To determine whether the High-P and High-NP subgroups differed for relevant clinical, histologic, and laboratory characteristics either at baseline or during subsequent follow-up, univariate and multivariate analyses were conducted. As shown in Table 2A, univariate analysis indicated associations between High-P status and younger recipient age, higher number of transplants, white recipient race, female recipient gender, nonuse of Thymoglobulin induction, transplant glomerulopathy on 1-year surveillance biopsy, and abnormal proteinuria within 1 year of the most recent eGFR measurement. There were also trends toward associations of High-P status with pretransplantation anti–class II DSA and with anti–class II DSA within 1 year of the most recent eGFR measurement, which did not reach significance (although posttransplantation data were available for only a limited number of study subjects). In multivariate analysis (Table 2B), the associations with higher transplant number, female recipient gender, nonuse of Thymoglobulin induction, and abnormal proteinuria within 1 year of the most recent eGFR measurement remained significantly associated with High-P status.
Alternative Approaches to Assessing Renal Function Trends
Comparisons were performed between the eGFRMDRD 6-m interval approach and alternative methods for estimating or measuring GFR (see Table S1, SDC, http://links.lww.com/TP/A710).
The slope cutoff for progressor status was independently determined for each method. The proportion of failed grafts considered to be progressors was similar for each method (83%–88%; see Table S1A, SDC, http://links.lww.com/TP/A710). However, the formula-based eGFR methods identified higher proportions of progressor grafts that failed during follow-up compared with iothalamate clearance (34%–40% vs. 17%). Overall, the similarity between eGFRMDRD 6-m interval and other methods was 88% to 96% (see Table S1B, SDC, http://links.lww.com/TP/A710).
Our results agree with existing literature indicating that renal allografts with low eGFRMDRD 1 year or less after transplantation have inferior subsequent graft survival (3, 9, 11) in the first few years after transplantation. However, in the current study, most allograft failures between 2.5 and 7 years after transplantation showed a 1-year eGFRMDRD 40 mL/min or greater (65%; 53/81). Thus, a low 1-year eGFR seems to contribute most of its predictive value during the first few posttransplantation years. Therefore, categorizing transplant recipients into low- and high-risk groups on the basis of a single early GFR estimate would fail to identify a substantial number of recipients who are destined for future graft failure beyond 2.5 years. We believe that this concept is an important and underappreciated finding and questions the validity of using a single measure of early renal function as a primary endpoint for clinical trials in kidney transplantation (13–15). We contend that the current study’s use of sequential eGFR values between 1 and 5 years to create an eGFR slope provides a fuller picture of the fate of renal allografts after transplantation and might provide a useful endpoint for clinical trials designed to improve long-term graft survival.
This study also extends our prior research in chronic injury, which showed that not all renal allografts are affected by chronic injury in the first 5 years after transplantation (8). Indeed, most renal allografts with 1-year eGFRMDRD of 40 mL/min or greater have stable or improving function between 1 and 5 years. Even after excluding all patients with low 1-year eGFR and grafts with limited survival or follow-up during the first 2.5 years after transplantation, 43% of the entire starting population (405/953) would have showed renal functional profiles comparable with healthy people up to 7 years after transplantation. These results are similar to findings reported from the U. S. Renal Data System and single centers using data from exclusively deceased-donor recipients (16, 17). Most notably, in a study by Gill et al. (16), in which the rate of functional decline was assessed for grafts surviving at least 2 years, the overall decline in renal function was slow (−1.66 mL/min/1.73 m2 per yr), and 50% of recipients showed no change or an improvement in eGFRMDRD.
We believe that these findings have important therapeutic implications. First, most well-functioning grafts at 1 year that have stable or improved function suggest that sweeping changes in immunosuppression are not needed to prevent chronic injury in most allografts in the first 5 years after transplantation. In contrast, if we are to improve overall long-term graft survival, we cannot focus solely on improving 1-year GFR but also must identify the causes of renal functional decline in grafts that have good function at 1 year.
For the 122 allografts identified as having progressive renal dysfunction, we investigated the possible causes using both univariate and multivariate analyses. Only a small proportion of progressors exhibited specific characteristics previously associated with increased risk of graft failure such as overt complications (BK nephropathy, recurrent disease, and calcineurin inhibitor), abnormal histologic condition (glomerulopathy and fibrosis+inflammation), and deceased-donor source (2, 4, 7). The relatively low frequency of these well-defined risks among the High-P group suggests that different factors may contribute to the progressive loss of function in these grafts compared with low GFR grafts. The significant associations with progressor status observed included female gender, retransplantation, and lack of Thymoglobulin induction, perhaps implicating a role for antidonor sensitization. Interestingly, despite a trend toward higher frequency of pretransplantation anti–class II DSA among the High-P compared with High-NP group (16% vs. 8%), this did not reach significance indicating that pretransplantation sensitization was not highly enriched among the progressors. Although the amount of data available to interrogate the role of time-dependent posttransplantation variables in this cohort was relatively limited, it is of interest that the most recent 24-hr urine protein measurements indicated that the frequency of abnormal proteinuria became higher over time in the High GFR progressors having been no different to nonprogressors at 1 year after transplantation. Clearly, more comprehensive, prospective analysis will be necessary to determine whether the emergence of de novo proteinuria, DSA, or other abnormalities occurs before, after, or concurrent with declining functional measurements.
A limited number of prior studies have used multiple measures of renal function collected within the first 2 years after transplantation and have determined that the change in function between two measurements can be used to improve the association with eGFR and long-term survival (5, 9, 10). Given the known variability in eGFR values (18), it is likely that the inclusion of additional data points, as we have performed here, adds further accuracy to the estimation of the rate of functional change. For all subjects in the study, we used five or more data points (range, 5–9), each representing the mean of all eGFRMDRD measurements available within the 6-month intervals between 1 and 5 years. On average, 40 (range, 6–242) unique eGFRMDRD measurements were available for the study-eligible grafts. Given the ubiquitous use of frequent serum creatinine and formula-based eGFR measurements in the follow-up of kidney transplant recipients, we believe that this approach can be readily applied both retrospectively and prospectively to routine clinical practice and to clinical trials.
A concern for any long-term prospective study of kidney transplant recipients is the collection of functional measurements in most patients. For example, 3 year follow-up of the Symphony study included eGFR data on only 45% of the original study population (710/1589) (19), and a 5-year analysis of the BENEFIT study included eGFR data on 52% (66/145) of patients originally randomized to belatacept (20). The large proportions of missing subjects from these studies make it difficult to confidently interpret the results. In contrast, our approach resulted in the inclusion of 76% of all adult conventional recipients who underwent transplantation from 2000 to 2005 (788/1039 if 86 grafts lost <1 year are included). To reach such a high inclusion rate in our cohort, we used eGFRMDRD, which is known to underestimate the rate of change in renal function when compared with iothalamate clearance (12). Consistent with this, only 59% of the progressors identified by uncorrected iothalamate were also identified by eGFRMDRD (as opposed to 95% of nonprogressors; see Table S1B, SDC, http://links.lww.com/TP/A710). However, the rate of graft failure among the iothalamate-defined progressors was lower than those identified by eGFRMDRD (17% vs. 34%, see Table S1A, SDC, http://links.lww.com/TP/A710), suggesting that a formula-based approach using a large number of sequential creatinine measurements has distinct value for identifying transplants at high risk for failure.
We conclude that a single GFR measurement at 1 year (or any time point), although associated with graft failure risk in the short term, is insufficient to provide long-term risk stratification of renal transplant recipients. Instead, a combination of early and repeated estimates of GFR can be used to identify grafts at high risk for failure out to 7 or more years after transplantation. This approach also more accurately identifies the 40% to 60% of all kidney transplant recipients who achieve good early function and maintain it for a prolonged period. The progressive decline in eGFR observed among a subset of grafts with good early function was associated with higher frequency of characteristics that are linked to immune-mediated injury. However, the poor outcome for this subset cannot be fully explained by these associations, and investigation of other candidate factors such as patient compliance, late development of antidonor antibody, and genetic variability is merited (21–23). Finally, we contend that to improve long-term renal allograft survival, attention must be focused on refining methods to accurately identify progressive loss of graft function as early as possible, with the goal of elucidating and treating the causes.
MATERIALS AND METHODS
The study protocol was approved by the Mayo Clinic institutional review board. All adult recipients of kidney transplants performed at Mayo Clinic, Rochester, MN, between January 2000 and December 2005 were identified. The following groups were excluded from further study: (1) pediatric (<18 years), (2) positive pretransplantation antidonor T- and B-cell flow cytometric crossmatch, (3) ABO blood group incompatibility, (4) combined solid organ transplants, and (4) nonconsent to research.
Seventy-eight percent of study subjects received calcineurin inhibitor–based immunosuppression, 3% received mammalian target of rapamycin inhibitor, and 19% received a combination of both classes. Eighty-one percent received induction with Thymoglobulin.
One-year surveillance biopsies were obtained from 75% of study subjects. Biopsies were performed as previously described and were interpreted by a consultant renal pathologist using the Banff ’97 classification (24). Proteinuria was assessed by 24-hr urine total protein measurements at 1 year after transplantation and annually thereafter, with abnormal proteinuria defined as greater than 150 mg/24 hr (25). Pretransplantation DSA screening was performed on stored serum samples by single antigen bead assay as previously described (6). Graft failure was defined as return to dialysis or eGFRMDRD consistently less than 20 mL/min for 6 months or more.
Assessment of Renal Function
Uncorrected iothalamate clearance and serum creatinine measurements were extracted from the Mayo Clinic Transplant database for all study subjects. Serum creatinine values were converted to eGFR using eGFRMDRD and other formula-based calculations (see Table S1, SDC, http://links.lww.com/TP/A710). A total of 2783 iothalamate clearances and 34,376 serum creatinine measurements between 1 and 5 years after transplantation were obtained for 953 subjects. Forty-five percent of the creatinine measurements were performed by Mayo Clinic laboratories; and 55%, by external laboratories. For the Mayo laboratory data, both the pre–isotope dilution mass spectrophotometry (IDMS) (26) and IDMS (27) equations were used, whereas for external laboratory values, only the pre-IDMS (26) formula was used.
Calculation of Slope of Renal Function
Change in estimated renal function over time was determined by linear regression of all eGFRMDRD values between 1 and 5 years. To reduce variation across time, individual eGFRMDRD values were combined into means within 6-month posttransplantation intervals (i.e., 1–1.5, 1.5–2 yr). Data for a minimum of five 6-month intervals were required equating to a minimum renal transplant follow-up of 2.6 years. The log10 of the 6-month averaged eGFRMDRD values was plotted over time for each study subject; and the slope of each plot, calculated. After this, the subjects were divided into quintiles based on the values for eGFRMDRD slope.
Subsequently, categorization as progressor status was based on the following criteria: (1) located in the quintile with the most negative eGFRMDRD slope, (2) absolute eGFRMDRD decline of 20% or greater between 1 year and most recent less than 5-year eGFRMDRD, and (3) average eGFRMDRD less than 60 mL/min for at least one 6-month interval.
Results are expressed throughout as means (SD). The proportions of nominal data were tested using chi-square (Pearson) test. Continuous variables were tested using the Student t test for parametric data and Wilcoxon test for nonparametric data. Univariate and multivariate logistic regression analyses were used to analyze clinical variables associated with unstable graft function between 1 and 5 years, and a receiver operating characteristic curve analysis was performed to determine if any combination of factors could predict outcomes. A P value of <0.05 was considered statistically significant. The JMP statistical software system (SAS, Cary, NC) was used to perform calculations.
1. 1. Meier-Kriesche HU, Schold JD, Kaplan B. Long-term renal allograft survival: have we made significant progress or is it time to rethink our analytic and therapeutic strategies? Am J Transplant
2004; 4: 1289.
2. Park WD, Griffin MD, Cornell LD, et al.. Fibrosis with inflammation at one year predicts transplant functional decline. J Am Soc Nephrol
2011; 21: 1987.
3. Kasiske BL, Israni AK, Snyder JJ, et al.. The relationship between kidney function and long-term graft survival
after kidney transplant. Am J Kidney Dis
2011; 57: 466.
4. Issa N, Cosio FG, Gloor JM, et al.. Transplant glomerulopathy: risk and prognosis related to anti-human leukocyte antigen class II antibody levels. Transplantation
2008; 86: 681.
5. Hariharan S, McBride MA, Cherikh WS, et al.. Post-transplant renal function in the first year predicts long-term kidney transplant survival. Kidney Int
2002; 62: 311.
6. Gloor JM, Sethi S, Stegall MD, et al.. Transplant glomerulopathy: subclinical incidence and association with alloantibody. Am J Transplant
2007; 7: 2124.
7. El-Zoghby ZM, Stegall MD, Lager DJ, et al.. Identifying specific causes of kidney allograft loss. Am J Transplant
2009; 9: 527.
8. Stegall MD, Park WD, Larson TS, et al.. The histology of solitary renal allografts at 1 and 5 years after transplantation. Am J Transplant
2011; 11: 698.
9. Magott-Procelewska M, Boratynska M, Janczak D, et al.. Estimated glomerular filtration rate
evolution between 6 and 24 months predicts long-term kidney transplant survival among patients with inferior graft function. Transplant Proc
2009; 41: 3028.
10. Wu J, Li H, Huang H, et al.. Slope of changes in renal function in the first year post-transplantation and one-yr estimated glomerular filtration rate
together predict long-term renal allograft survival. Clin Transplant
2010; 24: 862.
11. Lenihan CR, O’Kelly P, Mohan P, et al.. MDRD-estimated GFR at one year post-renal transplant is a predictor of long-term graft function. Ren Fail
2008; 30: 345.
12. Gera M, Slezak JM, Rule AD, et al.. Assessment of changes in kidney allograft function using creatinine-based estimates of glomerular filtration rate
. Am J Transplant
2007; 7: 880.
13. Guba M, Pratschke J, Hugo C, et al.. Renal function, efficacy, and safety of sirolimus and mycophenolate mofetil after short-term calcineurin inhibitor-based quadruple therapy in de novo renal transplant patients: one-year analysis of a randomized multicenter trial. Transplantation
2010; 90: 175.
14. Holdaas H, Rostaing L, Seron D, et al.. Conversion of long-term kidney transplant recipients from calcineurin inhibitor therapy to everolimus: a randomized, multicenter, 24-month study. Transplantation
2011; 92: 410.
15. Ekberg H, Tedesco-Silva H, Demirbas A, et al.. Reduced exposure to calcineurin inhibitors in renal transplantation. N Engl J Med
2007; 357: 2562.
16. Gill JS, Tonelli M, Mix CH, et al.. The change in allograft function among long-term kidney transplant recipients. J Am Soc Nephrol
2003; 14: 1636.
17. Gourishankar S, Hunsicker LG, Jhangri GS, et al.. The stability of the glomerular filtration rate
after renal transplantation is improving. J Am Soc Nephrol
2003; 14: 2387.
18. Buron F, Hadj-Aissa A, Dubourg L, et al.. Estimating glomerular filtration rate
in kidney transplant recipients: performance over time of four creatinine-based formulas. Transplantation
2011; 92: 1005.
19. Ekberg H, Bernasconi C, Tedesco-Silva H, et al.. Calcineurin inhibitor minimization in the Symphony study: observational results 3 years after transplantation. Am J Transplant
2009; 9: 1876.
20. Vincenti F, Blancho G, Durrbach A, et al.. Five-year safety and efficacy of belatacept in renal transplantation. J Am Soc Nephrol
2010; 21: 1587.
21. Morrissey PE, Flynn ML, Lin S. Medication noncompliance and its implications in transplant recipients. Drugs
2007; 67: 1463.
22. Terasaki PI. Humoral theory of transplantation. Am J Transplant
2003; 3: 665.
23. Jacobson PA, Schladt D, Israni A, et al.. Genetic and clinical determinants of early, acute calcineurin inhibitor-related nephrotoxicity: results from a kidney transplant consortium. Transplantation
2012; 93: 624.
24. Racusen LC, Solez K, Colvin RB, et al.. The Banff 97 working classification of renal allograft pathology. Kidney Int
1999; 55: 713.
25. Amer H, Fidler ME, Myslak M, et al.. Proteinuria
after kidney transplantation
, relationship to allograft histology and survival. Am J Transplant
2007; 7: 2748.
26. Levey AS GT, Kusek JW, Beck GJ. A simplified equation to predict glomerular filtration rate
from serum creatinine. J Am Soc Nephrol
2000; 11: A0828.
27. Levey AS, Coresh J, Greene T, et al.. Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate
. Ann Intern Med
2006; 145: 247.
Kidney transplantation; Glomerular filtration rate; Graft survival; Chronic allograft nephropathy; Proteinuria
Supplemental Digital Content
© 2012 Lippincott Williams & Wilkins, Inc.