Kidney Transplantation and Obesity: Are There Any Differences in Outcomes?

INTRODUCTION: Kidney transplantation (KT) is the gold standard treatment for end-stage renal disease (ESRD) patients. Obesity is a strong risk factor for developing cardiovascular disease, chronic kidney disease, and ESRD. This study aimed to investigate the outcomes of kidney transplantation in obese recipients. MATERIAL AND METHODS: We retrospectively reviewed the medical records of recipients from January 2016 to December 2021 in a single center. Outcomes in recipients of a kidney allograft with BMI ≥ 30 were compared with the outcomes in recipients with 30 < BMI. RESULTS: A total of 467 consecutive kidney transplantation recipients' files were studied. 213 (45.6%) allograft recipients had a BMI ≥ 30, and 254 (54.4%) allograft recipients had a BMI < 30. DGF rate was 29.1% in the BMI ≥ 30 and 30.7% in the BMI < 30 group (P = 0.41). On the other hand, 30 days readmission rate also did not show a significant difference between the BMI ≥ 30 and BMI < 30 allograft recipients (37 vs. 33.8%, P = 0.46). The mean overall costs of transplantation in the BMI ≥ 30 group was $254,395, and it was $256,029 in the BMI < 30 group (P = 0.84). CONCLUSION: Our study shows that the outcomes of renal allograft transplant were comparable between recipients with BMI ≥ 30 and BMI < 30 in terms of DGF, LOS, 30 days readmission, acute rejection rate, and survival rates, and BMI should not be a single independent criterion for decision making to select an optimal recipient.

Multi-institution analysis of tumor mutational burden and outcomes in pediatric central nervous system tumor patients.

BACKGROUND: Pediatric central nervous system (CNS) tumors are the leading cause of pediatric cancer mortality. Research addressing genomic biomarkers and clinical outcomes is needed to inform therapeutic decision-making. METHODS: We conducted a retrospective analysis of pediatric patients (age <21) diagnosed with a primary CNS tumor at four upstate New York hospitals from 2008 to 2021. Clinical and histopathologic data were identified from each patient, including genomic analysis of somatic mutations and tumor mutational burden (TMB) where available. These variables were each compared with overall survival using Cox regression analyses. Multivariable analysis was conducted to identify patient characteristics that may independently predict survival. RESULTS: We identified 119 patients. Common tumor types included low-grade glioma (N = 51), high-grade glioma (N = 29), and medulloblastoma (N = 11). Common driver mutations included TP53 inactivation (N = 16), BRAF-KIAA1549 fusion (N = 16), FGFR1 amplification (N = 12), BRAF V600E mutation (N = 12), NF1 loss (N = 12), and H3F3A K28M mutation (N = 6). Median TMB was one mutation/megabase (mut/Mb, range = 0-132). Overall survival was 79.9%. Variables associated with poorer survival on univariable analysis were higher TMB (p = .002, HR 4.97), high-grade tumors (p = .009, HR 84.3), and high-grade glioma histology (p = .021, HR 3.14). Multivariable analyses further identified TMB (p = .011, HR 4.46) and high-grade histology (p = .015, HR 5.28) as independently predictive of worse survival. Tumor progression was more common in high-TMB (N = 15, 44%) than in low-TMB tumors (N = 19, 35%). CONCLUSIONS: High TMB is correlated with higher rates of progression and death as compared to low-TMB tumors. These findings may help identify patients who may benefit from alternative treatments, such as immunotherapies.