Transcript Int-1 - Imedex

Risk Stratification of Patients with
Myelofibrosis and the Role of
Transplant
Alessandro M. Vannucchi
Section of Hematology,
University of Florence, Italy
Survival in PMF: the IPSS Cohort
reference
Median: 69 mo
(95% CI, 61-76)
N= 1,054
Cervantes F et al. Blood 2009;113:2895-901.
Improving Survival Trends in PMF
Whole series: actuarial survival (± 95% CI)
according to period of diagnosis
1.0
p < 0.0001
Probability
0.8
0.6
0.4
0.2
0.0
0
2
4
6
8
10
12 14
Years
1980 - 1995
16
18
20
22
24
26
1996 - 2007
Median survival: 4.6 versus 6.5 y
Cervantes F et al. JCO 2012; 24:2891-7.
Risk Stratification in PMF
Variable
IPSS
DIPSS
DIPSS-plus
Age >65 y



Constitutional symptoms



Hemoglobin <10 g/dL



Leukocyte count >25x109/L



Circulating blasts > 1%



Platelet count <100x109/L

RBC transfusion need

Unfavorable karyotype

+8,-7/7q-,i(17q),inv(3), -5/5q-,12p-, 11q23 rearr.
Cervantes et al, Blood 2009;113:2895-901
Passamonti et al, Blood 2010; 115:1703-8
Gangat N et al, J Clin Oncol 2011; 29:392-7
International Prognostic Scoring System-IPSS
Points
Median
survival
(mo)
Low
0
135
Int-1
1
95
Int-2
2
48
High
>3
27
Low
High
Int-2
Int-1
Cervantes F et al. Blood 2009;113:2895-901
Dynamic IPSS (DIPSS)
Points
Median
survival
(mo)
Low
0
Not reach.
Int-1
1-2
170
Int-2
3-4
48
High
5-6
18
Passamonti F et al. Blood 2010;115:1703-8
DIPSS-Plus
Risk
group
No.
Median
predictors survival, y
Low
0
15.4
Int-1
1
6.5
Int-2
2-3
2.9
High
>4
1.3
Gangat N et al, J Clin Oncol 2011; 29:392-7
Prognostically Detrimental Effect of
Monosomal Karyotype
Vaidya R et al. Blood 2011;117:5612-5615
“Very-High Risk” Patients: >80% Mortality
At 2 Years
Very-High risk variables
•
monosomal karyotype
•
inv(3)/i(17q)
or any 2 of the following:
•
PB blasts >9%
•
WBC >40x109/L
•
other unfavorable karyotype
Low (3%)
Int-1 (11%)
High (53%)
Int-2 (26%)
Very High (82%)
Tefferi A et al. Blood 2011; 118:4595-8
Improving Survival Trends in PMF
Age <65 y
Age >65 y
Relative survival by year of PMF diagnosis
Relative survival by year of PMF diagnosis
Age >= 65 years
Age < 65 years
1.0
1.0
0.8
1996-2007
Relative survival
Relative survival
0.8
0.6
0.4
0.6
1996-2007
0.4
1980-1995
0.2
0.2
P=0.01
P=0.02
0.0
0.0
0
1
2
3
4
5
6
Years from diagnosis
1980-1995
7
8
9
0
10
1
2
3
4
5
6
Years from diagnosis
1980-1995
1996-2007
IPSS Low/Int-1
7
8
9
10
1996-2007
IPSS Int-2/High
Relative survival by year of PMF diagnosis
Relative survival by year of PMF diagnosis
IPSS risk groups high & intermediate-2
IPSS risk groups low & intermediate-1
1.0
1.0
0.8
0.8
1996-2007
Relative survival
Relative survival
1980-1995
0.6
0.6
1980-1995
0.4
P=0.02
0.2
1996-2007
0.4
P=0.11
0.2
1980-1995
0.0
0.0
0
1
2
3
4
5
6
Years from diagnosis
1980-1995
7
8
1996-2007
9
10
0
1
2
3
4
5
6
Years from diagnosis
1980-1995
7
8
9
10
1996-2007
Cervantes F et al. JCO 2012; 24:2891-7.
Causes of Death in PMF
13%
4%
4%
5%
10%
14%
19%
31%
Cervantes F et al. Blood 2009;113:2895-901
Causes of Death in PMF
13%
4%
4%
5%
10%
14%
19%
31%
Cervantes F et al. Blood 2009;113:2895-901
Risk of Leukemia Transformation in MF
SIR
(95%CI)
Primary Myelofibrosis
63.8
(42.7-91.6)
Bjorkholm M et al, JCO 2011; 29: 2410-15.
DIPSS Predicts Progression to Leukemia in PMF
• The risk of progression to blast phase is 7.8-fold (Int-2) or 24.9-fold
(High) higher compared with Low/Int-1 category
Passamonti F et al, Blood 2010; 116:2857-8
Prognostic Impact of Mutations in PMF
Overall Survival
P< 0.001
EZH2 WT
EZH2 mut
Leukemia-free Survival
• Mutations of EZH2 are found in 6% of PMF subjects
P= 0.028
EZH2 WT
EZH2 mut
• In multivariate analysis, EZH2 mutated status was an IPSS-independent
variable significantly associated with reduced OS (P=0.016)
Guglielmelli P et al. Blood 2011; 118;19:5227-34
Risk-Adapted MF Treatment Algorithm
Obtain DIPPS/DIPPS-plus score
Low risk / Interm-1
Asymptomatic
Interm-2 / High risk
Symptomatic
Consider SCT
NO
•Conventional
drug therapy
• Ruxolitinib*
Refractory
Observation
* FDA approved for Interm/high-risk
•Conventional
drug therapy
• Ruxolitinib*
YES
MyA: <45-50y
RI : 45-65y
Refractory
Investigational
drug therapy
MyA, Myeloablative
RI, Reduced Intensity
Allogeneic SCT for Myelofibrosis
Myeloablative
Pts
Med. Age
OS
TRM
Guardiola (1999)
55
42
47% (5y)
27%
Deeg (2003)
56
43
58% (3y)
32%
Ballen (2010)
Sibling
MUD
170
117
45
47
39% (5y)
31% (5y)
22%
42%
Allogeneic SCT for Myelofibrosis
Reduced
intensity
Pts
Med. Age
OS (%)
TRM (%)
Rondelli (2005)
21
54
85% (2.5y)
10
Kröger (2005)
21
53
84% (3y)
16
Bacigalupo (2010)
46
51
45% (5y)
24
Alcalby (2010)
162
57
22% (5y)
22
Gupta (ASH2012)
222
55
37% (5y)
---
A «High-Risk Feature» for Transplant Outcome
Low risk= 0-1 variables
High risk= >2 variables
Variable
HR
Spleen >22 cm
2.8
RBC units >20
3.9
Alternative donor
3.4
Updated this ASH, 70 patients.
Actuarial 10-yr survival is 66% vs 20% for low vs high risk (P<0.001), due to both
higher TRM (38% vs 9%) and relapse related deaths (35% vs 21%)
Bacigalupo A, BMT 2010; 45:458-63 ; Bacigalupo et al, ASH2012
OS After SCT is Predicted by DIPPS Score
«Lille scoring system rather than DIPSS is a better predictive of overall mortality after
allo SCT using reduced intensity conditioning»
Gupta V, ASH2012
High-risk category: RR 2.22 vs low-risk
Scott B L et al. Blood 2012;119:2657-2664
Potential Impact of JAK2 Inhibitors on MF
Treatment Pathway
McLornan DP, BJH 2012; 157:413-25
Conclusions
• High-performance clinical risk score systems (IPSS
and derivatives) allow risk stratification of PMF
patients
• Novel cytogenetic and molecular information might
improve categorization
• Risk stratification is useful for therapeutic decisions,
mainly for referral to SCT, the only curative approach
• SCT performance is better in low risk categories
• SCT repositioning in the JAK2 inhibitors era?