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.

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.

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.

Clinical diagnosis of metabolic syndrome: predicting new-onset diabetes, coronary heart disease, and allograft failure late after kidney transplant.

Metabolic syndrome is associated with coronary heart disease (CHD) and new-onset diabetes after kidney transplant (NODAT). Using data collected from transplant centers worldwide for the Patient Outcomes in Renal Transplantation study, we examined associations of metabolic syndrome (n = 2253 excluding recipients with diabetes pretransplant), CHD (n = 2253), and NODAT (n = 1840 further excluding recipients with diabetes in the first year post-transplant), with the primary outcome of allograft failure. We assessed risk factors associated with secondary outcomes of metabolic syndrome, NODAT, and CHD after adjusting for type of baseline immunosuppression and transplant center effects. Metabolic syndrome prevalence was 39.8% at 12-24 months post-transplant and 35.4% at 36-48 months. Metabolic syndrome was independently associated with NODAT (hazard ratio 3.46, 95% confidence interval 2.40-4.98, P < 0.0001), CHD (2.03, 1.16-3.52, P = 0.013), and allograft failure (1.36, 1.03-1.79, P = 0.028). Allograft failure occurred in 218 patients (14.6%). After adjustment for metabolic syndrome, NODAT (1.63, 1.18-2.24, P = 0.003) and CHD (5.48, 3.27-9.20, P < 0.0001) remained strongly associated with increased risk of allograft failure. Metabolic syndrome, NODAT, and CHD are risk factors for allograft failure. NODAT and CHD are risk factors for allograft failure, independent of metabolic syndrome.

Cardiovascular disease medications after renal transplantation: results from the Patient Outcomes in Renal Transplantation study.

BACKGROUND: Cardiovascular disease (CVD) is the most common cause of death after kidney transplantation. Nevertheless, the use of potentially protective CVD medications has not been examined in a large international cohort of kidney transplant patients. METHODS: Using the Patient Outcomes in Renal Transplantation database, we retrospectively examined CVD medication use in 14,236 kidney transplant patients from 10 centers worldwide at 4 and 12 months posttransplant. RESULTS: Use of CVD medications posttransplant increased between 1990 to 1994 and 2000 to 2006, with a 12-fold increase in the use of statins (odds ratio [OR] 12.28, 95% confidence interval [CI] 10.18-14.80). Use of ß-blockers also increased (OR 3.74, 95% CI 3.20-4.38), as did use of angiotensin converting enzyme inhibitors or angiotensin II receptor blockers (OR 3.68, 95% CI 3.07-4.40) and antiplatelet agents (OR 1.93, 95% CI 1.66-2.24). Use of most CVD medications was not higher in patients with diabetes than in patients without diabetes, despite a higher risk of CVD among patients with diabetes. Although use of several CVD medications was higher in patients with previous CVD events than in patients with no previous CVD, less than 75% of patients with previous CVD were using a statin or antiplatelet agent. CONCLUSION: Although use of CVD medications after kidney transplant has increased in recent years, use of potentially cardioprotective medications may be suboptimal given the high CVD risk in kidney transplant patients.

Blood transfusions in kidney transplant candidates are common and associated with adverse outcomes.

Surprisingly, there are no data regarding transfusion frequency, factors associated with transfusion administration in patients on the kidney transplant waiting list, or transfusion impact on graft and recipient outcomes. We used United States Renal Data System data to identify 43,025 patients added to the waiting list in 1999-2004 and followed through 2006 to assess the relative risk of post-listing transfusions. In 69,991 patients who underwent transplants during the same time period, we assessed the association between pre-transplant transfusions and level of panel-reactive antibody (PRA) at the time of transplant, and associations between PRA and patient outcomes. The three-yr cumulative incidence of transfusions was 26% for patients added to the waiting list in 1999, rising to 30% in 2004. Post-listing transfusions were associated with a 28% decreased likelihood of undergoing transplant, and a more than fourfold increased risk of death. There was a graded association between percent PRA at the time of transplant and adjusted risk of death-censored graft failure, death with function, and the combined event of graft failure and death. These data demonstrate that transfusions remain common and confirm the adverse association between transfusions and PRA, and high PRA and inferior graft and patient outcomes.

The relationship between kidney function and long-term graft survival after kidney transplant.

BACKGROUND: Whether chronic kidney disease (CKD) staging provides a useful framework for predicting outcomes after kidney transplant is unclear. STUDY DESIGN: Retrospective cohort study. SETTING & PARTICIPANTS: We used data from the Patient Outcomes in Renal Transplantation (PORT) Study, including 13,671 transplants from 12 centers during 10 years of follow-up. PREDICTOR: Estimated glomerular filtration rate (eGFR; in milliliters per minute per 1.73 m(2)) at 12 months posttransplant. OUTCOMES: All-cause graft failure (a composite end point consisting of return to dialysis therapy, pre-emptive retransplant, or death with function), death-censored graft failure, and death with a functioning graft. MEASUREMENTS: The relationship between 12-month eGFR and subsequent graft outcomes through 10 years posttransplant was assessed using Cox proportional hazards analyses. RESULTS: Stage 3 included 63% of patients and was subdivided into stages 3a (eGFR, 45-59 mL/min/1.73 m(2); 34%) and 3b (eGFR, 30-44 mL/min/1.73 m(2); 29%). Compared with stage 2 (eGFR, 60-89 mL/min/1.73 m(2); 24%), adjusted Cox proportional HRs for graft failure were 1.12 (95% CI, 1.01-1.24; P = 0.04) for stage 3a, 1.50 (95% CI, 1.35-1.66; P < 0.001) for stage 3b, 2.86 (95% CI, 2.53-3.22; P < 0.001) for stage 4 (eGFR, 15-29 mL/min/1.73 m(2); 9%), and 13.2 (95% CI, 10.7-16.4; P < 0.001) for stage 5 (eGFR <15 mL/min/1.73 m(2); 1%). For stage 1 (eGFR ≥ 90 mL/min/1.73 m(2); 3%), risk of graft failure was increased (1.41 [95% CI, 1.13-1.75]; P < 0.001), likely due to serum creatinine associations independent of kidney function. Similar associations were seen between CKD stages and mortality. LIMITATIONS: Retrospective study; lack of gold-standard measurements of true GFR; lack of measures of comorbidity, inflammation, muscle mass, proteinuria, and other noncreatinine markers of eGFR. CONCLUSIONS: CKD stages validated in the general population provide a useful framework for predicting outcomes after kidney transplant.

A simple tool to predict outcomes after kidney transplant.

BACKGROUND: Surprisingly few tools have been developed to predict outcomes after kidney transplant. STUDY DESIGN: Retrospective observational cohort study. SETTING & PARTICIPANTS: Adult patients from US Renal Data System (USRDS) data who underwent deceased donor kidney transplant in 2000-2006. PREDICTOR: Full and abbreviated prediction tools for graft loss using candidate predictor variables available in the USRDS registry, including data from the Organ Procurement and Transplantation Network and the Centers for Medicare & Medicaid Services End-Stage Renal Disease Program. OUTCOMES: Graft loss within 5 years, defined as return to maintenance dialysis therapy, preemptive retransplant, or death with a functioning graft. MEASUREMENTS: We used Cox proportional hazards analyses to develop separate tools for assessment (1) pretransplant, (2) at 7 days posttransplant, and (3) at 1 year posttransplant to predict subsequent risk of graft loss within 5 years of transplant. We used measures of discrimination and explained variation to determine the number of variables needed to predict outcomes at each assessment time in the full and abbreviated equations, creating simple user-friendly prediction tools. RESULTS: Although we could identify 32, 29, and 18 variables that predicted graft loss assessed pretransplant and at 7 days and 1 year posttransplant ("full" models), 98% of the discriminatory ability and >80% of the variability explained by the full models could be achieved using only 11, 8, and 6 variables, respectively. LIMITATIONS: Comorbidity data were from the Centers for Medicare & Medicaid Medical Evidence Report, which may significantly underreport comorbid conditions; C statistic values may indicate only modest ability to discriminate risk for an individual patient. CONCLUSIONS: This method produced risk-prediction tools that can be used easily by patients and clinicians to aid in understanding the absolute and relative risk of graft loss within 5 years of transplant.

Eosinophil and T cell markers predict functional decline in COPD patients.

BACKGROUND: The major marker utilized to monitor COPD patients is forced expiratory volume in one second (FEV1). However, a single measurement of FEV1 cannot reliably predict subsequent decline. Recent studies indicate that T lymphocytes and eosinophils are important determinants of disease stability in COPD. We therefore measured cytokine levels in the lung lavage fluid and plasma of COPD patients in order to determine if the levels of T cell or eosinophil related cytokines were predictive of the future course of the disease. METHODS: Baseline lung lavage and plasma samples were collected from COPD subjects with moderately severe airway obstruction and emphysematous changes on chest CT. The study participants were former smokers who had not had a disease exacerbation within the past six months or used steroids within the past two months. Those subjects who demonstrated stable disease over the following six months (DeltaFEV1 % predicted = 4.7 +/- 7.2; N = 34) were retrospectively compared with study participants who experienced a rapid decline in lung function (DeltaFEV1 % predicted = -16.0 +/- 6.0; N = 16) during the same time period and with normal controls (N = 11). Plasma and lung lavage cytokines were measured from clinical samples using the Luminex multiplex kit which enabled the simultaneous measurement of several T cell and eosinophil related cytokines. RESULTS AND DISCUSSION: Stable COPD participants had significantly higher plasma IL-2 levels compared to participants with rapidly progressive COPD (p = 0.04). In contrast, plasma eotaxin-1 levels were significantly lower in stable COPD subjects compared to normal controls (p < 0.03). In addition, lung lavage eotaxin-1 levels were significantly higher in rapidly progressive COPD participants compared to both normal controls (p < 0.02) and stable COPD participants (p < 0.05). CONCLUSION: These findings indicate that IL-2 and eotaxin-1 levels may be important markers of disease stability in advanced emphysema patients. Prospective studies will need to confirm whether measuring IL-2 or eotaxin-1 can identify patients at risk for rapid disease progression.

Who is caring for kidney transplant patients? Variation by region, transplant center, and patient characteristics.

BACKGROUND/AIMS: Despite implications for long-term care, little is known about outpatient care for kidney transplant patients. METHODS: In this retrospective observational cohort study, outpatient claims were examined for 42,078 Medicare kidney transplant patients using United States Renal Data System data to ascertain location and timing of outpatient visits and type of physician seen. Logistic regression with generalized estimating equations was used to determine the odds and clinical correlates of visits in 4 post-transplant time periods. RESULTS: In months 1-3, 88% of patients visited their transplant centers, but this declined to 69% in months 25-36. In the adjusted analysis, Native Americans (odds ratio 0.56, 95% confidence interval 0.48-0.65) and Hispanics (OR 0.86, 95% CI 0.80-0.92) were less likely than whites to visit their transplant centers. Centers performing 18-34 (OR 1.44, 95% CI 1.30-1.59) and 35-61 transplants per year (OR 1.30, 95% CI 1.18-1.43) were more likely to see patients than centers performing <18 or >61. Almost 80% of patients saw nephrologists in months 1-3 after transplant. African-Americans (OR 0.85, 95% CI 0.80-0.90), Asians (OR 0.87, 95% CI 0.77-0.97), and Native Americans (OR 0.63, 95% CI 0.53-0.75) were less likely than whites to see nephrologists, as were Hispanics (OR 0.78, 95% CI 0.72-0.84) compared with non-Hispanics. CONCLUSION: Frequency of visits to transplant centers varied by center and region; most visits were to nephrologists. Patients from minority groups were less likely to visit transplant centers and nephrologists, with possibly significant public health implications.

Depressive disorder in renal transplantation: an analysis of Medicare claims.

BACKGROUND: Little is known about depression after kidney transplantation. STUDY DESIGN: Retrospective observational study. SETTING & PARTICIPANTS: US Renal Data System data; first kidney-only recipients who underwent transplantation in 1995 to 2003 with Medicare as primary payer (n = 47,899). PREDICTOR: Demographic and clinical characteristics of recipients (age, sex, race, ethnicity, primary cause of kidney disease, pretransplantation time on dialysis therapy, body mass index, initial immunosuppressive medications, and use of induction antibodies) and donors (age, sex, race, and living or deceased), transplantation year, and number of HLA mismatches. OUTCOMES & MEASUREMENTS: Depression incidence identified in Medicare claims and associations with clinical outcomes during the first 3 years posttransplantation. RESULTS: Depression was identified in 3,360 transplant recipients in the 3 years posttransplantation. Cumulative incidences were 5.05%, 7.29%, and 9.10% at 1, 2, and 3 years posttransplantation. In Cox proportional hazards analysis, white race, female sex, diabetes as primary cause of kidney disease, more than 3 years on dialysis therapy before transplantation, marked obesity (body mass index >or= 35 kg/m(2)), rapamycin use, antilymphocyte globulin or antithymocyte globulin for antibody induction therapy, donor age of 65 years or older, more recent transplantation, and presence of 6 HLA mismatches were associated with more depression, as identified in claims. Controlling for other known risk factors, time-dependent Cox proportional hazards analysis showed that depression was associated with increased graft failure (hazard ratio, 2.10; 95% confidence interval, 1.94 to 2.27; P < 0.001), return to dialysis therapy (hazard ratio, 1.97; 95% confidence interval, 1.76 to 2.19; P < 0.001), and death with a functioning graft (hazard ratio, 2.24; 95% confidence interval, 2.00 to 2.50; P < 0.001). LIMITATIONS: Depression identified through Medicare claims, limiting case ascertainment; limited number of recipient- or donor-related factors explored for potential associations; and limited depression treatment and pretransplantation depression information. CONCLUSIONS: Depression is associated with several identifiable factors and a 2-fold greater risk of graft failure and death with a functioning graft.

Menthol cigarettes and health risks in Lung Health Study data.

Whether menthol cigarettes confer a higher risk of death than plain cigarettes is not known. The Lung Health Study (LHS) enrolled 5,887 adult smokers in a clinical trial of smoking cessation and ipratropium in the prevention of chronic obstructive pulmonary disease. LHS participants have been subjected to surveillance for mortality from all causes for 14 years. We examined these data for differences between self-reported smokers of menthol cigarettes versus plain cigarettes. Using proportional hazards regression methods, we found no differences in hazard ratios for coronary heart disease, cardiovascular disease, lung cancer, or death from any cause. Contrary to expectations about nicotine dependence, we found that users of menthol cigarettes had smoked fewer pack-years at baseline. We found no difference in success at smoking cessation with or without menthol. We conclude that our data contain no evidence that mentholation of cigarettes increases the hazards of smoking.

Feasibility of retinoids for the treatment of emphysema study.

BACKGROUND: Retinoids promote alveolar septation in the developing lung and stimulate alveolar repair in some animal models of emphysema. METHODS: One hundred forty-eight subjects with moderate-to-severe COPD and a primary component of emphysema, defined by diffusing capacity of the lung for carbon monoxide (Dlco) [37.1 +/- 12.0% of predicted] and CT density mask (38.5 +/- 12.8% of voxels <- 910 Hounsfield units) [mean +/- SD] were enrolled into a randomized, double-blind, feasibility study at five university hospitals. Participants received all-trans retinoic acid (ATRA) at either a low dose (LD) [1 mg/kg/d] or high dose (HD) [2 mg/kg/d], 13-cis retinoic acid (13-cRA) [1 mg/kg/d], or placebo for 6 months followed by a 3-month crossover period. RESULTS: No treatment was associated with an overall improvement in pulmonary function, CT density mask score, or health-related quality of life (QOL) at the end of 6 months. However, time-dependent changes in Dlco (initial decrease with delayed recovery) and St. George Respiratory Questionnaire (delayed improvement) were observed in the HD-ATRA cohort and correlated with plasma drug levels. In addition, 5 of 25 participants in the HD-ATRA group had delayed improvements in their CT scores that also related to ATRA levels. Retinoid-related side effects were common but generally mild. CONCLUSIONS: No definitive clinical benefits related to the administration of retinoids were observed in this feasibility study. However, time- and dose-dependent changes in Dlco, CT density mask score, and health-related QOL were observed in subjects treated with ATRA, suggesting the possibility of exposure-related biological activity that warrants further investigation.

The effects of a smoking cessation intervention on 14.5-year mortality: a randomized clinical trial.

BACKGROUND: Randomized clinical trials have not yet demonstrated the mortality benefit of smoking cessation. OBJECTIVE: To assess the long-term effect on mortality of a randomly applied smoking cessation program. DESIGN: The Lung Health Study was a randomized clinical trial of smoking cessation. Special intervention participants received the smoking intervention program and were compared with usual care participants. Vital status was followed up to 14.5 years. SETTING: 10 clinical centers in the United States and Canada. PATIENTS: 5887 middle-aged volunteers with asymptomatic airway obstruction. MEASUREMENTS: All-cause mortality and mortality due to cardiovascular disease, lung cancer, and other respiratory disease. INTERVENTION: The intervention was a 10-week smoking cessation program that included a strong physician message and 12 group sessions using behavior modification and nicotine gum, plus either ipratropium or a placebo inhaler. RESULTS: At 5 years, 21.7% of special intervention participants had stopped smoking since study entry compared with 5.4% of usual care participants. After up to 14.5 years of follow-up, 731 patients died: 33% of lung cancer, 22% of cardiovascular disease, 7.8% of respiratory disease other than cancer, and 2.3% of unknown causes. All-cause mortality was significantly lower in the special intervention group than in the usual care group (8.83 per 1000 person-years vs. 10.38 per 1000 person-years; P = 0.03). The hazard ratio for mortality in the usual care group compared with the special intervention group was 1.18 (95% CI, 1.02 to 1.37). Differences in death rates for both lung cancer and cardiovascular disease were greater when death rates were analyzed by smoking habit. LIMITATIONS: Results apply only to individuals with airway obstruction. CONCLUSION: Smoking cessation intervention programs can have a substantial effect on subsequent mortality, even when successful in a minority of participants.