d. serón nephrology department hospital vall d’hebron barcelona
DESCRIPTION
Interpretation of sequential protocol biopsies in terms of prognosis and clinical implications. D. Serón Nephrology Department Hospital Vall d’Hebron Barcelona. Biopsy. SCr m mol/l. 300 250 200 150 100 50 0. 12345years. Lesions are too advanced - PowerPoint PPT PresentationTRANSCRIPT
D. SerónNephrology DepartmentHospital Vall d’HebronBarcelona
Interpretation of sequential protocol biopsies
in terms of
prognosis and clinical implications
1 2 3 4 5 years
300
250
200
150
100
50
0
BiopsySCr mol/l
Lesions are too advanced
The biopsy was done too late
There is nothing we can do
The assumption that renal allograft histology
should be perfectly normal
during quiescence
has not been adequately investigated
Burdick JF et al, Transplantation 1984; 38: 679
Characteristics of early routine renal allograft biopsies
Protocol biopsies done at 1-4 weeksQuantification of interstitial infiltrates
with a morphometric technique in HE stained biopsies
Diagnosis N cel/mm2 interstitium__________________________________________ATN in native kidney 9 451 101Stable function 4 1290 179Post-transplant ATN 7 1335 182Acute rejection 5 2269 215*__________________________________________
Burdick JF et al, Transplantation 1984; 38: 679
Protocol biopsies
Are lesions observed in protocol biopsies relevant from the clinical point of view?
CAN in (2y) protocol biopsies predicts renal function deterioration
Graft function deterioration: SCr >20% at 2-4yCADI: interstitial inflammation & fibrosis + glomerular sclerosis +mesangial matrix increase + vascular intimal proliferation + tubular atrophy
Stable Deteriorated_________________________________________CADI 1.79 1.89 5.67 2.94 <0.0001_________________________________________
N = 94 patients
Isoniemi H, Transplantation 1994
Chronic lesions at 6m and graft survival
0 1 2 3years
100
80
60
40
20
0
CGD<6 (n=54)
CGD>6 (n=35)
p=0.0009
Dimény E, Clin Transplantation 1995; 58(11): 1195
N = 89 patients%graft survival
IF/TA is an independent predictor of graft survival
Serón D, Kidney Int 1997: 51:310
0 1 2 3 years
100
80
60
40
20
0
4 5 6 7
CAN=41
Normal=53
p=0.024
N=94 patients
% graft survival
RR 95% CI
_____________________________SCr 1.026 (1.005-1.0047)
(mol/l)CAN 5.98 (1.15-31.25)(yes vs. no) _____________________________
Sirius red derived VIntFib and time to graft failure
Grimm PC et al, J Am Soc Nephrol 2003
CAN, transplant vasculopathy and survival 3 m protocol Bx, n=282
0
20
40
60
80
100
0 20 40 60 80 100 120 meses
p < 0.001
% deatt censored graft survival
Normal
IF/TA (cv-score 1
Serón D, Transplantation 2000; 69: 1849
Univariate Multivariate
Variable RR 95%CI RR 95%CI
__________________________________SCr (mol/l) 1.009 (1.001-1.016) -
Prot (g/l) 1.002 (1.001-1.004) -
IF/TA 4.64 (1.44-14.95) 4.53(1.39-14.82)
IF/TA (cv-score) 13.61(3.73-49.62) 9.45 (2.32-38.41)
IF/TA
SCR + IF/TA and graft survival95 pediatric recipients from a living donor
Shishido et al, JASN 2003; 14: 1046
IF/TA without SCR
IF/TA with SCR
Normal
1 year protocol Bx
Predicting decline in allograft functionBiopsy at 1 year (living 69%), Tx 1998-2001, n=292
Primary endpoint: death censored graft loss or > 50% GFR beyond 1y
Cosio FG et al, Am J Transplant 2005
SCR, CAN and graft survivalProtocol Bx < 6m; n=435
Moreso F et al Am J Transplant 2006; 6: 747
.25
.5
.75
1
0 50 100 150 200 months
Normal=186
SCR=74
IF/TA=110
IF/TA+SCR=65
Function and structure are independent predictors of outcome
Moreso F et al. AJT 2006; 6: 747
Predictive value of clinical variables and different histological patterns on 7 y death censored graft
survival
n=361 pts, protocol Bx before 6 m, follow up > 7y
Surrogate Category Accuracy Sensitivity Specificity
______________________________________________________________
Acute rejection yes 72% 30% 80%
3-month SCr >1.8 mg/dl 73% 58% 76%
Protocol biopsy IF/TA 67% 65% 67%
Protocol biopsy IF/TA + cv-score 1 81% 21% 92%
Protocol biopsy IF/TA + SCR 78% 31% 86%
______________________________________________________________
Seron D & Moreso F. Kidney Int 200; 72:690
Poor predictive value of serum creatinine
for renal allograft loss 1st RT > 17y, 1988-1999, at least 2y follow up SCr > 1.8 mg/dl
Variable Follow up Obs %Failed OR CI AUC_____________________________________________________________________________SCr at 1y 2y 74480 7.2 2.22 2.13-2.31 0.627SCr at 1y 7y 35255 45.2 2.4 2.31-2.50 0.624
_____________________________________________________________________________
Kaplan B et al. AJT 2003; 3: 1560
While renal function is a strong risk factorand highly correlated with graft failure, theutility of renal function as a predictive toolfor graft loss is limited
GFR
AUC = 0.679 (0.581 - 0.777); p=0.001
Banff score
AUC = 0.685 (0.598 - 0.771); p=0.001
ROC AUC for graft failure at 5 yn=430 early protocol BX
Unpublished observation
Histology is not only a predictive variable but a surrogate variable
SRL and CsA withdrawal
Randomization 3m: n = 430
SRL+CsA, n = 215 SRL, n = 215
SRL> 5 ng/mL
CsA150 - 400
ng/mL
Steroids+ +
N = 525
Oberbauer R, Transpl Int 2005; 1: 22
A reduction in CADI score is associated with improved survival
Mota A et al., AJT 2004; 4: 953
Benefit Risk
Questions
How much contributes one protocol biopsy to predict outcome?
Two sequential protocol biopsies improve the predictive value of histology
Questions
How much contributes a protocol biopsy to predict outcome?
Two Sequential protocol biopsies improve the predictive value of histology?
Inclusion criteria
Protocol Bx < 6m
GFR (MDRD4) > 30 ml/min/1.73 m2
Proteinuria < 1g/day
Stable function
> 5 years of follow up
Protocol Bx > 12-24 m
EARLY Prot Bx LATE Prot Bx
Patients and biopsiesjune 88-december 2003
Bx < 6m 458 Bx 12-24m 250
Bx < 6m 430with tissue
Bx 12-24m 231with tissue
PREDICTIVE VALUE OF
ONE BIOPSY
n=430
Statistical approach
Cox proportional hazard model
a.) Predictive clinical variables
b.) Predictive clinical and histological variables
Characteristics of patientsn=430
Donor age 37±17Donor sex (%male) 70%Recipient age 46±14Recipient sex (%male) 63%PRA (%) 7.5±19HLA DR mm 0.63±0.58CIT (h) 22±6Retransplantation 64/430 (17.5%)VHC 16%DGF 17%Acute rejection 19%Graft loss 146 (33.2%) Death censored graft loss 104 (24.2%)
Time of biopsy (months) 4.3±1.7
GFR ml/min/1.73m2 53±14Proteinuria g/d 0.30±0.21
Histological data at the time of biopsyn=430
______________________________N glomeruli 13±8N arteries 5±4g 0.15±0.48i 0.58±0.68t 0.38±0.61v 0.01±0.11ah 0.16±0.45Acute score 1.13±1.31cg 0.13±0.34ci 0.46±0.64ct 0.45±0.62cv 0.20±0.54mm 0.25±0.45Chronic score1.24±1.65______________________________
Clinical variables and death censored graft survival
Variable Univariate Multivariate
RR (95% CI) P RR (95% CI) p
Donor age 1.013 (1.002-1.025) 0.027 1.02 (1.006-1.034) 0.004
Recipient age 0.98 (0.97-0.99) 0.015 0.96 (0.95-0.98) 0.000
PRA (%) 1.014(1.007-1.021) 0.000 1.011 (1.003-1.020) 0.008
GFR (ml/min) 0.97 (0.96-0.99) 0.000 0.98 (0.96-0.99) 0.004
HCV pos 2.29 (1.49-3.52) 0.000 1.56 (0.94-2.58) ns
Proteinuria mg/d 1.001 (1.000-1.002) 0.041 1.001 (1.000-1.001) ns
SCR - IF/TA
No SCR - IF/TA
SCR - no IF/TA
No SCR - no IF/TA
,5
,6
,7
,8
,9
1
Cum
. S
urv
ival
0 50 100 150 200 250
Time (months)
P = 0.037
SCR - IF/TA
no SCR - IF/TA
Histological diagnosis and graft survival
Clinical variables and death censored graft survival
Variable Univariate Multivariate
RR (95% CI) P RR (95% CI) p
Donor age 1.013 (1.002-1.025) 0.027 1.02 (1.007-1.034) 0.003
Recipient age 0.98 (0.97-0.99) 0.015 0.97 (0.95-0.98) 0.001
PRA (%) 1.014(1.007-1.021) 0.000 1.011 (1.003-1.020) 0.008
GFR (ml/min) 0.97 (0.96-0.99) 0.000 0.98 (0.96-0.99) 0.009
HCV (pos) 2.29 (1.49-3.52) 0.000 1.62 (0.99-2.67) ns
Proteinuria mg/d 1.001 (1.000-1.002) 0.041 1.001 (1.000-1.001) ns
SCR-IF/TA 1.92 (1.18-3.12) 0.009 1.75 (1.06-2.89) 0.029
Is it worth to include histology in multivariate models to predict graft
survival?
The contribution of histology to predict death-censored graft failure
Donor age Recipient age, PRA, GFR
Clinical variables
Clinical + histologicalvariables
Donor ageRecipient agePRAGFRHistology
Model 1 Model 2
The contribution of histology to predict death-censored graft failure
Donor age Recipient age, PRA, GFR
Clinical variables
Clinical + histologicalvariables
Donor ageRecipient agePRAGFRHistology
Model 1 Model 2
The contribution of histology to predict death-censored graft failure
Donor age yearsRecipient age yearsPRA %GFR ml/min/1.73m2
Histology yes/no
First classification of acute rejction
The contribution of histology to predict death-censored graft failure
Donor age yearsRecipient age yearsPARA %GFR ml/minHistology yes/no
risk
Beta coefficient of Cox regression model to calculate risk scores
Variable β coefficient β coefficientwithout histology with histology
___________________________________________________
Donor age (year) +0.020 (+2.0) +0.020 (+2.0)Patient age (year) -0.035 (-3.5) -0.035 (-3.5)GFR (ml/min) -0.024 (-2.4) -0.022 (-2.2)PARA (%) +0.011 (+1.1) +0.011 (+1.1)
SCR&IF/TA n.a. +0.559 (+55.9) ____________________________________________________
H(t)=H0(t) x exp (β1x1+ β2x2+ β3x3+…+ βkxk)
Beta coefficient of Cox regression model to calculate risk scores
Risk score without histology=(2*Donor age)+ (-3.5*patient age)+ (-2.4*GFR)+ (1.1*PRA)
Risk score with histology=(2*Donor age)+ (-3.5*patient age)+ (-2.2*GFR)+(1.1*PRA)+(55.9*SCR&IF/TA)
Q1 Q2Q3 Q4
Classification of patients according to risk scores
Risk score
Q1 Q2 Q3 Q4
Q1 99 5 1 O
Q2 6 92 6 2
Q3 0 9 81 16
Q4 0 0 18 87
With histologyW
ith
ou
t h
isto
log
y
p<0.0001
Changes in quartile classification due to inclusion of histology in the
statistical model:
15%
0
,2
,4
,6
,8
1
Cum
. S
urvi
val
0 50 100 150 200 250
Time
Q4
Q3
Q2
Q1
Death censored graft failure using quartiles of risk scores
Without histology
0
,2
,4
,6
,8
1
Cum
. S
urvi
val
0 50 100 150 200 250
Time
Q4
Q3
Q2
Q1
With histology
months months
Validation
Modelling sample
Testing sample
TWO BIOPSIES<6m and 12-24m
N=231
Two sequential biopsies N=231
6m 12-24m_____________________________________________Time of biopsy (M) 4.3±1.7 16.5±6.0
GFR ml/min/1.73m2 53±14 52±15 ns
Proteinuria g/d 0.30±0.21 0.37±0.49 0.01______________________________________________
Acute score Chronic score
P=0.0001P=0.003
progression
Reliability of IF/TA diagnosis
I II III
Protocol Bx
regression
2nd without 2nd with IF/TA IF/TA
_____________________________________
1st without IF/TA 54 (34.8%) 39 (25.2%)
1st with IF/TA 19 (12.2%) 43 (27.7%)
_____________________________________
N
Serón D et al. KI 2002; 61:727
Error associated with the diagnosis of IF/TA in sequential protocol biopsies
Progression to IF/TA 25.2%Regression of IF/TA 12.2%
25%
Sampling + intraobserver error
Serón D et al. KI 2002; 61:727
Two sequential Bx
1st Bx1st diagnosis
2ndBx2nd diagnosis
Integrated diagnosis
Prediction of graft survival
Interpretation of sequential protocol biopsies
in terms of prognosis and clinical implications Normal 2nd SCR 2nd IF/TA 2nd SCR+IFTA
2nd
Normal 1st 53 5 34 16
SCR 1st 15 4 12 7
IF/TA 1st 16 1 26 9
SCR+IF/TA 1st 9 1 15 8
IF/TA
IF/TA + SCR
SCR
normal
Two sequential biopsies (integrated diagnosis)
(n = 231)
,5
,6
,7
,8
,9
1
Cum
. Surv
ival
0 50 100 150 200 250 300
Time
IF/TA - SCR
IF/TA - no SCR
No IF/TA - SCR
No IF/TA - no SCR
p=0.04
SCR-IF/TANo SCR-IF/TASCR-noIF/TANoSCR-noIF/TA
,5
,6
,7
,8
,9
1
0 50 100 150 200 250 300
Time
P = 0.12
,5
,6
,7
,8
,9
1
0 50 100 150 200 250 300
Time
P = 0.29
Early and late biopsies(n=231)
Early Late
Comments
Histology contributes to better define patients at risk for graft failure
Two sequential biosies done 1 year apart increase the predictive value of histology on graft failure
Acknowledgements
F MoresoD Hernandez
M HuesoC Fernandez Gamiz
M GomàJM CruzadoO BestardJM GrinyoM Carrera