Advertisement
The Journal of Heart and Lung Transplantation
International Society for Heart and Lung Transplantation.

The urgent priority for transplantation is to trim the waiting list

  • Lynne Warner Stevenson
    Correspondence
    Reprint requests: Lynne Warner Stevenson, MD, Brigham and Women's Hospital, Cardiovascular Division, 75 Francis Street, Boston, MA, 02115. Telephone: 617-732-7406. Fax: 617-264-5265
    Affiliations
    Advanced Heart Disease Section, Brigham and Women’s Hospital, Boston, Massachusetts
    Search for articles by this author
      The recognized success of cardiac transplantation has encouraged increased referrals of patients with refractory heart failure to major transplant centers. Potential candidates join the long waiting list, only to suspend their lives as they deteriorate to win higher priority. This is true both in Europe and in the United States, where we list >3,000 adults each year while performing about 2,000 transplants (Figure 1). This system jeopardizes outcomes for both the patients and the transplanted hearts, and inflates costs. Smits and coauthors in the accompanying article have taken steps to reexamine and redesign priority in a thoughtful pilot study of 448 patients listed with urgent status during an 8-month period, 189 of whom underwent transplantation.
      • Smits J.M.
      • de Vries E.
      • de Pauw M.
      • et al.
      Is it time for a cardiac allocation score? First results from the Eurotransplant pilot study on a survival benefit–based heart allocation.
      Figure thumbnail gr1
      Figure 1Trends in listing. Numbers of adult candidates (filled squares) added to the waiting list and number of adult transplants performed (open circles) each year since 1995, from national UNOS data.

      Organ Procurement and Transplantation Network. http://optn.transplant.hrsa.gov/latestData/step2.asp. Accessed May 30, 2013.

      Also shown are the annual number of candidates added as Status I (filled triangles). Note that, after 1999, Status I was divided into Status IA and IB, which are then added for the total number of Status I patients. The number of Status I patients has increased to equal the total number of patients transplanted in 2012. The number of candidates listed as Status II (filled diamonds) has declined during the same period.

      General considerations in setting priority for transplantation

      An allocation system for scarce donor hearts should maximize expected benefit, integrating risks with and without transplantation into a complex calculus. Optimally, the defined priority levels should support incentives to provide best care prior to transplantation, but they should at least not incentivize unnecessary interventions to escalate priority. The system should ensure that: (1) high-priority patients do have a high risk without transplantation; (2) transplantation will be performed with appropriately short waiting times for the highest priority patients; and (3) a reasonable proportion of patients can undergo transplantation at a lower priority level. No priority system can be effective or even evaluable except in the context of a waiting list length that is matched to the current donor heart supply.

      Maximize benefit over risk

      Risk scores

      Of the multiple scores proposed for heart failure risk, the Seattle Heart Failure Survival Score is the most widely known, with serial remodeling of a risk equation derived primarily from outpatient medication trials in Class II or III heart failure.
      • Kalogeropoulos A.P.
      • Georgiopoulou V.V.
      • Giamouzis G.
      • et al.
      Utility of the Seattle Heart Failure Model in patients with advanced heart failure.
      A more recent Seattle model modified to include inotropic therapy and ventilator support surprisingly fared less well in this population of advanced heart failure. In the study, the survival outcomes separated between lowest 3 risk groups and the highest risk group, which had a 3-month mortality of 24%, but included only 7.5% of the 448 urgent patients. The Heart Failure Survival Score was validated previously from the potential transplant population,
      • Aaronson K.D.
      • Schwartz J.S.
      • Chen T.M.
      • et al.
      Development and prospective validation of a clinical index to predict survival in ambulatory patients referred for cardiac transplant evaluation.
      which identified a high-risk group of 42% of the patients, with a 3-month mortality of 14%. This provides evidence of the deficiency of the current priority system to select patients at very high risk without transplant, as these mortality rates of <25% are the highest among a group of patients who were all listed for urgent transplant.
      For post-transplant risk, the IMPACT (Index for Mortality Prediction After Cardiac Transplantation) score
      • Weiss E.S.
      • Allen J.G.
      • Arnaoutakis G.J.
      • et al.
      Creation of a quantitative recipient risk index for mortality prediction after cardiac transplantation (IMPACT).
      was dominated by its highest risk group, which showed 3-month mortality of 70% in a group of only 7 patients, compared with another 182 patients, all with early mortality at <20%.

      Benefit scores

      Many of the factors predicting death on the waiting list also predict poor outcomes after transplant (or mechanical circulatory support), such as age, non-compliance and renal dysfunction. A key step taken by the Eurotransplant research group has been to move beyond the pre-transplant risk score to integrate the risk score for death after transplant as well. The resulting benefit score is based on estimation of the difference between survival time expected after transplant and survival time expected on the waiting list (analogous to the separate lung allocation scores in current use for different pulmonary diagnoses). Although their analysis focused on the 12-week data, it is the long-term outcomes after transplantation that will guide estimates of survival time. Patients at highest risk pre-transplant often have higher post-transplant risk early, which disappears during long-term follow-up. Previous Markov modeling of waiting list transitions and allocation has suggested that benefit is maximized when priority for donor hearts is awarded to patients most likely to die on the waiting list unless their post-transplant mortality approaches 50% in the first year.

      Stevenson LW, Warner SL, Hamilton MA, et al. Modeling distribution of donor hearts to maximize early candidate survival. Circulation 1992;86(suppl):II-224-30

      The authors described a key limitation of current scores in their pilot study. Neither the Seattle score nor the IMPACT score could predict outcomes for the patients on mechanical support. In the study, 26% of patients received implantable devices and 15% were on extracorporeal support at the time of listing. This proportion has continued to increase rapidly.

      Range of uncertainty around survival time benefit

      The margins of uncertainty around survival rates for populations stretch rapidly when applied to anticipate survival time for an individual patient. This is well-recognized in oncology, despite a more predictable pattern of decline than in heart failure. For cancer patients predicted to die at 180 days, half would instead live either <90 days or >1 year.
      • Henderson R.
      • Jones M.
      • Stare J.
      Accuracy of point predictions in survival analysis.
      The daunting expanse of these confidence intervals is further extended when estimating the difference between survival with two different therapies, particularly when one involves the front-loaded risk of surgery, with different distributions of early and late hazards.
      When comparing potential outcomes with and without transplantation, it is crucial to recognize that patients do not have an increase or decrease of risk, only survival or death. The functional and quality end-points offer higher relevance when sharing decisions with individual patients.
      • Allen L.A.
      • Stevenson L.W.
      • Grady K.L.
      • et al.
      Decision making in advanced heart failure: a scientific statement from the American Heart Association.
      This provides strong rationale for retaining assessments that connote both survival and functional capacity, such as the peak VO2 or Minnesota and Kansas City questionnaires, even when some of their predictive power can be replaced by integration of variables such as total lymphocyte count and diuretic doses that do not drive patient-reported outcomes.

      Incentives driven by priority

      Current definitions of priority levels have been based both on medical rationale and the attempt to protect the system from being “gamed.” When the requirements for inotropic therapy for Status IB and pulmonary artery catheters for Status IA were adopted in the USA, it was with optimism that they would be used only when absolutely necessary to prevent imminent death, because continuous inotropic infusions and indwelling pulmonary artery catheters are inconvenient and costly and have been associated with serious complications. Although individual cases trigger heated controversy in regional committees, it is generally agreed that these therapies are being overused in patients awaiting transplantation.
      If high priorities defined by therapies are the only route to access donor hearts, we face conflicted incentives as advocates for our patients. This is serious enough with incentives to inflate the description of severity of illness, but even more serious with incentive to impose interventions with complications, such as indwelling pulmonary artery catheters. One of the major conditions currently cited as justification for Status IA exceptions is vascular complications of indwelling catheters that preclude further catheterization. This complication on the list was virtually never seen before pulmonary artery catheters became an index of priority (although arrhythmia device leads have also added to the vascular complication rate).
      The strength of inverse incentives in care of our waiting patients is indexed to the concern that they will die before a transplant, or will develop unnecessary risk such as from cachexia before they finally enter into transplant. The priority status will more truly reflect patient illness when the listing physicians have reasonable confidence that patients will receive a heart in a timely manner, a confidence eroded by the lengthening waiting times, which in turn reflect the anasarca of the waiting list.

      Broken priority systems

      A well-functioning priority system as just described should be able to ensure that: (1) the high-priority patients do have high risk without transplantation; (2) transplantation will be performed with appropriately short waiting times for the highest priority patients; and (3) a reasonable proportion of patients can undergo transplantation at a lower priority level.

      Diluting the urgency

      The requirement that high-priority patients have appropriately high risk without transplantation is now challenged by their survival despite increasingly long waiting times. In this study, only 11% of urgently listed patients died, although only 42% had undergone transplant by the end of the study. In the USA system, the current high-priority status was originally defined with the expectation that patients would not survive more than a matter of days without transplant. For the high-priority Status IA exception as an example, the life expectancy is defined as <7 days. If this were an accurate reflection of the patients, the death rate on the list of highest priority patients would exceed 90%, as the average wait has doubled from <1 month in 2006 to almost 2 months in 2011. However, the waiting list mortality for patients listed as Status IA in the USA has declined from 92 to 35 per 100 waiting list years between 2006 and 2011.

      OPTN/SRTR 2011 annual report–heart. Richmond, VA: United Network of Organ Sharing; 2012:119-147

      Throughout the USA more than half of Status IA patients have been waiting <6 months. In Region 5 in the USA, 40% of patients waiting as Status IA have been waiting <1 month, compared with only 6% in Region 1 (Figure 2), although the proportions of patients listed as Status IA are comparable. (It should be noted that the amount of time patients spent in other statuses before Status I is not detailed in the current version of the publically available UNOS data.) Whatever the path, “urgency” has been seriously diluted. Is this the fault of how urgency is defined, or how the list has lengthened? When there is little confidence that even the highest status patients will soon receive a heart, the incentive is to list early and list high. The list is becoming the lottery.
      Figure thumbnail gr2
      Figure 2National and regional waiting times for candidates currently listed as Status IA. Center chart: waiting times in the USA. Upper left chart: waiting times in Region 5; lower right chart: waiting times in Region 1.10

      Is there really a lower priority?

      In many regions, there is currently little expectation of transplantation for patients in non-urgent priority. The introduction to the work by Smits et al addresses the situation in Germany, where heart donation has recently declined by 25%, which will soon lead to a doubling of the transplant list and distribution of 90% of all hearts to Status I patients. The problem was posed over 20 years ago in the USA, where the prediction was made based on modeling of listing in the early 1990s (before Status I split into Status IA and Status IB in 1999) that almost all hearts would soon go to patients with the high urgency status.
      • Stevenson L.W.
      • Warner S.L.
      • Steimle A.E.
      • et al.
      The impending crisis awaiting cardiac transplantation. Modeling a solution based on selection.
      In 2012, 95% of the transplants indeed went to patients in Status I (60% of transplants in Status IA and 35% in Status IB). This is the first year that the number of patients listed as Status I exceeded the total number of transplants performed (Figure 1). In fact, although only 20% of patients were listed as Status IA, patients in Status IA were receiving 70% of all transplants in the USA (Figure 3). By 2012, substantial disparity had grown between USA regions in the proportion of patients transplanted as Status IA, from 48% in in the California region (Region 5) to 85% of all transplants going to Status IA patients in the New England region.
      Figure thumbnail gr3
      Figure 3Status IA listing and transplant from 1999 to 2012 showing the proportion of adult patients listed as the highest status (IA) and the proportion of all adult patients undergoing heart transplantation who were Status IA at the time of transplant.

      Waiting list arithmetic

      It is necessary to have a small excess of patients listed over the anticipated number of donor hearts to allow for matching, improvement and death on the list and other causes of mismatch between supply and demand. However, the wide disparity between patients listed and those transplanted has led to an unwieldy waiting list. The highest number of patients listed was in 1995, falling to a nadir in 2005 (Figure 1). This is the last period during which we may study the natural experiment of how the median waiting time decreases as the number of listed patients decreases (Figure 4). Between 1999 and 2004, the median waiting time for Status IA patients declined from 61 to 50 days, for Status IB from 87 to 78 days and for Status II from 503 to 309 days. Unfortunately, the number of listings soon rose again, with an increase in the size of the list carried over each year into the next. This increase is unsustainable with the current donor situation.
      Figure thumbnail gr4
      Figure 4List length and time. The number of adult candidates added during each of three 2-year periods, and the median waiting time in days during the same periods, for candidates aged 50–64 years. For the recent past, the shortest waiting list length and the shortest waiting period were seen in 2004 (http://optn.transplant.hrsa.gov/latestData/step2.asp).10
      No system of priority, current or proposed, can allocate hearts equitably when there is such an excess of people listed compared with those transplanted. This is analogous to the oversold situation on airline flights. A large group of people moving no closer to their destination creates pandemonium whether waiting in the airport or on a transplant list.

      Limitations of current estimates

      The national UNOS data set provides an unparalleled resource both for longitudinal trends and for snapshots of different times and different regions.

      Organ Procurement and Transplantation Network. http://optn.transplant.hrsa.gov/latestData/step2.asp. Accessed May 30, 2013.

      The data presented here for the USA has been culled from publically available data, and these analyses for general estimates do not reflect expertise or review from the dedicated data analysts at UNOS. It is not possible from the national data set available to determine how often status has shifted for a given candidate, nor the subtleties of patients who are Status 7 or delisted. However, the definition of candidates rather than registrations within the data set is intended to minimize double counting. The data presented herein is for general illustration and thought experiments only.

      We can trim the list

      We cannot abdicate our responsibility to limit the number of patients we list. Of the alleged 150,000 patients who could benefit from heart transplantation, only about 3,000 are listed annually. We thus exercise severe restraint on listing every day, just not quite to the correct limit. We can regain control of the arithmetic, just as we balance household expenses to household income and the heart adjusts cardiac output to venous return. It is not clear how we decreased the number of patients newly listed yearly from almost 4,000 in 1995 to 3,000 in 2012, but it was probably not because there were fewer candidates or because they were less sick.
      Details of strategic list reform depend on how much consensus can be achieved and how quickly we aim to restore meaning of listing and priority. Using recent data and trends, we can project the impact of an immediate reduction of 20% in the number of patients listed each year from 3,000 to 2,400. Based on current event rates on the list, this number is enough lower than the number of patients removed from the list during the year to initiate a steady reduction in the carry-over list size. The removal rate is of course primarily due to transplantation, but is also due to patients removed for listed reasons of death, which has been decreasing, or “too sick to transplant,” which has been increasing (Figure 5A). This combined rate over the past 5 years has been approximately 8%.
      OPTN/SRTR. Annual report of the U.S
      Organ Procurement and Transplantation Network and the Scientific Registry of Transplant Recipient: transplant data 1995–2011.
      There is an additional rate of approximately 6% of listed patients removed due to improvement, patient reluctance or other causes.
      OPTN/SRTR. Annual report of the U.S
      Organ Procurement and Transplantation Network and the Scientific Registry of Transplant Recipient: transplant data 1995–2011.
      If the list additions were reduced soon to 2,400, the standing list would be decreased to <1,000 within 5 years (Figure 5B). Once the steady-state waiting list reaches <1,000, then the listing volume could increase slightly. The perennial mission to increase donor awareness and consent remains highly relevant, with any successful increase leading to an increase in the permitted number of annual candidate listings.
      Figure thumbnail gr5
      Figure 5(A) Past and future arithmetic of the waiting list. For most recent years, the number of waiting list additions has been slightly greater than the number subtracted due to transplantation, improvement, death or other reasons. Thus, the “carry-over list” has gradually grown. As there has been a slight decrease in the number of patients withdrawn due to death, there has been a slight increase in the number withdrawn as “too sick to transplant.” If the number of candidates added to the list were to be frozen at 3,000 per year, we will reach a steady state list of about 4,000 by 2020. (B) A progressive decline in the size of the waiting list if the number of listed candidates were reduced by 20% now and maintained at that level. Calculations based on data through 2012 as shown in (A). The projections assume that the proportional rate of death and removal on the list would remain the same, which is probably an overestimate as we approach the steady-state list of 700 by 2020.

      Where to trim?

      Register instead of list? The Status II list is an obvious target for some trimming, as Status II listing in most regions of the USA is tantamount to placebo therapy, except with blood group AB. Recognition of their limited access to donor hearts has already reduced numbers of Status II patients listed for transplantation (Figure 1). Although sober predictions of long waiting times are delivered to patients and families, optimism usually prevails in the message received. Once “waiting for a heart”, patients narrow their horizons and engagement in what may turn out to be a major chapter of their lives. However, referral to heart failure centers should not be delayed for patients with advanced heart failure, as it has long been recognized that function and outcomes on medical therapy benefit from ongoing heart failure management as offered at a transplant center.
      • Fonarow G.C.
      • Stevenson L.W.
      • Walden J.A.
      • et al.
      Impact of a comprehensive heart failure management program on hospital readmission and functional status of patients with advanced heart failure.
      Furthermore, the detailed evaluation necessary to determine eligibility for transplant is often incomplete or misleading in a patient in critical condition. For these reasons, the determination of “acceptability” for transplantation in a non-urgent candidate remains desirable. Perhaps the terminology could be updated to define such patients considered provisionally acceptable without contradictions as “registered for transplant” rather than “listed for transplant.”
      Benefit scores for listing rather than priority. There remains a set of ambulatory patients who have severely impaired function and high risk of poor outcomes, even as they can remain at home. Initial findings from the MedaMACS (Medical Arm of Mechanically Assisted Circulatory Support) pilot study suggests that patients at home on oral therapy with New York Heart Association (NYHA) Class IV symptoms with two or more recent hospitalizations have a mortality rate of >25% by 6 months, clearly with potential benefit from early transplantation or for ventricular assist devices (VADs) (Figure 6).
      • Stewart G.C.
      • Kittleson M.M.
      • Cowger J.
      • et al.
      High event rates in medically managed advanced heart failure patients followed at VAD centers..
      Ongoing studies, such as REVIVE-IT (Randomized Evaluation of VAD Intervention before Inotropic Therapy) and MedaMACS, will determine whether it is in these patients that scores of disease severity may have most utility. Perhaps scoring could be employed to determine listing rather than priority after listing. Those who do not pass the score for severity of disease to be listed could instead be registered for future listing, to preserve their access to close surveillance with optimal management of their advanced disease. Patients already listed would have to re-qualify at intervals of, for instance, 6 months. If they did not qualify while supported on inotropic therapy, it would need to be held to reassess. A strong case, based on the recent study by Kato et al, could be made for tightening the criteria on peak oxygen consumption to <10 ml/kg/min, as this describes not only the risk of mortality, but also a severe limitation in daily functional capacity that should improve dramatically after transplantation.
      • Kato T.S.
      • Collado E.
      • Khawaja T.
      • et al.
      Value of peak exercise oxygen consumption combined with B-type natriuretic peptide levels for optimal timing of cardiac transplantation.
      Furthermore, as emphasized by Rogers, this invokes the validity of intrinsic disease severity, rather than the therapies imposed.
      • Rogers J.G.
      Defining and refining heart failure risk stratification to optimize patient selection for cardiac transplantation.
      Patients who become candidates only after VAD insertion would need to have their own score for listing, but there would be fewer patients who would need VADs solely as bridges if there were fewer people competing for transplants. (To cover the inevitable but uncommon cases such as truly refractory ventricular tachycardia, each center could perhaps include 1 patient outside usual indications for every 10 patients listed according to the accepted benefit score.)
      Figure thumbnail gr6
      Figure 6Kaplan–Meier survival curve for ambulatory outpatients with advanced heart failure, according to the Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) profile. This screening pilot for MedaMACS followed 165 patients on optimal medical therapies without intravenous inotropic therapy at the time of enrollment at 10 VAD/transplant centers. Survival is depicted with censoring at time of transplant or mechanical circulatory support, showing 26% death by 6 months for the 37 patients enrolled with INTERMACS Profile 4 (resting symptoms of heart failure). If listed, these patients would be Status II and unlikely to undergo transplantation. Survival was better for the 53 patients in Profile 5 (housebound but comfortable at rest) and 75 patients in Profile 6 (walking wounded).
      • Stewart G.C.
      • Kittleson M.M.
      • Cowger J.
      • et al.
      High event rates in medically managed advanced heart failure patients followed at VAD centers..
      Anyone who attends weekly transplant meetings is familiar with the evaluation that yields a heavy burden of relative contraindications. Without specifying when that burden becomes unsupportable, the list could be shortened and resources redirected by an infinitesimal shift toward palliative care in patients with multiple non-cardiac limitations that will not be lifted by transplantation.
      A case for trimming by age? The percent of adult patients >65 years of age at the time of transplantation is 17% thus far in 2013, compared with 3.4% in 1990 (Figure 7). Some of us remember when the upper age was limited to 50 years. A modest restriction to age <65 years could bring us close to the 20% reduction needed. Furthermore, it would release almost as many hearts, as a higher proportion of the older patients receive hearts. Some of this reflects the use of alternative recipient lists, but good outcomes with donors labeled as “marginal” would generally support their use for the regular list instead.
      • Marelli D.
      • Laks H.
      • Bresson J.
      • et al.
      Sixteen-year experience with 1,000 heart transplants at UCLA.

      Lima B, Rajagopal K, Petersen RP, et al. Marginal cardiac allografts do not have increased primary graft dysfunction in alternate list transplantation. Circulation 2006;114(suppl):I-27-32

      • Russo M.J.
      • Davies R.R.
      • Hong K.N.
      • et al.
      Matching high-risk recipients with marginal donor hearts is a clinically effective strategy.
      Figure thumbnail gr7
      Figure 7Waiting list candidates added to the list and patients undergoing transplantation in the two age groups: 50 to 64 and ≥65 years. The number of older patients transplanted is closer to the number of older patients listed, and both are increasing. The absolute number of patients transplanted at 50 to 64 years remains higher but is decreasing. Data taken from the UNOS website.10
      Although there has historically been strong opposition in the USA to rationing resource-intensive therapy, rationing is inevitable and is happening now, although its manifestation is irrational as each program endeavors to increase its transplant volume at the expense of others. The age distinction is at least one that can be applied without penalty to disadvantaged populations who currently have a decreased option to relocate to lower waiting list regions. Furthermore, the increasing burden of comorbidity contributes to slightly but consistently worse outcomes post-transplant for older transplant patients.
      • Benden C.
      • Edwards L.B.
      • Kucheryavaya A.Y.
      • et al.
      The registry of the International Society for Heart and Lung Transplantation: fifteenth pediatric lung and heart–lung transplantation report—2012.
      On the other hand, the age disparity in outcomes after mechanical circulatory support has diminished with the use of continuous-flow devices. As 2-year survival exceeds 75% in low-risk recipients, a compelling case has been made to emphasize the use of mechanical devices as lifetime therapy rather than as a bridge to transplantation for older candidates who are even older by the time transplantation occurs.
      • Kirklin J.K.
      • Naftel D.C.
      • Pagani F.D.
      • et al.
      Long-term mechanical circulatory support (destination therapy): on track to compete with heart transplantation?.

      A thought experiment

      The debate over revised scores for priority will rapidly spiral into complexity. Before adding multiple factors, it may be illustrative to consider the simplest example. Working from a list appropriately trimmed to patients with high severity of illness, we could re-invoke the time-honored queue to determine transplant priority based solely on listing time. To be maintained until transplant, listed patients would receive inotropic therapy, intra-aortic balloon counterpulsation, mechanical ventilation, extracorporeal membrane oxygenation (ECMO) or implantable devices as necessary to survive rather than to shift priority. Think how few patients would warrant chronic indwelling pulmonary artery catheters for medical necessity. Knowing the position on the transplant list would guide decisions regarding the need for mechanical intervention, but there would be no priority awarded on the basis of therapies including VADs. One clock measures all time, and it starts at listing whether the patient is with or without a VAD. Consider the simplicity of the queue approach, the reduction of days spent captive in a hospital, the end of the argument about whether VAD patients should cut in line, and the re-alignment of incentives to provide exactly as much support as needed, and no more.
      In conclusion, the Eurotransplant research consortium has shared their valuable experience and perspective on a dilemma that exists in every country offering cardiac transplantation. They have shown the paradox of patients with urgent priority for transplantation who often survive without it. They have emphasized the importance of integrating risk without transplant with the risk after transplant. However, no application of the calculus will solve the waiting list problem until we have answered the simple arithmetic required to trim the list to the proper size. This will be different for every country depending on their listing practices and donor supply. However, a consistent increase in candidate listing without an increase in donor supply is unsustainable for any country. When there is equilibrium between the patients entering and leaving the list, there will be greater tolerance for the uncertainty around any risk score, because there are likely to once again be enough hearts in time for those who need them.

      Disclosure statement

      The author has no conflicts of interest to disclose. The content is the responsibility of the author alone and does not necessarily reflect the views or policies of the Department of Health and Human Services. I thank Jerry Cornish for expert assistance with the manuscript. The data cited in this report from the national UNOS website were supported in part by the Health Resources and Services Administration (Contract 234-2005-37011C).

      References

        • Smits J.M.
        • de Vries E.
        • de Pauw M.
        • et al.
        Is it time for a cardiac allocation score? First results from the Eurotransplant pilot study on a survival benefit–based heart allocation.
        J Heart Lung Transplant. 2013; 32: 873-880
        • Kalogeropoulos A.P.
        • Georgiopoulou V.V.
        • Giamouzis G.
        • et al.
        Utility of the Seattle Heart Failure Model in patients with advanced heart failure.
        J Am Coll Cardiol. 2009; 53: 334-342
        • Aaronson K.D.
        • Schwartz J.S.
        • Chen T.M.
        • et al.
        Development and prospective validation of a clinical index to predict survival in ambulatory patients referred for cardiac transplant evaluation.
        Circulation. 1997; 95: 2660-2667
        • Weiss E.S.
        • Allen J.G.
        • Arnaoutakis G.J.
        • et al.
        Creation of a quantitative recipient risk index for mortality prediction after cardiac transplantation (IMPACT).
        Ann Thorac Surg. 2011; 92: 914-921
      1. Stevenson LW, Warner SL, Hamilton MA, et al. Modeling distribution of donor hearts to maximize early candidate survival. Circulation 1992;86(suppl):II-224-30

        • Henderson R.
        • Jones M.
        • Stare J.
        Accuracy of point predictions in survival analysis.
        Stat Med. 2001; 20: 3083-3096
        • Allen L.A.
        • Stevenson L.W.
        • Grady K.L.
        • et al.
        Decision making in advanced heart failure: a scientific statement from the American Heart Association.
        Circulation. 2012; 125: 1928-1952
      2. OPTN/SRTR 2011 annual report–heart. Richmond, VA: United Network of Organ Sharing; 2012:119-147

        • Stevenson L.W.
        • Warner S.L.
        • Steimle A.E.
        • et al.
        The impending crisis awaiting cardiac transplantation. Modeling a solution based on selection.
        Circulation. 1994; 89: 450-457
      3. Organ Procurement and Transplantation Network. http://optn.transplant.hrsa.gov/latestData/step2.asp. Accessed May 30, 2013.

        • OPTN/SRTR. Annual report of the U.S
        Organ Procurement and Transplantation Network and the Scientific Registry of Transplant Recipient: transplant data 1995–2011.
        Rockville, MD: Department of Health and Human Services, Health Resources and Services Administration, Healthcare Systems Bureau, Division of Transplantation. 2011; : 125-141
        • Fonarow G.C.
        • Stevenson L.W.
        • Walden J.A.
        • et al.
        Impact of a comprehensive heart failure management program on hospital readmission and functional status of patients with advanced heart failure.
        J Am Coll Cardiol. 1997; 30: 725-732
        • Stewart G.C.
        • Kittleson M.M.
        • Cowger J.
        • et al.
        High event rates in medically managed advanced heart failure patients followed at VAD centers..
        J Heart Lung Transplant. 2012; 31: S11-2
        • Kato T.S.
        • Collado E.
        • Khawaja T.
        • et al.
        Value of peak exercise oxygen consumption combined with B-type natriuretic peptide levels for optimal timing of cardiac transplantation.
        Circ Heart Fail. 2013; 6: 6-14
        • Rogers J.G.
        Defining and refining heart failure risk stratification to optimize patient selection for cardiac transplantation.
        Circ Heart Fail. 2013; 6: 2-3
        • Marelli D.
        • Laks H.
        • Bresson J.
        • et al.
        Sixteen-year experience with 1,000 heart transplants at UCLA.
        Clin Transpl. 2000; : 297-310
      4. Lima B, Rajagopal K, Petersen RP, et al. Marginal cardiac allografts do not have increased primary graft dysfunction in alternate list transplantation. Circulation 2006;114(suppl):I-27-32

        • Russo M.J.
        • Davies R.R.
        • Hong K.N.
        • et al.
        Matching high-risk recipients with marginal donor hearts is a clinically effective strategy.
        Ann Thorac Surg. 2009; 87: 1066-1070
        • Benden C.
        • Edwards L.B.
        • Kucheryavaya A.Y.
        • et al.
        The registry of the International Society for Heart and Lung Transplantation: fifteenth pediatric lung and heart–lung transplantation report—2012.
        J Heart Lung Transplant. 2012; 31: 1087-1095
        • Kirklin J.K.
        • Naftel D.C.
        • Pagani F.D.
        • et al.
        Long-term mechanical circulatory support (destination therapy): on track to compete with heart transplantation?.
        J Thorac Cardiovasc Surg. 2012; 144: 584-603

      Linked Article

      • Is it time for a cardiac allocation score? First results from the Eurotransplant pilot study on a survival benefit–based heart allocation
        The Journal of Heart and Lung TransplantationVol. 32Issue 9
        • Preview
          Patients awaiting heart transplantation in Eurotransplant are prioritized by waiting time and medical urgency. To reduce mortality, the introduction of post-transplant survival in an allocation model based on the concept of survival benefit might be more appropriate. The aim of this study was to assess the prognostic accuracy of the Heart Failure Survival Score (HFSS), the Seattle Heart Failure Model (SHFM), the Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) model, and the Index for Mortality Prediction After Cardiac Transplantation (IMPACT) score for predicting mortality.
        • Full-Text
        • PDF