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Offering HCV-Positive Kidneys to HCV-Negative Patients on the Kidney Transplant Waitlist Is Lifesaving: Results of a Markov Model.

D. Goldberg, P. Reese, V. Potluri, F. Scott.

Medicine, University of Pennsylvania, Philadelphia, PA.

Meeting: 2016 American Transplant Congress

Abstract number: 450

Keywords: Allocation, Hepatitis C, Kidney transplantation

Session Information

Date: Tuesday, June 14, 2016

Session Name: Concurrent Session: Living Donation and Transplant: Operational and Economic Factors

Session Time: 2:30pm-4:00pm

 Presentation Time: 3:06pm-3:18pm

Location: Room 311

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Background: Patients with ESRD on the transplant waitlist face substantial risks of dying without a transplant. Because 2/3 of kidneys from hepatitis C virus (HCV)-positive donors are discarded, they represent a potential source of deceased-donor kidney transplants (DDKT) for HCV-negative patients with long expected waittimes and the highest risks of waitlist death. However, use of such organs should only be considered if the risks-benefit profile of HCV transmission is minimal.

Methods: We employed Markov modeling to assess risks and benefits for HCV-negative patients under two waitlisting strategies: accepting only kidneys from HCV-negative donors, or accepting the first-available kidney from an HCV-negative or HCV-positive donor, with immediate post-DDKT treatment with a direct-acting antiviral (DAA) after confirmed HCV transmission. We evaluated the risk-benefit profile for HCV-negative patients waitlisted for a kidney in the US since 2008, blood groups A, B, or O, without a living donor. The time horizon was 5 years, with 1-month cycles. Outcomes were in life-years (LYs). Transition probabilities were derived from UNOS data. Efficacy data for HCV therapy were based on published clinical trials (Zeuzem S, et al, Ann Int Med, 2015). Post-DDKT HCV-related complications were estimated from UNOS data and published data. Primary analyses used first-order Monte Carlo simulation (FOMCS) of 1,000 runs of 100,000 individuals. Additional analyses included Markov cohort analysis, simulating the clinical course of 1,000 HCV-negative individuals eligible to receive HCV-positive kidneys versus standard-of-care (SOC).

Results: In FOMCS, the mean LYs in the HCV-positive arm was 4.25 (95% CI: 4.22-4.28) vs 4.10 (95% CI: 4.06-4.13) for SOC, with an incremental effectiveness of 0.15 LYs. Eligibility for HCV-positive kidneys resulted in 95 fewer deaths (out of 1,000 patients), and 500 additional DDKTs over 5 years (405 patients remained waitlisted in the SOC arm at 5 years). Expected 5-year survival was 78.3% for those willing to accept an HCV-positive kidney vs. 68.8% for SOC.

Conclusions: This model suggests that for HCV-negative patients, the option to receive a DDKT from an HCV-positive deceased-donor would result in significantly more transplants and increased LYs for the waitlist population. These data would support clinical trials investigating the safety and efficacy of such strategies, provided that DAAs can be guaranteed post-DDKT.

CITATION INFORMATION: Goldberg D, Reese P, Potluri V, Scott F. Offering HCV-Positive Kidneys to HCV-Negative Patients on the Kidney Transplant Waitlist Is Lifesaving: Results of a Markov Model. Am J Transplant. 2016;16 (suppl 3).

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To cite this abstract in AMA style:

Goldberg D, Reese P, Potluri V, Scott F. Offering HCV-Positive Kidneys to HCV-Negative Patients on the Kidney Transplant Waitlist Is Lifesaving: Results of a Markov Model. [abstract]. Am J Transplant. 2016; 16 (suppl 3). https://atcmeetingabstracts.com/abstract/offering-hcv-positive-kidneys-to-hcv-negative-patients-on-the-kidney-transplant-waitlist-is-lifesaving-results-of-a-markov-model/. Accessed March 5, 2021.

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