Faculty Bibliography

IMPORTANCE/UNASSIGNED:Identifying the mechanisms of structural racism, such as racial and ethnic segregation, is a crucial first step in addressing the persistent disparities in access to live donor kidney transplantation (LDKT). OBJECTIVE/UNASSIGNED:To assess whether segregation at the candidate's residential neighborhood and transplant center neighborhood is associated with access to LDKT. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:In this cohort study spanning January 1995 to December 2021, participants included non-Hispanic Black or White adult candidates for first-time LDKT reported in the US national transplant registry. The median (IQR) follow-up time for each participant was 1.9 (0.6-3.0) years. MAIN OUTCOME AND MEASURES/UNASSIGNED:Segregation, measured using the Theil H method to calculate segregation tertiles in zip code tabulation areas based on the American Community Survey 5-year estimates, reflects the heterogeneity in neighborhood racial and ethnic composition. To quantify the likelihood of LDKT by neighborhood segregation, cause-specific hazard models were adjusted for individual-level and neighborhood-level factors and included an interaction between segregation tertiles and race. RESULTS/UNASSIGNED:Among 162 587 candidates for kidney transplant, the mean (SD) age was 51.6 (13.2) years, 65 141 (40.1%) were female, 80 023 (49.2%) were Black, and 82 564 (50.8%) were White. Among Black candidates, living in a high-segregation neighborhood was associated with 10% (adjusted hazard ratio [AHR], 0.90 [95% CI, 0.84-0.97]) lower access to LDKT relative to residence in low-segregation neighborhoods; no such association was observed among White candidates (P for interaction = .01). Both Black candidates (AHR, 0.94 [95% CI, 0.89-1.00]) and White candidates (AHR, 0.92 [95% CI, 0.88-0.97]) listed at transplant centers in high-segregation neighborhoods had lower access to LDKT relative to their counterparts listed at centers in low-segregation neighborhoods (P for interaction = .64). Within high-segregation transplant center neighborhoods, candidates listed at predominantly minority neighborhoods had 17% lower access to LDKT relative to candidates listed at predominantly White neighborhoods (AHR, 0.83 [95% CI, 0.75-0.92]). Black candidates residing in or listed at transplant centers in predominantly minority neighborhoods had significantly lower likelihood of LDKT relative to White candidates residing in or listed at transplant centers located in predominantly White neighborhoods (65% and 64%, respectively). CONCLUSIONS/UNASSIGNED:Segregated residential and transplant center neighborhoods likely serve as a mechanism of structural racism, contributing to persistent racial disparities in access to LDKT. To promote equitable access, studies should assess targeted interventions (eg, community outreach clinics) to improve support for potential candidates and donors and ultimately mitigate the effects of segregation.

BACKGROUND:Evidence suggests that older patients are less frequently placed on the waiting list for kidney transplantation (KT) than their younger counterparts. The trends and magnitude of this age disparity in access to first KT and repeat KT (re-KT) remain unclear. METHODS:Using the US Renal Data System, we identified 2 496 743 adult transplant-naive dialysis patients and 110 338 adult recipients with graft failure between 1995 and 2018. We characterized the secular trends of age disparities and used Cox proportional hazard models to compare the chances of listing and receiving first KT versus re-KT by age (18-64 y versus ≥65 y). RESULTS:Older transplant-naive dialysis patients were less likely to be listed (adjusted hazard ratio [aHR] = 0.18; 95% confidence interval [CI], 0.17-0.18) and receive first KT (aHR = 0.88; 95% CI, 0.87-0.89) compared with their younger counterparts. Additionally, older patients with graft failure had a lower chance of being listed (aHR = 0.40; 95% CI, 0.38-0.41) and receiving re-KT (aHR = 0.76; 95% CI, 0.72-0.81). The magnitude of the age disparity in being listed for first KT was greater than that for re-KT ( Pinteraction  < 0.001), and there were no differences in the age disparities in receiving first KT or re-KT ( Pinteraction  = 0.13). Between 1995 and 2018, the age disparity in listing for first KT reduced significantly ( P  < 0.001), but the age disparities in re-KT remained the same ( P  = 0.16). CONCLUSIONS:Age disparities exist in access to both first KT and re-KT; however, some of this disparity is attenuated among older adults with graft failure. As the proportion of older patients with graft failure rises, a better understanding of factors that preclude their candidacy and identification of appropriate older patients are needed.

BACKGROUND:Older adults with frailty and kidney failure face higher waitlist mortality and are more likely to be listed as inactive on the kidney transplant (KT) wait list. Photovoice is a qualitative participatory research method where participants use photographs to represent their environment, needs and experiences. It offers unique insight into the lived environment and experience of patients and may offer direction in how to improve functional independence, symptom burden, and kidney transplant outcomes in adults with frailty. METHODS:This photovoice study was embedded within a larger intervention adaptation project. Participants with pre-frailty or frailty awaiting a KT or recently post-transplant took photos with Polaroid cameras and wrote short descriptions for 11 prompts. Each participant completed a semi-structured interview wherein their photos were discussed. The team coded and discussed photos and interviews to determine overarching themes and implications. Focus groups were used to triangulate visual data findings. RESULTS:Sixteen participants completed both the photovoice and interview. Participants were a mean age of 60.5 years, 31.2% female, 43.4% self-identifying as Black, and 69% were frail. Outcomes were categorized into seven themes: functional space, home safety, medication management, adaptive coping, life changing nature of dialysis, support and communication. Visual data clarified and sometimes changed the interpretations of the text alone. Especially within the themes of home safety and functional space, safety hazards not previously recognized in the literature, like dialysis fluid storage, were identified. CONCLUSIONS:Photovoice contextualizes the living conditions and experiences of adults with frailty on the kidney transplant journey and could be a useful tool in geriatric nephrology and transplant. Addressing issues of home storage, organization, and accessibility should be explored as potential intervention targets. Incorporating participant values and goals into care decisions and interventional design should be further explored.

Kidney transplantation from blood type A2/A2B donors to type B recipients (A2→B) has increased dramatically under the current Kidney Allocation System (KAS). Among living donor transplant recipients, A2-incompatible transplants are associated with an increased risk of all-cause and death-censored graft failure. In light of this, we used SRTR data from 12/2014-6/2022 to evaluate the association between A2→B listing and time to deceased donor kidney transplantation (DDKT) and post-DDKT outcomes for A2→B recipients. Among 53,409 type B waitlist registrants, only 12.6% were listed as eligible to accept A2→B offers ("A2-eligible"). 1-/3-/5-year DDKT rates were 32.1%/61.4%/72.1% among A2-eligible candidates and 14.1%/29.9%/44.1% among A2-ineligible candidates, with the former experiencing a 133% higher rate of DDKT (Cox weighted HR = _2.192.33_2.47; p<0.001). The 7-year adjusted mortality was comparable between A2→B and B-ABOc (type B/O donors to B recipients) recipients (wHR _0.780.94_1.13, p=0.5). Moreover, there was no difference between A2→B vs. B-ABOc DDKT recipients with regards to death-censored graft failure (wHR _0.771.00_1.29, p>0.9) or all-cause graft loss (wHR _0.820.96_1.12, p=0.6). Following its broader adoption since the implementation of KAS, A2→B DDKT appears to be a safe and effective transplant modality for eligible candidates. As such, A2→B listing for eligible type B candidates should be expanded.

BACKGROUND:Cytomegalovirus (CMV)-seronegative lung transplant recipients (LTRs) with seropositive donors (CMV D+/R-) have the highest mortality of all CMV serostatuses. Due to immunosenescence and other factors, we hypothesized CMV D+/R- status might disproportionately impact older LTRs. Thus, we investigated whether recipient age modified the relationship between donor CMV status and mortality among CMV-seronegative LTRs. METHODS:Adult, CMV-seronegative first-time lung-only recipients were identified through the Scientific Registry of Transplant Recipients between May 2005 and December 2019. We used adjusted multivariable Cox regression to assess the relationship of donor CMV status and death. Interaction between recipient age and donor CMV was assessed via likelihood ratio testing of nested Cox models and by the relative excess risk due to interaction (RERI) and attributable proportion (AP) of joint effects. RESULTS:We identified 11,136 CMV-seronegative LTRs. The median age was 59 years; 65.2% were male, with leading transplant indication of idiopathic pulmonary fibrosis (35.6%); and 60.8% were CMV D+/R-. In multivariable modeling, CMV D+/R- status was associated with 27% increased hazard of death (adjusted hazard ratio: 1.27, 95% confidence interval: 1.21-1.34) compared to CMV D-/R-. Recipient age ≥60 years significantly modified the relationship between donor CMV-seropositive status and mortality on the additive scale, including RERI 0.24 and AP 11.4% (p = 0.001), that is, the interaction increased hazard of death by 0.24 and explained 11.4% of mortality in older CMV D+ recipients. CONCLUSIONS:Among CMV-seronegative LTRs, donor CMV-seropositive status confers higher risk of posttransplant mortality, which is amplified in older recipients. Future studies should define optimal strategies for CMV prevention and management in older D+/R- LTRs.

Body mass index is often used to determine kidney transplant (KT) candidacy. However, this measure of body composition (BC) has several limitations, including the inability to accurately capture dry weight. Objective computed tomography (CT)-based measures may improve pre-KT risk stratification and capture physiological aging more accurately. We quantified the association between CT-based BC measurements and waitlist mortality in a retrospective study of 828 KT candidates (2010-2022) with clinically obtained CT scans using adjusted competing risk regression. In total, 42.5% of candidates had myopenia, 11.4% had myopenic obesity (MO), 68.8% had myosteatosis, 24.8% had sarcopenia (probable = 11.2%, confirmed = 10.5%, and severe = 3.1%), and 8.6% had sarcopenic obesity. Myopenia, MO, and sarcopenic obesity were not associated with mortality. Patients with myosteatosis (adjusted subhazard ratio [aSHR] = 1.62, 95% confidence interval [CI]: 1.07-2.45; after confounder adjustment) or sarcopenia (probable: aSHR = 1.78, 95% CI: 1.10-2.88; confirmed: aSHR = 1.68, 95% CI: 1.01-2.82; and severe: aSHR = 2.51, 95% CI: 1.12-5.66; after full adjustment) were at increased risk of mortality. When stratified by age, MO (aSHR = 2.21, 95% CI: 1.28-3.83; P interaction = .005) and myosteatosis (aSHR = 1.95, 95% CI: 1.18-3.21; P interaction = .038) were associated with elevated risk only among candidates <65 years. MO was only associated with waitlist mortality among frail candidates (adjusted hazard ratio = 2.54, 95% CI: 1.28-5.05; P interaction = .021). Transplant centers should consider using BC metrics in addition to body mass index when a CT scan is available to improve pre-KT risk stratification at KT evaluation.

The first 2 living recipients of pig hearts died unexpectedly within 2 months, despite both recipients receiving what over 30 years of nonhuman primate (NHP) research would suggest were the optimal gene edits and immunosuppression to ensure success. These results prompt us to question how faithfully data from the NHP model translate into human outcomes. Before attempting any further heart xenotransplants in living humans, it is highly advisable to gain a more comprehensive understanding of why the promising preclinical NHP data did not accurately predict outcomes in humans. It is also unlikely that additional NHP data will provide more information that would de-risk a xenoheart clinical trial because these cases were based on the best practices from the most successful NHP results to date. Although imperfect, the decedent model offers a complementary avenue to determine appropriate treatment regimens to control the human immune response to xenografts and better understand the biologic differences between humans and NHP that could lead to such starkly contrasting outcomes. Herein, we explore the potential benefits and drawbacks of the decedent model and contrast it to the advantages and disadvantages of the extensive body of data generated in the NHP xenoheart transplantation model.

BACKGROUND:Since February 2020, exception points have been allocated equivalent to the median model for end-stage liver disease at transplant within 250 nautical miles of the transplant center (MMaT/250). We compared transplant rate and waitlist mortality for hepatocellular carcinoma (HCC) exception, non-HCC exception, and non-exception candidates to determine whether MMaT/250 advantages (or disadvantages) exception candidates. METHODS:Using Scientific Registry of Transplant Recipients data, we identified 23 686 adult, first-time, active, deceased donor liver transplant (DDLT) candidates between February 4, 2020, and February 3, 2022. We compared DDLT rates using Cox regression, and waitlist mortality/dropout using competing risks regression in non-exception versus HCC versus non-HCC candidates. RESULTS:Within 24 mo of study entry, 58.4% of non-exception candidates received DDLT, compared with 57.8% for HCC candidates and 70.5% for non-HCC candidates. After adjustment, HCC candidates had 27% lower DDLT rate (adjusted hazard ratio = 0.680.730.77) compared with non-exception candidates. However, waitlist mortality for HCC was comparable to non-exception candidates (adjusted subhazard ratio [asHR] = 0.931.031.15). Non-HCC candidates with pulmonary complications of cirrhosis or cholangiocarcinoma had substantially higher risk of waitlist mortality compared with non-exception candidates (asHR = 1.271.702.29 for pulmonary complications of cirrhosis, 1.352.043.07 for cholangiocarcinoma). The same was not true of non-HCC candidates with exceptions for other reasons (asHR = 0.540.881.44). CONCLUSIONS:Under MMaT/250, HCC, and non-exception candidates have comparable risks of dying before receiving liver transplant, despite lower transplant rates for HCC. However, non-HCC candidates with pulmonary complications of cirrhosis or cholangiocarcinoma have substantially higher risk of dying before receiving liver transplant; these candidates may merit increased allocation priority.

BACKGROUND:Kidney transplant (KT) candidates with HIV face higher mortality on the waitlist compared with candidates without HIV. Because the HIV Organ Policy Equity (HOPE) Act has expanded the donor pool to allow donors with HIV (D+), it is crucial to understand whether this has impacted transplant rates for this population. METHODS:Using a linkage between the HOPE in Action trial (NCT03500315) and Scientific Registry of Transplant Recipients, we identified 324 candidates listed for D+ kidneys (HOPE) compared with 46 025 candidates not listed for D+ kidneys (non-HOPE) at the same centers between April 26, 2018, and May 24, 2022. We characterized KT rate, KT type (D+, false-positive [FP; donor with false-positive HIV testing], D- [donor without HIV], living donor [LD]) and quantified the association between HOPE enrollment and KT rate using multivariable Cox regression with center-level clustering; HOPE was a time-varying exposure. RESULTS:HOPE candidates were more likely male individuals (79% versus 62%), Black (73% versus 35%), and publicly insured (71% versus 52%; P < 0.001). Within 4.5 y, 70% of HOPE candidates received a KT (41% D+, 34% D-, 20% FP, 4% LD) versus 43% of non-HOPE candidates (74% D-, 26% LD). Conversely, 22% of HOPE candidates versus 39% of non-HOPE candidates died or were removed from the waitlist. Median KT wait time was 10.3 mo for HOPE versus 60.8 mo for non-HOPE candidates (P < 0.001). After adjustment, HOPE candidates had a 3.30-fold higher KT rate (adjusted hazard ratio = 3.30, 95% confidence interval, 2.14-5.10; P < 0.001). CONCLUSIONS:Listing for D+ kidneys within HOPE trials was associated with a higher KT rate and shorter wait time, supporting the expansion of this practice for candidates with HIV.

The United States (U.S.) Department of Health and Human Services is interested in increasing geographical equity in access to liver transplant. The geographical disparity in the U.S. is fundamentally an outcome of variation in the organ supply to patient demand (s/d) ratios across the country (which cannot be treated as a single unit due to its size). To design a fairer system, we develop a nonlinear integer programming model that allocates the organ supply in order to maximize the minimum s/d ratios across all transplant centers. We design circular donation regions that are able to address the issues raised in legal challenges to earlier organ distribution frameworks. This allows us to reformulate our model as a set-partitioning problem. Our policy can be viewed as a heterogeneous donor circle policy, where the integer program optimizes the radius of the circle around each donation location. Compared to the current policy, which has fixed radius circles around donation locations, the heterogeneous donor circle policy greatly improves both the worst s/d ratio and the range between the maximum and minimum s/d ratios. We found that with the fixed radius policy of 500 nautical miles (NM), the s/d ratio ranges from 0.37 to 0.84 at transplant centers, while with the heterogeneous circle policy capped at a maximum radius of 500 NM, the s/d ratio ranges from 0.55 to 0.60, closely matching the national s/d ratio average of 0.5983. Our model matches the supply and demand in a more equitable fashion than existing policies and has a significant potential to improve the liver transplantation landscape.