Multiple listing in kidney transplantation

Evaluating US Multiple Listing Practices in Lung Transplantation: Unveiling Hidden Disparities

BACKGROUND

Multiple listing (ML) is a practice used to increase the potential for transplant but is controversial due to concerns that it disproportionately benefits patients with greater access to health care resources.

RESEARCH QUESTION

Is there disparity in ML practices based on social deprivation in the United States and does ML lead to quicker time to transplant?

STUDY DESIGN AND METHODS

A retrospective cohort study of adult (≥ 18 years of age) lung transplant candidates listed for transplant (2005-2018) was conducted. Exclusion criteria included heart only or heart and lung transplant and patients relisted during the observation period. Data were obtained from the United Network for Organ Sharing Standard Transplant Analysis and Research File. The first exposure of interest was the Social Deprivation Index with a primary outcome of ML status, to assess disparities between ML and single listing (SL) participants. The second exposure of interest was ML status with a primary outcome of time to transplant, to assess whether implementation of ML leads to quicker time to transplant.

RESULTS

A total of 35,890 patients were included in the final analysis, of whom 791 (2.2%) were ML and 35,099 (97.8%) were SL. ML participants had lower median level of social deprivation (5 units, more often female: 60.0% vs 42.3%) and lower median lung allocation score (35.3 vs 37.3). ML patients were more likely to be transplanted than SL patients (OR, 1.42; 95% CI, 1.17-1.73), but there was a significantly quicker time to transplant only for those whom ML was early (within 6 months of initial listing) (subdistribution hazard ratio, 1.17; 95% CI, 1.04-1.32).

INTERPRETATION

ML is an uncommon practice with disparities existing between ML and SL patients based on several factors including social deprivation. ML patients are more likely to be transplanted, but only if they have ML status early in their transplant candidacy. With changing allocation guidelines, it is yet to be seen how ML will change with the implementation of continuous distribution.

Listing at non-local transplant centers is associated with increased access to deceased donor kidney transplantation

The ability of kidney transplant candidates to travel outside of their usual place of care varies by sociodemographic factors, potentially exacerbating disparities in access. We used Transplant Referral Regions (TRRs) to overcome previous methodological barriers of using geographic distance to assess the characteristics and outcomes of patients listed for kidney transplant at centers in neighboring TRR or beyond neighboring TRRs. Among listed kidney transplant candidates, 20.9% traveled to a neighbor and 5.6% beyond a neighbor. A higher proportion of travelers were White, had some college education, and lived in ZIP codes with lower poverty. Travel to a neighbor was associated with a 7% increase in likelihood of deceased donor transplant (cHR: 1.07, 95% CI: 1.05, 1.09) and traveling beyond a neighbor with a 19% increase (cHR: 1.19, 95% CI: 1.15, 1.24). Travelers had similar rates of living donor transplant and waitlist mortality as patients who did not travel; those who traveled beyond a neighbor had slightly lower posttransplant mortality (HR: 0.91, 95% CI: 0.83, 0.99). In conclusion, the ability to travel outside of the recipient's assigned TRR increases access to transplantation and improves long-term survival.

Disparities in Lung Transplantation

Since the initial report of long-term survival after lung transplantation (LT) in 1983, there has been remarkable progress in the field and LT is now the gold-standard therapy for patients with end-stage lung disease. It confers a significant survival advantage and improves the quality of life in patients who often have few other treatment options. However, LT remains a complex undertaking and establishing and maintaining an LT program is resource intensive with multiple potential barriers. In this article, we focus on disparities in LT and the potential solutions to improving access to LT.

Design of a patient-centered decision support tool when selecting an organ transplant center

Patients in the US in need of a life-saving organ transplant must complete a long process of medical decisions, and a first step is to identify a transplant center to complete an evaluation. This study describes a patient-centered process of testing and refinement of a new website (www.transplantcentersearch.org) that was developed to provide data to patients who are seeking a transplant center. Mixed methods, including online surveys and structured usability testing, were conducted to inform changes in an iterative process. Survey data from 684 participants indicated the effects of different icon styles on user decisions. Qualitative feedback from 38 usability testing participants informed improvements to the website interface. The mixed methods approach was feasible and well suited to the need to address multiple development steps of a patient-facing tool. The combined methods allowed for large survey sample sizes and also allowed interaction with a functioning website and in-depth qualitative discussions. The approach is applicable for a broad range of target user groups who are faced with challenging decisions and a need for information tailored to individual users. The survey and usability testing concluded with a functioning website that is positively received by users and meets the objective to support patient decisions when seeking an organ transplant.

Association between Longer Travel Distance for Transplant Care and Access to Kidney Transplantation and Graft Survival in the United States

BACKGROUND

Transplant candidates may gain an advantage by traveling to receive care at a transplant center that may have more favorable characteristics than their local center. Factors associated with longer travel distance for transplant care and whether the excess travel distance (ETD) is associated with access to transplantation or with graft failure are unknown.

METHODS

This study of adults in the United States wait-listed for kidney transplantation in 1995-2015 used ETD, defined as distance a patient traveled beyond the nearest transplant center for initial waiting list registration. We used linear regression to examine patient and center characteristics associated with ETD and Fine-Gray models to examine the association between ETD (modeled as a spline) and time to deceased or living donor transplantation or graft failure.

RESULTS

Of 373,365 patients, 11% had an ETD≥50 miles. Traveling excess distance was more likely among patients who were of non-Black race or those whose nearest transplant center had lower annual living donor transplant volume. At an ETD of 50 miles, we observed a lower likelihood of deceased donor transplantation (subhazard ratio [SHR], 0.85; 95% confidence interval [95% CI], 0.84 to 0.87) but higher likelihood of living donor transplantation (SHR, 1.14; 95% CI, 1.12 to 1.16) compared with those who received care at their nearest center. ETD was weakly associated with higher risk of graft failure.

CONCLUSIONS

Patients who travel excess distances for transplant care have better access to living donor but not deceased donor transplantation and slightly higher risk of graft failure. Traveling excess distances is not clearly associated with better outcomes, especially if living donors are unavailable.

The Advantage of Multiple Listing Continues in the Kidney Allocation System Era

BACKGROUND

Transplant candidates can be listed at multiple transplant centers to increase the probability of receiving an organ. We evaluated the association between multilisting (ML) status and access to a deceased donor kidney transplant (DDKT) to determine if ML provides a long-term advantage regarding wait-list mortality and recipient outcomes.

MATERIALS AND METHODS

Candidates between January 2010 and October 2017 were identified as either singly or multiply listed using Organ Procurement and Transplantation Network data and cohorts before and after implementation of the Kidney Allocation System (KAS). Cross-sectional logistic regression was used to assess relationships between candidate factors and ML prevalence (5.4%).

RESULTS

Factors associated with ML pre-KAS included having blood type B (reference, type O; odds ratio [OR], 1.20; P < .001), having private insurance (OR, 1.5; P < .001), wait time (OR, 1.28; P < .001), and increasing calculated panel-reactive antibody (cPRA) (reference, cPRA 0-100; OR for cPRA 80-98, 2.83; OR for cPRA 99, 3.47; OR for cPRA 100, 5.18; P < .001). Transplant rates were double for multilisted vs singly listed recipients (adjusted hazard ratio [aHR], 2.16; P < .001). Extra-donor service area ML candidates received transplants 2.5 years quicker than single-listing (SL) candidates, conferring a 42% wait-list advantage. Recipient death (aHR, 0.94; P = .122) and graft failure (aHR, 0.91; P = .006) rates were also lower for ML recipients.

CONCLUSIONS

In the KAS era, ML continues to increase the likelihood of receiving a DDKT and lower the incidence of wait-list mortality, and it confers a survival advantages over SL.

A Simulation-Based Optimization Model to Study the Impact of Multiple-Region Listing and Information Sharing on Kidney Transplant Outcomes

More than 8000 patients on the waiting list for kidney transplantation die or become ineligible to receive transplants due to health deterioration. At the same time, more than 4000 recovered kidneys from deceased donors are discarded each year in the United States. This paper develops a simulation-based optimization model that considers several crucial factors for a kidney transplantation to improve kidney utilization. Unlike most proposed models, the presented optimization model incorporates details of the offering process, the deterioration of patient health and kidney quality over time, the correlation between patients’ health and acceptance decisions, and the probability of kidney acceptance. We estimate model parameters using data obtained from the United Network of Organ Sharing (UNOS) and the Scientific Registry of Transplant Recipients (SRTR). Using these parameters, we illustrate the power of the simulation-based optimization model using two related applications. The former explores the effects of encouraging patients to pursue multiple-region waitlisting on post-transplant outcomes. Here, a simulation-based optimization model lets the patient select the best regions to be waitlisted in, given their demand-to-supply ratios. The second application focuses on a system-level aspect of transplantation, namely the contribution of information sharing on improving kidney discard rates and social welfare. We investigate the effects of using modern information technology to accelerate finding a matching patient to an available donor organ on waitlist mortality, kidney discard, and transplant rates. We show that modern information technology support currently developed by the United Network for Organ Sharing (UNOS) is essential and can significantly improve kidney utilization.

An evaluation of the current status of kidney transplant in terms of the type of receipt among Iranian patients

Introduction

With the increasing prevalence and incidence of chronic renal failure leading to advanced kidney disease (ESRD), the use of renal transplant therapy is increasing globally. The aim of this study was to determine the status of kidney transplant in patients during a period of 4–5 years.

Materials and methods

In this retrospective, analytical study, patients undergoing renal transplant at one of the hospitals in northern Iran were studied. The data was collected using a checklist assessing the required information, including the age, sex, place of residence, source of the kidney for transplant (living related, living non-related, deceased), kidney receiving method (donated, purchased), and wait time for a kidney transplant.

Results

A total of 228 patients were included in the study, of which 73.7% were male and 26.3% were female. The average wait time for kidney transplant was 386.22 days. The mean age of patients was 32.7 ± 10.7 years. In addition, living non-related (66.2%) and deceased (14%) were the most and least frequent sources of kidney transplant, respectively. Moreover, 51.8% of all transplanted kidneys were purchased.

Conclusion

Over the past 5 years, there has been a decrease in wait time for kidney transplant in Rasht, Iran. Factors, such as being female, lower age, and living in urban areas, are related to a shorter wait time for kidney transplant. The most common types of kidney transplant are from non-related donors and purchased.

Comparing Pretransplant and Posttransplant Outcomes When Choosing a Transplant Center: Focus Groups and a Randomized Survey

BACKGROUND

In response to calls for an increased focus on pretransplant outcomes and other patient-centered metrics in public reports of center outcomes, a mixed methods study evaluated how the content and presentation style of new information influences decision-making. The mixed methods design utilized qualitative and quantitative phases where the strengths of one method help address limitations of the other, and multiple methods facilitate comparing results.

METHODS

First, a series of organ-specific focus groups of kidney, liver, heart, and lung patients helped to develop and refine potential displays of center outcomes and understand patient perceptions. A subsequent randomized survey included adult internet users who viewed a single, randomly-selected variation of 6 potential online information displays. Multinomial regression evaluated the effects of graphical presentations of information on decision-making.

RESULTS

One hundred twenty-seven candidates and recipients joined 23 focus groups. Survey responses were analyzed from 975 adults. Qualitative feedback identified patient perceptions of uncertainty in outcome metrics, in particular pretransplant metrics, and suggested a need for clear guidance to interpret the most important metric for organ-specific patient mortality. In the randomized survey, only respondents who viewed a note indicating that transplant rate had the largest impact on survival chose the hospital with the best transplant rate over the hospital with the best posttransplant outcomes (marginal relative risk and 95% confidence interval, 1.161.501.95).

CONCLUSIONS

The presentation of public reports influenced decision-making behavior. The combination of qualitative and quantitative research helped to guide and enhance understanding of the impacts of proposed changes in reported metrics.

How patients choose kidney transplant centers: A qualitative study of patient experiences

Little is known about how patients make the critical decision of choosing a transplant center. In the United States, acceptance criteria, waiting times, and mortality vary significantly by geography and center. We sought to understand patients' experiences and perspectives when selecting transplant centers. We included 82 kidney transplant patients in 20 semi-structured interviews, nine focus groups with local candidates, and three focus groups with national recipients. Sites included two local transplant centers in Minneapolis, Minnesota, and national recipients from across the United States. Transcripts were analyzed by two researchers using a thematic analysis. Several themes emerged related to priorities and barriers when choosing a center. Patients were often unfamiliar with options, even with multiple local centers. Patients described being referred to a specific center by a trusted provider. Patients prioritized perceived reputation, comfort, and convenience. Insurance coverage was both a source of information and a barrier to options. Patients underestimated differences across centers and the effects on being waitlisted and receiving a transplant. Barriers in decision making included an overwhelming scope of information and difficulty locating information relevant to patients with unique medical needs. Informed decisions could be improved by the dissemination of understandable information better tailored to individual patient needs.

Multiple listing in lung transplant candidates: A cohort study

Lung transplant candidates can be waitlisted at more than one transplant center, a practice known as multiple listing. The factors associated with multiple listing and whether multiple listing modifies waitlist mortality or likelihood of lung transplant is unknown. US lung transplant waitlist candidates were identified as either single or multiple listed using data from the Scientific Registry of Transplant Recipients. Characteristics of single and multiple listed candidates were compared and multivariable logistic regression was used to estimate associations with multiple listing. Multiple listed candidates were matched to single listed candidates using a combination of exact and propensity score matching methods. Cox proportional hazard models were used to estimate the relationship of multiple listing on waitlist mortality and receiving a transplant. Multiple listing occurred in 2.3% of lung transplant waitlist candidates. Younger age, female gender, white race, short stature, high antibody sensitization, college or postcollege education, lower lung allocation score, and a cystic fibrosis diagnosis were independently associated with multiple listing. Multiple listing was associated with an increased likelihood of lung transplant (adjusted hazard ratio [aHR] 2.74, 95% CI 2.37 to 3.16) but was not associated with waitlist mortality (aHR 0.99, 95% CI 0.68 to 1.44).

Outcomes of Multiple Listing for Adult Heart Transplantation in the United States: Analysis of OPTN Data From 2000 to 2013

OBJECTIVES

This study sought to assess the association of multiple listing with waitlist outcomes and post-heart transplant (HT) survival.

BACKGROUND

HT candidates in the United States may register at multiple centers. Not all candidates have the resources and mobility needed for multiple listing; thus this policy may advantage wealthier and less sick patients.

METHODS

We identified 33,928 adult candidates for a first single-organ HT between January 1, 2000 and December 31, 2013 in the Organ Procurement and Transplantation Network database.

RESULTS

We identified 679 multiple-listed (ML) candidates (2.0%) who were younger (median age, 53 years [interquartile range (IQR): 43 to 60 years] vs. 55 years [IQR: 45 to 61 years]; p < 0.0001), more often white (76.4% vs. 70.7%; p = 0.0010) and privately insured (65.5% vs. 56.3%; p < 0.0001), and lived in zip codes with higher median incomes (US$90,153 [IQR: US$25,471 to US$253,831] vs. US$68,986 [IQR: US$19,471 to US$219,702]; p = 0.0015). Likelihood of ML increased with the primary center's median waiting time. ML candidates had lower initial priority (39.0% 1A or 1B vs. 55.1%; p < 0.0001) and predicted 90-day waitlist mortality (2.9% [IQR: 2.3% to 4.7%] vs. 3.6% [IQR: 2.3% to 6.0]%; p < 0.0001), but were frequently upgraded at secondary centers (58.2% 1A/1B; p < 0.0001 vs. ML primary listing). ML candidates had a higher HT rate (74.4% vs. 70.2%; p = 0.0196) and lower waitlist mortality (8.1% vs. 12.2%; p = 0.0011). Compared with a propensity-matched cohort, the relative ML HT rate was 3.02 (95% confidence interval: 2.59 to 3.52; p < 0.0001). There were no post-HT survival differences.

CONCLUSIONS

Multiple listing is a rational response to organ shortage but may advantage patients with the means to participate rather than the most medically needy. The multiple-listing policy should be overturned.

Bioethics of organ transplantation

As the ability to transplant organs and tissues has grown, the demand for these procedures has increased as well--to the point at which it far exceeds the available supply creating the core ethical challenge for transplantation--rationing. The gap between supply and demand, although large, is worse than it appears to be. There are two key steps to gaining access to a transplant. First, one must gain access to a transplant center. Then, those waiting need to be selected for a transplant. Many potential recipients do not get admitted to a program. They are deemed too old, not of the right nationality, not appropriate for transplant as a result of severe mental impairment, criminal history, drug abuse, or simply because they do not have access to a competent primary care physician who can refer them to a transplant program. There are also financial obstacles to access to transplant waiting lists in the United States and other nations. In many poor nations, those needing transplants simply die because there is no capacity or a very limited capacity to perform transplants. Although the demand for organs now exceeds the supply, resulting in rationing, the size of waiting lists would quickly expand were there to suddenly be an equally large expansion in the number of organs available for transplantation. Still, even with the reality of unavoidable rationing, saving more lives by increasing organ supply is a moral good. Current public policies for obtaining organs from cadavers are not adequate in that they do not produce the number of organs that public polls of persons in the United States indicate people are willing to donate.

Multiple listing for pediatric heart transplantation in the U.S.A.: analysis of OPTN registry data from 1995 through 2009

Multiple listing is associated with shorter waitlist durations and increased likelihood of transplantation for renal candidates. Little is known about multiple listing in pediatric heart transplantation. We examined the prevalence and outcomes of multiple listing using OPTN data from 1995 through 2009. Characteristics and waitlist outcomes of propensity-score-matched single- and multiple-listed patients were compared. Multiple listing occurred in 23 of 6290 listings (0.4%). Median days between listings was 35 (0-1015) and median duration of multiple listings was 32 days (3-363). Among multiple-listed patients, there were trends toward less ECMO use (0% vs. 11%, p = 0.1) and more frequent requirement for a prospective cross-match (17% vs. 8%, p = 0.08). Multiple-listed patients more commonly had private insurance (78% vs. 56%; p = 0.03). Urgency status at listing was similar between groups (1/1A: 61% vs. 64%, 1B/2: 39 vs. 36%; p = 0.45) as were weight, age, diagnosis, ventilator/inotrope use, and median income (each p ≥ 0.17). There was a trend toward increased incidence of heart transplantation for multiple-listed patients at three, six, and 24 months (50%, 65%, 80%) vs. single-listed patients (40%, 54%, 64%; p = 0.11). Multiple listing for pediatric heart transplantation in the USA occurs infrequently and is more common in patients with private insurance.