Transcript Title

HIV-Related Predictors and Outcomes
in 275 Liver and/or Kidney
Transplant Recipients
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.
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
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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
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We describe rates and predictors of
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Patient survival
AIDS-related opportunistic infections (OI) and
neoplasms
Other serious infections with hospitalization (SI)
125 liver transplant recipients
150 kidney transplant recipients
Subjects
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Standard transplant criteria
CD4 > 200 for kidney & 100 for liver recipients
Undetectable HIV RNA
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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
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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
1 Liver
Proportional hazards models
2 Kidney
Patient Survival
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Median years follow-up post-transplant
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Kidney:
Liver:
2.3 [1.0, 3.7]
2.7 [1.8, 4.0]
1 & 3 year patient survival
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Kidney: 95% (90%, 98%) & 91% (84%, 95%)
Liver: 80% (72%, 86%) & 67% (56%, 75%)
Factors Associated with Mortality:
Kidney Recipients
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2.
HCV
Age
(HR 3.17; CI 1.10, 9.09; p=0.03)
(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
1.
2.
3.
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
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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
Transplant Associated
Survival Benefit
Liver
 Yes
MELD ≥15
HR: 0.09; 0.05, 0.16;
p<0.0001
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No…?
Kidney
 No… ?
HR: 0.67; 0.31, 1.45; p=0.31
MELD < 15
HR: 0.71; 0.27, 1.85; p=0.48
•Small sample size/event numbers limit power
for low MELD & kidney
•Also evaluating quality of life
Opportunistic Infections
Pre-transplant
52 (19%) had 90 OIs
Post-transplant
13
– 30 PCP
– 8 CMV
– 7 MAC
– 3 KS
– 4 KS (all cutaneous)
– 2 PCP
– 1 cryptosporidiosis
– 6 Candida
Most Common OIs
(5 esophageal, 1 bronch.)
No recurrences in patients with OI history
No survival differences based on OI history
There were many serious infections
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77 (51%) kidney recipients had 212
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64% bacterial, 8% fungal, 10% viral, 17% culture
negative/not done
23% genitourinary, 20% respiratory, 19% blood
70 (56%) liver recipients had 243
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71% bacterial, 7% fungal, 5% viral, 1% protozoal,
17% culture negative/not done
17% respiratory, 17% blood, 12% genitourinary
Factors Associated with Initial
Serious Infection
Kidney
1.
HCV
(HR 2.27; 1.33, 3.87; p = 0.003)
2.
Initial thymo (HR 2.10; 1.25, 3.53; p = 0.01)
3.
Nadir CD4 (HR 0.93; 0.87, 1.00; p=0.048)
Liver
1.
HCV
(HR 2.34; 1.13, 4.83; p = 0.02)
2. *CD4
(HR 0.88; 0.80, 0.98; p = 0.02)
3.
White race (HR 0.49; 0.28, 0.85; p = 0.01)
* Time dependent covariate
Conclusions
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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 California, SF
Peter Stock, MD, PhD (PI)
Michelle Roland, MD (Co-PI)
University of Pittsburgh
Margaret Ragni, MD, MPH (PI)
Ron Shaprio, MD (Co-PI)
Cedars-Sinai, LA
Fred Poordad, MD (PI)
Nicholas Nissen, MD (Co-PI)
Washington Hospital Center
Jimmy Light , MD(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)
Mt. Sinai
Barbara Murphy, MD(PI)
Thomas Schiano, MD (Co-PI)
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)
Columbia University
Lorna Dove, MD (PI)
Jean Emond, MD (Co-PI)
Rush University
David Simon, MD, PhD (PI)
Georgetown University
Lynt Johnson, MD (PI)
Tulane University
Douglas Slakey, MD (PI)
University of Chicago
J. Michael Millis, MD (PI)
Cleveland Clinic
John Fung, MD, PhD (PI)
University of Cincinnati
Kenneth Sherman, MD, PhD (PI)
Rita Alloway, PharmD (Co-PI)
Johns Hopkins
Aruna Subramanian, MD (PI)
Northwestern
Tina Stosor, MD (PI)
Richard Green, MD (Co-PI)