1. Risk Stratification of Patients with Myelofibrosis and the Role of Transplant Alessandro M. Vannucchi Section of Hematology, University of Florence, Italy

2. 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

3. 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

4. VariableIPSSDIPSSDIPSS-plus Age >65 y  Constitutional symptoms  Hemoglobin <10 g/dL  Leukocyte count >25x10 9 /L  Circulating blasts > 1%  Platelet count <100x10 9 /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 Risk Stratification in PMF

5. International Prognostic Scoring System-IPSS Low Int-1 Int-2High Cervantes F et al. Blood 2009;113:2895-901 Points Median survival (mo) Low0 135 Int-11 95 Int-22 48 High>3>3 27

6. Dynamic IPSS (DIPSS) Passamonti F et al. Blood 2010;115:1703-8 Points Median survival (mo) Low0 Not reach. Int-11-2 170 Int-23-4 48 High5-6 18

7. DIPSS-Plus Gangat N et al, J Clin Oncol 2011; 29:392-7 Risk group No. predictors Median survival, y Low015.4 Int-116.5 Int-22-32.9 High>4>41.3

8. Vaidya R et al. Blood 2011;117:5612-5615 Prognostically Detrimental Effect of Monosomal Karyotype

9. “Very-High Risk” Patients: >80% Mortality At 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 >40x10 9/ L other unfavorable karyotype

10. Improving Survival Trends in PMF 1980-1995 1996-2007 1980-1995 1996-2007 1980-1995 1996-2007 1980-1995 1996-2007 Age <65 yAge >65 y IPSS Int-2/HighIPSS Low/Int-1 P=0.01P=0.02 P=0.11 Cervantes F et al. JCO 2012; 24:2891-7.

11. Causes of Death in PMF Cervantes F et al. Blood 2009;113:2895-901 31% 19% 14% 10% 5% 4% 13%

12. Causes of Death in PMF Cervantes F et al. Blood 2009;113:2895-901 31% 19% 14% 10% 5% 4% 13%

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)

14. 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

15. 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 Overall Survival Leukemia-free Survival Mutations of EZH2 are found in  6% of PMF subjects Prognostic Impact of Mutations in PMF

16. Risk-Adapted MF Treatment Algorithm Obtain DIPPS/DIPPS-plus score Interm-2 / High risk AsymptomaticSymptomatic Observation Conventional drug therapy Ruxolitinib* Conventional drug therapy Ruxolitinib* Consider SCT Investigational drug therapy Investigational drug therapy Refractory NO MyA: <45-50y RI : 45-65y MyA: <45-50y RI : 45-65y YES Conventional drug therapy Ruxolitinib* Conventional drug therapy Ruxolitinib* Refractory MyA, Myeloablative RI, Reduced Intensity Low risk / Interm-1 * FDA approved for Interm/high-risk

17. Myeloablative Allogeneic SCT for Myelofibrosis PtsMed. AgeOSTRM Guardiola (1999)554247% (5y)27% Deeg (2003)564358% (3y)32% Ballen (2010) Sibling 170 45 39% (5y) 22% MUD 117 47 31% (5y) 42%

18. Allogeneic SCT for Myelofibrosis Rondelli (2005) 2154 85% (2.5y)10 Kröger (2005)215384% (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 (%)

19. A «High-Risk Feature» for Transplant Outcome Low risk= 0-1 variables High 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%) VariableHR Spleen >22 cm2.8 RBC units >203.9 Alternative donor3.4

20. 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, ASH2012 High-risk category: RR 2.22 vs low-risk

21. Potential Impact of JAK2 Inhibitors on MF Treatment Pathway McLornan DP, BJH 2012; 157:413-25

22. 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?