Results of Renal Transplantation





Introduction


The use of outcome data for renal transplantation in the United States (US) represents one of the best available examples of medical care supported by local and national databases to allow evidence-based decisions in the field. According to requirements directed by the United Network for Organ Sharing (UNOS), a federal government-authorized body, all transplant centers must submit transplant data to the Scientific Registry of Transplant Recipients (SRTR), where the data are collated and analyzed on both a center-specific basis and a cumulative national basis. Much of the data from the US summarized in this chapter is derived from the 2015 SRTR report on kidney and pancreas transplant outcomes, available in the American Journal of Transplantation ( http://onlinelibrary.wiley.com.easyaccess1.lib.cuhk.edu.hk/doi/10.1111/ajt.2017.17.issue-S1/issuetoc ). The massive amount of data in the 2015 SRTR report has been reduced to that which is included in this chapter for the purposes of greater usefulness and readability. The source of the data is acknowledged in figures and tables. In addition, other data have been added to supplement the SRTR report, including United States Renal Data System (USRDS) surveillance data, individual center reports and multicenter trial data, data from Europe through the Collaborative Transplant Study (CTS), and the Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry. These data inform decisions regarding patient access and outcomes and organ allocation. The data mentioned here refer to transplantation in the Western world; results from less well-developed countries are discussed in Chapter 38 .




Renal Failure Treatments—Dialysis Versus Transplantation


Renal failure is known to increase mortality from cardiovascular disease and from causes directly resulting from renal failure itself, including fluid and electrolyte imbalance and uremia. Although dialysis addresses the immediately life-threatening complications of renal failure, it does not provide fluid and electrolyte homeostasis comparable to that of a well-functioning kidney. Several additional metabolic functions of the kidney, such as vitamin D synthesis and erythropoietin synthesis, are also not regulated appropriately in the absence of a well-functioning kidney. This reality is reflected by the well-documented finding that patients with end-stage renal disease (ESRD) have improved survival with transplantation compared with dialysis therapy. Patients who receive dialysis have an expected remaining lifetime of 6.8 years, compared with 17.8 years for transplant recipients ( Table 39.1 ). In addition, kidney transplantation is cost effective compared with dialysis and offers improved quality of life. Studies have shown an increasing cardiovascular risk proportional to the increase in serum creatinine, suggesting that renal failure correlates with, if not causes, accelerated vascular and metabolic defects that predispose patients to cardiovascular death. Dialysis patients are known to experience accelerated atherosclerosis, and there are several inflammatory and atherogenic factors may account for this. Given these facts, it is not surprising that analysis of USRDS data revealed that longer time on the wait list for renal transplantation correlates with poorer death-censored graft survival after renal transplantation ( Fig. 39.1 ). Although there is a clear advantage in receiving a kidney transplant before ever starting dialysis, this practice, known as preemptive renal transplantation, is not widely adopted. In 2015, 15.9% of adult US kidney transplant recipients underwent preemptive transplantation, whereas the remaining patients were on dialysis at the time of transplant.



Table 39.1

Expected Remaining Lifetime (Years) by Age, Sex, and Treatment Modality of Period Prevalent Dialysis Patients, Prevalent Transplant Patients, and the General US Population (2015), based on United States Renal Data System Data and the National Vital Statistics Report (2014)

Data Source: Reference Tables H.13; special analyses, USRDS ESRDS Database; and Table 7 in National Vital Statistics Report , Deaths: Final Data for 2014.





















































































































































ESRD patients, 2015 General US population, 2014
Dialysis Transplant
Age Male Female Male Female Male Female
0–14 23.8 23.1 59.3 60.3 70.7 75.4
15–19 21.8 19.1 47.6 48.7 59.7 64.4
20–24 18.8 16.1 43.4 44.5 55.0 59.5
25–29 16.2 14.1 39.4 40.7 50.3 54.6
30–34 14.1 12.6 35.1 36.6 45.7 49.7
35–39 12.6 11.5 31.1 33.0 41.0 45.0
40–44 11.0 10.3 27.2 28.9 36.5 40.3
45–49 9.3 8.8 23.3 25.2 32.0 35.6
50–54 7.9 7.7 19.9 21.8 27.7 31.1
55–59 6.6 6.6 16.7 18.4 23.7 26.8
60–64 5.5 5.7 13.9 15.4 19.9 22.6
65–69 4.6 4.8 11.4 12.7 16.2 18.6
70–74 3.8 4.0 9.4 10.3 12.8 14.8
75–79 3.2 3.5 7.6 a 8.6 a 9.8 11.4
80–84 2.6 2.9 7.1 8.4
85+ 2.1 2.3 3.8 4.4

ESRD, end-stage renal disease.

a Cell values combine ages 75+.




Fig. 39.1


(A) Adjusted hazard ratios of all-cause mortality by time period for dialysis versus kidney transplantation across 38 cohorts. (B) Adjusted hazard ratios of all-cause mortality by time period for dialysis versus kidney transplantation across 38 cohorts.

A, Reprinted from Tonelli M, Wiebe N, Knoll G, Bello A, Browne S, Jadhav D, Klarenbach S, Gill J. Systematic review: kidney transplantation compared with dialysis in clinically relevant outcomes. Am J Transplant 2011;11(10):2093–109. B, Reprinted from Tonelli M, Wiebe N, Knoll G, Bello A, Browne S, Jadhav D, Klarenbach S, Gill J. Systematic review: kidney transplantation compared with dialysis in clinically relevant outcomes. Am J Transplant 2011;11(10):2093–109.




The better outcomes of patients with preemptive transplants and with shorter time on dialysis underscore the importance of early referral and evaluation for renal transplantation. However, patients with kidney disease face a number of barriers in accessing early nephrology care, including organ allocation policies and delayed referral to nephrology care or transplant centers. In the US, these barriers are particularly apparent for African Americans versus whites: African Americans have a lower rate of accessing each step of the kidney transplant process, including referral, evaluation, waitlisting, and transplant receipt. However, the new US kidney allocation system implemented in December of 2014 suggests that racial and ethnic disparities in kidney transplantation among waitlisted patients may have at least temporarily abated. Patients with ESRD benefit from transplantation as early as possible to maximize their potential for long survival after transplantation.




Kidney Donation


In the US the total number of deceased and live kidney transplants decreased 4.4% from 2006 to 2012, but increased 6.8% from 2012 to 2015. Kidney donation rates from deceased donors decreased slightly since 2014, at 72.2 eligible donors per 100 eligible deaths in 2015. The number of kidneys transplanted from living donors decreased 15.7% from 2009 to 2015, resulting in a total of 5386 donors in 2015. In Europe, there is wide variation in deceased donor rates between countries. Deceased donation has generally remained stagnant or even decreased over recent years, with the exception of Spain, Austria, and Belgium, where donor rates are the highest in the world after the introduction of presumed consent (opt-out) policies.


Donation After Cardiac Death


Donation after cardiac death (DCD) can yield either expanded criteria donors (ECD) or standard criteria donors (SCD). DCD has increased substantially since 2000: DCD/SCD represented 10.8%, and DCD/ECD represented 1.1% of all organ donors in the US in 2009. DCD kidneys are kidneys procured after cessation of cardiac activity (in Europe, often referred to as nonheart-beating donors); this also is discussed in Chapter 6, Chapter 9 . Growth in DCD donors for kidney transplantation represents the largest increase in a type of donor kidney available for recipients in the US. The ethics and methods of DCD recovery have been discussed at length by D’Alessandro and colleagues, and single-center experiences have resulted in outcomes not significantly different from SCD kidney transplantation. Several larger retrospective studies have compared short- and long-term outcomes of DCD versus SCD and ECD donors and found equivalent patient and graft survival at 5 years. In a large UNOS registry study that examined more than 75,000 transplant recipients, results suggest that DCD kidneys from donors younger than 50 years old have equivalent graft survival to SCD kidneys. The use of DCD donors, normal practice in the early days of transplantation, was pioneered in the modern era by Kootstra’s team at Maastricht and continued at the University of Wisconsin as the shortage of kidneys grew.


Recipient Pool


At the end of 2015, there were 97,680 patients awaiting renal transplantation in the US. New registrations for kidney transplantation in 2015 numbered 30,232 ( Table 39.2 ). The number of kidney transplants in the US has generally remained stable since 2005, although there was a 1% increase in kidney transplants from 2013 to 2014. The largest demographic increase in this population was in the 50- to 64-year-old age range. Since 2003, the age group with the greatest percentage increase in registration for renal transplantation comprised patients 65 years old and older. For pediatric patients in the US, access to the deceased donor waiting list and transplantation has increased since the introduction of the Organ Procurement and Transplantation Network (OPTN) Share 35 policy in 2005 that preferentially offers organs from deceased donors younger than 35 years of age to children less than 18 years old; however, this policy also resulted in a decline in the use of living donor transplants for this population. Factors contributing to the increase of older patients on the waiting list include the aging general population of the US, the increased incidence of ESRD with aging, and improvements in transplantation outcomes in the elderly. This disproportion between the increase in the waiting list and the number of patients receiving a transplant is similar throughout the Western world. In developing countries, where access to deceased donor transplantation is low, the disparity between need and provision of kidneys is even greater.



Table 39.2

Kidney Transplant Waiting List Activity Among Adult Patients, United States, 2013 to 2015

From OPTN/SRTR data, as of April 2016.







































































2013 2014 2015
Listings at start of year 92,761 96,848 99,120
Listings added during year 31,595 31,275 30,232
Listings removed during year 27,454 28,951 31,672
Listings at end of year 96,902 99,172 97,680
Removal reason
Deceased donor transplant 11,278 11,590 12,280
Living donor transplant 5,100 5,084 5,331
Transplant outside US 44 47 50
Patient died 4,749 4,958 4,981
Patient refused transplant 452 477 527
Condition improved, transplant not needed 194 196 211
Too sick to transplant 2,868 3,342 4,154
Other 2,769 3,257 4,138

Candidates concurrently listed at more than one center are counted once, from the time of earliest listing to the time of latest removal. Candidates who are listed, undergo transplant, and are relisted, are counted more than once. Candidates are not considered to be on the list on the day they are removed; counts on January 1 may differ from counts on December 31 of the prior year. Candidates listed for multiorgan transplants are included. Removal reason as reported to the Organ Procurement and Transplantation Network. Candidates with death dates that precede removal dates are assumed to have died waiting.


The racial representation on the US wait list includes 38% white and 32% African American, with the remaining 30% comprising an increasing percentage of Hispanics, Asians, and others. Gender representation remains unchanged, with males accounting for 60% and females 40% of the waiting list. The proportion of patients undergoing retransplantation in 2015 was 10% of living donor and 15% of deceased donor transplants. The length of time on the waiting list continues to increase, with 30% of active patients at the end of 2009 having waited 3 years or more, compared with 14% at the end of 1995.


Diabetes, hypertension, and glomerular disease are the most common primary diseases among adult waiting list patients, at 36% (diabetes), 23% (hypertension), and 14% (glomerular disease) (see Chapter 3, Chapter 4 ). Diabetes is likely to remain the most common diagnosis of patients awaiting renal transplantation in the US; in most European countries, diabetes is not the major cause of renal failure in patients on the waiting list. The median time from listing to transplantation was considerably different among ethnic minorities and whites. For registrants added to the waiting list in 2010, the median time to transplant for African Americans was 4.9 years, compared with 2.7 years for whites. Reasons for these racial disparities in waiting times in the US have been addressed in several publications and relate to human leukocyte antigen (HLA) typing and antigen representation in the donor population, poverty, social networks, patient preferences, or provider bias. However, major policy changes to the US national kidney allocation system, including the elimination of priority for HLA-B similarity in 2003, pediatric prioritization in Share 35 in 2005, and the 2014 “longevity matching” kidney allocation system that changed waiting time to start at ESRD diagnosis rather than the time a patient was approved for waitlisting, have reduced racial and ethnic disparities in access to kidney transplantation.


ABO blood groups significantly influence median time to transplant, with blood group B registrants waiting the longest, or 4.49 years for registrants listed in 2009. Blood group AB registrants had the shortest waiting time, at 1.70 years. Patients with a previous organ transplant wait nearly twice as long as registrants awaiting their first kidney transplant, owing to sensitization and presence of comorbidities.


Death on the waiting list for children 11 to 17 years old was about half that of children <6 years old in 2004, but because of a substantial decrease in death rates for children <6 years of age, death rates are about equal in these two age groups in 2015 ( Table 39.3 ). As expected, death on the waiting list increases with increasing age, although death rates for patients younger than age 50 have decreased over the past 10 years. As of 2015, death rates for patients 65 years old and older are nearly four times the rate for patients 18 to 34 years old.



Table 39.3

Pretransplant Mortality Rates Among Patients Wait Listed for a Kidney Transplant, By Age Group (Years), United States, 2004 to 2015

From OPTN/SRTR data, as of April 2016.


































































































Age Group (Years)
Year 18–34 35–49 50–64 ≥ 65 All
2004 3.31 5.59 8.65 12.70 7.37
2005 3.18 5.14 8.32 11.16 6.97
2006 3.22 5.13 8.28 11.38 7.05
2007 2.82 4.76 7.55 10.48 6.53
2008 2.77 4.51 7.13 10.23 6.29
2009 2.84 4.47 6.74 9.24 6.02
2010 2.41 3.76 6.53 8.47 5.60
2011 2.71 3.70 6.17 8.51 5.51
2012 2.19 3.56 5.77 7.70 5.13
2013 1.97 3.46 5.36 7.57 4.92
2014 2.08 3.25 5.43 7.66 4.94
2015 2.18 3.39 5.09 7.86 4.92

Mortality rates are computed as the number of deaths per 100 patient-years of waiting in the given year. Individual listings are counted separately. Age is determined at the later of listing date or January 1 of the given year. Rates with less than 10 patient-years of exposure are not shown.


In the US there were a total of 17,879 adult kidney transplant recipients in 2015, of which 69.9% were deceased donor and 30.1% were living donor transplants. Characteristics of transplant recipients are provided in Table 39.4 .



Table 39.4

Characteristics of Adult Kidney Transplant Patients, United States, 2015

From OPTN/SRTR data, as of April 2016.








































































































































































































































































































































































































































































































































Characteristic Deceased Living All
N Percent N Percent N Percent
Age
18–34 years 1694 13.6% 1013 18.8% 2707 15.1%
35–49 years 3702 29.6% 1523 28.3% 5225 29.2%
50–64 years 4849 38.8% 2026 37.6% 6875 38.5%
≥65 years 2248 18.0% 824 15.3% 3072 17.2%
Sex
Female 4977 39.8% 1995 37.0% 6972 39.0%
Male 7516 60.2% 3391 63.0% 10,907 61.0%
Race/ethnicity
White 4724 37.8% 3541 65.7% 8265 46.2%
Black 4426 35.4% 633 11.8% 5059 28.3%
Hispanic 2265 18.1% 806 15.0% 3071 17.2%
Asian 874 7.0% 353 6.6% 1227 6.9%
Other/unknown 204 1.6% 53 1.0% 257 1.4%
Diagnosis
Diabetes 3704 29.6% 1235 22.9% 4939 27.6%
Hypertension 3247 26.0% 883 16.4% 4130 23.1%
GN 2039 16.3% 1281 23.8% 3320 18.6%
CKD 1102 8.8% 932 17.3% 2034 11.4%
Other 2401 19.2% 1055 19.6% 3456 19.3%
Blood type
A 4360 34.9% 2130 39.5% 6490 36.3%
B 1617 12.9% 723 13.4% 2340 13.1%
AB 741 5.9% 218 4.0% 959 5.4%
O 5775 46.2% 2315 43.0% 8090 45.2%
CPRA
<1% 7204 57.7% 3940 73.2% 11,144 62.3%
1 to <20% 985 7.9% 476 8.8% 1461 8.2%
20 to <80% 1789 14.3% 675 12.5% 2464 13.8%
80 to <98% 888 7.1% 196 3.6% 1084 6.1%
98 to 100% 1624 13.0% 78 1.4% 1702 9.5%
unknown 3 0.0% 21 0.4% 24 0.1%
Wait time
<1 year 100 0.8% 164 3.0% 264 1.5%
<3 years 4603 36.8% 3322 61.7% 7925 44.3%
<5 years 4089 32.7% 1480 27.5% 5569 31.1%
≥5 years 2135 17.1% 318 5.9% 2453 13.7%
Unknown 1566 12.5% 102 1.9% 1668 9.3%
Dialysis time
None 1165 9.3% 1669 31.0% 2834 15.9%
<1 year 780 6.2% 1292 24.0% 2072 11.6%
<3 years 2086 16.7% 1280 23.8% 3366 18.8%
<5 years 2131 17.1% 437 8.1% 2568 14.4%
≥5 years 6331 50.7% 708 13.1% 7039 39.4%
Insurance
Private 2552 20.4% 3044 56.5% 5596 31.3%
Medicare 8757 70.1% 1978 36.7% 10,735 60.0%
Medicaid 834 6.7% 226 4.2% 1060 5.9%
Other government 211 1.7% 45 0.8% 256 1.4%
Unknown 139 1.1% 93 1.7% 232 1.3%
HLA mismatches
0 528 4.2% 361 6.7% 889 5.0%
1 197 1.6% 217 4.0% 414 2.3%
2 644 5.2% 705 13.1% 1349 7.5%
3 1829 14.6% 1266 23.5% 3095 17.3%
4 3353 26.8% 930 17.3% 4283 24.0%
5 3856 30.9% 1170 21.7% 5026 28.1%
6 2004 16.0% 679 12.6% 2683 15.0%
Unknown 82 0.7% 58 1.1% 140 0.8%
Transplant history
First 10,671 85.4% 4854 90.1% 15,525 86.8%
Retransplant 1822 14.6% 532 9.9% 2354 13.2%
DCD status a
DBD 10,236 81.9%
DCD 2257 18.1%
KDPI a
≤20% 2848 22.8%
21%–34% 1952 15.6%
35%–85% 6661 53.3%
>85% 969 7.8%
Unknown 63 0.5%
All recipients 12,493 100.0% 5386 100.0% 17,879 100.0%

CKD , cystic kidney disease; DBD , donation after brain death; DCD , donation after circulatory death; GN , glomerulonephritis; KDPI , kidney donor profile index.

Adult kidney transplant recipients, including retransplants.

a For deceased donor transplant only.





Factors Influencing Outcomes of Transplantation


Many factors influence the outcome of renal transplantation, as illustrated by an earlier analysis of consecutive deceased donor kidney transplants in the United Kingdom between 1994 and 1998. Factors such as HLA matching, donor age, cause of death, and cold ischemia time were found to have a significant effect on outcome. This section discusses these factors and others that influence outcome.


Donor Age


Analysis of 5-year outcomes by Gjertson showed that donor age was the most important factor governing the survival rates of living donor and deceased donor renal transplants. Logistic regression analysis of OPTN/UNOS Registry data from 1996 to 2003 was used to calculate the effect of 21 prognostic factors in 85,270 recipients whose grafts survived beyond 1 year and were followed for 5 years. This result underscores the importance of the quality of the donor kidney with respect to long-term function. European data from the CTS shows the same effect of donor age on graft outcome ( Fig. 39.2 ). Donor age was identified as the most important predictor of 3-year graft failure or patient mortality among the UK Transplant Registry.




Fig. 39.2


Effect of donor age on graft outcome. Donor age and graft survival of first deceased donor kidney transplants, 1990 to 2015, in Europe.

Data from Collaborative Transplant Study. http://www.ctstransplant.org .


Recipient Age


Since the first report of an acceptable outcome to renal transplantation in the elderly and the widespread introduction of cyclosporine-based immunosuppressive protocols, all units adopted a much more liberal approach to the selection of elderly recipients for transplantation. The results of renal transplantation in the elderly (arbitrarily defined as >55, >60, or >65 years old in various reports) have continued to confirm the validity of such policies ( Fig. 39.3 ). Patients aged 65 years and older represent nearly half of the ESRD population in the US. Although there is a higher mortality rate among elderly patients in the early years after transplantation, as reflected by a poorer graft survival, rejection is less common than in younger patients and rarely a major problem. Pulmonary embolism and infection are the two major causes of death in this age group. It is unusual for a graft to be lost through irreversible rejection.




Fig. 39.3


Effect of recipient age on graft outcome. Recipient age and graft survival of first deceased donor kidney transplants, 1990 to 2015, in Europe.

Data from Collaborative Transplant Study. http://www.ctstransplant.org .


Bearing in mind the shortage of deceased donor kidneys for renal transplantation, it is important to select elderly patients who are relatively low-risk recipients and to use lower levels of immunosuppression. Nyberg and colleagues pointed out that some of their elderly patients lost muscular strength after transplantation, which they did not regain, emphasizing that rehabilitation after transplantation is not as good as that in the younger patient. The study by Wolfe and associates, referred to earlier, points out that older patients have a survival advantage with a transplant compared with survival on dialysis. This study confirmed the same suggestion from an earlier Canadian study. A more recent analysis from SRTR examined the outcome of renal transplantation in patients on the waiting list who were age 70 years or older, the fastest-growing group in the US. This analysis showed that transplantation offered a significant reduction in mortality compared with dialysis for these elderly patients.


Obesity


Obesity has reached epidemic proportions in the US, reaching a prevalence of over 30% of the adult population in 2007 to 2008. Based on body mass index (BMI) criteria, defining obesity as BMI greater than or equal to 30, 32.2% of men and 35.5% of women are obese. Between 1987 and 2001, renal transplant patients classified as obese increased by 11.6%. Obesity in renal transplantation is a risk factor for wound infections, delayed graft function, acute rejection, increased radiographic monitoring, and need for biopsy, and is associated with worse graft survival ( Fig. 39.4 ). Although analysis of USRDS data by Meier-Kriesche and associates suggested a higher risk of patient death after renal transplantation in the obese, a subsequent study by Gore and colleagues showed that comorbidities, including hypertension, diabetes, and hyperlipidemia, accounted for the increased risk of death in obese patients. Donor obesity does not seem to have an effect on recipient outcomes. Voluntary weight loss and bariatric surgery before renal transplantation may achieve significant long-term weight loss and relief of comorbidities in obese patients anticipating renal transplantation.




Fig. 39.4


Graft and patient survival after renal transplantation stratified by recipient body mass index at the time of transplantation.

Reprinted from Hoogeveen EK, Aalten J, Rothman KJ, Roodnat JI, Mallat MJ, Borm G, Weimar W, Hoitsma AJ, de Fijter JW. Effect of obesity on the outcome of kidney transplantation: a 20-year follow-up. Transplantation 2011;91(8):869–74.


Race/Ethnicity


In the US graft and survival outcomes are best for individuals of Asian background; outcomes are worst for African Americans. The 5-year adjusted graft survival for 2009 deceased donor transplant recipients was nearly 6% lower for African Americans compared with Caucasians, and approximately 5% lower for African American living donor recipients compared with Caucasians. Much effort has been expended on determining why these differences exist. Biologic factors, such as increased immunologic risk and lower absorption of immunosuppressants among recipients or the presence of APOL1 gene variants in African American donors, are hypothesized to play a role. Potentially modifiable factors, such as distrust of the healthcare system, transportation barriers, poorer adherence to medications, and ability to pay for immunosuppressant drugs may also influence access to and quality of posttransplant follow-up care. An analysis of an experience of deceased donor transplantation from the University of Alabama, where more than half of recipients are African American, has shown a continuing improvement in graft survival in the non-African American population and in the African American population with the use of more potent immunosuppressive regimens. In a study of all-cause graft loss among 63,910 black and 145,482 white patients from the SRTR database (1990–2012) who received a first-time living or deceased donor kidney transplant, Purnell et al. found that racial disparities in graft loss have declined over the past 22 years, such that no significant racial differences are observed for 1- and 3-year outcomes and there was a narrowing of disparities for 5-year graft survival outcomes (adjusted black vs. white disparity in graft loss; hazard ratio (HR): 1.37; 95% confidence interval [CI]: 1.17–1.61). Long-term graft survival remains inferior, however, and research suggests the importance of nonimmunologic variables, such as time on dialysis before transplantation, diabetes, and access to medical care, may play a role.


In support of this hypothesis, a study by Pallet and coworkers of black recipients transplanted between 1987 and 2003 in France suggested that there was not a difference between white and black recipients. The authors suggest that the origin of the difference is not so much genetic, immunologic, or pharmacologic as it is related to universal access to immunosuppressive drugs (i.e., compliance, and social and economic factors). A study by Lunsford and associates from the University of South Carolina suggested that, from a study of 333 patients awaiting transplantation, of which 61% were African American, African Americans are less accepting of their renal failure and more likely to deny the need for renal transplantation than their counterparts. Similar to the findings for African Americans, Press and colleagues have reported that Hispanics also have a higher rate of graft failure compared with whites after adjustment for poverty and other covariates, and that poverty, but not race or ethnicity, is related to functional status after renal transplantation.


APOL1


There is emerging evidence that the presence of two apolipoprotein L1 gene ( APOL1 ) risk alleles (G1 an G2) among African American transplant recipients may be associated with poorer posttransplant outcomes, including reduced graft survival. In a study of 1153 deceased donor transplant recipients from African American donors, Freedman et al. found a doubling of the rate of graft failure among those with two APOL1 risk alleles compared with either 1 or 0 APOL1 risk alleles (HR: 2.05; p.03), but no effect on patient survival. It has also been hypothesized that additional genetic or environmental factors, or “second hits,” among those with APOL1 risk alleles may also confer increased risk of poor posttransplant outcomes. In the US, a new National Institutes of Health (NIH)-funded APOL1 Network consortium (APOLLO) was recently developed to design and conduct studies to determine the extent to which APOL1 may be associated with poor outcomes such as acute rejection, graft failure, and return to dialysis.


Hla Mismatch and Prior Sensitization


There continues to be an advantage of receiving a well-matched kidney, meaning fewer donor–recipient HLA mismatches, as illustrated by the CTS registry data ( Fig. 39.5 ) (see Chapter 10 ). In the US 5.0% of kidney transplant recipients in 2015 received a zero-mismatched kidney versus 7.9% in 2009. Transplants into patients with four or more HLA antigen mismatches in 2015 accounted for 73.7% of deceased donor, non-ECD transplants, reflecting decreased emphasis on HLA matching in allocation policy and increased accrued waiting time emphasis.




Fig. 39.5


Human leukocyte antigen (HLA)-A, HLA-B, and HLA-DR mismatches and deceased donor first kidney transplants, 1990 to 2015, in Europe. MM, mismatch.

Data from Collaborative Transplant Study. http://www.ctstransplant.org .


In other words, most recipients in the US of deceased donor kidneys are not well matched, if defined as at least three of six matches or fewer than four mismatches. An analysis of UNOS data in 2004 suggested that the effect of HLA compatibility on graft outcome has diminished in recent years with the advent of more potent immunosuppression. Opelz and Dohler analyzed CTS data in 2 decades, 1985 to 1994 and 1995 to 2004, and in more recent years have found that the influence of HLA on graft survival remains strong.


Between 2009 and 2015, the percentage of deceased donor, non-ECD kidney transplants into recipients with a panel-reactive antibody frequency of 80% or greater at the time of transplant increased from 8.1% to 20.1%. Highly sensitized patients, as measured by a high panel-reactive antibody percentage, are receiving transplants much more frequently, perhaps owing to the better definition of antibodies and the development of immunosuppressive strategies to aid in such cases in the US. Nevertheless, in 2015, 14.7% of wait-listed patients had a panel-reactive antibody greater than 80%. National data for success of these strategies are still lacking. Center data suggest that desensitization strategies may provide greater benefit than waiting for a compatible organ. In Europe, the acceptable mismatch strategy, which is based on the precise definition of antibodies in the recipient, is used more often (see Chapter 10 ).


The available data continue to support the benefit of more HLA matches compared with fewer, although it also can be argued that even a poorly matched kidney transplant is preferable to dialysis when measured by outcome analysis. Primary renal transplants have better outcomes than retransplants overall, which is well illustrated by the CTS registry data ( Fig. 39.6 ). Living donor transplants that are HLA-identical continue to have better outcomes, followed by haploidentical living donor transplants and deceased donor grafts ( Fig. 39.7 ).




Fig. 39.6


Number of deceased donor kidney transplants (TX) and graft survival, 1990 to 2015.

Data from Collaborative Transplant Study. www.ctstransplant.org .



Fig. 39.7


Relationship of donor type and graft survival of first kidney transplant recipients, 1990 to 2015.

Data from Collaborative Transplant Study. http://www.ctstransplant.org .


Cold Ischemia Time


The percentage of kidney transplants completed with cold ischemic times of less than 12 hours has significantly increased in the US (see Chapter 9 ). The shifts in overall percentages of kidneys transplanted with shorter cold ischemia times reflect the value of short preservation times. Most kidneys are now transplanted in less than 31 hours from the time of procurement. Regardless of the choice of preservation solution or cold storage versus machine perfusion, shorter preservation tends to be an advantage in graft function and survival; this is well illustrated by the CTS data ( Fig. 39.8 ). The University of Wisconsin preservation solution is the dominant choice worldwide for kidney preservation and, at least in the CTS European data, is associated with the best graft outcome ( Fig. 39.9 ). For ECD kidneys, longer cold ischemia time is a risk factor for delayed graft function but does not appear to affect graft survival.


Dec 26, 2019 | Posted by in NEPHROLOGY | Comments Off on Results of Renal Transplantation

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