Objectives: We evaluated risk factors that could adversely affect outcomes from elderly deceased-donor transplants.
Materials and Methods: In this single center retrospective study (112 patients), we studied the impact of acute rejection episodes, delayed graft function, donor-recipient age differences, HLA-DR mismatches, HLA antigen mismatches, recipient comorbidities, cold ischemia time, donor and recipient age, and donor serum creatinine level on short- and long-term graft survival.
Results: Mean ages of donors and recipients were 64.71 ± 4.09 and 50.39 ± 13.72 years. Delayed graft function was 40.2%, whereas acute rejection episode rate was 38%. Graft and patient survival rates were 80.4% and 67.7%, 63.6% and 91.9%, and 82.1% and 78.2% at 1, 3, and 5 years. Cold ischemia time, recipient comorbidity, and total HLA antigen mismatch did not significantly affect graft outcome. Acute rejection episode was an independent predictor of graft outcome (β level = 2.857, t test = 2.3, P = .025). Donor age was a predictor of total graft survival duration (log-rank test gave chi-square test with 2 df = 12.292, P = .002). Donor estimated glomerular filtration rates ≥ 60 mL/min produced better outcomes than those < 60 mL/min (log-rank test gave chi-squared test with 1 df = 7.213, P = .007). Multivariate Cox regression analysis showed that donor age and delayed graft function were not significant predictors of graft outcome (P > .05), whereas acute rejection episodes (hazard ratio 5.443; 95% confidence interval, 2.226-15.311; P < .001) and donor estimated glomerular filtration rate (hazard ratio 0.449; 95% confidence interval, 0.209-0.945; P = .035) remained significant predictors of cumulative graft survival.
Conclusions: The risk factors mentioned above should be avoided to achieve better graft survival. Emphasis should not be on donor age alone. Good donor kidney function and proper immunosuppressive therapy to reduce acute rejection episodes are cornerstones to improved outcomes.
Key words : Cold ischemia, Delayed graft function, Immunosuppressive agents
The rising global prevalence of chronic kidney disease has dramatically increased the number of patients who start renal replacement therapy.1 Kidney transplant is no doubt the preferred renal replacement therapy; it is superior to dialysis in terms of quality of life and long-term mortality risk.2,3
However, the imbalance between the numbers of candidates on the deceased-donor kidney wait list and the number of deceased donors has made expansion of the criteria for organ donation inevitable. This shortage has been reported to be increasing exponentially every year.4 Most studies have indicated that donor age has an adverse effect on graft survival.5-11 However, kidneys from very young donors are also associated with poor outcome, likely related to technical complications and graft thrombosis.12
Furthermore, studies have shown that patient survival at the end of the first and third year after transplant were comparable between expanded criteria donors and standard criteria donors13-15; however, graft survival and function were significantly worse with increased incidence of delayed graft function (DGF) and acute rejection episodes.15 Ferrer and associates identified DGF and acute rejection episodes as risk factors for graft failure.15 In addition, there are reports concluding that there is no statistical significant correlation between donor age and 5-year graft function.16 Therefore, donors who were previously considered as not ideal are now considered to be suitable.17 Here, we explored transplant outcomes of patients who received kidneys from elderly donors (aged 60 years and above) at a single center.
Materials and Methods
This was a retrospective study of all recipients who had deceased-donor kidney transplants, with donor age 60 years and above, at Sheffield Kidney Institute between March 1969 and February 2009. The inclusion criteria were deceased-donor transplants from donors ≥ 60 years old and kidney transplant that occurred between March 1969 and February 2009. The following recipients were excluded: deceased-donor transplants from donors < 60 years old, living-donor transplants of any donor age, and deceased- or living-donor transplants before March 1969 or after February 2009.
We determined graft and patient survival outcomes of kidney transplants from elderly donors by retrieving the following donor factors: donor age, sex, serum creatinine level, estimated glomerular filtration rate (eGFR), and cold ischemia time. The following recipient factors were also obtained: patient status (dead or alive), age, sex, comorbidities (cardiovascular disease, type 2 diabetes mellitus, cerebrovascular disease, and hypertension), type of immunosuppressants used, number of acute rejection episodes, DGF, and eGFR at 3, 12, and 60 months after transplant. Donor ages were categorized as follows: 60 to 64 years old, 65 to 69 years old, and ≥ 70 years old. The following donor-recipient factors were obtained: HLA antigen mismatches, HLA-DR only mismatches, total follow-up, total duration of graft survival, and graft and recipient survival at 1, 3, and 5 years after transplant.
The acute rejection episodes were as reported in hospital records. All of the episodes were confirmed by kidney allograft biopsy. Delayed graft function was defined as the need for dialysis within the first week of transplant. The eGFR was obtained using the Modification of Diet in Renal Disease equation because the creatinine methodology used in our laboratory is traceable to isotope dilution mass spectrometry. Graft loss or nongraft survival was defined as a rise in serum creatinine level requiring renal replacement therapy of any sort within the first week of transplant, whereas death of recipient was considered as nonpatient survival.
Statistical analyses were performed with SPSS software (SPSS: An IBM Company, version 21, IBM Corporation, Armonk, NY, USA). Continuous variables (donor age, recipient age, cold ischemia time, serum creatinine level, and length of hospital stay) were expressed as means ± standard deviation. Analysis of variance was used to analyze outcomes based on donor age categories (60-64 y, 65-69 y, and > 70 y). Categorical variables (sex, recipient ethnicity, primary renal disease, acute rejection episodes, delayed graft function, and posttransplant infections) were determined from hospital records and scored as 0 or 1. Any differences between continuous variables were analyzed with the t test. Categorical variables were analyzed by chi-squared analysis and Fisher exact test. Where appropriate, univariate relations between variables were determined by simple correlation or linear (least squares) regression analysis. Multivariate analysis of the variables was done using graft outcome as the dependent variable and acute rejection episodes, age difference, HLA antigen mismatch, cold ischemia time, donor eGFR, and recipient comorbidities as independent variables in a multinomial logistic regression. Survival analysis was performed with the Kaplan-Meier method.19 Cox regression model was used for multiple predictors of survival function.
In the 112 transplants performed during the study period, there were 112 donors. Fifty-nine of the donors were females (52.7%). The mean donor age was 64.71 ± 4.00 years. Basic donor characteristics are shown in Table 1.
Of 112 recipients, thirty-eight were females (33.9%). Basic recipient characteristics are shown in Table 1.
At 1 year, patient survival was 91.9%. At 3 years, patient survival was 82.1 %, whereas 5-year patient survival was 78.2%.
At 1 year, graft survival was 80.4%. At 3 years, graft survival was 67.7%, whereas 5-year graft survival was 63.6%.
Predictive analysis of graft survival with univariate analysis
Donor age (r = -0.292, P = .008) and donor serum creatinine level (r = -0.294, P = .011) were significantly correlated with total duration of graft survival. These and other associations among donor, recipient, and donor-recipient characteristics and total duration of graft survival are shown in Table 2.
Figure 1 and Table 3 show the multiple regression model of total duration of graft survival as the dependent variable. The independent variables included total HLA antigen mismatch, HLA-DR mismatch, recipient comorbidities, cold ischemia time, age differences, delayed graft function, acute rejection episodes, donor eGFR, and donor age. Age differences (β level = 0.179, t test = 3.829, P = .001), donor eGFR (β level = - 2.513, t test = -2.099, P = .04), and donor age (β level = -2.389, t test =-3.125, P = .03) are independent predictors of total duration of graft survival. Donor eGFR and age negatively predicted graft survival.
Figure 2 shows the Kaplan-Meier model of survival analysis as a function of eGFR. This model shows that the use of kidneys from donors with eGFR of 60 mL/min produced better cumulative graft survival than those with eGFR less than 60 mL/min.
Figure 3 shows the Kaplan-Meier survival model as a function of categorized donor age. Interestingly, kidneys from donors age 70 years and older had the highest cumulative survival. However, a multivariate survival analysis using Cox regression model for donor age with delayed graft function, acute rejection episodes, and donor eGFR as covariates showed that donor age was not a significant predictor of total duration of graft survival (P > .05), whereas acute rejection episodes (hazard ratio 5.443; 95% confidence interval, 2.226-15.311; P < .001) and donor eGFR (hazard ratio 0.449; 95% confidence interval, 0.209-0.945; P = .035) were significant predictors of cumulative graft survival (Table 4).
The acute shortage of donor organs for kidney transplant has necessitated the expansion of criteria for deceased donors in many institutions. The extended criteria donor has been well defined. Despite many criticisms against the use of kidneys from elderly donors, graft function has been found to be independent of age of the donor.20
This study demonstrated no significant association regarding donor age when other donor variables such as kidney function and donor-recipient variables (delayed graft function and acute rejection episodes) are taken into consideration. Similarly, cold ischemia time, recipient comorbidity, and total number of HLA antigen mismatches also had no significant association with graft survival, in either the short or long term. Conversely, Opelz and associates analyzed the impact of HLA antigen matching on kidney graft survival using the data of the Collaborative Transplant Study.21 They concluded that HLA antigen mismatches significantly influenced the outcome of kidney transplants.21 Reisaeter and associates highlighted the effect of HLA-DR mismatch on long-term graft survival in a single center study of 655 nonsensitized recipients of primary kidney grafts from deceased donors. One-year HLA-DR matched graft survival was 90% versus 82% (P = .004) and 73% (P = .001) for 1 and 2 HLA-DR antigen-mismatched grafts. Five-year survival rates were 76%, 62%, and 56%. The group also demonstrated that matching for HLA-A and HLA-B antigens did not significantly improve overall graft survival but improved graft survival at 1 year.22
Moreira and associates reported delayed graft function of 19% among 997 deceased-donor kidney transplants.23 The incidence of delayed graft function in our study was quite high (40.2%). This may indicate susceptibility of kidneys from elderly donors to delayed graft function. Moreira and associates also reported in their retrospective study a significant reduction in long-term graft survival of kidneys after delayed graft function without any effect on patient survival.23 In our study, delayed graft function did not predict long-term outcome in the general population of elderly donors who were greater than 60 years old.
It is noteworthy that the donor eGFR in this study was significantly associated with total duration of graft survival and was an independent predictor of cumulative survival even when other donor, recipient, and donor-recipient factors were taken into consideration. The associations between donor eGFR and transplant outcome have been generally underreported. The emphasis has been on donor age. Collins and associates reviewed deceased-donor kidney transplant in Australia and New Zealand over 14 years, during which they investigated the adjusted donor eGFR and its association with donor age. However, there was no reference to definitive measure of the association between the eGFR and graft survival.24 We attempted to examine the association between eGFR and graft survival, and this was statistically significant. This may point to the fact that the quality of donor kidneys (ie, donor eGFR) might be more important than donor age.
Furthermore, there are series of studies advocating age for transplant as a means of conserving the much needed kidneys from young donors. This actually formed the basis of the Eurotransplant Senior Program that was started in 1999,25 with the United States also having a similar program called Life Year From Transplant using the United Network for Organ Sharing.26 Although, Ferrari and associates demonstrated no significant effect of age difference on both patient and graft survival in living-donor kidney transplant,27 our study shows that age difference predicts graft survival. Age difference might have a role in kidneys from deceased donors in the presence of other risk factors discussed above.
We reported a high incidence of acute rejection episodes in this study (33.9%). This could be related to the reported high incidence of delayed graft function. It may also be due to reduction of immunosuppressive therapy in an attempt to help the elderly kidneys recover from delayed graft function. Acute rejection episodes demonstrated adverse effects on graft survival. This result is not surprising given the reduced nephron mass of these donor kidneys. Acute rejection could further reduce the nephron mass, enhancing further reduction of graft survival. Taherimahmoudi and associates demonstrated that, the lower the nephron mass index, the greater the short-term graft loss. However, in the long term, no significant correlation was found between graft survival and nephron mass index.28 The reported patient survival in this study is comparable with other single center reported survival results.29 It is worth mentioning that the immunosuppression protocols was changed in our unit from cyclosporine based to tacrolimus based in 2002. This had no effect on the message conveyed in this study as it addresses the various risk factors that could adversely lower graft survival regardless of the immunosuppressive agents used. Also, cold ischemia time was not significantly associated with overall graft survival in our study. However, there have been reports of similarities in graft outcomes between deceased-donor and living-donor transplants in a setting where the cold ischemia time in deceased-donor transplant was significantly decreased.30
Kidneys from deceased elderly donors could be a valuable source, provided that the risk factors mentioned above are avoided. Proper donor selection based on eGFR may ensure better posttransplant function and subsequently better graft survival; better HLA-DR matched kidneys will produce better outcomes. Proper immunologic manipulation to avoid the adverse effects of acute rejection episodes with their effects on reduction of the nephron mass is essential.
Volume : 14
Issue : 1
Pages : 32 - 37
DOI : 10.6002/ect.2015.0111
From the 1Lagos State University Teaching Hospital/College of
Medicine, Lagos, Nigeria; and the 2Sheffield Kidney Institute,
Sheffield Teaching Hospital NHS, United Kingdom
Acknowledgements: The authors declare that they have no conflicts of interest and received no funding for this study.
Corresponding author: Ahmed Halawa, Sheffield Kidney Institute, Sheffield Teaching Hospital NHS, Herries Road, Sheffield, S5 7AU, UK
Phone: +44 77 8754 2128
Fax: +44 11 4271 4604
Table 1. Basic Characteristics of Donors and Recipients
Table 2. Correlation Analyses of Total Duration of Graft Survival and Various Donor, Recipient, and Donor-Recipient Factors
Table 3. Multivariate Analyses of Total Duration of Graft Survival (Dependent Variable) and Donor, Recipient, and Recipient-Donor Variables (Independent Variables)
Table 4. Multivariate Analyses of Cumulative Graft Survival as a Function of Donor Age After Correcting for Acute Rejection Episodes, Delayed Graft Function, and Donor Estimated Glomerular Filtration Rate
Figure 1. Multivariate Analyses of Total Duration of Graft Survival (Dependent Variable) and the Donor, Recipient, and Recipient-Donor Factors (Independent Variables)
Figure 2. Kaplan-Meier Survival Model of Graft Function Based on Donor Estimated Glomerular Filtration Rate
Figure 3. Kaplan-Meier Survival Model of Graft Function Based on Donor Age Categories