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Beatty G1, Barin B2, Fox L3, Odim J3, Huprikar S4, Wong M5, Diego J6, Blumberg E7, Simon D8, Light J9, Yin M10, Davis C11, Jayaweera D12, Hardy D13, Ragni M14, Johnson L15, Subramanian A16, Stosor T17, Brayman K18, Pursell K19, Zhang R20, Lyon G21, Taege A22, Feinberg J23, Weikert B24, Stock P1, Roland M1. 1University of California, San Francisco; 2EMMES Corp.; 3National Institutes of Health; 4Mt. Sinai Medical Center; 5Beth Israel Deaconess Medical Center; 6University of Miami; 7University Pennsylvania; 8Rush University; 9Washington Hospital Center; 10Columbia University; 11University of Maryland; 12University of Miami; 13Cedars-Sinai Medical Center; 14University of Pittsburgh; 15Georgetown University; 16Johns Hopkins University; 17Northwestern University; 18University of Virginia; 19University of Chicago; 20Tulane University; 21Emory University; 22Cleveland Clinic; 23University of Cincinnati; 24Drexel University. HIV-Related Predictors and Outcomes in 275 Liver and/or Kidney Transplant Recipients On behalf of the investigators of Solid Organ Transplantation in HIV: Multi-Site Study Funded by the National Institute of Allergy and Infectious Diseases (AI052748) Sponsored by the University of California, San Francisco
6th IAS Conference on HIV Pathogenesis, Treatment, and Prevention George Beatty, MD, MPH UCSF Positive Health Program at SFGH University of California San Francisco I have no financial relationships to disclose within the past 12 months relevant to my presentation. My presentation does not include discussion of off-label or investigational use. I do not intend to reference unlabeled/unapproved uses of drugs or products in my presentation.
Rationale • Historically, HIV considered a contraindication to organ transplantation • End-organ disease emerging as major cause of morbidity/mortality in HIV1 • Limited experience with liver and kidney transplants in ART era has been encouraging, but optimal selection criteria and predictors of outcome remain undefined2 1Mocroft, et al. AIDS 2005 19:2117-2125; Ragni, et al. Liver Transpl 2002; 11:1425-1430; Palella, et al. NEJM 1998: 338:853-860; others. 2Roland, et al. Am J Trnsplnt 2008;8:355-365; Stock, et al. Am J Trnsplnt 2009; 9(2): 197; Terrault, et al. Liver Trnsplnt 2006; 12:801-807
Study Aim • We describe rates and predictors of • Patient survival • AIDS-related opportunistic infections (OI) and neoplasms • Other serious infections with hospitalization (SI) • 125 liver transplant recipients • 150 kidney transplant recipients
Subjects • Standard transplant criteria • CD4 > 200 for kidney & 100 for liver recipients • Undetectable HIV RNA • or expected control post-transplant for liver recipients who could not tolerate antiretrovirals • Treated OIs except visceral KS, PML, chronic cryptosporidiosis
Predictors of Post-Transplant Mortality • Demographics: age, sex, race • HIV factors: CD4 at nadir, study enrollment, and pre-TX; viral load at enrollment and pre-TX; OI history • Transplant factors: HCV, BMI at enrollment and pre-TX, rejection, dual organ TX1 , MELD score pre-TX1, initial thymoglobulin use2 • Donor factors: HCV, age, marginal donor1 • Proportional hazards models 1 Liver 2 Kidney
Patient Survival • Median years follow-up post-transplant • Kidney: 2.3 [1.0, 3.7] • Liver: 2.7 [1.8, 4.0] • 1 & 3 year patient survival • Kidney: 95% (90%, 98%) & 91% (84%, 95%) • Liver: 80% (72%, 86%) & 67% (56%, 75%)
Factors Associated with Mortality: Kidney Recipients • HCV (HR 3.17; CI 1.10, 9.09; p=0.03) • Age (HR 1.06; CI 1.01, 1.11; p=0.03) Marginally initial thymoglobulin use (HR 2.63; CI 0.94, 7.31; p=0.06)
Factors Associated with Mortality: Liver Recipients • Dual organ TX (HR 4.86; 1.93, 12.2; p=0.0008) • Pre-TX BMI <21 (HR 2.74; 1.25, 5.98; p=0.01) • Donor age >40 (HR 2.23; 1.07, 4.64; p=0.03) Marginally HCV (HR 2.47; 0.95, 6.44; p=0.06) Marginally detectable enrollment viral load (HR 2.07; 0.89, 4.81; p=0.09)
Impact of Transplant on Mortality • This analysis includes BOTH recipients and waitlisted, eligible subjects • Add transplant status as a variable to proportional hazards models • Same baseline and pre-tx factors (no donor) • CD4, viral load and MELD as time-dependent covariates
Liver Yes MELD ≥15 HR: 0.09; 0.05, 0.16; p<0.0001 No…? MELD < 15 HR: 0.71; 0.27, 1.85; p=0.48 Kidney No… ? HR: 0.67; 0.31, 1.45; p=0.31 Transplant Associated Survival Benefit • Small sample size/event numbers limit power • for low MELD & kidney • Also evaluating quality of life
Opportunistic Infections • Post-transplant • 13 • 4 KS (all cutaneous) • 2 PCP • 1 cryptosporidiosis • 6 Candida (5 esophageal, 1 bronch.) • Pre-transplant • 52 (19%) had 90 OIs • 30 PCP • 8 CMV • 7 MAC • 3 KS Most Common OIs No recurrences in patients with OI history No survival differences based on OI history
There were many serious infections • 77 (51%) kidney recipients had 212 • 64% bacterial, 8% fungal, 10% viral, 17% culture negative/not done • 23% genitourinary, 20% respiratory, 19% blood • 70 (56%) liver recipients had 243 • 71% bacterial, 7% fungal, 5% viral, 1% protozoal, 17% culture negative/not done • 17% respiratory, 17% blood, 12% genitourinary
Factors Associated withInitial Serious Infection Kidney • HCV (HR 2.27; 1.33, 3.87; p = 0.003) • Initial thymo (HR 2.10; 1.25, 3.53; p = 0.01) • Nadir CD4 (HR 0.93; 0.87, 1.00; p=0.048) Liver • HCV (HR 2.34; 1.13, 4.83; p = 0.02) • *CD4 (HR 0.88; 0.80, 0.98; p = 0.02) • White race (HR 0.49; 0.28, 0.85; p = 0.01) * Time dependent covariate
Conclusions • Kidney survival is excellent • Liver transplant in high MELD confers survival benefit • HIV factors are not associated with mortality or the development of OI • No recurrent OIs in those with history of select OI • Serious infections requiring/during hospitalization were common • Baseline factors (BMI & need for dual organ transplant) may influence recommendations re: selection criteria in liver candidates Preliminary data; analyses currently being updated for publication
We’d like to acknowledge the participating transplant centers and their study investigators and study coordinators, too many to name. We also thank the study participants and donors and donor families! University of Miami Jorge Diego, MD (PI – K) Andreas Tzakis, MD, PhD (PI – L) David Roth, MD (Co-PI – K) Beth Israel Deaconess Douglas Hanto, MD, PhD (PI) Michael Wong, MD (Co-PI) Emory University Tom Pearson, MD, DPhil (PI) Rush University David Simon, MD, PhD (PI) Tulane University Douglas Slakey, MD (PI) Cleveland Clinic John Fung, MD, PhD (PI) Johns Hopkins Aruna Subramanian, MD (PI) Northwestern Tina Stosor, MD (PI) Richard Green, MD (Co-PI) University of Pittsburgh Margaret Ragni, MD, MPH (PI) Ron Shaprio, MD (Co-PI) Washington Hospital Center Jimmy Light , MD(PI) Mt. Sinai Barbara Murphy, MD(PI) Thomas Schiano, MD (Co-PI) Columbia University Lorna Dove, MD (PI) Jean Emond, MD (Co-PI) Georgetown University Lynt Johnson, MD (PI) University of Chicago J. Michael Millis, MD (PI) University of Cincinnati Kenneth Sherman, MD, PhD (PI) Rita Alloway, PharmD (Co-PI) University of California, SF Peter Stock, MD, PhD (PI) Michelle Roland, MD (Co-PI) Cedars-Sinai, LA Fred Poordad, MD (PI) Nicholas Nissen, MD (Co-PI) University of Maryland Robert Redfield, MD (PI) Stephen Bartlett, MD (Co-PI) Drexel Anil Kumar, MD (PI – Kidney) Burkhardt Ringe, MD (PI – Liver) Jeffrey Jacobson, MD (Co-PI) University of Virginia Kenneth Brayman, MD, PhD (PI) University of Pennsylvania Kim Olthoff, MD (PI) Emily Blumberg, MD (Co-PI)