- Email: [email protected]
A critical assessment on kidney allocation systems
Transplantation Reviews xxx (2016) xxx–xxx
Contents lists available at ScienceDirect
Transplantation Reviews journal homepage: www.elsevier.com/locate/trre
A critical assessment on kidney allocation systems Richard N. Formica Jr. ⁎ Yale University School of Medicine, New Haven, CT
a b s t r a c t The kidney allocation system that took effect on December 4, 2014 represents a significant improvement over the prior approach. It seeks to improve outcomes by longevity matching — pairing kidneys expected to function the longest with recipients expected to live the longest. It addresses the biological barriers faced by highly sensitized patients in an evidence based fashion and it begins to introduce the concept of medical need into kidney allocation by crediting time from the starting dialysis to a patient's waiting time. Additionally, it adds a more granular and continuous approach to classifying deceased donor kidneys through the kidney donor profile index and moves away from the dichotomous and flawed, standard criteria/extended criteria approach to allocating kidneys. Despite these changes, access to kidney transplantation across the age spectrum has remained intact and equitable. However even with these numerous positive improvements the system is not without its flaws. The increased sharing and by extension shipping of kidneys have created logistical challenges for organ procurement organizations and transplant centers. Early results seem to indicate that there have been an increase in cold ischemic time, an increase in delayed graft function and an increase in organ discard rate. There is also a reduced offer rate for children and while not a statistically significant decline in the number of transplants, it is a trend that requires close monitoring. Finally, the new kidney allocation system has done nothing to address the glaring deficiencies in the multi-organ allocation practices, all of which include a kidney, in the United States. Therefore despite the improvements made in kidney allocation, there is work yet to be done to ensure that the allocation of life saving and life prolonging organs for transplantation is done in a fashion consistent with ethical principles, based on science and free from local self interest so that this national resource is used for the betterment of the population it is meant to serve. © 2016 Published by Elsevier Inc.
The Kidney Allocation System (KAS) that went into effect of December 4, 2014 represented 10 years of work and compromise [1,2]. Driving the need for a new approach to allocating kidneys was a desire to correct the deficiencies of the prior system. These deficiencies were the result of a system that was developed by successive changes that were in response to changes to the demographics of the waiting list. Some of major issues that needed to be addressed were that waiting time had become the primary driver of allocation, there was no accounting for medical need or urgency and there was no accounting for fact that not all patients can wait the same amount of time. Prior to 12/4/14 the challenges faced by highly sensitized patients were not fully appreciated and all patients with calculated panel reactive antibody (cPRA) received the same 4 additional allocation points. To be fair, before development of the KAS it was not appreciated how
disadvantage highly sensitized patients were and therefore this well meaning approach of allotting 4 additional points for p with calculated panel reactive antibody (cPRA) of 80% or greater resulted in too much advantage given to patients with cPRA 80%–95% while doing very little to help patients with cPRA 98%–100%. Additionally, there were no taking into account the needs of younger patients and no effort made to preferentially allocate kidneys with longer expected duration of function to patients expected to live longer. Therefore surgeons and physicians were confronted with accepting a kidney from an older donor for a younger recipient and vice versa. This longevity mismatching was bad for both patients and society as it represented an inefficient use of a valued societal resource. Finally, over time in response to what was believed to be inadequacies in the system regions and OPOs enacted their own micro-allocation rules, variances and alternative allocation units (ALUs), in an effort to address these deficiencies on a local level. These were enacted via a provision in the National Organ Transplantation Act (NOTA) [3]. This section of NOTA states:
⁎ Department of Medicine/Section of Nephrology, Yale University School of Medicine, Boardman 124, P.O. Box 208029, 330 Cedar Street, New Haven, CT, 06520. Tel.: +1 203 785 2565; fax: +1 203 785 7068. E-mail address: [email protected].
§121.8 (g) Variances. The OPTN may develop, in accordance with §121.4, experimental policies that test methods of improving allocation. All such experimental policies shall be accompanied by a research design and include data collection and analysis plans. Such variances shall
1. Introduction
http://dx.doi.org/10.1016/j.trre.2016.10.002 0955-470X/© 2016 Published by Elsevier Inc.
Please cite this article as: Formica RN, A critical assessment on kidney allocation systems, Transplant Rev (2016), http://dx.doi.org/10.1016/ j.trre.2016.10.002
2
R.N. Formica Jr. / Transplantation Reviews xxx (2016) xxx–xxx
be time limited. Entities or individuals objecting to variances may appeal to the Secretary under the procedures of §121.4. However, what occurred was that variances and (ALUs) were placed into effect with the required research design or method to assess them for success. Moreover, they were not time limited and once into effect remained so and became accepted as the new normal. Over time, developing new policies to kidney allocation became impossible because each change needed to be tested against this intertwined system of variances and ALU and this was logistically impossible from an information technology perspective. This manuscript will review the design and intent of KAS and areas where the system is justifiably criticized. Specific areas of discussion will be the impact of shipping of organs caused by the changes to prioritizing highly sensitized patients and allocating high kidney donor profile index (KDPI) kidneys on a regional level, the impact of awarding waiting time for the start of dialysis on transplant outcomes, the effect on children from larger geographic sharing of kidney and the fact that KAS did nothing to address the total lack of coherence in the allocation of multi-organ transplants. 1.1. Overview [1,2] In the KAS, it is the estimated duration the kidney will function that determines the allocation sequence. Kidneys with the longest expected duration of function will be paired with recipients expected to live the longest. This is done in an effort to avoid extreme longevity mismatches and therefore increase the number of total life years from transplantation experienced by the population in general and to decrease return to the waiting list for repeat transplantation. This concept of longevity matching will apply to those candidates 18 years or older. With the KAS children will still receive priority, both in terms of the quality of the kidneys they receive and by being placed in an allocation sequence above adults. However, it is important to note that he majority of the kidneys will be allocated in a fashion similar to the current method with waiting time being the primary determinant of place in line for an offer. Finally, the prior approach of allocating kidneys from extended criteria donors (ECD) has been modified [4]. The binary distinction between ECD and standard criteria donor (SCD) kidneys has been abandoned in favor of a linear scale. Additionally, the initial offer will be made on a region wide list in an effort to both more rapidly place the kidney with a recipient willing to accept the organ and incentivize donor services areas that currently do not recover these kidneys to do so, since there now may be a potential recipients for them [5]. 1.2. Estimated post transplant survival (EPTS) The first component of longevity matching is the assessment of how long a patient is expected to life after receiving a transplant. This is the Estimated Post Transplant Survival (EPTS) score [6]. The EPTS formula consists of four patient variables: age, time on dialysis, history of prior solid organ transplant, and diabetic status (either type 1 or 2 versus non-diabetic). This score is imperfect and has at best a moderate ability to discriminate between similar patients. It has a C-statistic of 0.69 [7]. However, the intended use of the EPTS score is not for precise rankordering of patients; rather, it is intended to distinguish between two broad categories, those patients whose expected longevity is in the Top 20% (of all adult kidney candidates) and those who are not. A criticism of this approach is that the top 20% is arbitrary [8]. A close review of the survival curves demonstrates that there is very little survival difference between candidates with the longest anticipated survival and those with survivals projected to be in middle of candidates. While this arbitrary cut off can be viewed as unfair, it is important to keep in mind that a cut off was needed to establish a method of allocating kidneys based on improving utilization of this scarce societal resource. Additionally, while it is tempting to level a charge of age
discrimination at this approach the following points should be recognized. First, age is a meaningful variable in predicting survival [9] and second age alone is not used to calculate EPTS. Analysis done prior to implementation demonstrated that 50-year old patients can have an EPTS score less than 20% and that 10.1% of individuals on the waiting list between the age of 46 and 55 have an EPTS score in the top 20% (Table 1). These individuals compose 25.4% of the waiting list and therefore 40% of individuals in this age bracket listed for transplant will be included in longevity matching (Table 2). While the 20% threshold was a reasonable starting point, it needs to be reexamined as data become available and adjusted to meet that overall goal of longevity matching. 1.3. Kidney donor profile index (KDPI) The Standard Criteria Donor (SCD)/Extended Criteria Donor (ECD) dichotomy has long been a problem in kidney transplantation. The binary distinction between and ECD and standard criteria donor (SCD) kidney that was driven by the clinical features of age greater than 60 or age greater than 50 and two or more of the following; death by stroke, history of hypertension, terminal creatinine greater than 1.5 mg/dl, results in significant overlap in the way kidneys performed [4] (Fig. 1). The intention of this approach was to offer kidneys that would not be expected to function as long to older individuals or those with co-morbidities in whom the trade off between sooner transplantation but lesser expected duration of function was felt to be appropriate. However, the significant overlap between ECD and SCD kidneys led to changes in physician behavior and resulted in placing most or all patients on both lists and then selectively choosing which kidney to offer which patient. This was particularly likely to occur in regions with long waiting times. The Kidney Donor Risk Index (KDRI) was developed to correct this because it uses a continuous grading scale for kidneys in lieu of a dichotomous one [10]. The KDRI is composed of 10 variables and is expressed as a “hazard ratio” that reflects the risk of graft failure with a transplanted kidney from a particular donor relative to a reference donor. In the KAS, the donors recovered in the previous year become the reference population. For utilization in KAS the KDRI is converted into the Kidney Donor Profile Index (KDPI) [11]. The KDPI is a linear percentage scale with 0% having the longest anticipated survival and 100% having the shortest anticipated survival. The KDPI, like the EPTS, has only moderate ability to discriminate between similar donor kidneys and this is often levied as criticism. While this is justified it also ignores that the KDPI was only intended to be used to divide the deceased donor kidneys into broad categories for the purposes of allocation and never intended to be used to decide upon the appropriateness of a specific kidney for a specific patient. However, other very legitimate criticisms of this approach to classifying kidneys exist. One concern is that ranking kidneys from “best” to “worse” creates an
Table 1 Vignettes demonstrating how the 4 variables of the EPTS score, age, year on renal replacement therapy, diabetes and prior organ transplants can combine and give a recipient an EPTS score in the top 20%. Age
Years on RRT
DM
Prior Txp
EPTS
18 25 18 25 25 40 18 25 40 50
0 0 2 5 2 0 0 0 5 0
No No No No No No Yes Yes No No
No No No No Yes No No No No No
1% 1% 2% 5% 7% 8% 12% 12% 17% 18%
RRT, renal replacement therapy; DM, diabetes mellitus, either type 1 or type 2; Txp, prior transplanted solid organ of any type, kidney, pancreas, liver, heart, lung or intestine; EPTS, estimated post transplant survival. Source: OPTN/UNOS, provided for OPTN Kidney Transplantation Committee, 2012.
Please cite this article as: Formica RN, A critical assessment on kidney allocation systems, Transplant Rev (2016), http://dx.doi.org/10.1016/ j.trre.2016.10.002
R.N. Formica Jr. / Transplantation Reviews xxx (2016) xxx–xxx Table 2 The number of adults on the kidney transplant waitlist by decade of age, the percentage of the entire waitlist they represent and the percentage of them scoring in the top 20% EPTS. Age
N on WL (adults)
% on WL
% in EPTS Top 20
18–25 26–35 36–45 46–55 56–65 66–75 76+ All
2742 8256 16,136 25,094 29,469 14,762 1516 98,848
2.8 8.4 16.3 25.4 29.8 14.9 1.5 100.0
96.7% 80.6% 43.8% 10.1% 0.0% 0.0% 0.0% 20.0%
WL, waitlist. Source: OPTN/UNOS, provided for OPTN Kidney Transplantation Committee, 2012.
environment where a surgeon of physician has to give a kidney from the “worst” category to patient, where in the SCD/ECD system the ECD kidneys were lumped together. This new approach could lead to organ discards based upon the KDPI score alone. While the issue of discards remains a moving target at present, and analysis done prior to the implementation of KAS suggested that the rate of discard was not affected by the utilization of the KDPI score [12]. A more clinically relevant criticism is the institution of the KDPI score has eliminated the ability of a surgeon or physician to match a donor kidney to a recipient based upon the unique characteristic of the pair. While the SCD/ECD distinction was flawed from an allocation perspective as mentioned above, it did allow a more patient focused approach to kidney allocation. Finally, while the KDPI does incorporate 10 clinical variables of the donor it does not include the histologic evaluation of the kidney made on a preimplantation biopsy and review of the “pump parameters” for kidneys preserved with machine perfusion. Whereas there is meaningful debate about whether or not these two approaches are helpful or harmful in kidney allocation, the reality is they are used by clinicians and unaccounted for in the allocation process. 1.4. Longevity matching EPTS and KDPI are used together in KAS to pair kidneys expected to last the longest, top 20% KDPI, with patients expected to live the longest, top 20% EPTS. The concept is called longevity matching. A primary objective of longevity matching is to decrease the allocation of kidneys from younger donors to older individuals who will potentially die with the graft still functioning. While this may benefit the individual, it is not a good use for a scarce societal resource. Because the demand for transplantable kidneys vastly outstrips supply, some degree of longevity matching is a societal imperative and cannot be ignored. Additionally, because longevity matching allocates kidneys with the
3
longest expected duration of function to the candidates that are expected to need them the longest, it is possible to reduce the need for retransplantation. Because patients awaiting a subsequent kidney transplant compose between 10 and 15% of individuals on the waiting list [13], longevity matching has the potential to improve the chances for transplantation in older individuals because it will lessen future demand by reducing the need for re-transplants. This aspect of KAS generated the most debate. Based upon the early results, this approach has decreased the number of mismatched transplants [14]. However, while on balance the principle is sound there are some very just criticisms. The first is a patient centered argument that while death with a functioning graft may not be in society's best interest, it is in the best interest of the patient. In this scenario, the patient lives out their life free of end stage renal disease and the need for dialysis. Currently in American culture the needs of the one are not subjugated but the needs of the many and this approach is contrary to the ethos. Additionally, because organ allocation by its nature has a lottery aspect to it an older individual does not demand an organ from a younger donor but may receive one by chance. This is not different for the rest of the allocation system and to preclude certain individuals from it can be seen as unfair. Another issue with longevity matching is that the supply of lower KDPI donors in any give DSA is greatly exceeded by the demand (Fig. 2). This is further exacerbated by the fact that multi-organ transplants have priority over isolated kidney transplants and the kidneys associated with multi-organ transplants by and large come from donors with KDPI less than .35 [15]. Therefore while the policy intent is to allocate organs with greater duration of function to younger patients the reality is that this only occurs in 50% of the transplants in these individuals. Therefore the policy is only somewhat effective and my not fully achieve the intent of reducing return to the waiting list for repeat transplant. 1.5. High KDPI kidney allocation It is recognized that the overlap in expected survival between SCD and ECD kidneys undermines the efficacy of this allocation system. The new approach to allocating kidneys with a diminished expected duration of function, those kidneys with KDPI N85%, was designed to correct the shortcomings of the SCD/ECD approach. Additionally, a design hypothesis of this approach is that it may promote increased organ recovery by providing OPOs whose centers do not traditionally use these kidneys with timely access to centers that want them for transplantation. The KPDI method of classifying deceased donor kidney does not result in an overlap in kidney quality and therefore there is no reason to list a recipient to accept a kidney with KDPI 86% or greater unless they will benefit from a more rapid time to transplant.
Fig. 1. The percentage of donor kidneys stratified by Kidney Donor Risk Index that would be classified as extended criteria donor kidneys or not extended donor criteria kidneys.
Please cite this article as: Formica RN, A critical assessment on kidney allocation systems, Transplant Rev (2016), http://dx.doi.org/10.1016/ j.trre.2016.10.002
4
R.N. Formica Jr. / Transplantation Reviews xxx (2016) xxx–xxx
Fig. 2. EPTS top 20% candidates vs. KDPI top 20% kidney transplants, by donor service area.
Additionally, the fact that kidneys with KDPI 86% and greater will be allocated on a regional list may incentivize increased organ recovery. Currently there are OPOs in which the utilization of what was classified as ECD kidneys is very low and these OPOs are adjacent to those with very high usage of these kidneys [5]. Because in practice an OPO’s incentive for organ recovery is only based upon the probability of an organ being placed, and not influenced by the fact it may be utilized by a transplant center within its distribution area, the creation of a market for these kidney in an adjacent area may promote more recovery. Additionally, the recovery and placement of organs outside the OPO, may cause a change in the behavior of the programs within the OPO toward increased utilization of these higher KDPI organs. At the time of this writing, this remains an experimental hypothesis. Additionally, sharing organs on a regional list increases the logistical challenges of both shipping sample to transplant centers for cross matching and shipping of organs. In high KDPI kidneys, those more susceptible to ischemic damage, the increased shipping time may lead to more organ discards.
1.6. Waiting time calculation In kidney transplantation, as opposed to other solid organ transplantation, there is no accounting for the severity of illness in organ allocation. This is due to the success of maintenance dialysis therapy in forestalling death from end stage renal disease. The allocation system prior to 12/4/2014 did not account for the severity of illness as a patient accumulated waiting time no earlier than the time of listing. Months or years of dialysis prior to the patient being added to the waiting list did not matter even though it is recognized that the duration of dialysis exposure prior to transplantation results in worse post transplant outcomes [16]. Moreover, individuals who had more dialysis exposure prior to listing tend to be from racially and socio-economically disadvantaged groups (Fig. 3). Therefore the KAS now will credit waiting time from the date of listing with a qualifying estimated glomerular filtration rate (less than or equal to 20 ml/min) or from the confirmed date of dialysis initiation, even if dialysis began years prior to listing.
Fig. 3. Cumulative distribution of pre-registration dialysis years by ethnicity, for adult kidney additions with pre-registration dialysis, 1/1/07–12/31/12.
Please cite this article as: Formica RN, A critical assessment on kidney allocation systems, Transplant Rev (2016), http://dx.doi.org/10.1016/ j.trre.2016.10.002
R.N. Formica Jr. / Transplantation Reviews xxx (2016) xxx–xxx
This change to KAS is an important step to mitigating the disparity in access to transplantation that is known to occur due to delay or no referral to transplantation from dialysis units. However the very issue this policy is designed to address, prolonged dialysis exposure prior to transplantation is also documented to result in poorer transplant outcomes [16]. This fact places this policy at cross purposes with one of the primary goals of KAS which was to increase life years from transplant. By giving credit for time on dialysis prior listing, the KAS is prioritizing those individuals with worse expected outcomes after transplantation. When the policy went into effect it was anticipated that there would be a bolus phenomenon of patients with accumulated dialysis time being transplanted. This has occurred. However where the steady state occurs is yet to be determined. 1.7. Highly sensitized patients In the allocation system prior to 12/4/2014 all patients with a cPRA of 80% or greater were given four additional allocation points. This was approximately equivalent 4 years of waiting time. The intent was to move these patients up the waiting list so that they would receive more offers. However its reasoning was flawed in three areas. The first was that it assumed everyone with cPRA greater than 80% was equally disadvantaged. During design of KAS an analysis was done to determine the time to next offer — how long a patient would be expected to wait for a second offer if the first offer was declined. It revealed the stark reality for these highly sensitized patients. The median time for a patient with cPRA 0% was 11.7 days. Not surprisingly, as the degree of sensitization increased, the median time to next offer increased however it increased in an exponential and not linear fashion. At a cPRA of 60%– 69% the median time more than doubles to 31.2 days and nearly doubles again to 55.2 when cPRA reaches 75%–79%. Once a patient is in the range that would be considered highly sensitized the increases in median time to next offer become even more dramatic. An increase in cPRA from 95% to 97% causes median time to climb from 175 to 330 days and an increase of to 99% triples the time to 993 days. Finally for a patient with cPRA of 100% the median time-to-next offer increases to 4969 days. This is more than 13 years [17]. The second flaw in the four points for patients with cPRA over 80% approach was that it ignored the importance of donor pool size to increase the chances of finding a matching kidney. Although sensitized patients were given additional points they were still restricted to organs from their own donor service area or alternative allocation unit that was in effect for their area. Modeling donor during the development of KAS demonstrated that patients with cPRA 100% needed access to the national pool of kidneys to have the transplantation rates approach their representation on the waiting list. Those patients with cPRA 99% needed regional sharing and those with cPRA of 98% needed prioritization within their own DSA [8]. The third flaw was that it gave to much advantage to patients with lesser degrees of sensitization. For patients in the cPRA 80%–95% range the additional 4 allocation points resulted in rates of transplantation that were in excess of their representation on the waiting list and therefore gave them an unfair advantage. Additionally, because there was a break point, there was no incentive for transplant centers to enter unacceptable antigens into the listing for their patients whose cPRA was less than 80%. This hypothesis is supported by the observation pre KAS that a very large number of patients were listed with cPRA of 0%, very few with cPRA 1%–79% and then a bolus of listing at 80%. The problem with this practice was that while a single or a few unacceptable antigens may not place an individual patient into the extra allocation points category, they could still result in unexpected positive cross matches and this results in a less efficient allocation system. In the new KAS, recipients are assigned a score on a sliding scale to more accurately reflect the biological reality of their degree of sensitization (Table 3). This had two unintended consequences. First it resulted in inappropriately high rates of transplantation for individuals in the CPRA 80% to
5
Table 3 Additional allocation points assigned per increasing CPRA. One allocation point is equivalent to one year of waiting time. If the candidate's CPRA score is… Then the candidate receives this many points… x=0 0 b x b 10 10 ≤ x b 20 20 ≤ x b 30 30 ≤ x b 40 40 ≤ x b 50 50 ≤ x b 60 60 ≤ x b 70 70 ≤ x b 75 75 ≤ x b 80 80 ≤ x b 85 85 ≤ x b 90 90 ≤ x b 95 95 ≤ x b 96 96 ≤ x b 97 97 ≤ x b 98 98 ≤ x b 99 99 ≤ x b 100 100
0.00 0.00 0.00 0.08 0.21 0.34 0.48 0.81 1.09 1.58 2.46 4.05 6.71 10.82 12.17 17.30 24.40 50.09 202.10
Source: OPTN Policy 8: Allocation of Kidneys. http://optn.transplant.hrsa.gov/governance/ policies/.
95% ranges and did nothing to help those individuals who are truly disadvantaged, those with cPRA greater than 98%. In an analysis of kidney offer for candidates by cPRA, candidates with cPRA 100% received a vanishingly small number of offers relative to other groups (Fig. 4). These patients were projected to have an average wait for a compatible kidney offer of approximately 13 years. The use of the 80% cPRA threshold also resulted in transplant programs not entering unacceptable antigens into uNET for recipients who they assumed would not achieve a score of cPRA 80%, contributing to unexpected positive cross matches [8]. Certainly the new approach that the KAS takes to highly sensitized patients is a significant advance however there are still many valid criticisms and room for improvement. First, patients with cPRA of 100% have access to kidney throughout the country; however those with lower cPRA are still constrained to geographic areas that are not designed to have equity in mind and therefore geographic disparities still exist for these patients. Moreover, while sharing of kidneys over larger geographic areas improves access for highly sensitized patients, it also requires the more frequent shipping of organs over greater distances. This increased shipping of organs may result in increased cold ischemic time and higher rates of delayed graft function and organ discards. In fact, the initial 6-month data do indicate that cold ischemic time has increased slightly and delayed graft function has increased from 24.5% to 31%. Additionally the discard rate, especially for kidneys in the higher KDPI range (0.86–100), has increased [14] Whether or not this is due to shipping of organs alone is not certain because KAS seems to have resulted in an increased rate of organ recovery and has occurred coincident with new therapies for treating hepatitis C which may reduce the demand for these organs. Additionally, in recent months the discard rate has returned to its pre-KAS baseline [18]. Therefore the increase in discards may be an anomaly and further tracking of this issue is required. Certainly the shipping of organs for highly sensitized candidates has imposed new logistical challenges to the allocation of kidneys that are still being resolved; when to send samples for cross matching, how many centers to send them to and how to allocate to another candidate if the intended candidate has positive cross match. While these challenges should not be diminished, they also offer the opportunity to test and evaluate how best to share kidneys over a larger geographic area in preparation for the next iteration of kidney allocation that will seek to reduce the glaring geographic disparities that currently exist in access to kidney transplantation [19,20]. Another concern is that highly sensitized patients will be used to draw in kidneys that will be cross matched positive with the intended
Please cite this article as: Formica RN, A critical assessment on kidney allocation systems, Transplant Rev (2016), http://dx.doi.org/10.1016/ j.trre.2016.10.002
6
R.N. Formica Jr. / Transplantation Reviews xxx (2016) xxx–xxx
Fig. 4. Offer rates by CPRA for adult, kidney-alone candidates alone in 2010.
candidate and then transplant them into another patient. Because in the KAS more kidneys are being shipped the total number of kidneys being placed in the unintended candidate has increased. However the overall percentage of kidneys shipped for highly sensitized patient going into the unintended recipient has decreased suggesting that the system is functioning more efficiently. (Unpublished data, UNOS/OPTN Kidney Transplantation Committee). Moreover, HLA DQ alpha and DP beta typing will soon be required to be entered into the required HLA types that must be entered into a candidate's record. Because a large number of unintended cross matches are due to these class II HLA molecules this improvement should further decrease the number of unexpected positive cross matches that occur after allocation and improve system efficacy [21–23]. Finally, by prioritizing highly sensitized patients, it is possible that the outcome of these transplanted kidneys will be worse than if transplanted into individuals with lower immunologic risk. However, because the expected half-life of a deceased donor kidney is between 5 and 11 years the final answer to this question will be some years in the future [24]. 1.8. A2, A2B donor kidneys allocated to B blood group recipients The national median waiting time for patients with blood type B is the longest in the country. Moreover, because recipients of blood type B tend to be of minority populations and because blood type B is rare, these groups are at a disadvantage [25]. In 2001, the OPTN Board of Directors approved a variance to enable the transplantation of blood type A2 (technically, “non-A1”) and A2B (technically, “non-A1B”) deceased donor kidneys into blood type B candidates. The goal of this variance was to increase the rate of transplantation in blood type B candidates by allocating these kidneys to them without negatively impacting post-transplant outcomes. Since implementation and prior to adoption into the KAS, nine OPOs participated in this variance. The available literature supports the fact that A2 and A2B kidneys transplanted into blood type B recipients have comparable survival rates and that this practice has shortened waiting times for this blood type [26,27]. However, since implementation of the KAS the number of these transplants performed has been insignificant [14]. Therefore the improvement in access to transplantation experienced by African American since the KAS started is more likely due to the adjustment in waiting time to include pre-registration dialysis time and not from the allocation of A2 and A2B donor kidneys in B blood group recipients [14]. Moreover, the implementation of a protocol to perform these transplants is logistically challenging from the transplant center perspective and the increased
resources required and increased risk incurred may outweigh the benefit of increased transplants.
1.9. Unintended consequences of KAS The increased priority and sharing of organs for highly sensitized patients have resulted in organs with KPDI less than .35, which would have been prioritized for children within the local donor service area, being offered first to adults. While there has not been a statistically significant drop in the number of pediatric transplants performed nationally, there has been a slight decrease in offer rates to children [14]. Additionally there have been many anecdotes about prolonged intervals between offers for children from various centers. Whether this reflects changes in acceptance patterns or a true lack of acceptable organs is not yet clear. What is clear is that with the change from allocating organs from donors age 35 years or less to donors with KDPI .35 or less, the quality of kidneys being offered to children has improved. Regardless the intention of the KAS was to improve outcomes in younger patients and if there has been a true decrease in access for children this must be remedied. With the initiation of the KAS local variances and alternative allocation units in organ allocation were retired. This was necessary both to make the KAS possible from a computer program perspective as well as to establish a new baseline by which future variance can be properly assessed. Nevertheless, while in aggregate the myriad local variances were detrimental to the system at large, some unquestionably addressed unique local challenges. Over time variances that conform to the standards put forth in the final rule will help to modify and improve the KAS. Finally and most significantly the KAS does nothing to address the fact that the multi-organ allocation system is broken and in need of a comprehensive review and in need of a complete overhaul. Currently, with the exception of simultaneous pancreas kidney allocation, all multi-organ transplantations are done without medical eligibility criteria or prioritization based on need. This is in direct violation of the final rule. Kidneys allocated in multi-organ transplants come from donors of low KPDI and therefore these kidneys are diverted from children and young adults and these diversions occur without consideration for the relative need of the recipients. It is worthwhile to note that the first full year of the KAS saw the greatest annual number of simultaneous liver kidney transplants performed (Unpublished data, UNOS/ OPTN Kidney Transplantation Committee).
Please cite this article as: Formica RN, A critical assessment on kidney allocation systems, Transplant Rev (2016), http://dx.doi.org/10.1016/ j.trre.2016.10.002
R.N. Formica Jr. / Transplantation Reviews xxx (2016) xxx–xxx
2. Conclusion The KAS is a significant improvement over the prior system used to allocate kidneys. It begins to move the distribution of kidney from one primarily based upon waiting time to one that takes into account patient need through longevity matching, waiting time based upon dialysis exposure and an evidence based approach to the highly sensitized patient. Moreover, it has been designed in a way to allow modification and improvement as data become available. However, like all major policies initiatives it is not perfect and it was not possible to anticipate and account for second and third tier consequences that resulted from the new policy or how policy affected and changed physician behavior. Therefore ongoing monitoring and critical assessment of the outcomes are necessary to direct necessary modifications. Conflict of interest Dr. Formica has not financial or fiduciary conflicts of interest with regards to this manuscript. References [1] Israni AK, Salkowski N, Gustafson S, et al. New national allocation policy for deceased donor kidneys in the United States and possible effect on patient outcomes. J Am Soc Nephrol 2014;25:1842–8. [2] Friedewald JJ, Samana CJ, Kasiske BL, et al. The kidney allocation system. Surg Clin North Am 2013;93:1395–406. [3] [updated December 23, 2015; cited 2015 December 26]. Available from. http:// www.ecfr.gov/cgi-bin/text-idx?SID=bb60e0a7222f4086a88c31211cac77d1&mc= true&node=pt42.1.121&rgn=div5View. [4] Keitel E, Michelon T, dos Santos AF, et al. Renal transplants using expanded cadaver donor criteria. Ann Transplant 2004;9:23–4. [5] 2012. http://srtr.transplant.hrsa.gov/annual_reports/2012/pdf/07_dod_13.pdf [cited 2016 January 2]. [6] Organ Procurement and Transplantation Network (OPTN). Estimated post transplant survival calculator. Available from. http://optn.transplant.hrsa.gov/converge/ resources/allocationcalculators.asp?index=82. [7] Harrell Jr FE, Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 1996;15:361–87. [8] Proposal to substantially revise the National Kidney Allocation System. 2014. [9] Ljungquist B, Berg S, Steen B. Determinants of survival: an analysis of the effects of age at observation and length of the predictive period. Aging (Milano) 1996;8:22–31.
7
[10] Organ Procurement and Transplantation Network (OPTN). Kidney donor profile index calculator. Available from. http://optn.transplant.hrsa.gov/resources/ allocationcalculators.asp?index=81. [11] Rao PS, Schaubel DE, Guidinger MK, et al. A comprehensive risk quantification score for deceased donor kidneys: the kidney donor risk index. Transplantation 2009;88: 231–6. [12] Stewart D, Samana CJ, Formica RN, Friedewald J. Has displaying KDPI in DonorNet led to a spike in discard rates for lower quality kidney? Available from:; 2013. http://www.atcmeetingabstracts.com/abstract/has-displaying-kdpi-in-donornetled-to-a-spike-in-discard-rates-for-lower-quality-kidneys/. [13] OPTN/SRTR annual data report: kidney. Available from. http://srtr.transplant.hrsa. gov/annual_reports/2012/pdf/01_kidney_13.pdf. [14] Stewart DE, Beck J, Kucheryavaya AY. Six-month evaluation of the new, national Kidney Allocation System (KAS); 2015. [15] Formica RN, Aeder M, Boyle G, et al. Simultaneous liver-kidney allocation policy: a proposal to optimize appropriate utilization of a scarce resources. Am J Transplant 2016;16:758–66. [16] Meier-Kriesche HU, Kaplan B. Waiting time on dialysis as the strongest modifiable risk factor for renal transplant outcomes: a paired donor kidney analysis. Transplantation 2002;74:1377–81. [17] 3Stewart DE. OPTN/UNOS kidney transplantation committee: time-to-offer analysis for adult kidney candidates. Estimating the average time between deceased donor kidney offers for adults on the waitlist, by level of allosensitization (CPRA); 2011. [18] Early data suggests kidney allocation system is meeting key expectations. [cited 2015 December 20]. Available from. https://www.unos.org/early-data-suggest-kidney-allocation-system-meeting-key-expectations-2/. [19] Cherikh WS, Stewart DE, Kucheryavaya AY, Baker T, Cheng Y. Kidney offer rates, transplant rates, supply/demand ratios, and median waiting times by DSA; 2014. [20] Davis AE, Mehrotra S, McElroy LM, et al. The extent and predictors of waiting time geographic disparity in kidney transplantation in the United States. Transplantation 2014;97:1049–57. [21] Morris GP, Phelan DL, Jendrisak MD, Mohanakumar T. Virtual crossmatch by identification of donor-specific anti-human leukocyte antigen antibodies by solid-phase immunoassay: a 30-month analysis in living donor kidney transplantation. Hum Immunol 2010;71:268–73. [22] Cecka JM, Kucheryavaya AY, Reinsmoen NL, Leffell MS. Calculated PRA: initial results show benefits for sensitized patients and a reduction in positive crossmatches. Am J Transplant 2011;11:719–24. [23] Gebel HM, Bray RA. The evolution and clinical impact of human leukocyte antigen technology. Curr Opin Nephrol Hypertens 2010;19:598–602. [24] Stewart DE, Kucheryavaya AY. Estimated graft half live for kidney transplants with KDPI 0–20%, 21–34%, 35–85% and 86–110% vs. living donor transplants; 2015. [25] Young CJ, Gaston RS. Renal transplantation in black Americans. N Engl J Med 2000; 343:1545–52. [26] Bryan CF, Winklhofer FT, Murillo D, et al. Improving access to kidney transplantation without decreasing graft survival: long-term outcomes of blood group A2/A2B deceased donor kidneys in B recipients. Transplantation 2005;80:75–80. [27] Bryan CF, Nelson PW, Shield III CF, et al. Transplantation of A2 and A2B kidneys from deceased donors into B waiting list candidates increases their transplantation rate. Clin Transpl 2004:127–33.
Please cite this article as: Formica RN, A critical assessment on kidney allocation systems, Transplant Rev (2016), http://dx.doi.org/10.1016/ j.trre.2016.10.002
Contents lists available at ScienceDirect
Transplantation Reviews journal homepage: www.elsevier.com/locate/trre
A critical assessment on kidney allocation systems Richard N. Formica Jr. ⁎ Yale University School of Medicine, New Haven, CT
a b s t r a c t The kidney allocation system that took effect on December 4, 2014 represents a significant improvement over the prior approach. It seeks to improve outcomes by longevity matching — pairing kidneys expected to function the longest with recipients expected to live the longest. It addresses the biological barriers faced by highly sensitized patients in an evidence based fashion and it begins to introduce the concept of medical need into kidney allocation by crediting time from the starting dialysis to a patient's waiting time. Additionally, it adds a more granular and continuous approach to classifying deceased donor kidneys through the kidney donor profile index and moves away from the dichotomous and flawed, standard criteria/extended criteria approach to allocating kidneys. Despite these changes, access to kidney transplantation across the age spectrum has remained intact and equitable. However even with these numerous positive improvements the system is not without its flaws. The increased sharing and by extension shipping of kidneys have created logistical challenges for organ procurement organizations and transplant centers. Early results seem to indicate that there have been an increase in cold ischemic time, an increase in delayed graft function and an increase in organ discard rate. There is also a reduced offer rate for children and while not a statistically significant decline in the number of transplants, it is a trend that requires close monitoring. Finally, the new kidney allocation system has done nothing to address the glaring deficiencies in the multi-organ allocation practices, all of which include a kidney, in the United States. Therefore despite the improvements made in kidney allocation, there is work yet to be done to ensure that the allocation of life saving and life prolonging organs for transplantation is done in a fashion consistent with ethical principles, based on science and free from local self interest so that this national resource is used for the betterment of the population it is meant to serve. © 2016 Published by Elsevier Inc.
The Kidney Allocation System (KAS) that went into effect of December 4, 2014 represented 10 years of work and compromise [1,2]. Driving the need for a new approach to allocating kidneys was a desire to correct the deficiencies of the prior system. These deficiencies were the result of a system that was developed by successive changes that were in response to changes to the demographics of the waiting list. Some of major issues that needed to be addressed were that waiting time had become the primary driver of allocation, there was no accounting for medical need or urgency and there was no accounting for fact that not all patients can wait the same amount of time. Prior to 12/4/14 the challenges faced by highly sensitized patients were not fully appreciated and all patients with calculated panel reactive antibody (cPRA) received the same 4 additional allocation points. To be fair, before development of the KAS it was not appreciated how
disadvantage highly sensitized patients were and therefore this well meaning approach of allotting 4 additional points for p with calculated panel reactive antibody (cPRA) of 80% or greater resulted in too much advantage given to patients with cPRA 80%–95% while doing very little to help patients with cPRA 98%–100%. Additionally, there were no taking into account the needs of younger patients and no effort made to preferentially allocate kidneys with longer expected duration of function to patients expected to live longer. Therefore surgeons and physicians were confronted with accepting a kidney from an older donor for a younger recipient and vice versa. This longevity mismatching was bad for both patients and society as it represented an inefficient use of a valued societal resource. Finally, over time in response to what was believed to be inadequacies in the system regions and OPOs enacted their own micro-allocation rules, variances and alternative allocation units (ALUs), in an effort to address these deficiencies on a local level. These were enacted via a provision in the National Organ Transplantation Act (NOTA) [3]. This section of NOTA states:
⁎ Department of Medicine/Section of Nephrology, Yale University School of Medicine, Boardman 124, P.O. Box 208029, 330 Cedar Street, New Haven, CT, 06520. Tel.: +1 203 785 2565; fax: +1 203 785 7068. E-mail address: [email protected].
§121.8 (g) Variances. The OPTN may develop, in accordance with §121.4, experimental policies that test methods of improving allocation. All such experimental policies shall be accompanied by a research design and include data collection and analysis plans. Such variances shall
1. Introduction
http://dx.doi.org/10.1016/j.trre.2016.10.002 0955-470X/© 2016 Published by Elsevier Inc.
Please cite this article as: Formica RN, A critical assessment on kidney allocation systems, Transplant Rev (2016), http://dx.doi.org/10.1016/ j.trre.2016.10.002
2
R.N. Formica Jr. / Transplantation Reviews xxx (2016) xxx–xxx
be time limited. Entities or individuals objecting to variances may appeal to the Secretary under the procedures of §121.4. However, what occurred was that variances and (ALUs) were placed into effect with the required research design or method to assess them for success. Moreover, they were not time limited and once into effect remained so and became accepted as the new normal. Over time, developing new policies to kidney allocation became impossible because each change needed to be tested against this intertwined system of variances and ALU and this was logistically impossible from an information technology perspective. This manuscript will review the design and intent of KAS and areas where the system is justifiably criticized. Specific areas of discussion will be the impact of shipping of organs caused by the changes to prioritizing highly sensitized patients and allocating high kidney donor profile index (KDPI) kidneys on a regional level, the impact of awarding waiting time for the start of dialysis on transplant outcomes, the effect on children from larger geographic sharing of kidney and the fact that KAS did nothing to address the total lack of coherence in the allocation of multi-organ transplants. 1.1. Overview [1,2] In the KAS, it is the estimated duration the kidney will function that determines the allocation sequence. Kidneys with the longest expected duration of function will be paired with recipients expected to live the longest. This is done in an effort to avoid extreme longevity mismatches and therefore increase the number of total life years from transplantation experienced by the population in general and to decrease return to the waiting list for repeat transplantation. This concept of longevity matching will apply to those candidates 18 years or older. With the KAS children will still receive priority, both in terms of the quality of the kidneys they receive and by being placed in an allocation sequence above adults. However, it is important to note that he majority of the kidneys will be allocated in a fashion similar to the current method with waiting time being the primary determinant of place in line for an offer. Finally, the prior approach of allocating kidneys from extended criteria donors (ECD) has been modified [4]. The binary distinction between ECD and standard criteria donor (SCD) kidneys has been abandoned in favor of a linear scale. Additionally, the initial offer will be made on a region wide list in an effort to both more rapidly place the kidney with a recipient willing to accept the organ and incentivize donor services areas that currently do not recover these kidneys to do so, since there now may be a potential recipients for them [5]. 1.2. Estimated post transplant survival (EPTS) The first component of longevity matching is the assessment of how long a patient is expected to life after receiving a transplant. This is the Estimated Post Transplant Survival (EPTS) score [6]. The EPTS formula consists of four patient variables: age, time on dialysis, history of prior solid organ transplant, and diabetic status (either type 1 or 2 versus non-diabetic). This score is imperfect and has at best a moderate ability to discriminate between similar patients. It has a C-statistic of 0.69 [7]. However, the intended use of the EPTS score is not for precise rankordering of patients; rather, it is intended to distinguish between two broad categories, those patients whose expected longevity is in the Top 20% (of all adult kidney candidates) and those who are not. A criticism of this approach is that the top 20% is arbitrary [8]. A close review of the survival curves demonstrates that there is very little survival difference between candidates with the longest anticipated survival and those with survivals projected to be in middle of candidates. While this arbitrary cut off can be viewed as unfair, it is important to keep in mind that a cut off was needed to establish a method of allocating kidneys based on improving utilization of this scarce societal resource. Additionally, while it is tempting to level a charge of age
discrimination at this approach the following points should be recognized. First, age is a meaningful variable in predicting survival [9] and second age alone is not used to calculate EPTS. Analysis done prior to implementation demonstrated that 50-year old patients can have an EPTS score less than 20% and that 10.1% of individuals on the waiting list between the age of 46 and 55 have an EPTS score in the top 20% (Table 1). These individuals compose 25.4% of the waiting list and therefore 40% of individuals in this age bracket listed for transplant will be included in longevity matching (Table 2). While the 20% threshold was a reasonable starting point, it needs to be reexamined as data become available and adjusted to meet that overall goal of longevity matching. 1.3. Kidney donor profile index (KDPI) The Standard Criteria Donor (SCD)/Extended Criteria Donor (ECD) dichotomy has long been a problem in kidney transplantation. The binary distinction between and ECD and standard criteria donor (SCD) kidney that was driven by the clinical features of age greater than 60 or age greater than 50 and two or more of the following; death by stroke, history of hypertension, terminal creatinine greater than 1.5 mg/dl, results in significant overlap in the way kidneys performed [4] (Fig. 1). The intention of this approach was to offer kidneys that would not be expected to function as long to older individuals or those with co-morbidities in whom the trade off between sooner transplantation but lesser expected duration of function was felt to be appropriate. However, the significant overlap between ECD and SCD kidneys led to changes in physician behavior and resulted in placing most or all patients on both lists and then selectively choosing which kidney to offer which patient. This was particularly likely to occur in regions with long waiting times. The Kidney Donor Risk Index (KDRI) was developed to correct this because it uses a continuous grading scale for kidneys in lieu of a dichotomous one [10]. The KDRI is composed of 10 variables and is expressed as a “hazard ratio” that reflects the risk of graft failure with a transplanted kidney from a particular donor relative to a reference donor. In the KAS, the donors recovered in the previous year become the reference population. For utilization in KAS the KDRI is converted into the Kidney Donor Profile Index (KDPI) [11]. The KDPI is a linear percentage scale with 0% having the longest anticipated survival and 100% having the shortest anticipated survival. The KDPI, like the EPTS, has only moderate ability to discriminate between similar donor kidneys and this is often levied as criticism. While this is justified it also ignores that the KDPI was only intended to be used to divide the deceased donor kidneys into broad categories for the purposes of allocation and never intended to be used to decide upon the appropriateness of a specific kidney for a specific patient. However, other very legitimate criticisms of this approach to classifying kidneys exist. One concern is that ranking kidneys from “best” to “worse” creates an
Table 1 Vignettes demonstrating how the 4 variables of the EPTS score, age, year on renal replacement therapy, diabetes and prior organ transplants can combine and give a recipient an EPTS score in the top 20%. Age
Years on RRT
DM
Prior Txp
EPTS
18 25 18 25 25 40 18 25 40 50
0 0 2 5 2 0 0 0 5 0
No No No No No No Yes Yes No No
No No No No Yes No No No No No
1% 1% 2% 5% 7% 8% 12% 12% 17% 18%
RRT, renal replacement therapy; DM, diabetes mellitus, either type 1 or type 2; Txp, prior transplanted solid organ of any type, kidney, pancreas, liver, heart, lung or intestine; EPTS, estimated post transplant survival. Source: OPTN/UNOS, provided for OPTN Kidney Transplantation Committee, 2012.
Please cite this article as: Formica RN, A critical assessment on kidney allocation systems, Transplant Rev (2016), http://dx.doi.org/10.1016/ j.trre.2016.10.002
R.N. Formica Jr. / Transplantation Reviews xxx (2016) xxx–xxx Table 2 The number of adults on the kidney transplant waitlist by decade of age, the percentage of the entire waitlist they represent and the percentage of them scoring in the top 20% EPTS. Age
N on WL (adults)
% on WL
% in EPTS Top 20
18–25 26–35 36–45 46–55 56–65 66–75 76+ All
2742 8256 16,136 25,094 29,469 14,762 1516 98,848
2.8 8.4 16.3 25.4 29.8 14.9 1.5 100.0
96.7% 80.6% 43.8% 10.1% 0.0% 0.0% 0.0% 20.0%
WL, waitlist. Source: OPTN/UNOS, provided for OPTN Kidney Transplantation Committee, 2012.
environment where a surgeon of physician has to give a kidney from the “worst” category to patient, where in the SCD/ECD system the ECD kidneys were lumped together. This new approach could lead to organ discards based upon the KDPI score alone. While the issue of discards remains a moving target at present, and analysis done prior to the implementation of KAS suggested that the rate of discard was not affected by the utilization of the KDPI score [12]. A more clinically relevant criticism is the institution of the KDPI score has eliminated the ability of a surgeon or physician to match a donor kidney to a recipient based upon the unique characteristic of the pair. While the SCD/ECD distinction was flawed from an allocation perspective as mentioned above, it did allow a more patient focused approach to kidney allocation. Finally, while the KDPI does incorporate 10 clinical variables of the donor it does not include the histologic evaluation of the kidney made on a preimplantation biopsy and review of the “pump parameters” for kidneys preserved with machine perfusion. Whereas there is meaningful debate about whether or not these two approaches are helpful or harmful in kidney allocation, the reality is they are used by clinicians and unaccounted for in the allocation process. 1.4. Longevity matching EPTS and KDPI are used together in KAS to pair kidneys expected to last the longest, top 20% KDPI, with patients expected to live the longest, top 20% EPTS. The concept is called longevity matching. A primary objective of longevity matching is to decrease the allocation of kidneys from younger donors to older individuals who will potentially die with the graft still functioning. While this may benefit the individual, it is not a good use for a scarce societal resource. Because the demand for transplantable kidneys vastly outstrips supply, some degree of longevity matching is a societal imperative and cannot be ignored. Additionally, because longevity matching allocates kidneys with the
3
longest expected duration of function to the candidates that are expected to need them the longest, it is possible to reduce the need for retransplantation. Because patients awaiting a subsequent kidney transplant compose between 10 and 15% of individuals on the waiting list [13], longevity matching has the potential to improve the chances for transplantation in older individuals because it will lessen future demand by reducing the need for re-transplants. This aspect of KAS generated the most debate. Based upon the early results, this approach has decreased the number of mismatched transplants [14]. However, while on balance the principle is sound there are some very just criticisms. The first is a patient centered argument that while death with a functioning graft may not be in society's best interest, it is in the best interest of the patient. In this scenario, the patient lives out their life free of end stage renal disease and the need for dialysis. Currently in American culture the needs of the one are not subjugated but the needs of the many and this approach is contrary to the ethos. Additionally, because organ allocation by its nature has a lottery aspect to it an older individual does not demand an organ from a younger donor but may receive one by chance. This is not different for the rest of the allocation system and to preclude certain individuals from it can be seen as unfair. Another issue with longevity matching is that the supply of lower KDPI donors in any give DSA is greatly exceeded by the demand (Fig. 2). This is further exacerbated by the fact that multi-organ transplants have priority over isolated kidney transplants and the kidneys associated with multi-organ transplants by and large come from donors with KDPI less than .35 [15]. Therefore while the policy intent is to allocate organs with greater duration of function to younger patients the reality is that this only occurs in 50% of the transplants in these individuals. Therefore the policy is only somewhat effective and my not fully achieve the intent of reducing return to the waiting list for repeat transplant. 1.5. High KDPI kidney allocation It is recognized that the overlap in expected survival between SCD and ECD kidneys undermines the efficacy of this allocation system. The new approach to allocating kidneys with a diminished expected duration of function, those kidneys with KDPI N85%, was designed to correct the shortcomings of the SCD/ECD approach. Additionally, a design hypothesis of this approach is that it may promote increased organ recovery by providing OPOs whose centers do not traditionally use these kidneys with timely access to centers that want them for transplantation. The KPDI method of classifying deceased donor kidney does not result in an overlap in kidney quality and therefore there is no reason to list a recipient to accept a kidney with KDPI 86% or greater unless they will benefit from a more rapid time to transplant.
Fig. 1. The percentage of donor kidneys stratified by Kidney Donor Risk Index that would be classified as extended criteria donor kidneys or not extended donor criteria kidneys.
Please cite this article as: Formica RN, A critical assessment on kidney allocation systems, Transplant Rev (2016), http://dx.doi.org/10.1016/ j.trre.2016.10.002
4
R.N. Formica Jr. / Transplantation Reviews xxx (2016) xxx–xxx
Fig. 2. EPTS top 20% candidates vs. KDPI top 20% kidney transplants, by donor service area.
Additionally, the fact that kidneys with KDPI 86% and greater will be allocated on a regional list may incentivize increased organ recovery. Currently there are OPOs in which the utilization of what was classified as ECD kidneys is very low and these OPOs are adjacent to those with very high usage of these kidneys [5]. Because in practice an OPO’s incentive for organ recovery is only based upon the probability of an organ being placed, and not influenced by the fact it may be utilized by a transplant center within its distribution area, the creation of a market for these kidney in an adjacent area may promote more recovery. Additionally, the recovery and placement of organs outside the OPO, may cause a change in the behavior of the programs within the OPO toward increased utilization of these higher KDPI organs. At the time of this writing, this remains an experimental hypothesis. Additionally, sharing organs on a regional list increases the logistical challenges of both shipping sample to transplant centers for cross matching and shipping of organs. In high KDPI kidneys, those more susceptible to ischemic damage, the increased shipping time may lead to more organ discards.
1.6. Waiting time calculation In kidney transplantation, as opposed to other solid organ transplantation, there is no accounting for the severity of illness in organ allocation. This is due to the success of maintenance dialysis therapy in forestalling death from end stage renal disease. The allocation system prior to 12/4/2014 did not account for the severity of illness as a patient accumulated waiting time no earlier than the time of listing. Months or years of dialysis prior to the patient being added to the waiting list did not matter even though it is recognized that the duration of dialysis exposure prior to transplantation results in worse post transplant outcomes [16]. Moreover, individuals who had more dialysis exposure prior to listing tend to be from racially and socio-economically disadvantaged groups (Fig. 3). Therefore the KAS now will credit waiting time from the date of listing with a qualifying estimated glomerular filtration rate (less than or equal to 20 ml/min) or from the confirmed date of dialysis initiation, even if dialysis began years prior to listing.
Fig. 3. Cumulative distribution of pre-registration dialysis years by ethnicity, for adult kidney additions with pre-registration dialysis, 1/1/07–12/31/12.
Please cite this article as: Formica RN, A critical assessment on kidney allocation systems, Transplant Rev (2016), http://dx.doi.org/10.1016/ j.trre.2016.10.002
R.N. Formica Jr. / Transplantation Reviews xxx (2016) xxx–xxx
This change to KAS is an important step to mitigating the disparity in access to transplantation that is known to occur due to delay or no referral to transplantation from dialysis units. However the very issue this policy is designed to address, prolonged dialysis exposure prior to transplantation is also documented to result in poorer transplant outcomes [16]. This fact places this policy at cross purposes with one of the primary goals of KAS which was to increase life years from transplant. By giving credit for time on dialysis prior listing, the KAS is prioritizing those individuals with worse expected outcomes after transplantation. When the policy went into effect it was anticipated that there would be a bolus phenomenon of patients with accumulated dialysis time being transplanted. This has occurred. However where the steady state occurs is yet to be determined. 1.7. Highly sensitized patients In the allocation system prior to 12/4/2014 all patients with a cPRA of 80% or greater were given four additional allocation points. This was approximately equivalent 4 years of waiting time. The intent was to move these patients up the waiting list so that they would receive more offers. However its reasoning was flawed in three areas. The first was that it assumed everyone with cPRA greater than 80% was equally disadvantaged. During design of KAS an analysis was done to determine the time to next offer — how long a patient would be expected to wait for a second offer if the first offer was declined. It revealed the stark reality for these highly sensitized patients. The median time for a patient with cPRA 0% was 11.7 days. Not surprisingly, as the degree of sensitization increased, the median time to next offer increased however it increased in an exponential and not linear fashion. At a cPRA of 60%– 69% the median time more than doubles to 31.2 days and nearly doubles again to 55.2 when cPRA reaches 75%–79%. Once a patient is in the range that would be considered highly sensitized the increases in median time to next offer become even more dramatic. An increase in cPRA from 95% to 97% causes median time to climb from 175 to 330 days and an increase of to 99% triples the time to 993 days. Finally for a patient with cPRA of 100% the median time-to-next offer increases to 4969 days. This is more than 13 years [17]. The second flaw in the four points for patients with cPRA over 80% approach was that it ignored the importance of donor pool size to increase the chances of finding a matching kidney. Although sensitized patients were given additional points they were still restricted to organs from their own donor service area or alternative allocation unit that was in effect for their area. Modeling donor during the development of KAS demonstrated that patients with cPRA 100% needed access to the national pool of kidneys to have the transplantation rates approach their representation on the waiting list. Those patients with cPRA 99% needed regional sharing and those with cPRA of 98% needed prioritization within their own DSA [8]. The third flaw was that it gave to much advantage to patients with lesser degrees of sensitization. For patients in the cPRA 80%–95% range the additional 4 allocation points resulted in rates of transplantation that were in excess of their representation on the waiting list and therefore gave them an unfair advantage. Additionally, because there was a break point, there was no incentive for transplant centers to enter unacceptable antigens into the listing for their patients whose cPRA was less than 80%. This hypothesis is supported by the observation pre KAS that a very large number of patients were listed with cPRA of 0%, very few with cPRA 1%–79% and then a bolus of listing at 80%. The problem with this practice was that while a single or a few unacceptable antigens may not place an individual patient into the extra allocation points category, they could still result in unexpected positive cross matches and this results in a less efficient allocation system. In the new KAS, recipients are assigned a score on a sliding scale to more accurately reflect the biological reality of their degree of sensitization (Table 3). This had two unintended consequences. First it resulted in inappropriately high rates of transplantation for individuals in the CPRA 80% to
5
Table 3 Additional allocation points assigned per increasing CPRA. One allocation point is equivalent to one year of waiting time. If the candidate's CPRA score is… Then the candidate receives this many points… x=0 0 b x b 10 10 ≤ x b 20 20 ≤ x b 30 30 ≤ x b 40 40 ≤ x b 50 50 ≤ x b 60 60 ≤ x b 70 70 ≤ x b 75 75 ≤ x b 80 80 ≤ x b 85 85 ≤ x b 90 90 ≤ x b 95 95 ≤ x b 96 96 ≤ x b 97 97 ≤ x b 98 98 ≤ x b 99 99 ≤ x b 100 100
0.00 0.00 0.00 0.08 0.21 0.34 0.48 0.81 1.09 1.58 2.46 4.05 6.71 10.82 12.17 17.30 24.40 50.09 202.10
Source: OPTN Policy 8: Allocation of Kidneys. http://optn.transplant.hrsa.gov/governance/ policies/.
95% ranges and did nothing to help those individuals who are truly disadvantaged, those with cPRA greater than 98%. In an analysis of kidney offer for candidates by cPRA, candidates with cPRA 100% received a vanishingly small number of offers relative to other groups (Fig. 4). These patients were projected to have an average wait for a compatible kidney offer of approximately 13 years. The use of the 80% cPRA threshold also resulted in transplant programs not entering unacceptable antigens into uNET for recipients who they assumed would not achieve a score of cPRA 80%, contributing to unexpected positive cross matches [8]. Certainly the new approach that the KAS takes to highly sensitized patients is a significant advance however there are still many valid criticisms and room for improvement. First, patients with cPRA of 100% have access to kidney throughout the country; however those with lower cPRA are still constrained to geographic areas that are not designed to have equity in mind and therefore geographic disparities still exist for these patients. Moreover, while sharing of kidneys over larger geographic areas improves access for highly sensitized patients, it also requires the more frequent shipping of organs over greater distances. This increased shipping of organs may result in increased cold ischemic time and higher rates of delayed graft function and organ discards. In fact, the initial 6-month data do indicate that cold ischemic time has increased slightly and delayed graft function has increased from 24.5% to 31%. Additionally the discard rate, especially for kidneys in the higher KDPI range (0.86–100), has increased [14] Whether or not this is due to shipping of organs alone is not certain because KAS seems to have resulted in an increased rate of organ recovery and has occurred coincident with new therapies for treating hepatitis C which may reduce the demand for these organs. Additionally, in recent months the discard rate has returned to its pre-KAS baseline [18]. Therefore the increase in discards may be an anomaly and further tracking of this issue is required. Certainly the shipping of organs for highly sensitized candidates has imposed new logistical challenges to the allocation of kidneys that are still being resolved; when to send samples for cross matching, how many centers to send them to and how to allocate to another candidate if the intended candidate has positive cross match. While these challenges should not be diminished, they also offer the opportunity to test and evaluate how best to share kidneys over a larger geographic area in preparation for the next iteration of kidney allocation that will seek to reduce the glaring geographic disparities that currently exist in access to kidney transplantation [19,20]. Another concern is that highly sensitized patients will be used to draw in kidneys that will be cross matched positive with the intended
Please cite this article as: Formica RN, A critical assessment on kidney allocation systems, Transplant Rev (2016), http://dx.doi.org/10.1016/ j.trre.2016.10.002
6
R.N. Formica Jr. / Transplantation Reviews xxx (2016) xxx–xxx
Fig. 4. Offer rates by CPRA for adult, kidney-alone candidates alone in 2010.
candidate and then transplant them into another patient. Because in the KAS more kidneys are being shipped the total number of kidneys being placed in the unintended candidate has increased. However the overall percentage of kidneys shipped for highly sensitized patient going into the unintended recipient has decreased suggesting that the system is functioning more efficiently. (Unpublished data, UNOS/OPTN Kidney Transplantation Committee). Moreover, HLA DQ alpha and DP beta typing will soon be required to be entered into the required HLA types that must be entered into a candidate's record. Because a large number of unintended cross matches are due to these class II HLA molecules this improvement should further decrease the number of unexpected positive cross matches that occur after allocation and improve system efficacy [21–23]. Finally, by prioritizing highly sensitized patients, it is possible that the outcome of these transplanted kidneys will be worse than if transplanted into individuals with lower immunologic risk. However, because the expected half-life of a deceased donor kidney is between 5 and 11 years the final answer to this question will be some years in the future [24]. 1.8. A2, A2B donor kidneys allocated to B blood group recipients The national median waiting time for patients with blood type B is the longest in the country. Moreover, because recipients of blood type B tend to be of minority populations and because blood type B is rare, these groups are at a disadvantage [25]. In 2001, the OPTN Board of Directors approved a variance to enable the transplantation of blood type A2 (technically, “non-A1”) and A2B (technically, “non-A1B”) deceased donor kidneys into blood type B candidates. The goal of this variance was to increase the rate of transplantation in blood type B candidates by allocating these kidneys to them without negatively impacting post-transplant outcomes. Since implementation and prior to adoption into the KAS, nine OPOs participated in this variance. The available literature supports the fact that A2 and A2B kidneys transplanted into blood type B recipients have comparable survival rates and that this practice has shortened waiting times for this blood type [26,27]. However, since implementation of the KAS the number of these transplants performed has been insignificant [14]. Therefore the improvement in access to transplantation experienced by African American since the KAS started is more likely due to the adjustment in waiting time to include pre-registration dialysis time and not from the allocation of A2 and A2B donor kidneys in B blood group recipients [14]. Moreover, the implementation of a protocol to perform these transplants is logistically challenging from the transplant center perspective and the increased
resources required and increased risk incurred may outweigh the benefit of increased transplants.
1.9. Unintended consequences of KAS The increased priority and sharing of organs for highly sensitized patients have resulted in organs with KPDI less than .35, which would have been prioritized for children within the local donor service area, being offered first to adults. While there has not been a statistically significant drop in the number of pediatric transplants performed nationally, there has been a slight decrease in offer rates to children [14]. Additionally there have been many anecdotes about prolonged intervals between offers for children from various centers. Whether this reflects changes in acceptance patterns or a true lack of acceptable organs is not yet clear. What is clear is that with the change from allocating organs from donors age 35 years or less to donors with KDPI .35 or less, the quality of kidneys being offered to children has improved. Regardless the intention of the KAS was to improve outcomes in younger patients and if there has been a true decrease in access for children this must be remedied. With the initiation of the KAS local variances and alternative allocation units in organ allocation were retired. This was necessary both to make the KAS possible from a computer program perspective as well as to establish a new baseline by which future variance can be properly assessed. Nevertheless, while in aggregate the myriad local variances were detrimental to the system at large, some unquestionably addressed unique local challenges. Over time variances that conform to the standards put forth in the final rule will help to modify and improve the KAS. Finally and most significantly the KAS does nothing to address the fact that the multi-organ allocation system is broken and in need of a comprehensive review and in need of a complete overhaul. Currently, with the exception of simultaneous pancreas kidney allocation, all multi-organ transplantations are done without medical eligibility criteria or prioritization based on need. This is in direct violation of the final rule. Kidneys allocated in multi-organ transplants come from donors of low KPDI and therefore these kidneys are diverted from children and young adults and these diversions occur without consideration for the relative need of the recipients. It is worthwhile to note that the first full year of the KAS saw the greatest annual number of simultaneous liver kidney transplants performed (Unpublished data, UNOS/ OPTN Kidney Transplantation Committee).
Please cite this article as: Formica RN, A critical assessment on kidney allocation systems, Transplant Rev (2016), http://dx.doi.org/10.1016/ j.trre.2016.10.002
R.N. Formica Jr. / Transplantation Reviews xxx (2016) xxx–xxx
2. Conclusion The KAS is a significant improvement over the prior system used to allocate kidneys. It begins to move the distribution of kidney from one primarily based upon waiting time to one that takes into account patient need through longevity matching, waiting time based upon dialysis exposure and an evidence based approach to the highly sensitized patient. Moreover, it has been designed in a way to allow modification and improvement as data become available. However, like all major policies initiatives it is not perfect and it was not possible to anticipate and account for second and third tier consequences that resulted from the new policy or how policy affected and changed physician behavior. Therefore ongoing monitoring and critical assessment of the outcomes are necessary to direct necessary modifications. Conflict of interest Dr. Formica has not financial or fiduciary conflicts of interest with regards to this manuscript. References [1] Israni AK, Salkowski N, Gustafson S, et al. New national allocation policy for deceased donor kidneys in the United States and possible effect on patient outcomes. J Am Soc Nephrol 2014;25:1842–8. [2] Friedewald JJ, Samana CJ, Kasiske BL, et al. The kidney allocation system. Surg Clin North Am 2013;93:1395–406. [3] [updated December 23, 2015; cited 2015 December 26]. Available from. http:// www.ecfr.gov/cgi-bin/text-idx?SID=bb60e0a7222f4086a88c31211cac77d1&mc= true&node=pt42.1.121&rgn=div5View. [4] Keitel E, Michelon T, dos Santos AF, et al. Renal transplants using expanded cadaver donor criteria. Ann Transplant 2004;9:23–4. [5] 2012. http://srtr.transplant.hrsa.gov/annual_reports/2012/pdf/07_dod_13.pdf [cited 2016 January 2]. [6] Organ Procurement and Transplantation Network (OPTN). Estimated post transplant survival calculator. Available from. http://optn.transplant.hrsa.gov/converge/ resources/allocationcalculators.asp?index=82. [7] Harrell Jr FE, Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 1996;15:361–87. [8] Proposal to substantially revise the National Kidney Allocation System. 2014. [9] Ljungquist B, Berg S, Steen B. Determinants of survival: an analysis of the effects of age at observation and length of the predictive period. Aging (Milano) 1996;8:22–31.
7
[10] Organ Procurement and Transplantation Network (OPTN). Kidney donor profile index calculator. Available from. http://optn.transplant.hrsa.gov/resources/ allocationcalculators.asp?index=81. [11] Rao PS, Schaubel DE, Guidinger MK, et al. A comprehensive risk quantification score for deceased donor kidneys: the kidney donor risk index. Transplantation 2009;88: 231–6. [12] Stewart D, Samana CJ, Formica RN, Friedewald J. Has displaying KDPI in DonorNet led to a spike in discard rates for lower quality kidney? Available from:; 2013. http://www.atcmeetingabstracts.com/abstract/has-displaying-kdpi-in-donornetled-to-a-spike-in-discard-rates-for-lower-quality-kidneys/. [13] OPTN/SRTR annual data report: kidney. Available from. http://srtr.transplant.hrsa. gov/annual_reports/2012/pdf/01_kidney_13.pdf. [14] Stewart DE, Beck J, Kucheryavaya AY. Six-month evaluation of the new, national Kidney Allocation System (KAS); 2015. [15] Formica RN, Aeder M, Boyle G, et al. Simultaneous liver-kidney allocation policy: a proposal to optimize appropriate utilization of a scarce resources. Am J Transplant 2016;16:758–66. [16] Meier-Kriesche HU, Kaplan B. Waiting time on dialysis as the strongest modifiable risk factor for renal transplant outcomes: a paired donor kidney analysis. Transplantation 2002;74:1377–81. [17] 3Stewart DE. OPTN/UNOS kidney transplantation committee: time-to-offer analysis for adult kidney candidates. Estimating the average time between deceased donor kidney offers for adults on the waitlist, by level of allosensitization (CPRA); 2011. [18] Early data suggests kidney allocation system is meeting key expectations. [cited 2015 December 20]. Available from. https://www.unos.org/early-data-suggest-kidney-allocation-system-meeting-key-expectations-2/. [19] Cherikh WS, Stewart DE, Kucheryavaya AY, Baker T, Cheng Y. Kidney offer rates, transplant rates, supply/demand ratios, and median waiting times by DSA; 2014. [20] Davis AE, Mehrotra S, McElroy LM, et al. The extent and predictors of waiting time geographic disparity in kidney transplantation in the United States. Transplantation 2014;97:1049–57. [21] Morris GP, Phelan DL, Jendrisak MD, Mohanakumar T. Virtual crossmatch by identification of donor-specific anti-human leukocyte antigen antibodies by solid-phase immunoassay: a 30-month analysis in living donor kidney transplantation. Hum Immunol 2010;71:268–73. [22] Cecka JM, Kucheryavaya AY, Reinsmoen NL, Leffell MS. Calculated PRA: initial results show benefits for sensitized patients and a reduction in positive crossmatches. Am J Transplant 2011;11:719–24. [23] Gebel HM, Bray RA. The evolution and clinical impact of human leukocyte antigen technology. Curr Opin Nephrol Hypertens 2010;19:598–602. [24] Stewart DE, Kucheryavaya AY. Estimated graft half live for kidney transplants with KDPI 0–20%, 21–34%, 35–85% and 86–110% vs. living donor transplants; 2015. [25] Young CJ, Gaston RS. Renal transplantation in black Americans. N Engl J Med 2000; 343:1545–52. [26] Bryan CF, Winklhofer FT, Murillo D, et al. Improving access to kidney transplantation without decreasing graft survival: long-term outcomes of blood group A2/A2B deceased donor kidneys in B recipients. Transplantation 2005;80:75–80. [27] Bryan CF, Nelson PW, Shield III CF, et al. Transplantation of A2 and A2B kidneys from deceased donors into B waiting list candidates increases their transplantation rate. Clin Transpl 2004:127–33.
Please cite this article as: Formica RN, A critical assessment on kidney allocation systems, Transplant Rev (2016), http://dx.doi.org/10.1016/ j.trre.2016.10.002