Choosing the order of deceased donor and living donor kidney transplantation in pediatric recipients: a Markov decision process model

Abstract

Background: Most pediatric kidney transplant recipients eventually require retransplantation, and the most advantageous timing strategy regarding deceased and living donor transplantation in candidates with only 1 living donor remains unclear.

Methods: A patient-oriented Markov decision process model was designed to compare, for a given patient with 1 living donor, living-donor-first followed if necessary by deceased donor retransplantation versus deceased-donor-first followed if necessary by living donor (if still able to donate) or deceased donor (if not) retransplantation. Based on Scientific Registry of Transplant Recipients data, the model was designed to account for waitlist, graft, and patient survival, sensitization, increased risk of graft failure seen during late adolescence, and differential deceased donor waiting times based on pediatric priority allocation policies. Based on national cohort data, the model was also designed to account for aging or disease development, leading to ineligibility of the living donor over time.

Results: Given a set of candidate and living donor characteristics, the Markov model provides the expected patient survival over a time horizon of 20 years. For the most highly sensitized patients (panel reactive antibody > 80%), a deceased-donor-first strategy was advantageous, but for all other patients (panel reactive antibody < 80%), a living-donor-first strategy was recommended.

Conclusions: This Markov model illustrates how patients, families, and providers can be provided information and predictions regarding the most advantageous use of deceased donor versus living donor transplantation for pediatric recipients.

Figure 1. Markov decision process model for order of deceased donor and living donor transplantation among pediatric kidney transplant candidates

Patients entered into the Markov model must decide whether to utilize their single available living donor for primary living donor transplantation. Declining patients start their first simulated month in the waitlist state (W), and their Markov state over the subsequent 240 months is determined by the probability of deceased donor kidney transplantation (W2T^D) or death (W2D). Patients who choose to utilize their living donor undergo immediate living donor transplantation, and their subsequent states are determined by the probability of death (T^L2D) and the probability of graft loss (T^L2W), necessitating a return to dialysis and immediate relisting for deceased donor retransplantation. Following deceased donor transplantation, a patient’s subsequent states are determined by the probability of death (T^D2D) and the probability of graft loss, necessitating either living donor retransplantation (shown with dashed line, if available) or rather a return to dialysis and immediate relisting for deceased donor retransplantation (T^D2W) if one’s living donor is no longer eligible for donation. After patients experience two graft failures, subsequent states are determined by the probability of death (GF2D).

Figure 2. Expected patient survival after the choice between primary living donor versus deceased donor KT: illustrative patient and donor phenotypes

2A: Living donor is a 20 year-old Caucasian female, HLA mismatches = 0, no smoking history 2B: Living donor is a 50 year-old Caucasian male, HLA mismatches = 6, smoking history 2C: Candidate is a 10 year-old Caucasian male, CAKUT, PRA 0–5%, ABO O, no prior dialysis or KT 2D: Candidate is a 15 year-old African American female, FSGS, PRA 96–100%, ABO B, no prior dialysis, previous KT Candidate for Figure 2A–B: 5 year-old Caucasian male, CAKUT, PRA 0–5%, ABO O, no prior dialysis or KT, expected pediatric time to deceased donor KT = 6 months, expected adult time to deceased donor KT = 2 years. Living donor for Figure 2C–D: 30 year-old Caucasian male, HLA mismatches = 3, no smoking history, expected pediatric time to deceased donor KT = 6 months, expected adult time to deceased donor KT = 2 years.

Figure 2. Expected patient survival after the choice between primary living donor versus deceased donor KT: illustrative patient and donor phenotypes

2A: Living donor is a 20 year-old Caucasian female, HLA mismatches = 0, no smoking history 2B: Living donor is a 50 year-old Caucasian male, HLA mismatches = 6, smoking history 2C: Candidate is a 10 year-old Caucasian male, CAKUT, PRA 0–5%, ABO O, no prior dialysis or KT 2D: Candidate is a 15 year-old African American female, FSGS, PRA 96–100%, ABO B, no prior dialysis, previous KT Candidate for Figure 2A–B: 5 year-old Caucasian male, CAKUT, PRA 0–5%, ABO O, no prior dialysis or KT, expected pediatric time to deceased donor KT = 6 months, expected adult time to deceased donor KT = 2 years. Living donor for Figure 2C–D: 30 year-old Caucasian male, HLA mismatches = 3, no smoking history, expected pediatric time to deceased donor KT = 6 months, expected adult time to deceased donor KT = 2 years.

Figure 2. Expected patient survival after the choice between primary living donor versus deceased donor KT: illustrative patient and donor phenotypes

2A: Living donor is a 20 year-old Caucasian female, HLA mismatches = 0, no smoking history 2B: Living donor is a 50 year-old Caucasian male, HLA mismatches = 6, smoking history 2C: Candidate is a 10 year-old Caucasian male, CAKUT, PRA 0–5%, ABO O, no prior dialysis or KT 2D: Candidate is a 15 year-old African American female, FSGS, PRA 96–100%, ABO B, no prior dialysis, previous KT Candidate for Figure 2A–B: 5 year-old Caucasian male, CAKUT, PRA 0–5%, ABO O, no prior dialysis or KT, expected pediatric time to deceased donor KT = 6 months, expected adult time to deceased donor KT = 2 years. Living donor for Figure 2C–D: 30 year-old Caucasian male, HLA mismatches = 3, no smoking history, expected pediatric time to deceased donor KT = 6 months, expected adult time to deceased donor KT = 2 years.

Figure 2. Expected patient survival after the choice between primary living donor versus deceased donor KT: illustrative patient and donor phenotypes

2A: Living donor is a 20 year-old Caucasian female, HLA mismatches = 0, no smoking history 2B: Living donor is a 50 year-old Caucasian male, HLA mismatches = 6, smoking history 2C: Candidate is a 10 year-old Caucasian male, CAKUT, PRA 0–5%, ABO O, no prior dialysis or KT 2D: Candidate is a 15 year-old African American female, FSGS, PRA 96–100%, ABO B, no prior dialysis, previous KT Candidate for Figure 2A–B: 5 year-old Caucasian male, CAKUT, PRA 0–5%, ABO O, no prior dialysis or KT, expected pediatric time to deceased donor KT = 6 months, expected adult time to deceased donor KT = 2 years. Living donor for Figure 2C–D: 30 year-old Caucasian male, HLA mismatches = 3, no smoking history, expected pediatric time to deceased donor KT = 6 months, expected adult time to deceased donor KT = 2 years.

Figure 3. Classification and regression tree (CART) analysis: patient and donor characteristics that are most predictive of 20-year survival benefit from undergoing primary living donor versus deceased donor KT

CART data from 336 hypothetical donor phenotypes and 81,920 hypothetical candidate phenotypes. Tree pruned to 2 levels to avoid overfitting. Donor characteristics included age, gender, race, HLA mismatches, and smoking history. Patient characteristics include age, gender, race, previous dialysis, previous KT, etiology of renal disease (FSGS, other glomerular disease, CAKUT, or other), PRA, ABO, and estimated times to deceased donor KT. To navigate the tree, start at the “PRA” node; if the candidate has PRA greater than 80% move left down the tree.