The Expanded Criteria Donor Policy: An Evaluation of Program Objectives and Indirect Ramifications


* Corresponding author: J. Schold,


The expanded criteria donor (ECD) policy was formalized in 2002, which defined higher-risk deceased donor kidneys recovered for transplantation. There has not been a comprehensive examination of the impact of policy on the allocation of ECD kidneys, waiting times for transplant, center listing patterns or human leukocyte antigen (HLA) matching.

We examined transplant candidates from 1998 to 2004 utilizing a national database. We constructed models to assess alterations in recipient characteristics of ECD kidneys and trends in waiting time and cold ischemia time (CIT) associated with policy. We also evaluated the impact of the proportion of center candidate listings for ECD kidneys on waiting times.

Elderly recipients were more likely to receive ECDs following policy (odds ratio = 1.36, p < 0.01). There was no association of decreased CIT or pretransplant dialysis time while increasing HLA mismatching with policy inception. Over one quarter of centers listed <20% of candidates for ECDs, while an additional quarter of centers listed >90%. Only centers with selective listing for ECDs offered reduced waiting times to ECD recipients.

The ECD policy demonstrates potential to achieve certain ascribed goals; however, the full impact of the program, reaching all transplant candidates, may only be achieved once ECD listing patterns are recommended and adopted accordingly.


The shortage of available organs in renal transplantation is well documented (1–5). The death rate for kidney transplant candidates on the waiting list increased 24% from 1995 to 2003 (6). The expected benefit associated with deceased donor kidneys varies widely based on characteristics of the organs; however, even higher-risk kidneys convey a significant survival advantage relative to maintenance dialysis for transplant candidates (6–9). Despite the benefit associated with kidney transplantation, a significant number of organs are discarded that are initially recovered for the purpose of transplantation (10,11).

The expanded criteria donor (ECD) policy in renal transplantation was implemented in October 2002 (12). The policy was developed to identify higher-risk deceased donor organs, with the intent to increase recovery and utilization rates of available kidneys and improve the efficiency of the kidney allocation process (12). Analysis by the Scientific Registry of Transplant Recipients (SRTR) demonstrated that ECD kidneys were associated with an increased risk of at least 70% for overall graft loss in transplant recipients relative to an ideal reference class of donations (13). ECD kidneys are identified as deriving from either a donor who is older than 60 years of age or one who is older than 50 years of age who has two additional risk factors, including a history of hypertension, a high elevated terminal creatinine or a cerebrovascular cause of death. As stated in the policy, transplant candidates must consent to accept an ECD transplant, generally at evaluation, and may be offered the potential incentive of receiving a donor organ sooner in exchange for one of a lower quality. The 2002 conference on the waiting list for kidney transplantation suggested that the most appropriate candidates for ECD transplants would likely be older patients, diabetics, patients with limited vascular access and nonsensitized patients (14). In general these recommendations reflect that patients with poor prognoses on dialysis cannot often afford extended waiting periods for a standard kidney donation. Subsequent studies have confirmed that there are specific patient groups who may particularly be appropriate for an ECD transplant in exchange for reduced waiting time on dialysis (15,16).

Utilizing data within 18 months of the program implementation, Sung et al. demonstrated that the goals intended by the ECD program have had mixed results (17). This report found an increase in the total number of recoveries associated with the period following policy implementation, but an insignificant change in the relative risk for graft loss among ECD recipients. Additionally, a significant decline in CIT for both ECD and standard donor (SD) kidneys was found. However, there were no significant changes in recovery or discard rates of ECD kidneys since policy inception.

In the present analysis, we used several alternative assessment criteria to further evaluate the impact of the ECD program. We investigated whether characteristics of those patients who received ECD transplants significantly changed following the inception of the policy. In addition, we estimated the impact of the policy on waiting time for both ECD and SD kidneys. We also examined the proportion of patients listed for ECD kidneys at individual transplant centers and the associated waiting times for transplant based on this proportion. Additionally, as policy has largely deemphasized HLA matching for ECD kidneys, we described the degree of mismatching among transplants following implementation of the policy (18).


We examined data from the national SRTR database for adult (age 18+ years) transplant candidates (n = 144 728) from 1998 through July 31, 2004. Neither patients who listed for or received multiple organ transplants nor those who received living donor transplants within the time frame of the analysis were included. We utilized the Organ Procurement and Transplantation Network (OPTN) definition of ECD deceased donor kidneys (13). For the purpose of examining the ramifications of the ECD policy, yearly intervals were examined for variables of interest, with data for candidates prior to October 31, 2002, categorized as pre-ECD policy and after that date, as post-ECD policy.

Independent Variables

Previous research has demonstrated certain disparities in waiting times of transplant candidates based on gender, income, race, primary diagnosis and age (19–21). In addition, estimated pretransplant waiting time significantly varies as a function of candidate blood type, panel reactive antibody (PRA) level and region of the country in which the candidate receives treatment (22). Transplant candidates' education level was dichotomously categorized as a bachelor's degree or higher or less than a bachelor's degree. Candidates' primary insurance status was categorized as Medicare, private (including PPO and HMO plans), or other. Candidates' PRA percentage was categorized as 0, 1–30, and 31+. Race was categorized as Caucasian, African American or other. Transplant centers were indicated by a numerical code in the database without reference to the name or location of the center.

Outcome Measures

We analyzed candidates' likelihood of receiving an ECD kidney (of all deceased donor transplants) prior to and following ECD policy inception. CITs (in hours) were log transformed to account for a relatively right-skewed distribution and analyzed based on the transformed values in order to create a relatively normal error distribution for linear models. Pretransplant dialysis time (in months) was also logarithmically transformed. Adjusted overall graft survival was calculated for ECD transplants relative to SD transplants in both eras. We also described the proportion of patient listings for ECD kidneys at the transplant center unit of analysis following the implementation of the policy. For this portion of the analysis, we limited the sample to centers with 50 or more listings in the post-ECD policy era. Time to transplantation was assessed in the postpolicy era for ECD and SD candidate listings and stratified by the proportion of ECD listings at the transplant centers. Additionally, we reported the degree of HLA (A, B and DR) mismatching in SD and ECD transplants.

Statistical Models

Multivariate logistic models were utilized to assess the likelihood of receiving an ECD transplant adjusted for potentially associated factors including patient age, peak PRA, race, education, primary insurance, blood type, primary diagnosis of diabetes, OPTN transplant region, waiting time on dialysis and gender. The interaction terms of patient characteristics and the year of listing were incorporated into the model to estimate the likelihood of receipt of an ECD transplant pre- and post-policy. Ordinary least-squares models were generated to examine the duration of waiting time and CITs in ECD and SD transplants by transplant year. For these models, we also generated predicted confidence intervals for the post-policy era based on prior trends and compared these intervals with actual levels. Adjusted Cox proportional hazard models were formed to estimate graft survival of ECD transplants relative to SD transplants. Kaplan-Meier plots were utilized to examine the time to transplantation for waitlisted candidates in the postpolicy era. These models were censored at the time of removal from the waiting list for any cause (including death or transfer to another center). In addition, recipients of living transplants were excluded from the models. We reported the proportion of patients who received a deceased donor transplant at 500 days following the policy and the projected median time to transplantation based on extrapolating the transplant rates. Chi-squared tests were used to test the independence of categorical variables. All analyses were conducted using SAS (v.9.1.3, Cary, NC).


Among all deceased donor transplants, the overall proportion of ECD transplants increased from 16.2% pre-ECD policy to 17.9% for the analysis period post-ECD policy. Table 1 displays the proportion of ECD transplants by recipient characteristics prior to and following implementation of ECD policy and the adjusted odds ratio representing the change in the likelihood of an ECD transplant following policy. Elderly transplant recipients (aged 65+) received ECD kidneys in 35% of all deceased donor transplants following policy as compared with 27% prior to policy (p < 0.001). Figure 1 represents the annual adjusted odds ratios for elderly patients (65+ years) for receipt of ECD kidneys relative to 18–34-year-old transplant recipients. The adjusted odds for an elderly recipient to receive an ECD prior to the policy was over 4-fold relative to the younger cohort (AOR = 4.2, 95% CI 3.7–4.8) and significantly higher after the policy (AOR = 7.8, 95% CI 6.1–9.9). This change in elderly patients represented a 36% increase in the adjusted odds (AOR = 1.36, 95% CI 1.18–1.57) for receiving an ECD transplant relative to the change in 18–34-year-old candidates associated with policy implementation. Highly sensitized patients received fewer ECD kidneys after the policy (14.6% prepolicy and 11.8% after policy), representing a significant difference relative to nonsensitized patients for whom the proportion of ECD transplants increased from 17.2% to 19.2%. The odds of receipt of an ECD transplant did not significantly change following policy by recipient race, blood type, gender, education level, primary insurance type or primary diagnosis. The adjusted hazard ratio for graft loss in ECD transplants prior to the ECD policy was 1.73 (95% CI 1.64–1.82) relative to SD transplants in the same era. Following policy, the adjusted hazard ratio for graft loss in ECD transplants was 1.83 (95% CI 1.55–2.17) relative to SD transplants following policy.

Table 1.  Likelihood of an ECD transplant pre- and post-ECD policy implementation for all deceased donor transplant recipients
Recipient characteristicLevelPercentage of ECDs pre-policy1Percentage of ECDs post-policy1Odds ratio for difference in likelihood of an ECD transplant2
  1. 1Percentage of ECD transplants of all deceased donor transplants in the respective period.

  2. 2Adjusted odds ratio for change in likelihood of an ECD transplant in the post-policy era compared with pre-policy relative to change in likelihood for reference group. 95% confidence intervals in parentheses.

35–5413.312.71.11 (0.97, 1.27)
55–6421.421.91.16 (1.01, 1.33)
65+27.434.81.36 (1.18, 1.57)
Female16.016.70.95 (0.90, 1.01)
Peak PRA%017.219.2Reference
1–3015.217.61.04 (0.97, 1.12)
31+14.611.80.85 (0.76, 0.94)
Primary diagnosesOther14.715.5Reference
Hypertension17.420.21.05 (0.98, 1.14)
Diabetes18.821.51.03 (0.96, 1.11)
Recipient raceCaucasian15.817.3Reference
African American16.518.61.03 (0.96, 1.10)
Other19.319.50.97 (0.87, 1.08)
Blood typeO16.818.9Reference
A, AB, B15.817.10.99 (0.94, 1.05)
Education levelBachelor's degree or more16.018.2Reference
Less than bachelor's degree16.318.00.99 (0.91, 1.08)
Primary insurance typeMedicare16.818.2Reference
Private15.418.01.03 (0.97, 1.11)
Other14.416.60.99 (0.89, 1.10)
ALL 16.217.9 
Figure 1.

Adjusted odds ratio for receipt of an ECD transplant for elderly recipients by year*.*2003 estimate includes transplants in November and December of 2002 following policy implementation.

The log-transformed mean levels of CIT and pretransplant waiting time over the analysis period are illustrated in Figure 2. The confidence intervals for the predicted transformed mean CITs and actual mean levels in ECD transplants did not significantly deviate with policy implementation (transplant year 2003, predicted 95% CI [2.80, 2.89], actual = 2.81 and transplant year 2004, predicted 95% CI [2.75, 2.87], actual = 2.87). Waiting times for transplant recipients increased overall, but did not significantly deviate from projected waiting times based on prior trends. This result was consistent stratified by ECD and SD transplants separately and restricted to elderly recipients.

Figure 2.

Cold ischemia and pretransplant dialysis times for deceased donor transplants by year of transplant. ECD transplants indicate deceased donor expanded criteria donor transplants. SD transplants indicate deceased donor transplants not meeting the ECD definition.

Figure 3 illustrates the proportion of candidates listed for ECD kidneys at the transplant center unit of analysis. The graph depicts the percentage of candidates listed for ECD transplants among centers with at least 50 candidates listed in the post-ECD policy era. The bimodal distribution included 24% of centers with more than 90% of candidates and almost 20% of centers with fewer than 10% of candidates listed for ECD transplants. Figure 4A–C illustrate the association of a transplant center's proportion of ECD-listed candidates and the time to receipt of a deceased donor transplant. ECD candidates in centers in which there were relatively few such candidates (<20%) received their transplant significantly more rapidly, with 24% of candidates attaining transplant at 500 days compared with only 10% of candidates who were not listed for ECD transplants. This projected rate equated to a difference of over 4 years in median time to receipt of a deceased donor transplant based on listing status. There was a less pronounced difference in projected median times to transplant for ECD-listed candidates in centers in which there was an intermediate proportion of such patients; 1312 days and 1813 days for ECD and non-ECD listed candidates, respectively. ECD candidates at centers with a high proportion of listings (>90%) received transplants less rapidly, with a projected median 1664 days as compared with 1274 days for non-ECD candidates.

Figure 3.

Percentage of ECD listings at transplant centers post-ECD policy*.*Transplant centers included with 50 or more candidate listings in the post-ECD policy era.

Figure 4.

Kaplan-Meier model of time to transplant at (A) a low-level ECD listing center, (B) an intermediate-level ECD listing center and (C) a high-level ECD listing center.*Model censored for removal from list and excluded living transplant recipients. **Median days to transplant estimated assuming constant rate until 50% of candidates reached transplant.

The levels of HLA mismatching by deceased donor transplant type and year of transplant are summarized in Table 2. For standard deceased donor transplants, there was a mild increase in 0-HLA mismatched transplants over the analysis period (14.0–16.4% from 1998 to 2004). In addition, there was an elevation in transplants, with 4–6 HLA mismatches (26.6–40.0% from 1998 to 2004) among SD transplants. In contrast, among ECD transplants, 0-HLA mismatched transplants declined (11.1–4.3% from 1998 to 2004), and 4–6 HLA mismatched transplants dramatically increased (26.3–56.6% from 1998 to 2004), particularly following implementation of the ECD policy.

Table 2.  Human leukocyte antigen-matching by deceased donor transplant type and year
 Year of transplant
Standard donor transplants
 0 HLA-MM (%)14.014.614.514.915.115.216.4
 1–3 HLA MM (%)59.556.856.254.751.647.243.6
 4–6 HLA MM (%)26.628.529.330.433.237.540.0
ECD transplants
 0 HLA-MM (%)
 1–3 HLA MM (%)62.660.757.558.554.841.439.1
 4–6 HLA MM (%)26.329.232.032.937.053.156.6


Our analysis suggests that ECD policy has had an impact on the renal transplant allocation process on several levels. Our results demonstrate a strong association between ECD policy implementation and allocation of ECD kidneys to elderly recipients. This distribution is consistent with initial proposals to direct these transplants to patients with shorter life expectancies. However, our analysis also suggests that the goals of decreased cold ischemia and waiting times that were hoped to accompany this allocation process have not been accomplished. Differentials in pretransplant waiting time appear to be directly related to the proportion of ECD listings at transplant centers. The perceived benefit of accepting an ECD transplant in exchange for shorter waiting times on dialysis appears to be a reality only in centers with discriminate listing patterns.

The overall disproportionate allocation of lower-quality donations to older candidates in renal transplantation has been described previously (13,23). A portion of this effect following the ECD policy may be attributable to an objective definition of a higher-risk donation that subsequently has allowed physicians to recommend these organs to candidates whom they deem to be appropriate. Although age is not a factor in allocation policy for adult candidates, elderly candidates may have a greater incentive to accept ECD transplants if their prognosis on maintenance dialysis is poor (24,25). The strong association of waiting time and pre- and posttransplant mortality renders these factors crucial in organ-selection decisions (26–29). The novelty of the present analysis is that the ECD policy—and, inferentially, the consenting process—appears to have had a substantial effect on the distribution of these higher-risk donor transplants to elderly recipients.

There also appear to be differential patterns of receipt of ECD kidneys among sensitized patients relative to nonsensitized patients in the post-ECD policy era. In particular, sensitized patients are less likely to receive ECD kidneys in the post-policy era. Given the obvious barriers to receiving a transplant for sensitized patients, this finding may reflect increased acceptance of ECD kidneys among nonsensitized patients and, consequently, the unavailability of these transplants for highly sensitized patients. Nonsensitized patients who are willing to accept ECD kidneys clearly have greater access to these donor organs and appear to accept them at higher rates relative to years prior to the ECD policy.

The distribution of ECD kidneys after policy implementation has not significantly changed with regard to other characteristics of the waitlisted population. In particular, diabetic patients, who have a significantly shorter life expectancy on dialysis, do not appear to be affected by the ECD policy (30). In a similar fashion, patients' blood type, which has a significant effect on projected waiting time, does not appear to result in a different rate of ECD kidney transplantation. These patient characteristics, among other factors that affect patient prognoses after ESRD onset, may also represent appropriate candidates for ECD kidneys, particularly for those who are able to receive these organs with reduced exposure to dialysis.

We conclude that in contrast to the findings of Sung et al., the ECD policy has not had an impact on CITs associated with both standard and ECD transplants. Theoretically, clearer identification of ECD candidates should facilitate the efficiency of the transplant process; however, considering temporal trends, a significant reduction does not appear to be attributable to the program. Carter et al. have demonstrated that these goals are possible at a single center, but from a population perspective, they have yet to be achieved (31). These results are important, as research has demonstrated the increased sensitivity of ECD kidneys to CIT. Moreover, they underscore the necessity to implement the policy in such a way to achieve the goal of greater efficiency to accompany increased organ recoveries (32).

Overall, the impact of the ECD policy on reducing waiting times for ECD candidates appears to be minimal. Considering that research has shown that patients may only benefit from an ECD transplant relative to a standard transplant if their exposure to dialysis significantly decreases, these results are disconcerting (24). However, these broad observations may reflect competing effects based on the proportion of ECD candidate listings at individual transplant centers. At a minimum, patients should be advised of a center's policy and pattern of ECD listings before giving their consent. Alternatively, clearer standards regarding which patients should list for ECD transplants may facilitate efficiency and more discriminate listings, thereby allowing an ECD candidate to receive a transplant earlier in exchange for a lower-quality organ. Failing this, most candidates at centers with high rates of ECD listings have little to benefit from the policy.

The ECD policy also may be more attractive because of its straightforward approach to managing the waiting list by deemphasizing HLA matching in the point system for allocation. As expected, the degree of mismatching has significantly increased among ECD transplants. Although there is substantial evidence to suggest that the impact of HLA matching has not been as great in recent years, its effect in the long term will have to be carefully monitored (33).

In summary, the ECD policy warrants detailed evaluation of the utility, equity and efficiency of the allocation process for kidney transplantation. Beyond the stated objectives of the policy, the impact on individual patient groups must be carefully considered in the application and assessment of the policy. Our analysis suggests that the policy has had a significant impact on receipt of ECD transplants among elderly candidates and limited impact on waiting time and CIT. Furthermore, it has resulted in a significant increase in HLA mismatching in ECD transplant recipients. In order to achieve the full potential of the ECD program, clearer candidate criteria and more direct application of the policy may be necessary. Future analyses focusing on the process of listing candidates for ECD transplants and longer-term outcomes will be necessary to monitor the policy's ultimate impact.


The data reported here have been supplied by the University Renal Research and Education Association (URREA) as the contractor for the Scientific Registry of Transplant Recipients (SRTR). The interpretation and reporting of these data are the responsibility of the authors and in no way should be seen as an official policy of or interpretation by the SRTR or the U.S. government. IRB approval or exemption determination is the responsibility of the authors as well.

We would like to express our gratitude to Jayne Plymale for her excellent editorial comments and review of this manuscript.