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Andrew L. Rivard, MD, MS, Cleveland Clinic Abu Dhabi Naoru Koizumi, PhD, George Mason University

HLA Compatibility and Heart Transplant Survival Using A Validated Matching Algorithm. Andrew L. Rivard, MD, MS, Cleveland Clinic Abu Dhabi Naoru Koizumi, PhD, George Mason University. Relevant Financial Relationship Disclosure Statement.

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Andrew L. Rivard, MD, MS, Cleveland Clinic Abu Dhabi Naoru Koizumi, PhD, George Mason University

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  1. HLA Compatibility and Heart Transplant Survival Using A Validated Matching Algorithm Andrew L. Rivard, MD, MS, Cleveland Clinic Abu DhabiNaoru Koizumi, PhD, George Mason University

  2. Relevant Financial Relationship Disclosure Statement • Human Leukocyte Compatibility and Heart Transplant Survival • Using A Validated Matching Algorithm • I will not discuss off label use and/or investigational use • No relevant financial relationships exist related to this presentation.

  3. Outline • Post heart transplant survival determinants • Donor / recipient tissue typing • UNOS – STARS file • HLA mismatching algorithm • Survival as based upon HLA mismatch • Future 3

  4. UNET Web Data Entry Form 4

  5. Methods • UNOS - STARS file 2003-2015 • 121,368 HTx recipients • 209 US transplant centers • HLA mismatching algorithm • 0-6 mismatches HLA-A, -B, -DR • >4 missing loci excluded 5

  6. Methods • UNOS - STARS file 2003-2015 • 121,368 HTx recipients • 209 US transplant centers • HLA mismatching algorithm • 0-6 mismatches HLA-A, -B, -DR • >4 missing loci excluded 6

  7. Methods • UNOS - STARS file 2003-2015 • 121,368 HTx recipients • 209 US transplant centers • HLA mismatching algorithm • 0-6 mismatches HLA-A, -B, -DR • >4 missing loci excluded 7

  8. Methods • UNOS - STARS file 2003-2015 • 121,368 HTx recipients • 209 US transplant centers • HLA mismatching algorithm • 0-6 mismatches HLA-A, -B, -DR • >4 missing loci excluded 8

  9. Methods • UNOS - STARS file 2003-2015 • 121,368 HTx recipients • 209 US transplant centers • HLA mismatching algorithm • 0-6 mismatches HLA-A, -B, -DR • >4 missing loci excluded 9

  10. Methods • UNOS - STARS file 2003-2015 • 121,368 HTx recipients • 209 US transplant centers • HLA mismatching algorithm • 0-6 mismatches HLA-A, -B, -DR • >4 missing loci excluded 10

  11. Database Relationship Design Individual Table 11

  12. HLA Table 12

  13. HLA Table 13

  14. Mismatch Algorithm • Step 1 – Data validation • Demonstrate data validity • Step 2 – Donor-Recipient mismatching • Logic (A ? X) comparison • Error handling • Demonstration of equivalency 14

  15. Mismatch Algorithm • Step 1 – Data validation • Demonstrate data validity • Step 2 – Donor-Recipient mismatching • Logic (A ? X) comparison • Error handling • Demonstration of equivalency 15

  16. User Interface 16

  17. Results • 21,878 HTx patients met criteria • 398 patients (0-1 mismatch) • 3 yr Survival ≤ 3 mismatch ≥ 4 mismatch (p=0.001) • Cox regression HLA-DR (p=0.003) 17

  18. 18

  19. 19

  20. Survival Based Upon Mismatch 20

  21. 21

  22. Conclusion • Largest analysis of HLA data to date • UNOS independent mismatching algorithm • Survival ≤ 3 mismatch ≥ 4 mismatch • *HLA-DR Thompson JS, Thacker Ii LR, Takemoto S. The influence of conventional and cross-reactive group HLA matching on cardiac transplant outcome: an analysis from the United Network of Organ Sharing Scientific Registry. Transplantation 2000; 69: 2178. 14535 patients! 22

  23. Thank you! 23

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