Prognostic Factors in the Blastic and Accelerated Phase of Patients with Chronic Myeloid Leukemia (CML) in the Tyrosine Kinase Inhibitor (TKI) Era

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 3786-3786
Author(s):  
Young Kwang Chae ◽  
Hagop M. Kantarjian ◽  
Carlos G. Romo ◽  
Clay Whitaker ◽  
Elias J. Jabbour ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Prognostic Factors ◽  
Ace Inhibitors ◽  
Research Funding ◽  
Chronic Phase ◽  
Initial Diagnosis ◽  
Favorable Outcome ◽  
Spleen Size ◽  
Platelet Counts ◽  
Concurrent Use

Abstract Abstract 3786 With the advent of TKIs, significant improvement has been made in the survival outcome of CML patients. Many prognostic factors have in identified in chronic phase CML patients. However, prognostic factors in blastic phase (BP) and accelerated phase (AP) of CML patients have not been previously investigated, especially in the era of TKIs. We have analyzed CML patients either been diagnosed in or progressed into BP or AP from 2000 to 2010 enrolled into the clinical trials with different TKIs such as imatinib, nilotinib, dasatinib, and bosutinib at MD Anderson Cancer Center. All demographic, clinicopathologic variables and medication data including TKIs and other medication were collected at the time of the diagnosis of BP or AP. Primary outcomes; progression free survival (PFS) and overall survival (OS) were defined as time from diagnosis of either BP or AP to treatment failure and death, respectively. Among a total of 260 CML patients, mean age was 51.4 (SD 14.1). Males were 59%. Caucasians were 72%; African-Americans, 12%; and Hispanics, 14%. Only 17% reached complete hematologic remission and 62% eventually died during the follow up (mean 4.1 yrs, SD 4.0 yrs). 26% were in BP and 74% in AP. 38 patients were in BP (n=9) or AP (n=29) at initial diagnosis. Mean time from initial diagnosis in chronic phase to BP or AP was 4.1 yrs (0 to 23 yrs). Among BP, 17% had lymphoid BP and 84% myeloid BP. Cytogenetic analysis at diagnosis demonstrated 38% had only Philadelphia chromosome (Ph) present while 62% had other chromosomal abnormalities besides Ph. 30% had received one or more prior TKI by the time of transformation. 64% started on monotherapy imatinib (no prior TKI), 15% nilotinib (86% prior TKI), 14% dasatinib (93% prior TKI), and 3% bosutinib (100% prior TKI); 3.5% received imatinib combined with other agents (57% prior monotherapy with imatinib). Median PFS was 0.7 yr and median OS, 2.4 yrs. Factors linked with worse PFS were higher bone marrow (BM) blast % (HR=1.01, p<0.001), higher peripheral blood (PB) blast % (HR=1.01, p<0.001), higher PB basophil % (HR=1.01, p=0.02), lower PB polymononuclear cells (HR=0.98, p<0.001), lower hemoglobin (HR=0.91, p=0.02), lower platelet counts (HR=0.99, p=0.045), and higher number of prior TKI treatments (HR=1.52, p<0.001). In AP, compared to other TKIs, imatinib was associated with superior PFS (HR=0.63, p=0.03) while nilotinib was linked with inferior PFS (HR=1.81, p=0.04). Dasatinib (HR=1.17, p=0.57) and bosutinib (HR=1.85, p=0.18) did not show difference in PFS. In BP, there was no difference in OS by TKIs. Concurrent use of ACE inhibitors, ARBs, statins, aspirin, or metformin with TKIs was not associated with change in PFS. In multivariate analysis adjusting for the above variables, only prior TKI use was associated with worse PFS (adjusted HR [AHR]=1.57, p=0.001). Imatinib (AHR=0.70, p=0.36) nor dasatinib (AHR=0.67, p=0.11) were no longer associated with favorable or unfavorable PFS. Factors associated with inferior OS were old age (HR=1.02, p<0.001), bigger spleen size (HR=1.03, p=0.001), higher BM blast % (HR=1.02, p<0.001), higher PB blast % (HR=1.02, p<0.001), lower PB polymononuclear cells (HR=0.98, p<0.001), lower hemoglobin (HR=0.80, p<0.001), lower platelet counts (HR=0.99, p=0.008), higher LDH (HR=1.0002, p<0.001), presence of other cytogenetic abnormality besides Ph (HR=1.45, p=0.03),and higher number of prior TKI treatments (HR=1.64, p<0.001). In AP, imatinib was associated with more favorable OS (HR=0.65, p=0.07) compared to others (nilotinib: HR=1.28, p=0.47; dasatinib: HR=1.70, p=0.077; bosutinib: HR=1.09, p=0.88). In BP, there was no difference in OS by TKIs. Concurrent use of ACE inhibitors, ARBs, statins, aspirin, or metformin with TKIs was not associated with change in OS. In multivariate analysis adjusting for the above variables, only age (AHR=1.01, p=0.002) and BM blast% (AHR=1.02, p=0.005) were associated with worse OS. Imatinib was no longer associated with favorable outcome (AHR=1.27, p=0.57). In conclusion, we identified spleen size, blast counts, and number of prior TKI use as major prognostic factors in CML patients in BC or AP. Imatinib was associated with favorable outcome. This is likely due to the fact that patients treated with imatinib had received no prior TKIs while most patients treated with 2nd generation TKI had. Further studies are required to validate our findings in a larger and prospective cohort. Disclosures: Kantarjian: Novartis: Research Funding; Bristol Myers Squibb: Research Funding; Ariad: Research Funding; Pfizer: Research Funding. Jabbour:Bristol Myers Squibb: Honoraria; Pfizer: Honoraria; Novartis: Honoraria. Cortes:Pfizer: Consultancy, Research Funding; Bristol Myers Squibb: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Ariad: Consultancy, Research Funding.

scholarly journals Baseline Characteristics of CML Patients Accross Europe - Comparing Real-World Patients with Patient Collectives Included in Clinical Trials

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 3160-3160 ◽  
Author(s):  
Michele Baccarani ◽  
Verena Sophia Hoffmann ◽  
Gianantonio Rosti ◽  
Fausto Castagnetti ◽  
Susanne Saussele ◽  
...  
Keyword(s):  
Real World ◽  
Clinical Studies ◽  
Research Funding ◽  
Chronic Phase ◽  
Population Based ◽  
Costal Margin ◽  
Spleen Size ◽  
Newly Diagnosed ◽  
Baseline Characteristics ◽  
Population Based Registry

Abstract Introduction: Most of the knowledge about treatments and outcome of CML patients originates from clinical studies. To get new and unbiased insights in the epidemiology, treatment and outcome of CML, the EUTOS population-based registry of newly diagnosed CML patients was established, - as part of the European Treatment and Outcome Study (EUTOS) for CML. The aim was to collect the data of all adults with newly diagnosed CML, irrespective of treatment and of enrolment in studies. Patients and Methods: The EUTOS population-based registry collected data of newly diagnosed CML patients, 18 years or older, over a specified period of time from 2008 till 2012 living in defined regions. The data were collected by 22 study groups in 20 European countries. Data were gathered via a web-based CRF-system. For comparison we used the already published data from five Company-sponsored registration studies IRIS (O’Brien et.all, NEJM, 2003), TOPS (Cortes et al, JCO, 2009) ENESTnd (Saglio et al, NEJM, 2010), DASISION (Kantarjian et al, NEJM, 2010) and BELA (Cortes et al, JCO, 2012), from three Investigator-sponsored studies GIMEMA (Castagnetti et al, JCO, 2010 and Gugliotta et al, Blood, 2011), French SPIRIT (Preudhomme et al, NEJM, 2010) and German CML IV (Hehlmann et al, JCO, 2011) and from two single referral centers HAMMERSMITH (De Lavallade et al, JCO, 2008) and MDA (Jain et al, Blood, 2013). Results: Till 15.05.2014 2978 patients were registered in the EUTOS Population-based registry. 94.3% of the patients were diagnosed in chronic phase (CP), 3.6% in accelerated phase (AP), and 2.2% in blastic phase (BP). For the calculation of the prognostic scores 361 patients had to be excluded because they were pretreated. For the comparison we used 2350 patients in Chronic Phase with laboratory values before any treatment. 54% of the patients in the EUTOS Population-based registry were male, less than in all studies (56.6 - 60.6%). The median age at diagnosis was 56 years, higher than in all studies (46 - 55). In EUTOS the proportion of patients more than 60 years and more than 65 years old was 40.4 % and 21.9 % respectively. Similar data were rarely reported in all other studies. Median value of the spleen size below costal margin was 0. 46.1% of the patients had a palpable spleen and 15.2% had a spleen size ≥ 10 (spleen size is always reported in cm under costal margin in this abstract). The % of palpable spleen is only reported by IRIS, 25.0% and by the FRENCH Spirit group, 49.8%. The median spleen is only reported by GIMEMA, 2.0. Spleen size ≥ 10 is reported by IRIS, 6.0%, ENESTnd, 12.4% and HAMMERSMITH 25.5%. While the median values for Platelets and Hemoglobin show no big differences, the median WBC in EUTOS is 83.9 x109/l and in the Company-sponsored registration studies: IRIS 18-20 x109/l , in ENESTnd 23-26 x109/l, in DASISION 23-25 x109/l , and in BELA 22-23 x109/l, in the Investigator-sponsored studies: GIMEMA 55 x109/l , in the FRENCH SPIRIT 83-104 x109/l , in the GERMAN CML IV 75-91 x109/l , and in the single referral center study HAMMERSMITH 140 x109/l, clearly indicating that in company-sponsored, registration studies, the reported values of the WBC were not recorded prior to any treatment. The median values for Blasts, Basophils and Eosinophils show also not so big differences. The % of Sokal low risk patients is in EUTOS with 34.5% lower than in all studies (35.2 - 60%) with the exception of HAMMERSMITH 28.9%. Discussion: The EUTOS Population-based registry provides the first European wide real-world series of patients with newly diagnosed Ph+, BCR-ABL+ CML. The age and sex distribution and some baseline characteristics such as Sokal Score as well as median WBC count in the EUTOS population-based registry are different from many prospective studies. This should be taken in due consideration before extrapolating the results of treatment studies to real life. Spleen size, which is known as an important value for prediction, is only very rarely reported in clinical studies. With further follow-up, this registry will provide a population-based insight on treatment, survival, and causes of death. Disclosures Baccarani: Novartis, BMS, Pfizer, Ariad: Consultancy, Honoraria, Speakers Bureau. Hoffmann:Novartis: Research Funding. Rosti:Novartis: Consultancy, Honoraria; Bristol Myers Squibb: Consultancy, Honoraria. Castagnetti:Novartis: Consultancy, Honoraria; Bristol Myers Squibb: Consultancy, Honoraria; Pfizer: Consultancy. Saussele:Novartis: Honoraria, Research Funding; Bristol Myers Squibb: Honoraria, Research Funding; Pfizer: Honoraria. Steegmann:Novartis, BMS, Pfizer: Honoraria, Research Funding. Mayer:Ariad: Consultancy, Research Funding; Bristol Myers Squibb: Consultancy, Research Funding; Novartis: Consultancy, Research Funding. Turkina:Novartis: Consultancy, Honoraria; Bristol Myers Squibb: Consultancy, Honoraria. Zaritskey:Novartis: Consultancy. Clark:Novartis Pharmaceuticals Corporation: Honoraria, Research Funding, Speakers Bureau; Bristol Myers Squibb: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding. Porkka:BMS: Honoraria; BMS: Research Funding; Novartis: Honoraria; Novartis: Research Funding; Pfizer: Research Funding. Hehlmann:Novartis: Research Funding; Bristol-Myers Squibb: Research Funding. Hasford:Novartis: Research Funding. Lindoerfer:Novartis: Research Funding.

Improved Survival in Chronic Myeloid Leukemia (CML) Since the Introductin of Imatinib Therapy - A Single Institution Historical Experience

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 2750-2750
Author(s):  
Hun Lee ◽  
Jorge E. Cortes ◽  
Susan O'Brien ◽  
Elias Jabbour ◽  
Guillermo Garcia-Manero ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Median Survival ◽  
Myeloid Leukemia ◽  
Research Funding ◽  
Chronic Phase ◽  
Imatinib Therapy ◽  
Blastic Phase ◽  
Group A ◽  
The Impact ◽  
Over Time

Abstract Abstract 2750 Background: Outcome of CML since introduction of imatinib therapy has improved. Aims: analyze improvement of CML outcome in different phases. Study Group: A total of 1,569 patients with CML referred since 1965, within 1 month from diagnosis, were reviewed and used to identify phase-specific prognostic factors: 1,148 chronic, 175 accelerated, 246 blastic. Results: The median survival was 8.9 years in chronic, 4.8 years in accelerated, and 6 months in blastic phase. In chronic phase, the 8-year survival was ≤ 15% before 1983, 42–65% from 1983 to 2000, and 87% since 2001 (Figure 1). Survival was worse in older patients (p=0.004), but less significant since 2001 (p=0.07). Survival by Sokal risk was significantly different before 2001 (p<0.001), but not since 2001 (p=0.4). In accelerated phase, survival improved over time (p<0.001); the 8-year survival in patients treated since 2001 was 75% (Figure 2). Survival by age was not different in years < 2001 (p=0.09), but was better since 2001 in patients ≤ 70 years (p=0.004). Multivariate analysis derived adverse factors since 2001: older age (p=0.049), increased marrow blasts (p=0.03). In blastic phase, the median survival improved over time (p<0.001), although it is only 7 months since 2001. Conclusions: Survival in CML significantly improved significantly since 2001, particularly so in chronic and accelerated phases. Imatinib therapy minimized the impact of known prognostic factors and Sokal risk in chronic phase, and accentuated the impact of age in accelerated and blastic phases. Disclosures: Cortes: Novartis: Consultancy; Novartis: Research Funding; BMS: Consultancy, Research Funding; Ariad: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding. Kantarjian:Novartis: Consultancy; Novartis: Research Funding; Pfizer: Research Funding; BMS: Research Funding.

Post Transplant Lymphoproliferative Disorders (PTLD) after Solid Organ Transplant: Cleveland Clinic Experience

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 3008-3008 ◽  
Author(s):  
Deepa Jagadeesh ◽  
Sharjeel Hooda ◽  
Kathleen B Fenner ◽  
Lisa Rybicki ◽  
Robert M Dean ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Prognostic Factors ◽  
Median Time ◽  
Research Funding ◽  
Lung Transplant ◽  
Lymphoproliferative Disorders ◽  
Large Cohort ◽  
Age At Diagnosis ◽  
Solid Organ ◽  
Post Transplant

Abstract Background: Post transplant lymphoproliferative disorders (PTLD) are rare pathologically and clinically heterogeneous diseases arising in the setting of immunosuppression following hematopoietic stem cell and solid organ transplants (SOT). Our understanding of PTLD is restricted by its low incidence and heterogeneous treatment approaches, resulting in paucity of data. We sought to further describe characteristics and outcomes in PTLD patients who underwent treatment at our institution. Methods and Patients: We performed a retrospective study to describe our institutional experience in a relatively large cohort of PTLD patients after SOT. Patient and disease characteristics were examined and prognostic factors for survival were determined using univariate and multivariate Cox analysis. Results: Between May 1987 to January 2014, 98 patients with a confirmed diagnosis of PTLD underwent treatment at our institution. Median time from SOT to PTLD diagnosis was 60 months with median follow of 68 months from PTLD diagnosis. Baseline characteristics include male gender 77%, ECOG performance status (PS) 0-1 in 61%, and stage III-IV 69% with a median age at diagnosis of 47 years. Most common transplanted organ included heart 30%, lung 24%, kidney 20% and liver 19% and median time from SOT to PTLD diagnosis was 60 months. Most cases had monomorphic histology (81%) and were EBV+ (82%). Graft involvement and rejection were observed in 32% and 43% respectively. Of the 84% with extranodal (EN) involvement, gastrointestinal tract (37%) and lung (27%) were the common sites, while 3.2% had bone marrow (BM) involvement. Central nervous system (CNS) was involved in 11% of the cases. Only 58% received rituximab as part of the initial therapy, as significant part of our cohort was treated prior to rituximab era. Reduction in immunosuppression (73%), chemotherapy (40%), radiation (11%) and surgery (8%) were utilized either as single modality or in combination for treatment. Of the 66 patients with response data, 59% had complete response (CR) and 14% had progressive disease (PD). Relapse occurred in 23% of cases. Median overall survival (OS) from diagnosis of PTLD was 6 years (Figure 1), but in rituximab treated patients it was 8 years. On univariate analysis, higher age at diagnosis (HR 1.19, 95% CI 1.01-1.40, p=0.033), lung transplant (HR 2.42, 95% CI 1.36-4.33, p=0.003), higher IPI (HR 1.83, 95% CI 1.40-2.39, p=<0.001), decreased PS (HR 2.43, 95% CI 1.70-3.48, p=<0.001), and platelet count <200,000 (HR 2.84, 95% CI 1.27-6.33, p=0.011) were associated with lower OS, whereas liver transplant (HR 0.24, 95% CI 0.09-0.68, p=0.007) and GI involvement (HR 0.47, 95% CI 0.24-0.95, p=0.036) predicted better OS. Rituximab treatment (Figure 2) and achieving CR were associated with better OS. Histology, EN involvement, and EBV status were not significant predictors for survival. On multivariate analysis only lung transplant, IPI, and PS were predictive for OS. Lung transplant patients had a higher risk of mortality compared to other SOT (HR 2.63, 95% CI 1.39-4.95, p=0.003). Both higher IPI (HR 1.66, 95% CI 1.18-2.32, p=0.003) and poor PS (HR 1.94, 95% CI 1.27-2.96, p=0.002) were associated with inferior OS. Conclusions: In this large cohort of PTLD patients after SOT, lung transplants, higher IPI and poor PS were identified as poor prognostic factors for OS on both univariate and multivariate analysis. Rituximab treatment was a favorable prognostic factor for OS that resulted in prolonged survival observed in this cohort. Figure 1 Figure 1. Figure 2 Figure 2. Disclosures Hill: Millenium: Research Funding; Novartis: Research Funding.

Use of First or Second Generation TKI for CML after Allogeneic Stem Cell Transplantation: a Study By the CMWP of the EBMT

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 4685-4685 ◽  
Author(s):  
Yves Chalandon ◽  
Simona Iacobelli ◽  
Jennifer Hoek ◽  
Linda Koster ◽  
Liisa Volin ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Stem Cell ◽  
Stem Cell Transplantation ◽  
Cell Transplantation ◽  
Research Funding ◽  
Chronic Phase ◽  
Time Interval ◽  
Hematopoietic Stem ◽  
Persistent Disease ◽  
Factors Influencing

Abstract Background: Patients (pts) relapsing with CML after allogeneic hematopoietic stem cell transplantation (alloHSCT) may be treated with tyrosine kinase inhibitors (TKI) and/or donor lymphocyte infusions (DLI). As nowadays the majority of CML patients would have received at least imatinib prior to transplantation, we were interested in analizing a) the type of TKI used after alloHSCT, b) the indication for TKI treatment, c) the outcome of this treatment and d) the temporal relationship with DLI if given. Patients and methods: 435 pts received TKI after first allogeneic HSCT for CML for different reasons. Transplants had been performed in first chronic phase (CP1, n=194), accelerated phase (AP, n= 60) or for more advanced disease (blast crisis (BC)/> CP1, n=177) from HLA identical siblings (n=231) or unrelated donors (n=204) between 2000 and 2013. TKI given prior to transplant was imatinib (n=268), dasatinib (n=162), nilotinib (n=88), bosutinib (n=4) and ponatinib (n=7). Median age at transplant was 44 (18.5-68) years, 274 pts (63%) were male. TKI post alloHSCT were given between 2000 and 2015. 1st TKI given was either imatinib (n=223), dasatinib (n=131), nilotinib (n=67), bosutinib (n=2) or ponatinib (12). The indications for TKI therapy were the same as for transplantation (n=262), for relapse/progression/persistent disease (n=124), for prophylaxis/pre-emptive (n=32), planned (n=5), others (n=8) and missing (n=4). Results: Median follow-up from start of TKI was 55 (1-171) months. The median time interval from transplant to TKI was 6 (0.2-165) months. It was longer for TKI given for relapse/progression with 15 (1-89) months and shorter for TKI given for prophylaxis/pre-emptive with 1.6 (0.2-43) months. It was longer for imatinib with 11 (0.2-121) months vs 3.8 (0.2-165) months for other TKI. Imatinib as 1st TKI was mainly given for relapse/progression/persistent disease (48%) and the other TKI for the same reason as for transplantation (83%). 103/223 (46%) of pts with imatinib, 99/131 (76%) with dasatinib, 55/67 (82%) with nilotinib and 11/14 (79%) with bosutinib/ponatinib post-transplantation had been treated with imatinib prior to transplantation. In total, 196 (45%) patients received DLI after alloHSCT, of which 63/435 (14.5%) had DLI prior to TKI post-alloHSCT, 19/435 (4.4%) had DLI at the same time of TKI and 114/435 (26%) had DLI post-TKI. Best response after TKI was complete molecular remission in 17.7%, cytogenetic remission in 4.4%, hematological remission in 20.2% and no response/progression/relapse in 57.7% of pts. 50% of pts treated with imatinib had a response (molecular/cytogenetic/hematological) vs 34% with nilotinib, 33% with dasatinib and 33% with bosutinib/ponatinib, p=0.014. OS was 60% (55-65%) at 5 years. It was 66% (60-73%) with imatinib vs 51% (42-60%) with other TKI, p=0.0024. 5 years RFS was 47% (42-53%). It was 53% (46-60%) with imatinib vs 40% (32-48%) with other TKI, p=0.0102. 5 years RI was 25% (21-30%). It was 21% (16-27%) with imatinib vs 31% (24-38%) with other TKI, p=0.0454. 5 years NRM was 27% (23-32%). It was 26% (20-31%) with imatinib vs 29% (22-36%) with other TKI, p=0.365. In multivariate analysis for OS, imatinib vs other TKI post-transplant did not show anymore an effect, HR 1.19 (0.85-1.67), p=0.317. Factors influencing OS were time from diagnosis to transplant, HR 1.01 (1.00-1.01), p=0.009, AP vs CP1, HR 1.80 (1.11-2.91), p=0.017 and BC/>CP1 vs CP1, HR 2.3 (1.58-3.33), p<0.0001. In multivariate analysis for RFS as for OS, imatinib vs other TKI did not have an effect, HR 1.11 (0.83-1.48), p=0.496. Other factors having a tendency or influencing RFS were time from diagnosis to transplant, HR 1.00 (1.00-1.01), p=0.054, AP vs CP1, HR 1.52 (1.00-2.31), p=0.050 and BC/>CP1 vs CP1, HR 2.11 (1.55-2.88), p<0.001. Conclusion: These data suggest that TKI after alloHSCT induce a response in about 42% of pts regardless of the type of TKI used and that time from diagnosis to transplantation as well as the phase of disease at transplant remain the main factors influencing the outcome of CML patients relapsing after alloHSCT. Disclosures Kröger: Riemser: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Neovii: Honoraria, Research Funding; Sanofi: Honoraria, Research Funding.

scholarly journals Clinical Significance of Clonal Cytogenetic Heterogeneity (CCH) at Diagnosis in Adult Patients with Acute Lymphoblastic Leukemia (ALL)

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 2820-2820
Author(s):  
Hiroaki Shimizu ◽  
Nahoko Hatsumi ◽  
Satoru Takada ◽  
Takuma Ishizaki ◽  
Akihiko Yokohama ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Prognostic Factors ◽  
Research Funding ◽  
Clonal Evolution ◽  
Statistical Significance ◽  
Prognostic Impact ◽  
Common Ancestry ◽  
Complex Karyotype ◽  
Abnormal Karyotype ◽  
Cytogenetic Abnormalities

Abstract Background:Although cytogenetic abnormalities at diagnosis are recognized as one of the most potent prognostic factors in acute leukemia patients, CCH acquisition at diagnosis, which are considered as a result of clonal evolution of leukemia cells, is not taken into account in prognostic classifications. Recent studies reported that CCH acquisition was observed in 24 - 32% of adult AML patients with abnormal karyotype, was more likely to occur in patients with older age and complex karyotype, and showed adverse prognostic impact. However, the clinical significance of CCH acquisition has not been investigated in adult ALL patients to date. Patients and methods: Of the 238 adult ALL patients diagnosed between 1990 and 2016, 120 patients with abnormal karyotype at diagnosis, who underwent intensive chemotherapy, were included in this study. CCH was defined as presence of two or more cytogenetically abnormal clones. A defined ancestral clonal evolution included either mother-daughter and/or branched patterns. In the mother-daughter pattern, a daughter clone showed all cytogenetic abnormalities of a mother clone plus additional abnormality(s), which define a distinct subclone. In a branch pattern, all subclones possessed common cytogenetic abnormalities suggesting presence of a common ancestry, but each subclone acquires unique additional abnormality(s), which define them as distinctive subclones. Both patterns of cytogenetic clonal evolution were sometimes seen in a patient. Composite karyotypes were applied to patients where a common ancestry could not be clearly determined because of too complicated cytogenetic findings. Fisher's exact test was used to compare binary variables. The logistic regression model was used for multivariate analysis of predisposing factors. Overall survival (OS) was estimated with the Kaplan-Meier method and compared using the log-rank test. The Cox proportional hazard model was used for multivariate analysis of prognostic factors. Values of p < 0.05 were considered to indicate statistical significance. Results:Of the 120 patients included in this study, 64 patients were male, and 56 were female. The median age was 50 years (range, 16-79 years). Karyotypes at diagnosis were Philadelphia chromosome (Ph) in 56 patients, complex in 15, and t(8;14) in seven. According to the definition described above, 47 patients (39%) showed CCH at diagnosis, and two (4%) among them were categorized as composite karyotype. Of the 45 patients harboring a defined ancestral clonal evolution, numbers of subclones were two, three, and four in 32 patients (68%), 11 (24%), and 2 (4%), respectively. Mother-daughter pattern, branched pattern, and both were seen in 34 patients (76%), 5 (11%), and 6 (13%). In univariate analysis for predisposing factors of CCH acquisition, only younger age was significantly associated with CCH acquisition (48% in age <= 50 vs. 29% in age > 50; p = 0.04), but not karyotype. This statistical significance was confirmed with multivariate analysis (odds ratio = 0.44; p = 0.03). When investigating the prognostic impact of CCH acquisition, patients were divided into Ph-negative or Ph-positive ALL groups. In the 64 Ph-negative ALL patients, the CR rates were not significantly different between patients with or without CCH (78% vs. 78%, respectively; p = 1.00). The OS rates were similar between two groups (26% vs. 39% at five years, respectively; p = 0.56). Multivariate analysis for OS revealed that complex karyotype and t(8;14) were independent prognostic factors, but not CCH acquisition. Likewise, in the 56 Ph-positive ALL patients, CCH acquisition was not significantly associated with the CR rates (92% vs. 78%, respectively; p = 0.27), and the OS rates did not significantly differ between the two groups (34% vs. 40% at five years, respectively; p = 0.90). In multivariate analysis for OS, no independent prognostic factor was identified. Conclusion: Adult ALL patients with abnormal karyotype acquired CCH at diagnosis with a frequency comparable to that of AML patients. However, unlike AML patients, CCH acquisition was more frequently observed in younger population and did not show any prognostic impact in ALL patients. These findings suggested that biological backgrounds of CCH acquisition at diagnosis were possibly different between in patients with ALL and AML. So, to confirm these important findings, clinical studies with larger study subjects are warranted. Disclosures Handa: Celgene: Honoraria, Research Funding, Speakers Bureau; Takeda: Consultancy, Honoraria, Research Funding, Speakers Bureau.

Varying Importance of Prognostic Factors in Subgroups of Myelodysplastic Syndromes Defined by Blast Count, Cytogenetic Risk Group, or WHO Classification.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 2776-2776
Author(s):  
Andrea Kuendgen ◽  
Corinna Strupp ◽  
Kathrin Nachtkamp ◽  
Barbara Hildebrandt ◽  
Rainer Haas ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Prognostic Factors ◽  
High Risk ◽  
Research Funding ◽  
Risk Group ◽  
Univariate Analysis ◽  
Risk Groups ◽  
High Risk Group ◽  
Intermediate Risk ◽  
Blast Count

Abstract Abstract 2776 Poster Board II-752 Introduction: We wondered whether prognostic factors have similar relevance in different subpopulations of MDS patients. Methods: Our analysis was based on patients with primary, untreated MDS, including 181 RA, 169 RARS, 649 RCMD, 322 RSCMD, 79 5q-syndromes, 290 RAEB I, 324 RAEB II, 266 CMML I, 64 CMML II, and 209 RAEB-T. The impact of prognostic variables in univariate analysis was compared in subpopulations of patients defined by medullary blast count, namely <5%, ≥5% (table), ≥10%, and ≥20% (not shown), as well as 3 subpopulations defined by the cytogenetic risk groups according to IPSS (table). Multivariate analysis of prognostic factors was performed for cytogenetically defined subgroups and WHO-subtypes. Results: Strong prognostic factors in all blast-defined subgroups were hemoglobin, transfusion dependency, increased WBC, age, and LDH. However, all variables became less important in patients with ≥20% blasts (RAEB-T) and increased WBC was rare. Platelet count and cytogenetic risk groups were relevant in patients with <5%, ≥5%, and ≥10% marrow blasts, but not in RAEB-T. Marrow fibrosis was important in patients with <5% or ≥5% blasts, but not ≥10%. Gender and ANC <1000/μl were significant only in patients with a normal blast count. Furthermore, we looked for the effect of the karyotypes, relevant for IPSS scoring (-Y, del5q, del20q, others, del7q/-7, complex), and found a comparable influence on survival, irrespective whether patients had < or ≥5% marrow blasts. In subpopulations defined by cytogenetic risk groups, several prognostic factors were highly significant in univariate analysis, if patients had a good risk karyotype. These included hemoglobin, sex, age, LDH, increased WBC, transfusion need, and blast count (cut-offs 5%, 10%, and 20%). In the intermediate risk group only LDH, platelets, WBC, and blasts were significant prognostic factors, while in the high risk group only platelets and blast count remained significant. Multivariate analysis was performed for the cytogenetic risk groups and for subgroups defined by WHO subtypes. The analysis considered blast count (</≥5%), hemoglobin, platelets, ANC, cytogenetic risk group, transfusion need, sex, and age. In the subgroup including RA, RARS, and 5q-syndrome, LDH, transfusion, and age in descending order were independent prognostic parameters. In the RCMD+RSCMD group, karyotype, age, transfusion, and platelets were relevant factors. In the RAEB I+II subgroup, the order was hemoglobin, karyotype, age, and platelets, while in CMML I+II only hemoglobin had independent influence. In RAEB-T none of the factors examined was of independent significance. Looking at cytogenetic risk groups, in the favorable group, several variables independently influenced survival, namely transfusion, blasts, age, sex, and LDH (in this order). Interestingly, in the intermediate and high risk group, only blast count and platelets retained a significant impact. Conclusion: Univariate analysis showed prognostic factors (except ANC) included in IPSS and WPSS are relevant in most subgroups defined by marrow blast percentage. However, they all lose their impact if the blast count exceeds 20%. Regarding cytogenetic risk groups, several prognostic factors lose their influence already in the intermediate risk group. This underscores the prognostic importance of MDS cytogenetics. Multivariate analysis showed MDS subpopulations defined by WHO types also differ with regard to prognostic factors. In particular, CMML and RAEB-T stand out against the other MDS types. Disclosures: Kuendgen: Celgene: Honoraria. Hildebrandt:Celgene: Research Funding. Gattermann:Novartis: Honoraria, Participation in Advisory Boards on deferasirox clinical trials. Germing:Novartis, Celgene: Honoraria, Research Funding.

Effects Of Ruxolitinib Therapy On Megakaryocyte Morphology and Inflammatory Bone Marrow Reaction In Patients With Myelofibrosis

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 4056-4056 ◽  
Author(s):  
Hans Michael Kvasnicka ◽  
Juergen Thiele ◽  
Carlos E. Bueso-Ramos ◽  
Shilpa Kamalanabhaiah ◽  
Jorge E. Cortes ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Research Funding ◽  
Plasma Cells ◽  
Size Reduction ◽  
Published Data ◽  
Spleen Size ◽  
Ongoing Research ◽  
Hematopoietic Stem ◽  
Platelet Counts ◽  
Median Change

Abstract Background Bone marrow (BM) microenvironment plays an important role in the initiation and progression of myelofibrosis (MF). The dysregulation of proinflammatory cytokine production by both hematopoietic stem cells via JAK-activating mutations and surrounding stromal cells generates a microenvironment that is functionally linked to disease-associated increase in BM fibrosis, constitutional symptoms, splenomegaly, and extramedullary hematopoiesis. It has been shown that proliferation of atypical megakaryocytes (MK) and their pathologic interaction with the marrow stroma plays a central role in MF. Recent data indicate that ruxolitinib (RUX) treatment results in a reduction in the level of cytokines and other inflammatory markers. However, it is still not clear whether these effects are reflected by corresponding BM changes, in particular with regard to macrophages (MAK), plasma cells (PL) and morphology of MK. Methods A total of 46 patients (pts) with MF presenting at baseline with various degrees of BM fibrosis (grade 1: n=8; grade 2: n=24; grade 3: n=14) were selected from a MD Anderson Cancer Center phase 1/2 study (NCT00509899). All cases had a sequential BM biopsy taken at 24 months (mo) following RUX therapy. Analysis included immunohistochemical and morphometric assessment of MK (overall frequency, degree of clustering and dysplastic changes), amount of erythropoiesis (ERY), frequency of macrophages (MAK) and plasma cells (PL). Specific antibodies were applied to identify these subpopulations (CD61 – MK; Glycophorin C [Ret40f] – ERY; CD68 [PGM-1] – MAK; MUM1 – PL). Individual changes were calculated for each parameter and correlated with clinical features. Results Following therapy the majority of pts revealed a stabilization or improvement of BM fibrosis (improvement: 13%, stabilization: 57%, worsening: 30%). In line with previously published data an increased number of MAK was found at baseline independent of BM fibrosis grade. In 56% of pts therapy induced a reduction of MAK, 37% pts revealed no effect, and 3 cases showed an increase (7%). As indicator of an underlying inflammatory stroma reaction, about half of the pts displayed increased numbers of PL at baseline. In the majority of pts amount of PL remained stable (64%), 24% had a reduction, and 12% showed a further increase. Initially 80% of cases presented with a marked increase in MK, however, frequency was reduced over therapy in about 50%. Dense clustering of MK was slightly decreased (baseline 63% vs 24 mo 39%), but no significant treatment effect was observed concerning evolution of myelodysplastic features. In most cases a significant reduction of hematopoietic cellularity was encountered (median change -36%). Therapy had no significant effect on ERY (median change -5%). Pts with increased numbers of MAK at 24 mo had a greater spleen size reduction compared to those with reduced MAK during therapy (median change -13.5 vs -6.5 cm; Mann-Whitney U test: p=0.006). Therapy induced increase in MAK was not associated with hemoglobin levels at 24 mo (median change -0.2 vs -0.9 g/dl; p=0.217), furthermore no correlation with platelets or symptoms was found. In contrast, reduction of PL at 24 mo was associated with pronounced spleen size reduction (median change -16.0 vs -5.5 cm; p=0.062) and higher levels of hemoglobin (median change +0.6 vs -0.8 g/dl; p=0.077). No effects were observed on platelet counts and reduction of MF related symptoms (p=0.265). Improvement in BM fibrosis at 24 mo was associated in 67% with a corresponding lowering of overall MK frequency, contrasting cases with progression that revealed in 80% an increase in dysplastic features. Overall, changes in MK frequency and morphology were not linked with spleen size reduction, hemoglobin or symptoms. However, decrease in MK quantity resulted in lower platelet counts at 24 mo (median change -299 vs -162 x109/l; p=0.165). Conclusions Our results highlight recent data on JAK inhibitor therapy in pts with MF with regard to improvement in BM fibrosis and an overall reduction of an inflammatory condition. RUX therapy induces a modulation of the BM microenvironment that is linked with spleen size reduction and normalization of MK morphology. Ongoing research is further exploring the significance of our current findings, including a correlation with other proinflammatory cytokines and extracellular matrix proteins like LOX. Disclosures: Kvasnicka: Novartis: Consultancy; Incyte Corporation: Consultancy; Novartis: Research Funding; Incyte Corporation: Research Funding; Shire: Research Funding; AOP Orphan Pharmaceuticals: Research Funding; Novartis: Honoraria; Shire: Honoraria; Incyte Corporation: Honoraria. Thiele:AOP Orphan Pharmaceuticals: Consultancy; Incyte Corporation: Consultancy; Novartis: Consultancy; Shire: Consultancy; Sanofi: Consultancy; Novartis: Research Funding; Shire: Research Funding; AOP Orphan Pharmaceuticals: Honoraria; Incyte Corporation: Honoraria; Novartis: Honoraria; Shire: Honoraria; Sanofi: Honoraria. Cortes:Ambit: Research Funding. Kantarjian:Ariad: Research Funding; Novartis: Research Funding; BMS: Research Funding; Pfizer: Research Funding. Verstovsek:Incyte Corporation: Research Funding.

Prognostic Factors Of Response and Survival To Azacitidine (AZA) +/- EPO In RBC Transfusion Dependent (TD) IPSS Low and Int-1 (LR) MDS Resistant To EPO, With Particular Emphasis Of Genetic Lesions: A Study By The GFM

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 658-658 ◽  
Author(s):  
Sylvain Thepot ◽  
Raouf Ben Abdelali ◽  
Sylvie Chevret ◽  
Aline Renneville ◽  
Odile Beyne Rauzy ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Prognostic Factors ◽  
Genetic Markers ◽  
Research Funding ◽  
Prognostic Value ◽  
Response Rate ◽  
Univariate Analysis ◽  
Snp Array ◽  
Erythroid Response ◽  
Rbc Transfusion

Abstract Background Although anemia of LR MDS initially responds to erythroid stimulating agents (ESA) in 40-50% of patients, response is generally transient. AZA may lead to RBC transfusion independence (RBC-TI) in 30-40% of LR-MDS patients but it has not been studied prospectively in those resistant to ESA. While prognostic factors of response and survival to AZA have been largely analysed in high risk MDS, including by our group (Itzykson, Blood, 2011), they remain uncertain in LR-MDS, especially regarding new genetic factors. We previously reported (J Clin Oncol 30, 2012 # 6523) in a randomized phase II trial comparing AZA and AZA+EPO in 93 LR-MDS that were RBC-TD and resistant to ESA, a similar erythroid response rate in the 2 treatment arms (NCT01015352). Here, we report prognostic factors of response and overall survival in this trial, including genetic markers (SNP array-based karyotype and somatic mutations). Methods Patients included in the trial received AZA 75mg/m2/d for 5 days every 28 days for 6 cycles (AZA arm) or with added EPO 60000U/week (AZA+EPO arm). Erythroid response was evaluated after 4 and 6 cycles of AZA, according to the IWG 2000 criteria. Responders were then eligible for 12 AZA+/-EPO maintenance cycles. Affymetrix SNP array 6.0 (SNPa) analysis was performed at baseline on marrow mononuclear cells, and mutations of SF3B1, TET2, DNMT3A, ASXL1, JAK2 and 19 other genes were screened by next generation sequencing and validated by Sanger sequencing. The following factors were analysed for their prognostic value on erythroid response (IWG 2000) and survival: age, gender, IPSS, IPSS cytogenetics, WHO diagnosis, time since MDS diagnosis, SNPa karyotype, SF3B1, TET2, DNMT3A, ASXL1 and JAK2 mutations. Results In the 93 patients, M/F was 65/28; median age 72 y (IQR: 65-78); WHO diagnosis: RA 5.3%, RARS 40.9%, RCMD 15.1%, RCMD-RS 17.2%, RAEB-1 12.9%, CMML 7.5%, MDS-U 1%. Median MDS duration prior to inclusion was 37.2 months. IPSS was low in 35 and int-1 in 57 patients (NA in 1). IPSS cytogenetics was fav in 65, int in 9, defav in 2 patients, and failed or not done at study entry in 17 (but cytogenetics at MDS diagnosis was available in 16 of them). An abnormal SNPa karyotype was present in 33/79 patients analysed, including 9 with normal conventional cytogenetics. SF3B1, TET2, DNMT3A, ASXL1 and JAK2 mutations were detected in 59/86, 29/87, 12/87, 5/89 and 3/87 patients. Of the 19 other genes analysed, 12 showed no mutation and 7 (UA2F1, CBL, EZH2, RUNX1, ETV6, KIT, IDH2) were mutated in ≤3 patients and were not further considered in this analysis. In ITT analysis (N=93), erythroid response was 34% after 4 courses (37.5 % vs. 31% in the AZA and AZA+EPO arms, respectively, p=0.82) and 30% after 6 courses (35% vs. 24%, p=1.00). In univariate analysis, none of the factors listed above, including genetic markers, significantly predicted treatment response after 4 or 6 courses, while a trend was observed for a higher response rate after 6 cycles for SF3B1 mutated versus wt. patients (35.6 vs. 14.8 % respectively, P=0.07). Median follow-up of the 93 patients was 30 months (IQR: 23-34). Five patients developed AML (1 in AZA arm and 4 in AZA+EPO arm, P=0.19), all 5 in non-responders after 6 cycles. Median OS was 42.2 months and 2.5 years-OS 79.2% (95%CI: 71.2-88.1), with no difference between randomization arms (P=0.69). In univariate analysis, a shorter time since MDS diagnosis (HR=0.97, 95%CI: 0.95-0.99,P=0.011), IPSS int-1 (HR=2.83, 95%CI: 1.05-7.63, P=0.04), an abnormal SNPa karyotype (HR=3.01, 95%CI: 1.26-7.22, P=0.013) and presence of ASXL1 mutation (HR=5.08, 95%CI: 1.48-17.48, P=0.010) were associated with worse survival. In multivariate analysis, however, only time since MDS diagnosis (HR=0.97, 95%CI: 0.95-0.99) and abnormal SNPa karyotype (HR=2.92, 95%CI: 1.07-8.01) remained of prognostic value. Conclusions In this prospective AZA trial in LR-MDS resistant to ESA, no significant prognostic factor for response to AZA+/- EPO was identified, but a trend for better response (p=0.07) was seen in SF3B1 mutated patients, i.e 2/3 of patients. Among mutations analysed, only ASXL1 mutation predicted survival in univariate analysis, while abnormal SNPa karyotype predicted survival both in univariate and multivariate analysis (together with MDS duration). Thus, SNP array-based karyotyping and ASXL1 gene mutation analysis may become important tools to predict the long-term outcome of ESA resistant LR-MDS treated by AZA Disclosures: Guerci-Bresler: Novartis: Honoraria; BMS: Honoraria; Celgene: Honoraria; Amgen: Honoraria. Fenaux:Celgene, Inc: Consultancy, Membership on an entity’s Board of Directors or advisory committees, Research Funding, Speakers Bureau. Gardin:Celgene, inc: Research Funding.

Prognostic Factors of Infections and Effect of Primary Anti-Infectious Prophylaxis in MDS Patients Treated with Azacitidine (AZA): A Prospective Study

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 1917-1917
Author(s):  
Marie Sebert ◽  
Claire Aguilar ◽  
Sylvie Chevret ◽  
Lionel Ades ◽  
Olivier Lortholary ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Prognostic Factors ◽  
High Risk ◽  
Fungal Infection ◽  
Predictive Factors ◽  
Invasive Fungal Infection ◽  
Research Funding ◽  
Pulmonary Infection ◽  
Influenza B ◽  
Fatal Infection

Abstract Background: Hypomethylating agents, especially AZA, have become the reference first line treatment of high-risk MDS. Myelosupression, although less important than with chemotherapy, is however observed, leading to potentially life threatening infections. A retrospective study found unfavorable (unfav) cytogenetics and low platelet counts to be predictive factors of infections in high risk MDS and AML patients (pts) receiving AZA (Merkel and al, Am j Hemat 2012). However, prognostic factors of infections, and whether infection prophylaxis would be useful in this situation, has not been prospectively evaluated. Methods: Between June 2011 and March 2013, 120 high-risk MDS pts were included in a randomized phase II trial seeking the most promising drug association with AZA by comparison with AZA alone in higher risk MDS (including AML with 20 to 30% marrow blasts and CMML with > 10% marrow blasts) (NCT01342692). Pts received AZA (75mg/m²/dx7d every 4 weeks) alone (N=40), with Valproic acid (N=40) or with Lenalidomide (N=40) (10mg/dx14d every 4 weeks). G-CSF was not used. Infectious events (IE) (diagnosed as such by the treating physician), hospitalizations for sepsis and pts receiving antimicrobial prophylaxis were reported at each cycle. Predictive factors of the occurrence of IE were analyzed. Results: 75 (62.5%) pts developed 259 IE, including 61 requiring hospitalization in 46 pts (61.3% of infected patients). The number of IE and of infected patients were similar in the 3 study arms. 39 pts died during the study, 12 of them because of infection, none of whom had responded to AZA (4 progressions, 4 failures and 4 deaths before evaluation). IE were more common during the first two cycles of therapy, with 86 (31.3%), 52 (23.5%) 45 (18.9%), 26 (15%), 15(19.2%) and 24 (19.7%) IE during cycles 1, 2, 3, 4, 5, and 6, respectively. Fever of unknown origin (FUO) (39.6%) and pneumonia (28.8%) were the most common type of infections followed by ENT (9.9%), urinary tract (8.1%), skin (5.4%), dental (4.5%) and intra-abdominal (3.6%). 6,3% were bacteriemia. Among the 26 microbiologically documented IE, 13 were CG+ (4 staph aureus, 4 enteroccus species, 4 coag neg staph and 1 other), 9 were BG- (6 E Coli, 1 pseudomonas and 2 others) and 3 were viral (HSV1, influenza B, Hepatitis E) and only one patient had documented invasive fungal infection (asp fumigatus). Overall, 23 (19%), 22 (18%), 10(8%) pts received bacterial (Levofloxacine), fungal (posaconazole) and viral (Valaciclovir) prophylaxis resp. Predictive factors of IE were unfav karyotype (79.5% infections vs. 50.8% in pts with fav or int karyotype; p=0.005) and platelets (PLT) < 20 G/L (92.3% infections vs. 58.9% for platelets > 20 G/L; p=0.03). In multivariate analysis, only unfav karyotype was predictive of IE (p=0.01). Other baseline parameters (including ANC, IPSS, age, sex, Hb level, and BM blast %) and bacterial, fungal or viral prophylaxis had no significant predictive value on the occurrence of IE. In multivariate analysis, predictive factors of pulmonary infection were anemia at baseline (p=0.04) and unfav karyotype (p<0.001), while prophylaxis had no significant impact. Infected pts had significantly more hospitalizations and deaths than non-infected pts (p<0.0001 and p=0.028 resp.). In multivariate analysis, unfav karyotype (p<0.001) and PLT <20 G/L (p=0.05) were significantly predictive of hospitalization for infection, while baseline Hb <10g/dL (p=0.02), and unfav karyotype (p=0.03) were predictors of fatal infection. Conclusion: 62.5% of the 120 pts developed infections during AZA treatment, mainly during the first 2 cycles, and 10% of the pts died from infection. Only one invasive fungal infection was documented. Unfav karyotype was strongly predictive of IE, hospitalization for infection and fatal infections. Other significant predictive factors were baseline anemia for pulmonary infection and fatal infection, and thrombocytopenia for hospitalization for infection, while ANC was not a significant factor. Moreover, prophylaxis was not associated with a decrease of IE in our study, but the small number of pts who received it precludes any conclusion. Disclosures Ades: celgene: Research Funding; Novartis: Research Funding. Fenaux:Novartis: Research Funding; celgene: Research Funding; Janssen: Research Funding.

scholarly journals Allotransplants for Patients 65 Years or Older with High-Risk Acute Myeloid Leukemia

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 4667-4667
Author(s):  
Paul Lin ◽  
Lauren Westfall Veltri ◽  
Katy Rezvani ◽  
Betul Oran ◽  
Sairah Ahmed ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Prognostic Factors ◽  
High Risk ◽  
Myeloid Leukemia ◽  
Research Funding ◽  
Risk Group ◽  
Morphological Evidence ◽  
Consolidation Chemotherapy ◽  
Medical Event ◽  
History Of

Abstract Outcome of persons >65 years with acute myeloid leukemia (AML) is poor. Allogeneic transplant can cure some of these patients but is associated with substantial transplant-related mortality (TRM) and high relapse risk. We analyzed 185 consecutive patients >65 years with high-risk AML between 2010 and 2015 who had measurable residual disease (MRD) and molecular risk assessments and who received myeloablative conditioning (MAC, n=42) or reduced-intensity conditioning (RIC, n=143) and a transplant from an HLA-identical sibling (n=66) or a 10/10 loci HLA-matched unrelated donor (MUD, n=119) in order to identify patients who would benefit from allotransplant. MRD was assessed by flow cytometry in bone marrow samples. AML cytogenetic and molecular risk were defined using the 2017 European Leukemia Net genetic risk stratification. The patients who were MRD-negative at time of transplant had a better 2-year cumulative incidence of relapse (CIR 17.6%) and a 2-year overall survival (OS, 69.4%) as compared to the patients in remission but MRD-positive (55.6% CIR, 21.5% OS) or the patients who had morphological evidence of leukemia prior to transplant (48.7% CIR, 19.9% OS), (p<0.0001). Multivariate analysis for 2-year CIR showed that having detectable leukemia at time of SCT (defined as MRD-positive or morphological evidence of leukemia) (HR=14.5, CI=3.4-61.4, p<0.0001), having received <3 cycles of chemotherapy prior to SCT (HR=1.8, CI=1.1-2.8 p=0.01), and high-risk genetics were independent predictors of relapse. However, high-risk genetics only had a deleterious effect on outcomes for MRD-negative patients (HR=9.4, CI=2.0-43.6, p=0.004), and did not affect the outcome of patients with detectable leukemia (HR=1.1, CI=0.7-1.9, p=0.61). Patients who received RIC (Flu-Mel-RIC or Bu-Flu-RIC) or MAC (Bu-Flu-MAC) had similar proportion of MRD-negative patients (p=1.0). However, MRD-negative patients who received Flu-Mel-RIC had a superior OS than patients who received Bu-Flu-RIC (adjusted HR=1 vs 5.3, p=0.02) or patients who received Bu-Flu-MAC (HR=1 vs 5.093, p=0.04), which is explained by a significantly lower relapse rate in patients receiving Flu-Mel-RIC (adjusted HR=1 vs 4.8, p=0.03) and a significantly lower TRM as compared to patients receiving Bu-Flu-MAC (adjusted HR= 5.1, p=0.01). Patients who had major medical complications (MMC), defined as a medical event requiring admission to the intensive care unit for ventilatory or inotropic support or a medical event that prolonged the patient hospitalization for more than 2 weeks, during induction or consolidation chemotherapy preceding the transplant, had a higher day +100 mortality (30.6% vs 6.0%, p<0.0001), 2-year TRM (55.6% vs 16.8%, p<0.0001) and lower 2-year OS (8.3% vs 44.6%, p<0.0001). Multivariate analysis for 2-year OS showed that history of delayed hematological recovery during induction or consolidation chemotherapy prior to transplantation (HR=1.5, CI=1.0-2.3, p=0.04), high risk genetics (HR=1.8 CI:1.2-2.6, p=0.006), donor-recipient HLA-DRβ3/4/5-DP mismatch (HR=2.2, CI=1.3-3.6, p=0.001), history of cardiovascular disease (HR=1.7, CI=1.1-2.6, p=0.02) were independent predictors for OS. Other variables such as secondary leukemia, CMV sero-status, FEV1 or creatinine clearance prior to SCT, sex mismatch, ABO group mismatch, donor type, or stem cell source did not have a significant impact on OS or TRM. Outcomes were also similar between patients transplanted in CR1 or in ≥ CR2 or in CR or CRi. We sought to identify those patients who may clearly benefit from a SCT. To that end, we classified patients according to the MRD status prior to transplantation and the presence or absence of the other prognostic factors identified in the multivariate analysis. As seen in the Figure, the High risk group which includes patients with detectable leukemia and >1 additional adverse prognostic factors (or a MMC), had a 2-year OS of 7.7% (CI=3.1-17.8). In comparison, the Low risk group which includes MRD-negative patients with ≤3 other prognostic factors (and no MMC), had a 2-year OS of 76.2% (CI=63.3-85.6). Finally, the Intermediate risk group which constituted the remaining patients, had a 2-year OS of 32.2% (CI=22.1-44.3, p<0.00001). These data indicate the possibility to identify persons >65 years with high-risk AML likely to benefit from an allotransplant. Figure. Figure. Disclosures Rezvani: Affirmed GmbH: Research Funding. Oran:ASTEX: Research Funding; Celgene: Consultancy, Research Funding; AROG pharmaceuticals: Research Funding. Shpall:Affirmed GmbH: Research Funding. Champlin:Otsuka: Research Funding; Sanofi: Research Funding.

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