Bonnie E. Lonze

Key Points: In this cohort study of 720,348 adults referred for kidney transplantation from 2014 to 2025, only 48% were evaluated and 19% were waitlisted. Progression from referral to evaluation, waitlisting and kidney transplantation was limited by individual, center-level, and geographic factors. Some centers evaluated and waitlisted patients at rates far below the national average, and low-volume centers had lower rates of transplantation. Background: Kidney transplantation is a cost-effective, lifesaving treatment of kidney failure, compared with dialysis. Unfortunately, most patients with kidney failure never undergo transplantation. Methods: Using Epic Cosmos electronic health record data on all patients referred for kidney transplantation from 2014 to 2025, we assessed the stage-specific progression and attrition in the process of evaluation, waitlisting, and kidney transplantation. Center-level and individual (socioeconomic, geographic, and insurance status) factors associated with access to evaluation, waitlisting, and kidney transplantation were characterized using modified Poisson regression. Results: Among 720,348 referred candidates, the median age was 55 years (interquartile range [IQR], 42–64); 47% of patients were White, 52% were male, and 87% were English speaking. Eighty-five percent of patients lived in urban areas. Of the referred candidates, 48% initiated evaluation, 19% were waitlisted, and 10% ultimately underwent transplantation. Among the referred patients who initiated evaluation, the median (IQR) time to evaluation initiation was two (1–4) months after referral; among the patients who were waitlisted, the median (IQR) time to waitlisting was four (2–9) months after evaluation initiation. Patients who were never married (0.94; 95% confidence interval [CI], 0.93 to 0.94), had severe obesity (0.70; 95% CI, 0.69 to 0.72), or were from rural zip codes (relative risk, 0.98; 95% CI, 0.97 to 1.00) were less likely to initiate evaluation. Low-volume centers had lower relative rates of transplantation (0.92; 95% CI, 0.88 to 0.96). In centers with documentation for nonprogression to evaluation, reasons for removal included not meeting criteria/not a candidate (18%), patient decision (13%), unable to contact (12%), death (4%), and financial/insurance complications (7%). Conclusions: Our study shows substantial attrition before kidney transplant waitlisting.

Background: In out‐of‐sequence (OOS) allocation of deceased donor kidney transplants (DDKTs), providers are allowed to choose recipients irrespective of waitlist priority. Whether candidate obesity affects OOS recipient selection is unknown. Methods: We examined access to OOS‐DDKT by candidate body mass index (BMI) using kidney offers from Organ Procurement and Transplantation Network data (1/2022–12/2023). We compared characteristics of OOS‐DDKT versus being last‐skipped candidate at the same center using donor‐level conditional logistic regression and multilevel modeling among the top‐20 OOS‐performing centers. Results: We identified 4970 OOS‐placements and 4588 list‐skipped candidates. OOS candidates were older and less likely to be Black. We found a dose–response relationship between weight class and odds of OOS‐DDKT. Compared to normal weight candidates, candidates with Class 1, 2, and 3 obesity had 32%, 50%, and 69% lower odds of receiving OOS‐DDKT. Mediation analysis suggested candidate BMI partially explained higher access among Asian and Hispanic candidates. There was substantial center‐level variation; a 10‐unit increase in BMI was associated with >50% lower odds of OOS‐DDKT at 3/20 centers, 20%–50% lower odds at 12/20 centers, and comparable odds at 5/20 centers. Conclusions: DDKT candidates with obesity have lower access to OOS kidney allocation. However, equitable distribution irrespective of candidate obesity was observed at a small number of top‐performing centers.

This study describes secular trends in organ donation after circulatory death in the United States between 2000 and 2025.