Social Determinants of Health and Race Disparities in Kidney Transplant

Wesselman, Hannah M.; Ford, C. Graham; Leyva, Yuridia; Li, Xingyuan; Chang, Chung‐Chou H.; Dew, Mary Amanda; Kendall, Kay; Croswell, Emilee; Pleis, John R.; Ng, Yue Harn; Unruh, Mark; Shapiro, Ron; Myaskovsky, Larissa

doi:10.2215/cjn.04860420

Cited by 103 publications

(93 citation statements)

References 65 publications

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“…Older age, higher number of comorbidities, transplantation before changes to the KAS, greater religiosity, less social support, and fewer learning activities were each associated with a decreased probability of deceased-donor kidney transplant [ 175 ]. Black race, older age, lower income, public insurance status, higher body mass index, dialysis before kidney transplant, not presenting with a potential living donor, religious objection to living-donor transplant, and less transplant knowledge were each associated with a decreased probability of living-donor transplant.…”

Section: Resultsmentioning

confidence: 99%

A scoping review of inequities in access to organ transplant in the United States

Park

Jones

Kaplan

et al. 2022

Int J Equity Health

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Background Organ transplant is the preferred treatment for end-stage organ disease, yet the majority of patients with end-stage organ disease are never placed on the transplant waiting list. Limited access to the transplant waiting list combined with the scarcity of the organ pool result in over 100,000 deaths annually in the United States. Patients face unique barriers to referral and acceptance for organ transplant based on social determinants of health, and patients from disenfranchised groups suffer from disproportionately lower rates of transplantation. Our objective was to review the literature describing disparities in access to organ transplantation based on social determinants of health to integrate the existing knowledge and guide future research. Methods We conducted a scoping review of the literature reporting disparities in access to heart, lung, liver, pancreas and kidney transplantation based on social determinants of health (race, income, education, geography, insurance status, health literacy and engagement). Included studies were categorized based on steps along the transplant care continuum: referral for transplant, transplant evaluation and selection, living donor identification/evaluation, and waitlist outcomes. Results Our search generated 16,643 studies, of which 227 were included in our final review. Of these, 34 focused on disparities in referral for transplantation among patients with chronic organ disease, 82 on transplant selection processes, 50 on living donors, and 61 on waitlist management. In total, 15 studies involved the thoracic organs (heart, lung), 209 involved the abdominal organs (kidney, liver, pancreas), and three involved multiple organs. Racial and ethnic minorities, women, and patients in lower socioeconomic status groups were less likely to be referred, evaluated, and added to the waiting list for organ transplant. The quality of the data describing these disparities across the transplant literature was variable and overwhelmingly focused on kidney transplant. Conclusions This review contextualizes the quality of the data, identifies seminal work by organ, and reports gaps in the literature where future research on disparities in organ transplantation should focus. Future work should investigate the association of social determinants of health with access to the organ transplant waiting list, with a focus on prospective analyses that assess interventions to improve health equity.

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Section: Resultsmentioning

confidence: 99%

A scoping review of inequities in access to organ transplant in the United States

Park

Jones

Kaplan

et al. 2022

Int J Equity Health

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“…Cluster 3 recipients were young, black, and had hypertension or glomerular-related kidney disease. The reduced graft survival in cluster 3 recipients underscores at-risk disparities such as socioeconomic post-transplant support and minorities being disadvantaged in access to preemptive and living donor transplants [ 35 , 36 ]. In contrast, the majority of cluster 1 and 4 recipients were white.…”

Section: Discussionmentioning

confidence: 99%

Machine Learning Consensus Clustering of Morbidly Obese Kidney Transplant Recipients in the United States

Mao

Jadlowiec

Mao

et al. 2022

JCM

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Background: This study aimed to better characterize morbidly obese kidney transplant recipients, their clinical characteristics, and outcomes by using an unsupervised machine learning approach. Methods: Consensus cluster analysis was applied to OPTN/UNOS data from 2010 to 2019 based on recipient, donor, and transplant characteristics in kidney transplant recipients with a pre-transplant BMI ≥ 40 kg/m2. Key cluster characteristics were identified using the standardized mean difference. Post-transplant outcomes, including death-censored graft failure, patient death, and acute allograft rejection, were compared among the clusters. Results: Consensus clustering analysis identified 3204 kidney transplant recipients with a BMI ≥ 40 kg/m2. In this cohort, five clinically distinct clusters were identified. Cluster 1 recipients were predominantly white and non-sensitized, had a short dialysis time or were preemptive, and were more likely to receive living donor kidney transplants. Cluster 2 recipients were older and diabetic. They were likely to have been on dialysis >3 years and receive a standard KDPI deceased donor kidney. Cluster 3 recipients were young, black, and had kidney disease secondary to hypertension or glomerular disease. Cluster 3 recipients had >3 years of dialysis and received non-ECD, young, deceased donor kidney transplants with a KDPI < 85%. Cluster 4 recipients were diabetic with variable dialysis duration who either received non-ECD standard KDPI kidneys or living donor kidney transplants. Cluster 5 recipients were young retransplants that were sensitized. One-year patient survival in clusters 1, 2, 3, 4, and 5 was 98.0%, 94.4%, 98.5%, 98.7%, and 97%, and one-year death-censored graft survival was 98.1%, 93.0%, 96.1%, 98.8%, and 93.0%, respectively. Cluster 2 had the worst one-year patient survival. Clusters 2 and 5 had the worst one-year death-censored graft survival. Conclusions: With the application of unsupervised machine learning, variable post-transplant outcomes are observed among morbidly obese kidney transplant recipients. Recipients with earlier access to transplant and living donation show superior outcomes. Unexpectedly, reduced graft survival in cluster 3 recipients perhaps underscores socioeconomic access to post-transplant support and minorities being disadvantaged in access to preemptive and living donor transplants. Despite obesity-related concerns, one-year patient and graft survival were favorable in all clusters, and obesity itself should be reconsidered as a hard barrier to kidney transplantation.

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“…For the same reason, we chose not to control for socioeconomic factors and race, known to affect listing for and receipt of organ transplantation. 32,33 Finally, we explicitly decided to focus on patients who received SHK and not those listed for SHK, therefore not capturing the true variation in listing practices. However, a sensitivity analysis did show a strong correlation between listing for and receipt of SHK, indicating that these results may extrapolate to the listed population as well.…”

Section: Discussionmentioning

confidence: 99%

“…We chose not to adjust for center‐level factors in our model, such as transplant volume, as we posited that center‐level characteristics themselves would contribute to center‐level differences in meaningful ways and our goal was to capture these differences that were attributable to practice variation and organizational differences. For the same reason, we chose not to control for socioeconomic factors and race, known to affect listing for and receipt of organ transplantation 32,33 . Finally, we explicitly decided to focus on patients who received SHK and not those listed for SHK, therefore not capturing the true variation in listing practices.…”

Section: Discussionmentioning

confidence: 99%

Center variations in patient selection for simultaneous heart‐kidney transplantation

Shaw

Samoylova

Barbas

et al. 2022

Clinical Transplantation

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There are no established regulations governing patient selection for simultaneous heart‐kidney (SHK) transplantation, creating the potential for significant center‐level variations in clinical practice. Methods Using the United Network for Organ Sharing (UNOS) Standard Transplant Analysis and Research (STAR) file, we examined practice trends and variations in patient selection for SHK at the center level between January 1, 2004 and March 31, 2019. Results Overall, SHK is becoming more common with most centers performing heart transplants also performing SHK. Among patients who underwent heart transplant who were receiving dialysis, the rate of SHK varied from 22% to 86% at the center level. Among patients not on dialysis, the median estimated glomerular filtration rate (eGFR) of patients receiving SHK varied between 19 and 59 mL/min/1.73 m2. When adjusting for other factors, the odds of SHK varied 57‐fold between the highest and lowest SHK performing centers. Conclusion Variation in SHK at the center level suggests the need for national guidelines around the selection of patients for SHK.

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Social Determinants of Health and Race Disparities in Kidney Transplant

Cited by 103 publications

References 65 publications

A scoping review of inequities in access to organ transplant in the United States

A scoping review of inequities in access to organ transplant in the United States

Machine Learning Consensus Clustering of Morbidly Obese Kidney Transplant Recipients in the United States

Center variations in patient selection for simultaneous heart‐kidney transplantation

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