Characteristics of Kidney Transplant Recipients with Prolonged Pre-Transplant Dialysis Duration as Identified by Machine Learning Consensus Clustering: Pathway to Personalized Care
Issued Date
2023-08-01
Resource Type
eISSN
20754426
Scopus ID
2-s2.0-85169036338
Journal Title
Journal of Personalized Medicine
Volume
13
Issue
8
Rights Holder(s)
SCOPUS
Bibliographic Citation
Journal of Personalized Medicine Vol.13 No.8 (2023)
Suggested Citation
Thongprayoon C., Tangpanithandee S., Jadlowiec C.C., Mao S.A., Mao M.A., Vaitla P., Acharya P.C., Leeaphorn N., Kaewput W., Pattharanitima P., Suppadungsuk S., Krisanapan P., Nissaisorakarn P., Cooper M., Craici I.M., Cheungpasitporn W. Characteristics of Kidney Transplant Recipients with Prolonged Pre-Transplant Dialysis Duration as Identified by Machine Learning Consensus Clustering: Pathway to Personalized Care. Journal of Personalized Medicine Vol.13 No.8 (2023). doi:10.3390/jpm13081273 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/89383
Title
Characteristics of Kidney Transplant Recipients with Prolonged Pre-Transplant Dialysis Duration as Identified by Machine Learning Consensus Clustering: Pathway to Personalized Care
Author's Affiliation
Thammasat University Hospital
Mayo Clinic Scottsdale-Phoenix, Arizona
Texas Tech University Health Sciences Center El Paso
UMKC School of Medicine
Faculty of Medicine Ramathibodi Hospital, Mahidol University
Faculty of Medicine, Thammasat University
Medical College of Wisconsin
Phramongkutklao College of Medicine
Mayo Clinic
University of Mississippi Medical Center
Harvard Medical School
Mayo Clinic in Jacksonville, Florida
Mayo Clinic Scottsdale-Phoenix, Arizona
Texas Tech University Health Sciences Center El Paso
UMKC School of Medicine
Faculty of Medicine Ramathibodi Hospital, Mahidol University
Faculty of Medicine, Thammasat University
Medical College of Wisconsin
Phramongkutklao College of Medicine
Mayo Clinic
University of Mississippi Medical Center
Harvard Medical School
Mayo Clinic in Jacksonville, Florida
Other Contributor(s)
Abstract
Longer pre-transplant dialysis duration is known to be associated with worse post-transplant outcomes. Our study aimed to cluster kidney transplant recipients with prolonged dialysis duration before transplant using an unsupervised machine learning approach to better assess heterogeneity within this cohort. We performed consensus cluster analysis based on recipient-, donor-, and transplant-related characteristics in 5092 kidney transplant recipients who had been on dialysis ≥ 10 years prior to transplant in the OPTN/UNOS database from 2010 to 2019. We characterized each assigned cluster and compared the posttransplant outcomes. Overall, the majority of patients with ≥10 years of dialysis duration were black (52%) or Hispanic (25%), with only a small number (17.6%) being moderately sensitized. Within this cohort, three clinically distinct clusters were identified. Cluster 1 patients were younger, non-diabetic and non-sensitized, had a lower body mass index (BMI) and received a kidney transplant from younger donors. Cluster 2 recipients were older, unsensitized and had a higher BMI; they received kidney transplant from older donors. Cluster 3 recipients were more likely to be female with a higher PRA. Compared to cluster 1, cluster 2 had lower 5-year death-censored graft (HR 1.40; 95% CI 1.16–1.71) and patient survival (HR 2.98; 95% CI 2.43–3.68). Clusters 1 and 3 had comparable death-censored graft and patient survival. Unsupervised machine learning was used to characterize kidney transplant recipients with prolonged pre-transplant dialysis into three clinically distinct clusters with variable but good post-transplant outcomes. Despite a dialysis duration ≥ 10 years, excellent outcomes were observed in most recipients, including those with moderate sensitization. A disproportionate number of minority recipients were observed within this cohort, suggesting multifactorial delays in accessing kidney transplantation.