Expected effect of the lung Composite Allocation Score system on US lung transplantation.

Efforts are underway to transition the current lung allocation system to a continuous distribution framework whereby multiple factors are simultaneously combined into a Composite Allocation Score (CAS) to prioritize candidates for lung transplant. The purpose of this study was to compare discrete CAS scenarios with the current concentric circle-based allocation system to assess their potential effects on the US lung transplantation system using the Scientific Registry of Transplant Recipients' thoracic simulated allocation model. Six alternative CAS scenarios were compared over 10 simulation runs using data from individuals on the lung transplant waiting list from January 1, 2018, through December 31, 2019. Outcome measures were transplant rate, count, waitlist deaths, posttransplant deaths within 2 years, donor-to-recipient distance, and percentage of organs predicted to have flown. Across scenarios, waitlist deaths decreased by 36% to 47%, with larger decreases in deaths at lower placement efficiency weight and higher weighting of the waitlist outcomes. When waitlist outcomes were equally weighted to posttransplant outcomes, more transplants occurred in individuals with the highest expected posttransplant survival. All CAS scenarios led to improved overall measures of equity compared with the current Lung Allocation Score system, including reduced waitlist deaths, and resulted in similar posttransplant survival.

Impact of incorporating long-term survival for calculating transplant benefit in the US lung transplant allocation system.

BACKGROUND: The lung allocation score prioritizes candidates for a lung transplant in the United States. As the country adopts the continuous distribution framework for organ allocation, we must reevaluate lung allocation score assumptions to maximize transplant benefit. METHODS: We used Scientific Registry of Transplant Recipients data to study the impact of these changes: (1) updating cohorts; (2) transitioning from 1- to 5-year posttransplant survival; (3) using time-varying effects for non-proportional hazards; and (4) weighting waitlist and posttransplant area under the curve differently. Models were compared using Spearman correlations and C-statistics. The thoracic simulation allocation model characterized transplant rates and proportions of recipient subgroups under the current and new systems. RESULTS: Posttransplant areas under the curve models were estimated with recipients aged ≥12 from January 1, 2014, to December 31, 2018. All models had similar C-statistics and Spearman correlations, indicating similar predictive performance and posttransplant area under the curve rankings. Five-year posttransplant area under the curve across age and diagnosis groups varied more than 1-year groups. Using the thoracic simulation allocation model, 1- and 5-year posttransplant model under the curve models showed similar transplant rates and recipient characteristics under the current system, but under continuous distribution, 5-year posttransplant area under the curve resulted in increased transplant rates with more recipients younger and in diagnosis groups B and C. CONCLUSION: Incorporating equally weighted waitlist and posttransplant models using 5-year posttransplant survival detected the largest variability in survival under the continuous distribution system, which could improve long-term survival in the United States.

Effects of broader geographic distribution of donor lungs on travel mode and estimated costs of organ procurement.

On November 24, 2017, US lung transplant policy replaced donor service area with 250-nautical-mile radius as the first unit of allocation. Understanding this policy's economic impact is important, because the United States is poised to adopt the broadest feasible geographic organ distribution. All lung transplant recipients from January 1, 2015, to December 31, 2018, in the Scientific Registry of Transplant Recipients, were included. Recipients before and after November 24, 2017 were in the donor service area-first and 250-nautical-mile donor service area-free periods, respectively. Travel time was estimated using a Google application; mode was assigned as flying when driving time was longer than 60 min. Travel costs were estimated by mode and distance. Travel distance and time for organ procurement increased under the policy change. The estimated proportion of organs traveling by air increased from 61% to 76%. Estimated average costs increased by $14 051 if travel mode changed to flying, resulting in an average increase of $1264 for all transplants. Travel costs were highest for candidates <18 years and adults with high lung allocation scores. Broader geographic distribution increased estimated organ procurement costs for a small percentage of lung transplants. Further analysis should elucidate the broad economic impact of such policies.

Cost burden of post-transplant lymphoproliferative disease following kidney transplants in Medicare-eligible patients by survival status.

AIMS AND OBJECTIVES: Patients diagnosed with post-transplant lymphoproliferative disease (PTLD) experience high mortality within the first 2 years of diagnosis; however, few data exist on the economic burden of PTLD in these patients. We determined the healthcare resource utilization (HRU) and cost burden of post-kidney transplant PTLD and evaluated how these differ by survival status. MATERIALS AND METHODS: Utilizing data from the United States Renal Data System and the Scientific Registry of Transplant Recipients, we identified 83,818 Medicare-covered kidney transplant recipients between 2007 and 2016, of which 347 had at least one Medicare claim during the first year after diagnosis of PTLD. We tabulated Medicare Part A and Part B and calculated per patient-year (PPY) costs. RESULTS: Patients diagnosed with PTLD in the first year post-transplant had Part A + B costs of $222,336 PPY, in contrast with $83,546 PPY in all kidney transplants. Post-transplant costs in the first year of PTLD diagnosis were similar regardless of the year of diagnosis. Cost burden for PTLD patients who died within 2 years of diagnosis was >3.3 times higher than PTLD patients still alive after 2 years. Of those who died within 2 years, the majority died within 6 months and costs were highest for these patients, with almost 7 times higher costs than PTLD patients who were still alive after 2 years. LIMITATIONS: Medicare costs were the only costs examined in this study and may not be representative of other costs incurred, nor be generalizable to other insured populations. Patients were only Medicare eligible for 3 years after transplant unless aged ≥62 years, therefore any costs after this cut-off were not included. CONCLUSIONS: PTLD represents a considerable HRU and cost burden following kidney transplant, and the burden is most pronounced in patients who die within 6 months.

Impact of Socioeconomic Position on Access to the U.S. Lung Transplant Waiting List in a Matched Cystic Fibrosis Cohort.

Rationale: Referrals for lung transplant and transplant rates in the United States are lower than in Canada for patients with advanced cystic fibrosis (CF) lung disease. Further study of factors limiting access are needed to optimize referral and transplant for this population.Objectives: To determine the effect of socioeconomic position, while accounting for disease severity, on the likelihood of wait-listing for lung transplant in the United States.Methods: A case-control study of 3,110 patients (1,555 wait-listed, 1,555 never wait-listed) in the linked CF Foundation Patient Registry/Scientific Registry of Transplant Recipients was performed with 1:1 matching for age, forced expiratory volume in 1 second, and year. Logistic regression was performed with univariate and multivariate analyses accounting for eight clinical factors (sex, oxygen use, body mass index, hemoptysis, forced vital capacity, methicillin-resistant Staphylococcus aureus, multidrug-resistant Pseudomonas aeruginosa, and i.v. antibiotic days) and six socioeconomic factors (race, marital status, education, health insurance, median zip code income, and distance to transplant program). The CF Health Score and Socioeconomic Barrier Score were created based on summation of variables. Interactions between scores were calculated.Results: We found an inverse relationship between the probability of wait-listing and CF Health Score and Socioeconomic Barrier Score. As the CF Health Score decreased (less healthy), the probability of wait-listing increased by 69.3% from a score of 7 to 2. As the Socioeconomic Barrier Score decreased (fewer barriers), the probability of wait-listing increased by 31.7% from a score of ≥5 to 1). Regardless of illness severity, socioeconomic barriers presented an impediment to wait-listing. Individuals with higher Socioeconomic Barrier Scores accessed transplant about half as often as those with lower scores at the same level of medical severity. Analysis of interactions demonstrated a higher probability of wait-listing for individuals with moderate health severity and fewer social barriers compared with sicker individuals with more socioeconomic barriers.Conclusions: Accrual of socioeconomic barriers limits access to lung transplant irrespective of disease severity, a finding of substantial concern for patients with CF and for transplant providers. Future interventions can focus on this at-risk population early in the disease course.

Posttransplant outcome assessments at listing: Long-term outcomes are more important than short-term outcomes.

Posttransplant outcome assessments are publicly reported for patient and regulatory use. However, the currently reported 1-year posttransplant graft survival assessments are commonly criticized for not identifying clinically meaningful differences between programs, and not providing information about longer-term posttransplant outcomes. We investigated the association of different posttransplant outcome assessments available to patients at the time of listing with subsequent posttransplant graft survival. The posttransplant assessments were from period prevalent, rather than incident, cohorts with more timely 1-, 3-, and 5-year follow-up and 6-, 12-, 18-, 24-, and 30-month cohort windows. The association of these assessments at listing with subsequent posttransplant graft survival included candidates listed between July 12, 2011, and December 15, 2015, who subsequently underwent transplant before December 31, 2018. The assessments with 1-year follow-up had uniformly weaker associations than the assessments with 3- and 5-year follow-up. The assessments with 5-year follow-up had the strongest association in kidney and liver transplantation. For kidney, liver, and lung transplantation, assessment windows of at least 18 months typically had the strongest associations with subsequent graft survival. Posttransplant assessments with 5-year follow-up and 18-30-month cohort windows are better than the current posttransplant assessment with 1-year follow-up, particularly at the time of listing.

Validating thoracic simulated allocation model predictions for impact of broader geographic sharing of donor lungs on transplant waitlist outcomes.

BACKGROUND: The thoracic simulated allocation model (TSAM) is used by the Scientific Registry of Transplant Recipients to predict the relative effect of organ allocation policy changes. A new lung allocation policy changing the first unit of allocation from donation service area to 250 nautical miles took effect on November 24, 2017. We studied TSAM's ability to correctly predict trends caused by changes in allocation policy. METHODS: We compared the population characteristics from the TSAM cohort, 6,386 lung transplant candidates from 2009 to 2011, with the observed cohort of 7,601 candidates from the year before the policy change on November 24, 2017, and the year after. Simulations were run 10 times. Waitlist mortality and transplant rates were calculated and compared with observed mortality and transplant rates in the years before and after the policy change. RESULTS: TSAM correctly predicted no change in overall waitlist mortality or transplant rates with the policy change. Observed waitlist mortality values were higher, as were transplant rates, because of increased organ donation and population change. TSAM predicted increased transplant rates for diagnosis group D (idiopathic pulmonary fibrosis), decreased rates for group A (chronic obstructive pulmonary disease), and increased rates for candidates with lung allocation score ≥50, but these changes did not occur in the waitlist and transplant populations after the policy change. CONCLUSIONS: TSAM correctly predicted the relative trends caused by a change in allocation policy but smaller sub-group predictions were not seen.

Effect of Including Important Clinical Variables on Accuracy of the Lung Allocation Score for Cystic Fibrosis and Chronic Obstructive Pulmonary Disease.

Rationale: Clinical variables associated with shortened survival in patients with advanced-stage cystic fibrosis (CF) are not included in the lung allocation score (LAS).Objectives: To identify variables associated with wait-list and post-transplant mortality for CF lung transplant candidates using a novel database and to analyze the impact of including new CF-specific variables in the LAS system.Methods: A deterministic matching algorithm identified patients from the Scientific Registry of Transplant Recipients and the Cystic Fibrosis Foundation Patient Registry. LAS wait-list and post-transplant survival models were recalculated using CF-specific variables. This multicenter, retrospective, population-based study of all lung transplant wait-list candidates aged 12 years or older from January 1, 2011, to December 31, 2014, included 9,043 patients on the lung transplant waiting list and 6,110 lung transplant recipients between 2011 and 2014, comprising 1,020 and 677 with CF, respectively.Measurements and Main Results: Measured outcomes were changes in LAS and lung allocation rank. For CF candidates, any Burkholderia sp. (hazard ratio [HR], 2.8; 95% confidence interval [CI], 1.2-6.6), 29-42 days hospitalized (HR 2.8; CI 1.3-5.9), massive hemoptysis (HR 2.1; CI 1.1-3.9), and relative drop in FEV1 ≥30% over 12 months (HR 1.7; CI 1.0-2.8) increased wait-list mortality risk; pulmonary exacerbation time 15-28 days (1.8; 1.1-2.9) increased post-transplant mortality risk. A relative drop in FEV1 ≥10% in chronic obstructive pulmonary disease (COPD) candidates was associated with increased wait-list mortality risk (HR 2.6; CI 1.2-5.4). Variability in LAS score and rank increased in patients with CF. Priority for transplant increased for COPD candidates. Access did not change for other diagnosis groups.Conclusions: Adding CF-specific variables improved discrimination among wait-listed CF candidates and benefited COPD candidates.

Association of pretransplant and posttransplant program ratings with candidate mortality after listing.

The Scientific Registry of Transplant Recipients (SRTR) is responsible for understandable reporting of program metrics, including transplant rate, waitlist mortality, and posttransplant outcomes. SRTR developed five-tier systems for each metric to improve accessibility for the public. We investigated the associations of the five-tier assignments at listing with all-cause candidate mortality after listing, for candidates listed July 12, 2011-June 16, 2014. Transplant rate evaluations with one additional tier were associated with lower mortality after listing in kidney (hazard ratio [HR], 0.93 0.950.97 ), liver (HR, 0.87 0.900.92 ), and heart (HR, 0.92 0.961.00 ) transplantation. For lung transplant patients, mortality after listing was highest at programs with above- and below-average transplant rates and lowest at programs with average transplant rates, suggesting that aggressive acceptance behavior may not always provide a survival benefit. Waitlist mortality evaluations with one additional tier were associated with lower mortality after listing in kidney (HR, 0.94 0.960.99 ) transplantation, and posttransplant graft survival evaluations with one additional tier were associated with lower mortality after listing in lung (HR, 0.90 0.940.98 ) transplantation. Transplant rate typically had the strongest association with mortality after listing, but the strength of associations differed by organ.

Comparing Scientific Registry of Transplant Recipients posttransplant program-specific outcome ratings at listing with subsequent recipient outcomes after transplant.

To improve accessibility of program-specific reports to patients, the Scientific Registry of Transplant Recipients released a 5-tier system for categorizing 1-year posttransplant program evaluations. Whether this system predicts subsequent posttransplant outcomes at the time patients are waitlisted has been questioned. We investigated the association of tier at listing and the corresponding continuous score used for tier assignment, which ranges from 0 (poor outcomes) to 1 (good outcomes), with eventual 1-year posttransplant graft survival for candidates listed between July 12, 2011, and June 16, 2014, who underwent transplant before December 31, 2016. One additional tier at listing was associated with better 1-year posttransplant outcomes in liver (hazard ratio [HR], 0.93; 95% confidence interval [CI], 0.89-0.97) and lung transplant (HR, 0.90; 95% CI, 0.84-0.97) but not kidney (HR, 0.96; 95% CI, 0.92-1.01) or heart transplant (HR, 1.02; 95% CI, 0.93-1.10). In liver and lung transplant, longer time between listing and transplant was associated with stronger protective effects for high-tier programs. In kidney, liver, and lung transplant, posttransplant evaluations at listing had nonlinear associations with eventual posttransplant outcomes: relatively flat for 5-tier scores <0.5 and decreasing for scores >0.5. After adjustment for measured recipient and donor risk factors, posttransplant evaluations at listing predicted differences in eventual outcomes in liver and lung transplant, providing useful information to patients.

The relationship between the C-statistic and the accuracy of program-specific evaluations.

The C-statistic of the risk-adjustment model is often used to judge the accuracy of program evaluations. However, the C-statistic depends on the variability in risk for individual transplants and may be inappropriate for determining the accuracy of program evaluations. A simulation study investigated the association of the C-statistic with several metrics of program evaluation accuracy, including categorizing programs into the 5-tier system and identifying programs for regulatory review. The simulation study used data from deceased donor kidney-alone transplants for adult recipients in the program-specific reports released January 2018. A range of C-statistics was generated by changing the variability in risk for individual transplants. The C-statistic had no association with any metric of program evaluation accuracy. Instead, the number of expected events at a program was the most important factor. For example, Spearman's rho, which is the correlation of ranks, was -0.27 and -0.72 between the true program-specific hazard ratios and assigned tiers for programs with, respectively, <3 and >10 expected events. Presence of unadjusted risk factors did not modify the associations, although the accuracy of program evaluations was systematically lower. Therefore, the C-statistic provides no information on the accuracy of program evaluations.

Heart and lung organ offer acceptance practices of transplant programs are associated with waitlist mortality and organ yield.

Variation in heart and lung offer acceptance practices may affect numbers of transplanted organs and create variability in waitlist mortality. To investigate these issues, offer acceptance ratios, or adjusted odds ratios, for heart and lung transplant programs individually and for all programs within donation service areas (DSAs) were estimated using offers from donors recovered July 1, 2016, and June 30, 2017. Logistic regressions estimated the association of DSA-level offer acceptance ratios with donor yield and local placement of organs recovered in the DSA. Competing risk methodology estimated the association of program-level offer acceptance ratios with incidence and rate of waitlist removals due to death or becoming too sick to undergo transplant. Higher DSA-level offer acceptance was associated with higher yield (odds ratios [ORs]: lung, 1.04 1.111.19 ; heart, 1.09 1.211.35 ) and more local placement of transplanted organs (ORs: lung, 1.01 1.121.24 ; heart, 1.47 1.691.93 ). Higher program-level offer acceptance was associated with lower incidence of waitlist removal due to death or becoming too sick to undergo transplant (hazard ratios [HRs]: heart, 0.80 0.860.93 ; lung, 0.67 0.750.83 ), but not with rate of waitlist removal (HRs: heart, 0.91 0.981.06 ; lung, 0.89 0.991.10 ). Heart and lung offer acceptance practices affected numbers of transplanted organs and contributed to program-level variability in the probability of waitlist mortality.

Risk of Second Malignancies in Solid Organ Transplant Recipients Who Develop Keratinocyte Cancers.

Solid organ transplant recipients have increased risk for developing keratinocyte cancers, including cutaneous squamous cell carcinoma (SCC) and basal cell carcinoma (BCC), in part as a result of immunosuppressive medications administered to prevent graft rejection. In the general population, keratinocyte cancers are associated with increased risks of subsequent malignancy, however, the risk in organ transplant populations has not been evaluated. We addressed this question by linking the U.S. Scientific Registry of Transplant Recipients, which includes data on keratinocyte cancer occurrence, with 15 state cancer registries. Risk of developing malignancies after keratinocyte cancer was assessed among 118,440 Caucasian solid organ transplant recipients using multivariate Cox regression models. Cutaneous SCC occurrence (n = 6,169) was associated with 1.44-fold increased risk [95% confidence interval (CI), 1.31-1.59] for developing later malignancies. Risks were particularly elevated for non-cutaneous SCC, including those of the oral cavity/pharynx (HR, 5.60; 95% CI, 4.18-7.50) and lung (HR, 1.66; 95% CI, 1.16-2.31). Cutaneous SCC was also associated with increased risk of human papillomavirus-related cancers, including anal cancer (HR, 2.77; 95% CI, 1.29-5.96) and female genital cancers (HR, 3.43; 95% CI, 1.44-8.19). In contrast, BCC (n = 3,669) was not associated with overall risk of later malignancy (HR, 0.98; 95% CI, 0.87-1.12), including any SCC. Our results suggest that transplant recipients with cutaneous SCC, but not BCC, have an increased risk of developing other SCC. These findings somewhat differ from those for the general population and suggest a shared etiology for cutaneous SCC and other SCC in the setting of immunosuppression. Cutaneous SCC occurrence after transplantation could serve as a marker for elevated malignancy risk. Cancer Res; 77(15); 4196-203. ©2017 AACR.

Current Status of Kidney Transplant Outcomes: Dying to Survive.

Kidney transplantation is associated with improved survival compared with maintenance dialysis. In the United States, post-transplant outcomes have steadily improved over the last several decades, with current 1-year allograft and patient survival rates well over 90%. Although short-term outcomes are similar to those in the international community, long-term outcomes appear to be inferior to those reported by other countries. Differences in recipient case mix, allocation polices, and health care coverage contribute to the long-term outcome disparity. This review presents the current status of kidney transplant outcomes in the United States and compares them with the most recent outcomes from Australia and New Zealand, Europe, and Canada. In addition, early trends after implementation of the new kidney allocation system in the United States and its potential impact on post-transplant outcomes are discussed.

Impact of increased time at the highest urgency category on heart transplant outcomes for candidates with ventricular assist devices.

BACKGROUND: Ventricular assist devices (VADs) have improved survival among end-stage heart disease patients. Since 2002, heart transplant candidates with VADs have been afforded 30 days of elective time at the highest urgency category (Status 1A) under Organ Procurement and Transplantation Network (OPTN) policy. We aimed to determine the effect of increasing elective time at the highest urgency category for heart transplant candidates with VADs. This analysis was requested by OPTN during its evaluation of heart allocation policy. METHODS: We simulated several allocation schemes wherein elective Status 1A time was increased to 45, 60, and 90 days; results were compared with a baseline simulation of 30 days and with the actual observed heart transplant waiting list cohort. RESULTS: The simulations showed that increasing elective Status 1A time for candidates with VADs did not substantially change waiting list mortality overall or for sub-groups of concern, which were candidates with VADs listed at a lower-urgency category (Status 1B), those with with VAD complications, total artificial heart, or intraaortic balloon pump support; or those with extracorporeal membrane oxygenation. Across the different time allowances, the average post-transplant death rate remained stable. It also remained stable for recipients previously listed as Status 1A or 1B categories for VAD and for recipients with VAD complications or an intraaortic balloon pump at transplant, on extracorporeal membrane oxygenation, and those without devices. CONCLUSIONS: Our results suggest that increasing time in the highest urgency category for candidates with VADs would not improve waiting list mortality or post-transplant outcomes for heart transplant candidates overall.

Scientific Registry of Transplant Recipients: collecting, analyzing, and reporting data on transplantation in the United States.

Founded in 1987, the Scientific Registry of Transplant Recipients (SRTR) operates under a contract from the US government administered by the Health Resources and Services Administration (HRSA). SRTR maintains a database of comprehensive information on all solid organ transplantation in the US. The registry supports the ongoing evaluation of the clinical status of solid organ transplantation, including kidney, heart, liver, lung, intestine, pancreas, and multi-organ transplants. Data in the registry are from multiple sources, but most are collected by the Organ Procurement and Transplantation Network (OPTN) from hospitals, organ procurement organizations, and immunology laboratories. The data include information on current and past organ donors, transplant candidates, transplant recipients, transplant outcomes, and outcomes of living donors. SRTR uses these data to create reports and analyses for HRSA, OPTN committees that make organ allocation policy, and the Centers for Medicare & Medicaid Services to carry out quality assurance surveillance activities; SRTR also creates standard analysis files for scientific investigators. In addition, SRTR and OPTN produce an Annual Data Report and provide information upon request for the general public. Thus, SRTR supports the transplant community with information services and statistical analyses to improve patient access to and outcomes of organ transplant.