This proposal is an application for a K08 award for Dr. Scott Biggins, a transplant hepatologist at the University of California, San Francisco (UCSF). Dr. Biggins is establishing himself as [sic] young clinical-scientist investigating evidence-based improvements in transplant recipient selection and donor organ allocation systems. This award will provide Dr. Biggins with the support necessary to accomplish the following goals: (1) develop expertise in outcome modeling of end-stage liver disease and liver transplantation;(2) investigate the novel application of marginal structural models (MSM) to enhance the survival benefit from scarce donor organs;and (3) implement applied mathematics and medical ethics in organ allocation policymaking. To achieve these goals, Dr. Biggins has assembled a mentoring team comprised of a primary mentor: Dr. John Inadomi, Director of the Health Outcomes Policy and Economics (HOPE) Program, who conducts research to optimize use of the clinical and financial resources in colorectal cancer screening;two co-mentors: Dr Norah Terrault, Director of Hepatitis Research in Liver Transplantation and Dr. John Roberts, Chief of Transplantation Surgery;and two consultants: Dr. Peter Bacchetti, Director of the Biostatistical Consulting Unit and Dr. Bernard Lo, Director of Medical Ethics. At present, liver grafts are allocated for retransplantation using the identical protocol as for initial transplantation. This standard protocol is based on predicted pre-transplant mortality (urgency) using the MELD score. To optimize use of these scarce organs, policymakers now advocate for incorporation of predicted post-procedure survival (outcome) into the allocation of liver grafts for retransplantation. Yet, current retransplantation outcome models are susceptible to bias inherent in the candidate selection (listing) criteria, particularly with respect to patients infected with hepatitis C virus. Dr. Biggins will develop a comprehensive retrospective (N=1022) and prospective (N=107) database of prior liver transplant recipients with liver graft dysfunction to identify factors that predict listing for retransplantation (Aim 1), evaluate the impact of the selection bias in current outcome models predicting post-retransplantation survival (Aim 2), develop new outcome models avoiding bias from listing and maximize the survival benefit of retransplantation (Aim 3), and develop a prospective cohort of potential retransplantation candidates for further refinement of candidate selection criteria and liver allocation (Aim 4). Unlike prior modeling studies that used only a subset of potential retransplant candidates (candidates who are listed or who have undergone retransplantation), Dr. Biggins will use the novel statistical application of inverse probability weighting, also known as marginal structural models, to expand the candidate population to include all potential retransplantation candidates with liver graft dysfunction. Public health relevance: Optimized candidate selection and allocation of livers for retransplantation will limit the misuse of a life-saving and scarce resource.

National Institute of Health (NIH)
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Clinical Investigator Award (CIA) (K08)
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Application #
Study Section
Diabetes, Endocrinology and Metabolic Diseases B Subcommittee (DDK)
Program Officer
Podskalny, Judith M,
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Project End
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Budget End
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University of Colorado Denver
Internal Medicine/Medicine
Schools of Medicine
United States
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Hung, Kenneth; Gralla, Jane; Dodge, Jennifer L et al. (2015) Optimizing repeat liver transplant graft utility through strategic matching of donor and recipient characteristics. Liver Transpl 21:1365-73
Dirchwolf, Melisa; Dodge, Jennifer L; Gralla, Jane et al. (2015) The corrected donor age for hepatitis C virus-infected liver transplant recipients. Liver Transpl 21:1022-30
Wedd, Joel; Bambha, Kiran M; Stotts, Matt et al. (2014) Stage of cirrhosis predicts the risk of liver-related death in patients with low Model for End-Stage Liver Disease scores and cirrhosis awaiting liver transplantation. Liver Transpl 20:1193-201
Biggins, S W; Gralla, J; Dodge, J L et al. (2014) Survival benefit of repeat liver transplantation in the United States: a serial MELD analysis by hepatitis C status and donor risk index. Am J Transplant 14:2588-94
Stotts, Matthew J; Hung, Kenneth W; Benson, Alexander et al. (2014) Rate and predictors of successful cardiopulmonary resuscitation in end-stage liver disease. Dig Dis Sci 59:1983-6
Regalia, Kirsten; Zheng, Patricia; Sillau, Stefan et al. (2014) Demographic factors affect willingness to register as an organ donor more than a personal relationship with a transplant candidate. Dig Dis Sci 59:1386-91
Biggins, Scott W; Trotter, James; Gralla, Jane et al. (2013) Differential effects of donor and recipient IL28B and DDX58 SNPs on severity of HCV after liver transplantation. J Hepatol 58:969-76
Biggins, Scott W (2012) Futility and rationing in liver retransplantation: when and how can we say no? J Hepatol 56:1404-11
Biggins, Scott W; Bambha, Kiran M; Terrault, Norah A et al. (2012) Projected future increase in aging hepatitis C virus-infected liver transplant candidates: a potential effect of hepatocellular carcinoma. Liver Transpl 18:1471-8
Somsouk, Ma; Kornfield, Rachel; Vittinghoff, Eric et al. (2011) Moderate ascites identifies patients with low model for end-stage liver disease scores awaiting liver transplantation who have a high mortality risk. Liver Transpl 17:129-36

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