risk stratification of p atients with m yelofibrosis and the r ole of t ransplant
DESCRIPTION
Risk Stratification of P atients with M yelofibrosis and the R ole of T ransplant. 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. - PowerPoint PPT PresentationTRANSCRIPT
Risk Stratification of Patients with Myelofibrosis and the Role of Transplant
Alessandro M. VannucchiSection of Hematology,
University of Florence, Italy
Survival in PMF: the IPSS Cohort
N= 1,054
Median: 69 mo (95% CI, 61-76)
Cervantes F et al. Blood 2009;113:2895-901.
reference
0.0
0.2
0.4
0.6
0.8
1.0P
roba
bilit
y
0 2 4 6 8 10 12 14 16 18 20 22 24 26Years
1980 - 1995 1996 - 2007
Whole series: actuarial survival (± 95% CI)according to period of diagnosis
p < 0.0001
Improving Survival Trends in PMF
Cervantes F et al. JCO 2012; 24:2891-7.
Median survival: 4.6 versus 6.5 y
Variable IPSS DIPSS DIPSS-plusAge >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;113:2895-901Passamonti et al, Blood 2010; 115:1703-8
Gangat N et al, J Clin Oncol 2011; 29:392-7
Risk Stratification in PMF
International Prognostic Scoring System-IPSS
Low
Int-1Int-2High
Cervantes F et al. Blood 2009;113:2895-901
Points Median survival
(mo)
Low 0 135
Int-1 1 95
Int-2 2 48
High >3 27
Dynamic IPSS (DIPSS)
Passamonti F et al. Blood 2010;115:1703-8
Points Median survival
(mo)
Low 0 Not reach.
Int-1 1-2 170
Int-2 3-4 48
High 5-6 18
DIPSS-Plus
Gangat N et al, J Clin Oncol 2011; 29:392-7
Risk group
No.predictors
Median survival, y
Low 0 15.4
Int-1 1 6.5
Int-2 2-3 2.9
High >4 1.3
Vaidya R et al. Blood 2011;117:5612-5615
Prognostically Detrimental Effect of Monosomal Karyotype
“Very-High Risk” Patients: >80% MortalityAt 2 Years
Tefferi A et al. Blood 2011; 118:4595-8
Low (3%)
Int-1 (11%)
Int-2 (26%)High (53%)
Very High (82%)
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
Improving Survival Trends in PMF
0.0
0.2
0.4
0.6
0.8
1.0
Rel
ativ
e su
rviv
al
0 1 2 3 4 5 6 7 8 9 10Years from diagnosis
1980-1995 1996-2007
IPSS risk groups high & intermediate-2Relative survival by year of PMF diagnosis
0.0
0.2
0.4
0.6
0.8
1.0
Rel
ativ
e su
rviv
al
0 1 2 3 4 5 6 7 8 9 10Years from diagnosis
1980-1995 1996-2007
IPSS risk groups low & intermediate-1Relative survival by year of PMF diagnosis
0.0
0.2
0.4
0.6
0.8
1.0
Rel
ativ
e su
rviv
al
0 1 2 3 4 5 6 7 8 9 10Years from diagnosis
1980-1995 1996-2007
Age >= 65 yearsRelative survival by year of PMF diagnosis
0.0
0.2
0.4
0.6
0.8
1.0
Rel
ativ
e su
rviv
al
0 1 2 3 4 5 6 7 8 9 10Years from diagnosis
1980-1995 1996-2007
Age < 65 yearsRelative survival by year of PMF diagnosis
1980-1995
1996-2007
1980-1995
1996-2007
1980-1995
1996-2007
1980-1995
1996-2007
Age <65 y Age >65 y
IPSS Int-2/HighIPSS Low/Int-1
P=0.01 P=0.02
P=0.02 P=0.11
Cervantes F et al. JCO 2012; 24:2891-7.
Causes of Death in PMF
Cervantes F et al. Blood 2009;113:2895-901
31%
19%
14%
10%
5%
4%
4%
13%
Causes of Death in PMF
Cervantes F et al. Blood 2009;113:2895-901
31%
19%
14%
10%
5%
4%
4%
13%
Risk of Leukemia Transformation in MF
Bjorkholm M et al, JCO 2011; 29: 2410-15.
SIR(95%CI)
Primary Myelofibrosis 63.8(42.7-91.6)
DIPSS Predicts Progression to Leukemia in PMF
Passamonti F et al, Blood 2010; 116:2857-8
• 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
Guglielmelli P et al. Blood 2011; 118;19:5227-34
• In multivariate analysis, EZH2 mutated status was an IPSS-independent variable significantly associated with reduced OS (P=0.016)
P< 0.001
EZH2 WT
EZH2 mut
P= 0.028
EZH2 WT
EZH2 mut
Ove
rall
Surv
ival
Leuk
emia
-free
Sur
viva
l
• Mutations of EZH2 are found in 6% of PMF subjects
Prognostic Impact of Mutations in PMF
Risk-Adapted MF Treatment Algorithm
Obtain DIPPS/DIPPS-plus score
Interm-2 / High risk
Asymptomatic Symptomatic
Observation
•Conventional drug therapy• Ruxolitinib*
Consider SCT
Investigationaldrug therapy
Refractory
NOMyA: <45-50y RI : 45-65y
YES
•Conventional drug therapy• Ruxolitinib*
Refractory
MyA, MyeloablativeRI, Reduced Intensity
Low risk / Interm-1
* FDA approved for Interm/high-risk
Myeloablative
Allogeneic SCT for Myelofibrosis
Pts Med. Age OS TRM
Guardiola (1999) 55 42 47% (5y) 27%
Deeg (2003) 56 43 58% (3y) 32%
Ballen (2010) Sibling 170 45 39% (5y) 22% MUD 117 47 31% (5y) 42%
Allogeneic SCT for Myelofibrosis
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) ---
Reduced intensity Pts Med. Age OS (%) TRM (%)
A «High-Risk Feature» for Transplant Outcome
Low risk= 0-1 variablesHigh risk= >2 variables
Bacigalupo A, BMT 2010; 45:458-63 ; Bacigalupo et al, ASH2012
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%)
Variable HR
Spleen >22 cm 2.8
RBC units >20 3.9
Alternative donor 3.4
Scott B L et al. Blood 2012;119:2657-2664
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, ASH2012High-risk category: RR 2.22 vs low-risk
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?