common cause and accounted for 15.9% of all deaths. The remaining causes of death all accounted for o10% of mortality within the first year post kidney transplantation (see Figure 1). There was no significant difference between area socioeconomic deprivation quintile and cause of mortality within the first year post kidney transplantation (P ¼ 0.081). Survival analysis
At 1 year post kidney transplantation, recipients living in the area with the least socioeconomic deprivation had a significantly lower hazard ratio for death post kidney
transplantation compared with those living in the area with most socioeconomic deprivation (hazard ratio 0.66, 95% CI (0.57–0.76). Po0.001). At 5 years post kidney transplantation, recipients living in the area with least socioeconomic deprivation continued to have a lower hazard ratio for death post kidney transplantation compared with those living in the area with the most socioeconomic deprivation (hazard ratio 0.65, 95% CI (0.54–0.77), Po0.001) (see Table 2). Adding allograft failure into additional Cox regression model retained the same result (see Table 3), with individuals residing within areas of least socioeconomic deprivation having lower hazard ratio for death 1 year post kidney transplantation compared with those recipients living in areas with the most socioeconomic deprivation (hazard ratio 0.61, 95% CI (0.47–0.79), Po0.001). Owing to the inability to obtain allograft failure data (using our surrogate definition) preceding 2006, we did not perform any supportive analysis incorporating allograft failure into the statistical model for 5-year mortality risk post kidney transplantation. However, the absence of a major difference including/ excluding allograft failure on the hazard ratio at 1 year post kidney transplantation for area socioeconomic deprivation makes us speculate a similar negligible impact on 5-year mortality. Kaplan–Meier survival curves were performed and showed a constant disparity in the first year and long-term patient Cardiovascular Cerebrovascular Vascular Infection Malignancy Trauma Renal Metabolic Gl/liver Pulmonary Other Unknown
5.8%
3.0%
15.9%
5.5%
5.5% 5.8% 1.4%
6.4%
8.0%
4.6%
7.2%
30.9%
Figure 1 | Pie chart demonstrating the cause of 1-year mortality for all kidney allograft recipients (adult and pediatric) between 2001 and 2012 based upon registered death certificate details submitted to Office for National Statistics. Infection and cardiovascular death were the two most common causes of death at 30.9 and 15.9%, respectively, with all other causes o10% each. There was no significant difference in the cause of death between area socioeconomic deprivation quintiles (P ¼ 0.081). Kidney International (2013) 84, 803–809
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Table 2 | Cox regression output regarding 1- and 5-year mortality post kidney transplantation (assessing short- and medium-term risk of death, respectively) Mortality
Hazard ratio
95% Confidence interval
P-value
1-Year mortality Area socioeconomic deprivation quintile Most deprived (1) 1.00 (2) 0.83 (3) 0.85 (4) 0.80 Least deprived (5) 0.66
0.006 0.019 0.002 o0.001
0.73–0.95 0.75–0.97 0.70–0.92 0.57–0.76
5-Year mortality Area socioeconomic deprivation quintile Most deprived (1) 1.00 (2) 0.85 (3) 0.83 (4) 0.81 Least deprived (5) 0.65
0.035 0.026 0.010 o0.001
0.72–0.99 0.71–0.98 0.68–0.95 0.54–0.77
DISCUSSION
Cox regression model looking at area socioeconomic deprivation and mortality; adjusted for age, gender, ethnicity, living donor versus deceased donor, transplantation year, and selected medical comorbidities (history of myocardial infarction, peripheral vascular disease, cerebrovascular disease, congestive cardiac failure pulmonary disease, liver disease, peptic ulcer, previous cancer, and diabetes).
Table 3 | Cox regression output regarding mortality post kidney transplantation incorporating allograft failure (data from April 2006 onward, n ¼ 11,961) Mortality
Hazard ratio
1-Year mortality Area socioeconomic deprivation quintile Most deprived (1) 1.00 (2) 0.84 (3) 0.86 (4) 0.87 Least deprived (5) 0.61
survival comparing kidney allograft recipients living in the most and the least socially deprived neighborhoods, respectively (see Figure 2).
P-value
95% Confidence interval
0.119 0.198 0.232 o0.001
0.67–1.05 0.69–1.08 0.69–1.09 0.47–0.79
Cox regression model looking at area socioeconomic deprivation and mortality, adjusted for age, gender, ethnicity, living donor versus deceased donor, allograft failure*, transplantation year, and selected medical comorbidities (history of myocardial infarction, peripheral vascular disease, cerebrovascular disease, congestive cardiac failure pulmonary disease, liver disease, peptic ulcer, previous cancer, and diabetes). *Allograft failure surrogate definition: X10 dialysis sessions from 90 days post transplant (only transplants from 1 April 2006 to 31 March 2012). In this time period, there were 11,961 transplants in England.
In this study, we show that kidney transplant recipients who reside in a socially deprived neighborhood have increased mortality post kidney transplantation independent of age, gender, donor type (living vs. deceased), ethnicity, transplant year, allograft failure, medical comorbidities, and financial coverage. To our knowledge, this is the first clear description of an association between area socioeconomic deprivation and mortality post kidney transplantation, introducing an important and hitherto unconfirmed risk factor for posttransplant mortality. Further research is required to investigate this sociological association and the factors contributing to increased mortality for recipients residing in socially deprived environments. The efficacy and/or viability of developing support frameworks for recipients residing in areas of area socioeconomic deprivation post kidney transplantation to attenuate this risk also require further exploration. There is a paucity of literature linking area socioeconomic deprivation and adverse postkidney transplant outcomes, and little is known of social determinants of health in this population in general. Caskey et al.14 showed area socioeconomic deprivation to be associated with mortality post commencement of renal replacement therapy, although the data were skewed toward a dialysis population predominantly. To that effect, our analysis is the first to focus on mortality post kidney transplantation. More recently, Stephens et al.13 reported on the influence of area socioeconomic deprivation on graft outcomes after kidney transplantation in a single-center analysis of 621 consecutive recipients transplanted between 1997 and 2005. By using the Welsh Index of Multiple Deprivation (similar domains to our English index), the authors found that individuals living in the most deprived areas had a significantly greater risk of rejection requiring treatment (most deprived vs. least Long-term Kaplan–Meier survival plot
1-Year Kaplan–Meier survival plot 1.00
1.00
0.95 0.99
0.90 0.85
0.98
0.80
0.97
0.75 0.70
0.96 0
100
200
300
Survival time (days)
400
0
2 4 6 Survival time (years)
The most deprived (1)
The most deprived (1)
The least deprived (5)
The least deprived (5)
8
Figure 2 | Kaplan–Meier survival plots comparing the kidney transplant recipients in the most and the least socioeconomically deprived areas for their risk of death within the first year and in the long term post transplantation in England, respectively (2000–2012). 806
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deprived, 36% vs. 27% respectively, P ¼ 0.01). No association between area socioeconomic deprivation and death-censored graft survival was observed; income deprivation alone was associated with worse death-censored graft survival (hazard ratio 1.48, P ¼ 0.046). This is consistent with data from the United States where recipient employment status (peri- and post-transplantation, respectively) was found to have a strong and independent association with both patient and graft survival in a retrospective registry data analysis.15 Utilizing employment data alone is difficult, as transplantation can be associated with change in employment status. For example, Helantera et al.16 recently demonstrated increased employment opportunity post kidney transplantation compared with in-center hemodialysis, which one would anticipate improves income. This supports the use of more broadly defined assessments of area socioeconomic deprivation rather than reliance on single isolated domains. An important limitation in the analysis from Stephens et al.13 was the lack of ethnicity data, and its subsequent omission as a variable in the multivariate analysis, which could confound the data (although the authors cited very low numbers of non-whites within their transplant program). Regardless of such limitations, this analysis provides valuable insight into adverse outcomes post transplantation associated with broadly defined area socioeconomic deprivation that is independent of financial coverage for immunosuppression. Previous studies have predominantly focused on the association between area socioeconomic deprivation and poor access to transplantation.9–11,17 Two of these analyses11,17 focused on inferior access to living-donor transplantation for residents in areas of socioeconomic deprivation, and this is consistent with our findings. Exploring this link further is vital in the context of the survival advantages of living-donor and/or preemptive kidney transplantation. It is also important to determine why recipients residing in socioeconomically deprived areas have increased mortality post kidney transplantation. It may be that such residents have an inherent risk for higher mortality, and kidney transplantation does not significantly attenuate this risk. These individuals may also have weaker social support networks or negative health behavior that drives the risk for mortality (such as smoking, alcohol consumption, sedentary lifestyle, and poor diet). Our understanding of social epidemiological impact on health inequalities is limited,18 and developing targeting interventions such as support networks lack evidence-base for efficacy. Although such sociological interventions may improve the quality of life for kidney transplant recipients, it remains to be determined whether social support frameworks improve hard clinical end points, such as mortality or graft loss. The advantage of this study is the utilization of the Index of Multiple Deprivation classification,19,20 which attempts to measure a broader concept of area socioeconomic deprivation and is superior to the frequently cited Townsend Index.21 In addition, we have adjusted our data Kidney International (2013) 84, 803–809
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for a variety of important confounders in our Cox regression model. Most important is the adjustment for ethnicity, which our analysis demonstrated has unequal distribution across the area socioeconomic deprivation quintiles. Another strength is the linking of data between HES and Office for National Statistics, ensuring that all mortality events are captured for the study cohort. We are therefore confident that the robust association ascertained between area socioeconomic deprivation and mortality post kidney transplantation in our analysis is valid, although we acknowledge that statistics can never fully adjust for all the effects from observational data. There are several limitations of this analysis that must be appreciated in the interpretation of our results. There are likely to be numerous recipient-related confounders that have an impact on mortality post kidney transplantation that we were unable to factor in (e.g., smoking, lifestyle, dialysis vintage, etc.). Allograft failure within the first year is an important confounder, and the absence of robust data is an important limitation of our analysis, although in the context of our methodology unfortunately unavoidable. In the absence of obtainable data, we incorporated a surrogate for allograft failure in the Cox regression analysis. Although suboptimal, reassuringly, the inclusion/exclusion of the surrogate did not alter the hazard ratio linking area socioeconomic deprivation and 1-year mortality analysis. We can therefore speculate that the impact on 5-year mortality is similarly limited but was not analyzed (owing to the absence of pre-2006 data). Missing data (and misclassification bias) also have an implication on the analyses performed. The inaccuracy of HES data in relation to UK Transplant activity should also be acknowledged as demonstrated in our validation analysis. It should be appreciated that the area socioeconomic deprivation assessment by Index of Multiple Deprivation calculation is an indirect appraisal of the quality of health-care delivery. Determination of deprivation is at the level of postal code area and not the individual; the area socioeconomic deprivation calculation indicates that a particular area has a level of deprivation, and it does not necessitate that a specific individual within that area is socially deprived. The dynamic nature of residence suggests caution in attributing area socioeconomic deprivation to an individual who is newly resided in that local environment. Finally, mortality data are readily available and were the sole analytical end point of this analysis. However, the absence of recorded death may not necessarily translate to an assumption that a recipient remains alive (e.g., lost to follow-up owing to emigration). To conclude, this is the first study showing that area socioeconomic deprivation is independently associated with increased mortality 1 and 5 years post kidney transplantation. Further work is essential to investigate this sociological phenomenon, to aid our inadequate understanding of the social and environmental pressures faced by kidney allograft recipients residing in socially deprived neighborhoods. The ability to perform linkage analyses across different data 807
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registries is currently limited, but if feasible it would significantly enhance our ability to perform and/or enhance epidemiological analyses such as this with significant robustness. In the context of overwhelming health and economic advantages of kidney transplantation, exploring links between area socioeconomic deprivation and mortality is essential and may attenuate the long-term risk of death and allograft attrition rates. MATERIALS AND METHODS Data sources We obtained data on all kidney transplant procedures performed in England between April 2001 and March 2012, with patient demographics obtained at the time of transplant, including age, gender, donor type (living vs. deceased), ethnicity, allograft failure, medical comorbidities, and area socioeconomic deprivation. Data were obtained from HES,22 an administrative data warehouse containing admissions to all National Health Service hospitals in England. It contains detailed records relating to individual patient treatments, with data extraction facilitated using codes on procedural classifications (Office of Population Censuses and Surveys Classification of Interventions and Procedures, 4th revision (OPCS-4))23 and medical classifications (World Health Organization International Classification of Disease, 10th revision (ICD-10)).24 This study included all kidney transplant procedures (OPCS-4 codes; M01-M05, M08, and M09) performed in England between 2001 and 2012. With regard to outcome analysis, HES data alone have the limitation of only capturing deaths occurring in a hospital setting. To obtain the complete mortality list, the study cohort was cross-referenced with mortality data from the Office for National Statistics, which collects information on all registered deaths in the United Kingdom. Combining sources via this data linkage process creates a comprehensive data set with regard to mortality, which was the end point of interest in this analysis. Data regarding allograft failure were defined using a surrogate marker in the absence of specific obtainable data (return to dialysis for X10 dialysis sessions beyond 90 days post kidney transplantation). These data were only obtainable for years from April 2006 onward (11,961 kidney transplant procedures performed during this time period in England) and constituted the supportive analysis for the Cox regression models. This study did not require institutional review board approval owing to the pseudoanonymized nature of the data retrieved—data were linked by NHS Informatics using a special HES ID code and avoided patient-identifiable codes.
a single composite termed the Index of Multiple Deprivation. On the Index of Multiple Deprivation quintile scale, 1 represented the most deprived and 5 the least deprived area, respectively. Statistical analysis The primary outcome measure was mortality 1 year post kidney transplantation (for recipients transplanted between 2001 and 2012), with 5-year mortality (for recipients transplanted between 2001 and 2007) being the secondary outcome measure. These time points were arbitrarily chosen to represent short- and medium-term mortality risk, respectively. Cox’s Proportional Hazards Model was used (Stata 12, StataCorp LP, College Station, TX). The proportionality assumption was checked for each variable and the whole model (using scaled Schoenfeld Residuals). Variables included in the model were age, gender, donor type (living vs. deceased), area socioeconomic deprivation, ethnicity, year of transplant, and selected medical comorbidities (history of myocardial infarction, peripheral vascular disease, cerebrovascular disease, congestive cardiac failure pulmonary disease, liver disease, peptic ulcer, previous cancer, and diabetes). Additional analyses that included allograft failure in the model (defined as X10 dialysis sessions from 90 days of the transplant) were performed to adjust for this important variable— this was only possible for recipients transplanted from April 2006 onward (n ¼ 11,961). Recipients were identified as having allograft failure if they fulfilled the above criteria, and this was added as a covariate in the Cox model. Because of the small numbers of pediatric kidney transplant recipients, they were not analyzed in isolation and were incorporated into the main analyses. Missing data regarding area socioeconomic deprivation was ascertained in only 3% of the data. With the assumption that these data were missing at random, we simply performed list-wise deletion and excluded the missing values from the analysis. Other missing data (e.g., ethnicity) were adjusted for as dummy variables in the models as required. Survival analyses were performed by generation of Kaplan–Meier curve estimates. A P-value o0.05 was considered statistically significant in the analysis. DISCLOSURE
All the authors declared no competing interests. REFERENCES 1. 2.
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