OPTN/SRTR 2022 Annual Data Report: Lung.

For the first time since the COVID-19 pandemic, the annual number of lung transplants performed in the United States increased. The year 2022, encompassed in this report, marks the last full calendar year where the Lung Allocation Score was used for ranking transplant candidates based on their estimated transplant benefit and donor lung allocation in the United States. In March 2023, a major change in transplant allocation policy occurred with the implementation of the Composite Allocation Score. Transplant rates have increased over the past decade, although there is variability among age, diagnosis, racial and ethnic, and blood groups. Over half of candidates received a lung transplant within 3 months of placement on the waiting list, with nearly 75% of candidates accessing transplant by 1 year. Pretransplant mortality rates remained stable, with approximately 13% of lung transplant candidates dying or being removed from the waiting list within a year of listing. Posttransplant survival remained stable; however, variability exists by age, diagnosis, and racial and ethnic groups.

Incorporating Effects of Time Accrued on the Waiting List into Lung Transplantation Survival Models.

Rationale: U.S. lung transplant mortality risk models do not account for patients' disease progression as time accrues between mandated clinical parameter updates. Objectives: To investigate the effects of accrued waitlist (WL) time on mortality in lung transplant candidates and recipients beyond those expressed by worsening clinical status and to present a new framework for conceptualizing mortality risk in end-stage lung disease. Methods: Using Scientific Registry of Transplant Recipients data (2015-2020, N = 12,616), we modeled transitions among multiple clinical states over time: WL, posttransplant, and death. Using cause-specific and ordinary Cox regression to estimate trajectories of composite 1-year mortality risk as a function of time from waitlisting to transplantation, we quantified the predictive accuracy of these estimates. We compared multistate model-derived candidate rankings against composite allocation score (CAS) rankings. Measurements and Main Results: There were 11.5% of candidates whose predicted 1-year mortality risk increased by >10% by day 30 on the WL. The multistate model ascribed lower numerical rankings (i.e., higher priority) than CAS for those who died while on the WL (multistate mean; median [interquartile range] ranking at death, 227; 154 [57-334]; CAS median [interquartile range] ranking at death, 329; 162 [11-668]). Patients with interstitial lung disease were more likely to have increasing risk trajectories as a function of time accrued on the WL compared with other lung diagnoses. Conclusions: Incorporating the effects of time accrued on the WL for lung transplant candidates and recipients in donor lung allocation systems may improve the survival of patients with end-stage lung diseases on the individual and population levels.

Miscalibration of lung allocation models leads to inaccurate waitlist mortality predictions.

The importance of waitlist (WL) mortality risk estimates will increase with the adoption of the US Composite Allocation Score (CAS) system. Calibration is rarely assessed in clinical prediction models, yet it is a key factor in determining access to lung transplant. We assessed the calibration of the WL-lung allocation score (LAS)/CAS models and developed alternative models to minimize miscalibration. Scientific Registry of Transplant Recipients data from 2015 to 2020 were used to assess the calibration of the WL model and for subgroups (age, sex, diagnosis, and race/ethnicity). Three recalibrated models were developed and compared: (1) simple recalibration model (SRM), (2) weighted recalibration model 1 (WRM1), and (3) weighted recalibration model 2 (WRM2). The current WL-LAS/CAS model underestimated risk for 78% of individuals (predicted mortality risk, <42%) and overpredicted risk for 22% of individuals (predicted mortality risk, ≥42%), with divergent results among subgroups. Error measures improved in SRM, WRM1, and WRM2. SRM generally preserved candidate rankings, whereas WRM1 and WRM2 led to changes in ranking by age and diagnosis. Differential miscalibration occurred in the WL-LAS/CAS model, which improved with recalibration measures. Further inquiry is needed to develop mortality models in which risk predictions approximate observed data to ensure accurate ranking and timely access to transplant. IMPACT: With changes to the lung transplant allocation system planned in 2023, evaluation of the accuracy and precision of survival models used to rank candidates for lung transplant is important. The waitlist model underpredicts risk for 78% of US transplant candidates with an unequal distribution of miscalibration across subgroups leading to inaccurate ranking of transplant candidates. This work will serve to inform future efforts to improve modeling efforts in the US lung transplant allocation system.

OPTN/SRTR 2021 Annual Data Report: Lung.

The number of lung transplants has continued to decline since 2020, a period that coincides with the onset of the COVID-19 pandemic. Lung allocation policy continues to undergo considerable change in preparation for adoption of the Composite Allocation Score system in 2023, beginning with multiple adaptations to the calculation of the Lung Allocation Score that occurred in 2021. The number of candidates added to the waiting list increased after a decline in 2020, while waitlist mortality has increased slightly with a decreased number of transplants. Time to transplant continues to improve, with 38.0% of candidates waiting fewer than 90 days for a transplant. Posttransplant survival remains stable, with 85.3% of transplant recipients surviving to 1 year; 67%, to 3 years; and 54.3%, to 5 years.

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 COVID-19 pandemic on the size of US transplant waiting lists.

BACKGROUND: More patients are waitlisted for solid organs than transplants are performed each year. The COVID-19 pandemic immediately increased waitlist mortality and decreased transplants and listings. METHODS: To calculate the number of candidate listings after the pandemic began and short-term changes that may affect waiting time, we conducted a Scientific Registry of Transplant Recipients surveillance study from January 1, 2012 to February 28, 2021. RESULTS: The number of candidates on the liver waitlist continued a steady decline that began before the pandemic. Numbers of candidates on the kidney, heart, and lung waitlists decreased dramatically. More than 3000 fewer candidates were awaiting a kidney transplant on March 7, 2021, than on March 8, 2020. Listings and removals decreased for each solid organ beginning in March 2020. The number of heart and lung listings returned to equal or above that of removals. Listings for kidney transplant, which is often less urgent than heart and lung transplant, remain below numbers of removals. Removals due to transplant decreased for all organs, while removals due to death increased for only kidneys. CONCLUSIONS: We found no evidence of the predicted surge in listings for solid organ transplant with a plateau or control of the pandemic.

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.

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.

Risk of lung cancer in lung transplant recipients in the United States.

Lung transplant recipients have an increased risk of lung cancer that is poorly understood. Prior studies are largely descriptive and single-center, and have not examined risk factors or outcomes in this population. This registry-linkage study utilized matched transplant and cancer registry data from 17 US states/regions during 1987-2012. We used standardized incidence ratios (SIRs) to compare incidence with the general population, Poisson models to identify lung cancer risk factors, and Cox models to compare survival after diagnosis. Lung cancer risk was increased among lung recipients (SIR 4.8, 95% confidence interval [CI] 4.1-5.5). Those with single lung transplant had 13-fold (95% CI 11-15) increased risk in the native lung. Native lung cancer risk factors included age, prior smoking, time since transplant, and idiopathic pulmonary fibrosis. Compared with cases in the general population, lung cancers in recipients were more frequently localized stage (P = .02) and treated surgically (P = .05). However, recipients had higher all-cause (adjusted hazard ratio 1.90, 95% CI 1.52-2.37) and cancer-specific mortality (adjusted hazard ratio 1.67, 95% CI 1.28-2.18). In conclusion, lung cancer risk is increased after lung transplant, especially in the native lung of single lung recipients. Traditional risk factors are associated with lung cancer in these patients. Lung cancer survival is worse among lung recipients despite earlier diagnosis.

Variables of importance in the Scientific Registry of Transplant Recipients database predictive of heart transplant waitlist mortality.

The prelisting variables essential for creating an accurate heart transplant allocation score based on survival are unknown. To identify these we studied mortality of adults on the active heart transplant waiting list in the Scientific Registry of Transplant Recipients database from January 1, 2004 to August 31, 2015. There were 33 069 candidates awaiting heart transplantation: 7681 UNOS Status 1A, 13 027 Status 1B, and 12 361 Status 2. During a median waitlist follow-up of 4.3 months, 5514 candidates died. Variables of importance for waitlist mortality were identified by machine learning using Random Survival Forests. Strong correlates predicting survival were estimated glomerular filtration rate (eGFR), serum albumin, extracorporeal membrane oxygenation, ventricular assist device, mechanical ventilation, peak oxygen capacity, hemodynamics, inotrope support, and type of heart disease with less predictive variables including antiarrhythmic agents, history of stroke, vascular disease, prior malignancy, and prior tobacco use. Complex interactions were identified such as an additive risk in mortality based on renal function and serum albumin, and sex-differences in mortality when eGFR >40 mL/min/1.73 m. Most predictive variables for waitlist mortality are in the current tiered allocation system except for eGFR and serum albumin which have an additive risk and complex interactions.

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.

The Association Between Lung Recipient Travel Distance and Posttransplant Survival.

INTRODUCTION: Recipient travel distance may be an unrecognized burden in lung transplantation. DESIGN: Retrospective single-center cohort study of all adult (≥18 years) first-time lung-only transplants from January 1, 2010, until February 28, 2017. Recipient distance to transplant center was calculated using the linear distance from the recipient's home zip code to the Cleveland Clinic in Cleveland, Ohio. RESULTS: 569 recipients met inclusion criteria. Posttransplant graft survival was 85%, 88%, 91%, and 91% at 1 year and 49%, 52%, 57%, and 56% at 5 years posttransplant for recipient travel distances of ≤50, >50 to ≤250, >250 to ≤500, and >500 miles, respectively ( P = .10). DISCUSSION: We found no significant relationship between recipient travel distance and posttransplant graft survival. In carefully selected recipients, travel distance is not a significant barrier to successful posttransplant outcomes which may be important for patient decision-making and donor allocation policy. These data should be validated in a national cohort.

Management of the Potential Organ Donor in the ICU: Society of Critical Care Medicine/American College of Chest Physicians/Association of Organ Procurement Organizations Consensus Statement.

This document was developed through the collaborative efforts of the Society of Critical Care Medicine, the American College of Chest Physicians, and the Association of Organ Procurement Organizations. Under the auspices of these societies, a multidisciplinary, multi-institutional task force was convened, incorporating expertise in critical care medicine, organ donor management, and transplantation. Members of the task force were divided into 13 subcommittees, each focused on one of the following general or organ-specific areas: death determination using neurologic criteria, donation after circulatory death determination, authorization process, general contraindications to donation, hemodynamic management, endocrine dysfunction and hormone replacement therapy, pediatric donor management, cardiac donation, lung donation, liver donation, kidney donation, small bowel donation, and pancreas donation. Subcommittees were charged with generating a series of management-related questions related to their topic. For each question, subcommittees provided a summary of relevant literature and specific recommendations. The specific recommendations were approved by all members of the task force and then assembled into a complete document. Because the available literature was overwhelmingly comprised of observational studies and case series, representing low-quality evidence, a decision was made that the document would assume the form of a consensus statement rather than a formally graded guideline. The goal of this document is to provide critical care practitioners with essential information and practical recommendations related to management of the potential organ donor, based on the available literature and expert consensus.

An official American Thoracic Society/International Society for Heart and Lung Transplantation/Society of Critical Care Medicine/Association of Organ and Procurement Organizations/United Network of Organ Sharing Statement: ethical and policy considerations in organ donation after circulatory determination of death.

RATIONALE: Donation after circulatory determination of death (DCDD) has the potential to increase the number of organs available for transplantation. Because consent and management of potential donors must occur before death, DCDD raises unique ethical and policy issues. OBJECTIVES: To develop an ethics and health policy statement on adult and pediatric DCDD relevant to critical care and transplantation stakeholders. METHODS: A multidisciplinary panel of stakeholders was convened to develop an ethics and health policy statement. The panel consisted of representatives from the American Thoracic Society, Society of Critical Care Medicine, International Society for Heart and Lung Transplantation, Association of Organ Procurement Organizations, and the United Network of Organ Sharing. The panel reviewed the literature, discussed important ethics and health policy considerations, and developed a guiding framework for decision making by stakeholders. RESULTS: A framework to guide ethics and health policy statement was established, which addressed the consent process, pre- and post mortem interventions, the determination of death, provisions of end-of-life care, and pediatric DCDD. CONCLUSIONS: The information presented in this Statement is based on the current evidence, experience, and clinical rationale. New clinical research and the development and dissemination of new technologies will eventually necessitate an update of this Statement.

Costs of End-of-Life Hospitalizations in the United States for People With Pulmonary Diseases.

BACKGROUND: Lung transplantation is a lifesaving intervention for people with advanced lung disease, but it is costly and resource-intensive. To investigate the cost-effectiveness of lung transplantation as a treatment option in pulmonary disease, we must understand costs attributable to end-of-life hospitalizations for end-stage lung disease. RESEARCH QUESTION: What are the costs associated with end-of-life hospitalizations for people with pulmonary disease, and how have these trends changed over time? STUDY DESIGN AND METHODS: Adults aged 18 to 74 years with hospitalization data in the Cost and Utilization Project National Inpatient Sample data from 2009 to 2019 with a pulmonary disease admission were included in this analysis. Those with a history of lung transplantation were excluded. International Classification of Diseases codes were used to identify pulmonary disease admissions, complications, and procedures and interventions. Total charges were calculated for hospitalizations and stratified by patient status at time of discharge. Trends in charges over time were assessed by demographic and hospital factors. RESULTS: One hundred nine thousand nine hundred twenty-four (4.1%) hospital admissions for pulmonary disease resulted in in-hospital mortality. Those with obstructive lung disease accounted for 94.1% of hospitalizations and 88.1% cases of in-hospital mortality. Estimated costs for end-of-life hospitalizations were $29,981 on average with wide variation in cost by diagnosis and procedure utilization. Inpatient costs were highest for younger people who received more procedures. Among the most expensive admissions, mechanical ventilation accounted for the greatest proportion of interventions. Significant increases in the use of mechanical ventilation, extracorporeal membrane oxygenation, and dialysis occurred over the time period. The rate of hospital transfers increased with a proportionately greater increase across admissions resulting in in-hospital mortality. INTERPRETATION: Costs accrued during end-of-life hospitalizations vary across people but represent a significant health care cost that can be averted for selected people who undergo lung transplantation. These costs should be considered in studies of cost-effectiveness in lung transplantation.

A modular simulation framework for organ allocation.

BACKGROUND: We describe and validate a new simulation framework addressing important limitations of the Simulated Allocation Models (SAMs) long used to project population effects of transplant policy changes. METHODS: We developed the Computational Open-source Model for Evaluating Transplantation (COMET), an agent-based model simulating interactions of individual donors and candidates over time to project population outcomes. COMET functionality is organized into interacting modules. Donors and candidates are synthetically generated using data-driven probability models which are adaptable to account for ongoing or hypothetical donor/candidate population trends and evolving disease management. To validate the first implementation of COMET, COMET-Lung, we attempted to reproduce lung transplant outcomes for U.S. adults from 2018-2019 and in the 6 months following adoption of the Composite Allocation Score (CAS) for lung transplant. RESULTS: Simulated (median [Interquartile Range, IQR]) vs observed outcomes for 2018-2019 were: 0.162 [0.157, 0.167] vs 0.170 waitlist deaths per waitlist year; 1.25 [1.23, 1.28] vs 1.26 transplants per waitlist year; 0.115 [0.112, 0.118] vs 0.113 post-transplant deaths per patient year; 202 [102, 377] vs 165 nautical miles travel distance. The model accurately predicted the observed precipitous decrease in transplants received by type O lung candidates in the six months following CAS implementation. CONCLUSIONS: COMET-Lung closely reproduced most observed outcomes. The use of synthetic populations in the COMET framework paves the way for examining possible transplant policy and clinical practice changes in populations reflecting realistic future states. Its flexible, modular nature can accelerate development of features to address specific research or policy questions across multiple organs.

Creating synthetic populations in transplantation: A Bayesian approach enabling simulation without registry re-sampling.

Computer simulation has played a pivotal role in analyzing alternative organ allocation strategies in transplantation. The current approach to producing cohorts of organ donors and candidates for individual-level simulation requires directly re-sampling retrospective data from a transplant registry. This historical data may reflect outmoded policies and practices as well as systemic inequities in candidate listing, limiting contemporary applicability of simulation results. We describe the development of an alternative approach for generating synthetic donors and candidates using hierarchical Bayesian network probability models. We developed two Bayesian networks to model dependencies among 10 donor and 36 candidate characteristics relevant to waitlist survival, donor-candidate matching, and post-transplant survival. We estimated parameters for each model using Scientific Registry of Transplant Recipients (SRTR) data. For 100 donor and 100 candidate synthetic populations generated, proportions for each categorical donor or candidate attribute, respectively, fell within one percentage point of observed values; the interquartile ranges (IQRs) of each continuous variable contained the corresponding SRTR observed median. Comparisons of synthetic to observed stratified distributions demonstrated the ability of the method to capture complex joint variability among multiple characteristics. We also demonstrated how changing two upstream population parameters can exert cascading effects on multiple relevant clinical variables in a synthetic population. Generating synthetic donor and candidate populations in transplant simulation may help overcome critical limitations related to the re-sampling of historical data, allowing developers and decision makers to customize the parameters of these populations to reflect realistic or hypothetical future states.

Strengthening protections for human subjects: proposed restrictions on the publication of transplant research involving prisoners.

Publication is one of the primary rewards in the academic research community and is the first step in the dissemination of a new discovery that could lead to recognition and opportunity. Because of this, the publication of research can serve as a tacit endorsement of the methodology behind the science. This becomes a problem when vulnerable populations that are incapable of giving legitimate informed consent, such as prisoners, are used in research. The problem is especially critical in the field of transplant research, in which unverified consent can enable research that exploits the vulnerabilities of prisoners, especially those awaiting execution. Because the doctrine of informed consent is central to the protection of vulnerable populations, we have performed a historical analysis of the standards of informed consent in codes of international human subject protections to form the foundation for our limit and ban recommendations: (1) limit the publication of transplant research involving prisoners in general and (2) ban the publication of transplant research involving executed prisoners in particular.