Transcript Syphilis

Analysis and Review of Clinical and Scientific
Findings of Preservation Solutions to
Minimize Donor Organ Damage
March 26 and April 1, 2009
1
Histidine-Tryptophan-Ketoglutarate
Solution Vs. University of Wisconsin
Solution for Deceased Donor Liver
Transplantation: Analysis of SRTR
Database
John Fung, MD, PhD
Chairman of the Department of General Surgery
Cleveland Clinic
Purpose
• This analysis aims to evaluate the impact of the organ
preservation solutions (OPS) ,(Histidine-TryptophanKetoglutarate (HTK) vs. University of Wisconsin (UW) solution)
on the outcome of adult deceased donor liver transplantation
(DDLT) using the Scientific Registry of Transplant Recipient
(SRTR) database.
Materials and Methods
Only adult first liver-only transplants from 2002-2006. We
included only those for whom both flush and storage solutions
were the same. Risk-unadjusted graft survival was estimated
non-parametrically by the method of Kaplan and Meier, and
parametrically by a multiphase hazard decomposition method
Statistical Analysis
• Risk factors for graft survival were determined
using nonproportional, multiphase,
multivariable hazard methodology. This
methodology allows modeling of recipient,
donor, and procedure variables in all phases
of the hazard model simultaneously.
Bootstrap aggregating was used for variable
selection with a probability for inclusion of
.001; variables appearing in at least 50% of
bootstrap analyses were considered reliably
statistically significant at p<.001.
Patients
• The data set included 20,908 patients, 17,559 (84%) with UW
and 3349 (16%) with HTK solutions. Mean follow-up was 2.9 ±
1.5 years (3.0 ± 1.5 years for UW and 1.9 ± 1.0 years for HTK).
We defined an early phase (EP) shortly after DDLT followed by
a constant phase (CP) of hazard for graft failure.
Results
• Significant predictors of graft failure in the EP after DDLT
include the following recipient factors: older age, race either
White or Black, portal vein thrombosis, last creatinine and last
MELD for the transplant (tx) candidacy, on life support just prior
to tx, and previous kidney tx.
Risk Factors for Graft Failure Early Phase
Risk Factor
P
Bootstrap %
Early hazard phase
Older recipient age (years)
<.0001
93
.0005
69
Recipient portal vein thrombosis
<.0001
95
Recipient previous abdominal surgery
<.0001
48
Candidate last creatinine (used for MELD)
<.0001
86
Candidate last MELD
<.0001
71
Recipient on life support just prior to tx
<.0001
100
Recipient previous kidney transplant
<.0001
90
Donor race non-White
<.0001
67
Donor donation after cardiac death
<.0001
100
Donor risk index
<.0001
46
Recipient race White or Black
Risk Factors for Graft Failure Constant Phase
Risk Factor
P
Bootstrap %
Constant hazard phase
African American recipient
<.0001
97
Recipient tumor (incidental) at transplant
<.0001
88
Recipient primary diagnosis for tumors
<.0001
87
Recipient hepatitis C virus
<.0001
100
Donor age (years)
<.0001
97
Donor history of diabetes
<.0001
77
Results
• Significant donor factors in the EP are: race other than White,
donation after cardiac death (DCD) and donor risk index (DRI).
OPS did not appear as a statistically significant predictor of graft
failure.
Results
• OPS was not statistically significant (p=.06, EP; p=.2, CP).
Hospital death, re-transplant rates (overall and within 14 days of
initial transplant) and relisting rates (overall and within 30 days
of tx) were similar (p>0.05).
Patient Survival - Donor >65
•
•
•
•
Donor Age > 65
N=1698 UW
N= 311 HTK
p=.46 log rank
test
Patient Survival - Donor <65
•
•
•
•
Donor Age <65
N=15861 UW
N= 3038 HTK
p=.28 log rank
test
Patient Survival - DCD Donor
•
•
•
•
DCD Donor
N=570 UW
N=159 HTK
p=.73 log rank
test
Patient Survival - Non-DCD
Donor
• Non-DCD
Donor
• N=16989 UW
• N=3190 HTK
• p=.55 log rank
test
Patient Survival - DRI >2.5
•
•
•
•
Donor DRI >2.5
N=8663 UW
N=1682 HTK
p=.25 log rank
test
Patient Survival - DRI <2.5
•
•
•
•
Donor DRI <2.5
N=6600 UW
N=1218 HTK
p=.37 log rank
test
Graft Survival - Donor Age >65
•
•
•
•
Donor Age >65
N=1698 UW
N= 311 HTK
p=.64 log rank
test
Graft Survival - Donor Age <65
•
•
•
•
Donor Age <65
N=15861 UW
N= 3038 HTK
p=.045 log rank
test
Graft Survival - DCD Donor
•
•
•
•
DCD Donor
N=570 UW
N=159 HTK
p=.17 log rank
test
Kaplan-Meier Adult Graft Survival
Primary Deceased Donor Liver Transplants
2000-2006
Survival Rate (%)
.
100
90
80
70
60
50
40
30
20
10
0
0
2
4
6
8 10 12 14 16 18 20 22 24 26 28 30 32 34 36
Months Post Transplant
DBD
DCD-UW
DCD-HTK
SRTR
Includes adult, primary, liver alone transplants
Graft Survival - Non-DCD Donor
• Non-DCD
Donor
• N=16989 UW
• N=3190 HTK
• p=.23 log rank
test
Graft Survival - DRI >2.5
•
•
•
•
Donor DRI >2.5
N=8663 UW
N=1682 HTK
p=.053 log rank
test
Graft Survival - DRI <2.5
•
•
•
•
Donor DRI <2.5
N=6600 UW
N=1218 HTK
p=.15 log rank
test
Analyzing Studies
• In addition to the common underlying OPTN
data, SSAF files include extra ascertainment
of outcomes from SSDMF, and from crosslinking of records within the OPTN data for
the same person. Files are linked by a patient
key so that the entire history of a particular
person can be studied. The extent to which
these links are made, and the specific
matching process, may be different between
the two sets of files.
SRTR Information Flow
Monthly
Transfer
OPTN
Person
Linking
SRTR
CMSESRD
SSDMF
SEER
Data
Quality
Analysis File Creation
Data
Fixes
Feedback
OPTN
MPSC
OPOSpecific
Reports
Data Use Agreements
Standard
Analysis
Files
Center-Specific Analyses
CenterSpecific
Reports
NCHS,
AHA, etc
Reorganization for Research
Cleaning and Validation
Analysis Variables Added
Public
Release
External
Research
Analytical Procedures and Products
TAC
RFI
Journal
Articles
Conference
Present’ns
OPTN,
ACOT
Committees
Annual,
Biennial
Reports
Hopkins UNOS Analysis
Used casewise deletion of missing data, i.e.
threw out cases that were missing any of the
predictor variables they were studying. Doing
this can potentially bias the results. It means
they are using only patients for whom all
variables were reported - and these patients
might come from centers where they are
more diligent about data reporting, etc.
Implications of Casewise
Deletions
• While they do say that data were missing for less than 4% of
covariates, if the missing values were scattered over 20% of
patients, then 20% of total data might have been deleted.
• Example:
– SRTR CIT data: 100% complete
– UNOS CIT data: 86% complete
Critique
• Last transplant included was 2/28/08 - the
paper was submitted on 7/17/08. Assuming
that it took 45 days to analyze and write the
paper, then it would be safe to say that the
data cutoff was 6/1/08, meaning that the last
patients only had a 3 month followup. However, the first recipient follow-up form
required by UNOS is at 6 months and then
they only release data after a 60 day period
for completion, meaning that for a 6/1/08
cutoff, they only have data for transplants
performed before 11/1/07.
%
Unvalidate…
Validation of Follow-Up Forms by Year
100%
50%
Pr
eU…
0%
0 … Months
6 after
12Form18
is
Source: SRTR analyses, August 2003 for the 2003 OPTN/SRTR Annual Report, Figure II-4.
Other Considerations
• Slightly different timeframes:
– is there a change in clinical practice?
– is there a learning curve for new users of HTK?
• Do the conclusions make sense?
– Recipient age 18-34 HR 1.14
– COD - CVA, HR 1.04 (SRTR HR 1.16)
– COD - DCD, HR 1.97 (SRTR HR 1.51)
Does Not Fit Clinical Impressions
• Cleveland Clinic DCD experience
– 15 controlled DCD LTX preserved with HTK since
2005
– Heparin could not be given prior to declaration of death
– Mean donor age was 38 ± 12 years
– Mean WIT and CIT was 25 ± 9 min and 427 ± 97 min,
respectively
– No recipient developed ITBS. PNF was seen in one
recipient who was salvaged with retransplantation
Analysis and Review of Clinical and Scientific
Findings of Preservation Solutions to
Minimize Donor Organ Damage
Richard S. Mangus, MD, MS
Assistant Professor of Surgery and Transplant Surgeon
Transplant Division, Department of Surgery
Indiana University, School of Medicine
March 26 and April 1, 2009
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Disclosure
Dr. Mangus has participated in the advisory board and speaker’s
bureau for Essential Pharmaceuticals in the last 12 months.
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Assessment of Scientific Research
•
Systematic assessment of data quality
•
Study types:
Expert opinion
Non-experimental studies (questionnaire)
Observational studies (retrospective analysis)
Non-randomized parallel cohort studies (prospective)
Randomized, blinded, prospective trial (RCTs)
Systematic review and meta-analysis of randomized trials
•
Issues:
CONFOUNDING
Relevance
Accuracy
Timeliness
Bias
Timeliness
Comparability
Reproducibility
Incomplete data
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Randomized, controlled trials (RCTs)
•
Kidney
1 European, 3-year follow-up
1998, n = 650 transplants, Deceased donors
•
Pancreas
1 European
2009, n=68 transplants
•
Liver
3 European
1994 (n=60) – Deceased donors
2003 (n=30) – Living donors
2005 (n=40) – Deceased donors
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Kidney preservation
Transplants:
HTK 332, UW 312
DGF:
Need for dialysis 2 or more times
during first 7-days post-transplant
Flush volume:
HTK 5 – 6 L
UW 1 – 2 L
EC
4L
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Kidney preservation
de Boer, et al, Transpl Proc, 1999; 31: 2065
40
Kidney preservation
de Boer, et al, Transpl Proc, 1999; 31: 2065
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Kidney preservation
Lynch RJ, et al. AJT 2008; 8:567-73
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Kidney preservation
Post-transplant kidney graft survival
Living Donor:
HTK n=475
UW n=475
Deceased donor:
HTK n=317
UW n=317
Lynch RJ, et al. AJT 2008; 8:567-73
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Pancreas preservation
Transplants:
68 transplants over 18 months at 4 centers
Outcomes:
6-month graft survival –
NO DIFFERENCE
Graft function –
NO DIFFERENCE
Fasting BG C-peptide level
HbA1c
Insulin requirement
Flush volume:
HTK
UW
5–8L
3L
n=41
n=67
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Pancreas preservation
Figure 1. No insulin requirement
Figure 2. Serum amylase level
Figure 3. Serum lipase level
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Pancreas preservation
Figure 4. C-peptide level
Figure 5. Units exogenous insulin
Figure 6. HbA1c
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Pancreas preservation
Indiana University, 2003 to 2007
N = 310
HTK 262, UW 48
Simultaneous, retrospective
1-year graft survival – 91% (U.S. 79-86%)
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Pancreas preservation
•
ISSUES:
Graft pancreatitis
Alonso D, et al. Increased pancreatitis in allografts flushed with
histidine-tryptophan-ketoglutarate solution: a cautionary tale.
AJT 2008; 8: 1942-45.
• Overall rate of graft pancreatitis 28/97 (29%)
• Two centers, retrospective, low volume (HTK 16, UW 81)
Flush volume
• 10 L likely too much and may cause pancreas graft injury from
edema (related to low viscosity and high volume flush)
• Indiana University –
3000-4000cc routinely
no graft pancreatitis
graft thombosis rate 3-4%
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Liver preservation
3 Randomized Studies:
1. Erhard J, et al. Comparison of HTK versus UW for organ preservation in human liver
transplantation: A prospective, randomized study. Transplant International 1994; 7: 177-81.
• 60 deceased donor liver transplants (HTK n=30 and UW n=30)
• No difference in early and late graft survival, even for 7 donor livers with cold ischemia time >15 hrs
• More late biliary complications in UW group.
• Higher initial transaminases in HTK group.
2. Testa G, et al. HTK versus UW in living donor liver transplantation: results of a prospective
study. Liver Transplantation 2003; 9(8): 822-26.
• 30 consecutive living donor right lobe transplants flushed alternately with HTK (n=16) or UW (n=14)
• Patients were randomly allocated based upon timing of transplantation
• 1-year post-transplant, there is no difference in graft and patient survival, liver enzymes and complications
3. Nardo B, et al. Preliminary results of a clinical randomized study comparing Celsior and HTK
solutions in liver preservation for transplantation. Transpl Proc 2005; 37:320-2.
• European randomized trial comparing Celsior and HTK.
• No difference in initial function or survival up to 1-year post-transplant.
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Liver preservation
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Liver preservation
Indiana University, 2001 to 2008
All adult, deceased donor
n=1013
HTK 632, UW 381
Simultaneous, retrospective
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Liver preservation
Indiana University, 2001 to 2008
Post-liver transplant serum ALT, n=1013
600
All adult, deceased donor
Simultaneous, retrospective
500
HTK 632 UW 381
HTK
300
UW
Serum ALT
200
100
0
0
5
10
15
20
25
30
35
Days post-transplant
Post-liver transplant serum total bilirubin, n=1013
4
3.5
Serum total bilirubin
n=1013
Serum ALT
400
3
2.5
HTK
2
UW
1.5
Serum
Bilirubin
1
0.5
0
0
5
10
15
20
25
30
35
Days post-transplant
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Recent retrospective database reviews
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Recent retrospective database reviews
• Data review:
– Usually large database is better to increase numbers
– In large transplant research, single center better to maintain
homogeneous patient, donor and management factors
• Database review
– Only as strong as weakest data
– Selection bias ->
• Do surgeons who use HTK differ from those that use UW ?
• Multiple comparisons dilute findings
• CONFOUNDING – database differences likely just highlight differences
in practice patterns between surgeons who use HTK and those who
use UW
– Kidney study – exclude all machine pumped kidneys
– Pancreas study – unable to differentiate high risk grafts
– Liver study – no ability to analyze steatosis, hypernatremia, etc
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Summary
•
All randomized controlled trials across multiple organs, countries and time
periods demonstrate no difference in clinical outcomes between HTK and UW
•
Large single center case series across multiple organs, countries and time
periods consistently demonstrate no difference in clinical outcomes between
HTK and UW
•
Question of appropriate flush volume - of particular importance to the
pancreas
•
Recent database reviews of tens of thousands of patients likely reflect
difference in practice patterns between surgeons who use HTK and those
who use UW. Unlikely to represent a true difference in the clinical outcomes
of the two solutions when higher quality studies show no difference.
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