Background
When selecting a human leukocyte antigen (HLA) matched unrelated donor (URD) for hematopoietic cell transplantation (HCT) it is generally accepted that donor age, sex, ABO blood group and viral serologic status should be considered. However, the inter-relationship among these variables is not well established and a consensus on how strongly to consider each variable has not been reached. Selection of the optimal donor gets more complicated as new donor recipient pair (DRP) selection parameters, including killer immunoglobulin-like receptors (KIR) haplotypes are included. In this study we seek to develop a logic-based method to reduce the inconsistencies in donor selection in the HLA matched HCT.
Methods
VCU IRB approval was obtained for a retrospective review of eligible subjects who were adults with known KIR genotyping receiving HLA-A, B, C & DRB1 allelically matched URD HCT for hematologic malignancy between 2014 and 2017. Donor recipient pairs were selected based on donor age, sex match, CMV sero-status match, and ABO compatibility when possible; KIR genotype was not considered in DRP selection. KIR-KIR ligand interactions were calculated for each DR pair and interaction unit values were ascribed as follows; -1, when the donor possessed an inhibitory KIR (iKIR) and the recipient the corresponding HLA; +1, when the donor possessed iKIR and recipient lacked corresponding HLA (mKIR score, missing ligand). A novel inhibitory-missing KIR (IM-KIR) score was calculated for each HLA matched DRP by summing the interaction values as in equation 1.
IM KIR Score = |iKIR| + |mKIRL| ………. [1]
Univariate and multivariate analysis using Cox regression methods were utilized to evaluate donor parameters associated with overall survival. Weights of each donor risk variable (age, sex, CMV & ABO match) contribution were ascribed and summed up to determine donor risk parameter. Donor risk parameters and reciprocal-IM-KIR were finally combined into a donor risk index. Receiver operating characteristic curve- area under the curve (ROC-AUC) analysis was utilized to compare indices.
Results
Ninety-eight DRP with known HLA & KIR genotyping were studied. Median follow up at the time of analysis was 583 days. A higher IM-KIR score describes a DRP with increased iKIR-KIR ligand interactions and missing KIR ligand interactions; which was associated with a favorable survival after HCT, HR of 0.44 (95%CI: 0.26 to 0.73; P=0.002). Further analyses were performed using a reciprocal of this score. Univariate analysis of overall survival for donor age, sex match, ABO compatibility and CMV status were all statistically insignificant (p>0.05). However, the donor risk parameter was predictive of mortality with a hazard ratio (HR) of 2.76 (95% CI: 1.22-6.18, p=0.014). Covariate analysis of the donor risk parameter and reciprocal IM-KIR score were both predictive of survival independent of each other with HR 2.41 (1.05-5.54, p=0.038) and 2.35 (1.18-4.70, p=0.016) respectively. Combining the two into a donor risk index was predictive of survival with a HR of 2.38 (1.44-3.92, p=0.001). ROC-AUC comparison of survival for IM-KIR score and donor risk parameter showed statistically significant AUCs of 0.63 and 0.67 respectively. Further, the combined donor risk index shows improved sensitivity and specificity over the donor risk parameter with AUCs of 0.72 and 0.67 respectively.
Conclusions
A novel KIR-HLA interaction score, the IM-KIR score independently predicts survival in HLA matched DRP, as does a formalized donor risk parameter which includes non-HLA donor characteristics. Moreover, the addition of IM-KIR score to the donor risk parameter enhanced the specificity and sensitivity of predicting survival in these patients. If validated in a larger exploration and validation cohort this method of donor selection may improve the donor selection process, decreasing variability in clinical outcomes and improve overall survival.
No relevant conflicts of interest to declare.
Author notes
Asterisk with author names denotes non-ASH members.
