Hanson, Curtis A.

Abstract BACKGROUND. The detection of minimal residual disease (MRD) at the level of 0.01%/10-4 or above is a strong independent predictor of reduced progression-free (PFS) and overall survival (OS) in patients with CLL treated with chemoimmunotherapy. Although newer agents such as B-cell receptor pathway inhibitors can result in prolonged survival without achieving complete response, there remains a important role for MRD analysis in assessing therapeutic strategies aimed at disease eradication and cure. This is particularly important in front-line trials for fit patients which now require at least five years of follow-up if PFS is used as an endpoint. The feasibility of using MRD as a surrogate or intermediate endpoint for accelerated approval of new treatments is under review by regulatory agencies but further prospective validation is required. At the same time technology is rapidly evolving and high-throughput sequencing (HTS) technologies now detect MRD at the 0.0001%/10-6 level. It is therefore important to determine the most effective approaches for quantifying MRD that are compatible with previous studies but sufficiently sensitive for current treatments. AIMS. This collaborative project had two objectives. First, to identify the simplest and most flexible flow cytometry panel capable of detecting MRD at the 0.01%/10-4 or lower, that is compatible with published data and independent of instrument/reagent manufacturer. Second, to compare the flow cytometry approach with HTS analysis using the ClonoSEQ assay (Adaptive Biotechnologies, Seattle, WA). METHODS AND RESULTS. A core panel of antibodies for MRD detection was identified by testing an 8-marker combination in 52 samples (27 post-treatment and 25 dilution study) and re-analysing data with serial exclusion of single markers to determine redundancy. A 1-tube core panel of CD19, CD20, CD5, CD43, CD79b, and CD81 was identified and validated against the previously published 2-tube 6-marker and 4-tube 4-marker ERIC panels in 76 samples (19 post-treatment and 57 dilution study). The results showed good concordance (for log-transformed data above the LoQ, linearity=0.977, Pearson correlation co-efficient=0.983, average difference=0.026 log, 95% limit of agreement 0.20log) and a limit of detection of 0.001%/10-5 for the 1-tube core panel. Inter-operator variation was similar to CML MRD monitoring with both experienced operators, or inexperienced cytometrists after ~1 hour of specific education, achieving a 95% limit of agreement less than 0.3log in samples with MRD levels ranging from 0.0001 – 100%. The flow cytometry approach was compared with the ClonoSEQ HTS assay in 109 samples (21 dilution study and 88 post-treatment samples, complete data currently available on 13/88). The assay was applicable to the vast majority CLL patients, often with two clonal markers. There was 94% concordance at the 0.01% (10-4) threshold (15 samples with ≥0.01% CLL by both methods, 14 samples with <0.01% by both methods, 1 sample with 0.03% CLL by HTS and <0.003% CLL by flow cytometry, and 1 sample with 0.005% CLL by HTS and 0.012% by flow cytometry. HTS detected CLL IGH sequences in 22% (7/31) samples with no detectable CLL cells by flow cytometry (i.e. CLL level 0.0001-0.001%, 3/13 patient samples and 4/18 dilution samples). HTS demonstrated a relatively high variability in quantification, as seen in previous studies, but with a clear superiority in the limit of detection and good linearity (linearity=0.905, Pearson correlation co-efficient=0.870, average difference=0.078 log, 95% limit of agreement 1.5 log). CONCLUSIONS. The 1-tube 6-marker flow cytometry core panel is compatible with published studies, manufacturer-independent and flexible, providing directly quantitative results to 0.001%/10-5 without requiring a pre-treatment sample. HTS requires further work to standardise the quantitative analysis and prospective validation but the ClonoSEQ assay is applicable to >95% of CLL patients, does not require viable cells and is extremely sensitive, detecting residual disease in a significant proportion of cases with <0.01% CLL. The results indicate that flow cytometry and HTS are complementary technologies with a combined approach offering the most reliable way of quantifying CLL at the 0.01%/10-4 threshold while allowing higher sensitivity in clinical trials aimed at disease eradication. Disclosures Rawstron: Roche: Honoraria; Biogen Idec: Consultancy; Gilead: Consultancy, Honoraria; Abbvie: Honoraria; BD Biosciences: Intrasure reagent Patents & Royalties; Celgene: Honoraria; GSK: Honoraria. Williamson:Adaptive Biotechnologies: Employment, Equity Ownership. Sanders:Adaptive Biotechnologies: Employment, Equity Ownership. Robins:Adaptive Biotechnologies: Consultancy, Equity Ownership, Patents & Royalties. Hallek:Celgene: Honoraria, Research Funding; Mundipharma: Honoraria, Research Funding; Roche: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; GSK: Honoraria; Gilead: Honoraria. Hillmen:Roche: Honoraria, Research Funding; GSK: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Pharmacyclics: Honoraria, Research Funding; Gilead: Honoraria, Research Funding.

Abstract Background : Prognosis in chronic myelomonocytic leukemia (CMML) is dire and blast transformation (BT) is a main cause of death. Current risk factors and prognostic models are mostly designed to predict overall (OS) and not leukemia-free (LFS) survival. Established risk factors for OS in CMML include anemia, thrombocytopenia, leukocytosis, monocytosis, presence of circulating immature myeloid cells (IMC), peripheral blood (PB) and bone marrow (BM) blasts, lymphocytosis, ASXL1 mutations, high risk abnormal karyotype and advanced age. In the current study, we examined risk factors for BT in CMML and survival outcome after BT. Methods : All CMML patients seen at our institution and with complete presentation data were considered. Clinical and laboratory variables, including cytogenetic information, at time of CMML diagnosis and also at time of BT were collected. DNA analysis for SRSF2, SF3B1, U2AF1, ASXL1 and SETBP1 mutations was carried out on specimens obtained at time of CMML diagnosis. We used both conventional and revised (see accompanying ASH 2014 abstract) cytogenetic risk models to query their influence in the current study population. Results: Clinical and laboratory features at time of CMML diagnosis: 277 consecutive patients (median age 71 years, range 18-91; 67% males) with WHO-defined CMML were considered. 236 (85%) patients had CMML-1 and the remainder CMML-2. According to the molecular Mayo risk model, 86 (33%) were high, 77 (29%) were intermediate-2, 77 (29%) were intermediate-1 and 24 (9%) were low risk. Mutational frequencies were 40% for ASXL1 (n evaluable =264), 44% for SRSF2 (n evaluable =263), 5% for SETBP1 (n evaluable =263). According to the revised Mayo-French consortium cytogenetic risk model, karyotype was high risk in 5%, intermediate in 21% and low risk in 74%. Risk factors for blast transformation (BT) : At a median follow-up of 16.2 months for all 277 patients from time of CMML diagnosis, 204 (74%) deaths and 38 (14%) BTs were documented. Median time from CMML diagnosis to BT was 13.3 months. In univariate analysis, female sex, younger age, lower hemoglobin, higher leukocyte count, higher absolute monocyte count, higher lymphocyte count, presence of circulating immature myeloid cells (IMC), increased peripheral blood (PB) blast %, increased bone marrow (BM) blast %, BM blasts ≥10%, CMML-2, abnormal karyotype, high risk karyotype per the Spanish or Mayo-French consortium, and higher risk disease per Mayo, MDACC or Dusseldorf models were all associated with higher risk of BT. In contrast, ASXL1 (p=0.84), SRSF2 (p=0.28) or SETBP1 (p=0.97) mutations were not found to be significant. In multivariable analysis, only PB blast % (p<0.0001), presence of PB IMC (p=0.004) and younger age (p=0.03) remained significant. Outcome of blast transformation : At time of BT, karyotype was abnormal in 58% and clonal evolution from time of CMML diagnosis was documented in 13 (36%) of 36 evaluable patients. Among the 38 patients with BT, induction chemotherapy was documented in 12 patients and allogeneic stem cell transplant (ASCT) in 6. At a median follow-up of 4.2 months from time of BT, 34 (89%) of the 38 patients with BT had died. Among the four patients who were alive at the time of this writing, 3 had received induction chemotherapy and two ASCT. Median survival of patients with BT, from time of disease transformation, was 4.5 months with 1, 2 and 3 year survival rates of approximately 30%, 16% and 3%, respectively. In univariate analysis, higher leukocyte count (p=0.01) and not receiving induction chemotherapy (p=0.03) were associated with shortened survival. Neither ASXL1 nor SRSF2 mutations affected survival after BT. Conclusions : Blast transformation in CMML occurs in approximately 14% of patients followed for a median of less than 1.5 years. Presence of circulating immature cells and percentage of peripheral blood blasts are the major determinants of BT in CMML. Genetic risk factors for overall survival did not appear to influence leukemia-free survival. Prognosis of post-CMML BT is dismal with median survival of less than 6 months and a 3-year survival of less than 5%. Outcome was better in patients receiving induction chemotherapy followed by ASCT. Disclosures No relevant conflicts of interest to declare.

Abstract Abstract 430 Background: The Dynamic International Prognostic Scoring System (DIPSS-plus) uses eight risk factors to predict overall survival (OS) in primary myelofibrosis (PMF): unfavorable karyotype, peripheral blood (PB) blast count ≥1%, platelet count <100 × 109/L, white blood cell count (WBC) >25 × 109/L, hemoglobin level <10 g/dL, red blood cell transfusion need, constitutional symptoms, and age >65 years (JCO 2011;29:392). Among these risk factors, karyotype holds a dominant role in predicting both overall (OS) and leukemia-free (LFS) survival (Blood 2011;118:4595). More recently, certain PMF-associated somatic mutations (IDH, EZH2, ASXL1, SRSF2) have been reported (in print or at recent meetings) to carry prognostic relevance for OS or LFS in PMF while other mutations (JAK2, MPL, TET2, SF3B1) did not. The purpose of the current study was to examine the individual and combined prognostic relevance of the former in the context of cytogenetic risk stratification and DIPSS-plus. Methods: An updated Mayo Clinic database of 1008 karyotypically- and DIPSS-plus-annotated patients with PMF was used to identify study patients in whom DNA at time of referral was available for mutation analysis. OS and LFS were calculated from the time of referral, which was also the time of study sample collection. Results: In an ongoing project, a total of 397 PMF patients have so far been studied for IDH1/2 (n=367), SRSF2 (n=355), ASXL1 (n=260) and EZH2 (n=43) mutations. The corresponding mutational frequencies were 5.4% (20/367), 14.4% (51/355), 31.2% (81/260) and 7% (3/43). These mutations were not exclusive of either each other or JAK2 or MPL mutations and a significant clustering was noted between SRSF2 and IDH mutations; IDH mutational frequency was 21% (10/48) in SRSF2-mutated versus 3% (9/279) in unmutated cases (P<0.0001). Mutational hotspots were P95 in exon 1 for SRSF2 and exons 1, 2 and 5 for ASXL1. OS and LFS effect have so far been examined for ASXL1, SRSF2 and IDH 1/2 mutations; in univariate analysis, all three mutations significantly affected OS (ASXL1 RR 1.9, 95% CI 1.4–2.7; SRSF2 RR 1.7, 95% CI 1.2–2.5; IDH 1/2 RR 1.8, 95% CI 1.1–3.1) whereas only IDH 1/2 (RR 5.5, 95% CI 2.5–11.8) and SRSF2 (RR 3.5, 95% CI 1.7–7.0) but not ASXL1 (p=0.29) mutations affected LFS. The observed prognostic relevance for OS was sustained during multivariable analysis that included ASXL1 with either SRSF2 or IDH mutations, as co-variates, whereas both IDH and SRSF2 mutations remained significant for LFS. Based on the above observations, study patients were classified into two groups: i) unmutated for ASXL1, SRSF2 and IDH1/2 (all unmutated; n=146) and ii) mutated for at least one of the three mutations (one or more mutated; n=130); the latter group constituted 62%, 52%, 18% and 27% of DIPSS-plus high, intermediate-2, intermediate-1and low risk patients, respectively (p<0.0001). The corresponding rates for patients with favorable and unfavorable karyotype were 47% and 43% (p=0.7) and for normal vs. abnormal karyotype were 53% and 36% (p=0.008). The “all unmutated group”, compared to the “one or more mutated group” enjoyed a significantly superior OS (RR 0.5, 95% CI 0.4–0.7) and LFS (RR 0.3, 95% CI 0.2–0.7) that was DIPSS-plus-independent for OS (p=0.03) and karyotype-independent for LFS (p=0.004). The prognostic value of distinguishing “all unmutated” from “one or more mutated” patient groups was most evident for DIPSS-plus intermediate-2 or lower risk groups (p=0.002) and its added value for high-risk group was limited (p=0.23) (Figure). Conclusions: A concomitant analysis strategy reveals that SRSF2, ASXL1 and IDH mutations carry inter-independent prognostic relevance for overall or leukemia-free survival in PMF. Any one of these three mutations is more likely to occur in patients with normal karyotype and such an event predicts shortened survival that is not accounted for by DIPSS-plus and a higher risk of leukemic transformation that is independent of karyotype. The current study suggests that such information might be useful in treatment decisions involving intermediate-2 or lower risk patients. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 4931 Background: Autoimmunity, evidenced by positive serology or autoimmune diseases, has been noted to co-exist in pts with MDS. Autoimmune dysfunction has been found in some pts with a variant of MDS called hypocellular MDS, where immune suppressant medications have role in treatment. Clinical implications of AI on survival are not well described. Aim: To study clinical influence of autoimmunity on pts with LR-MDS. Methods: All adult pts diagnosed with LR (RCUD, RARS, and RCMD) MDS at the Mayo Clinic between 1996 to 2000 were studied. Retrospective data collection included pts' demographics, laboratory tests, bone marrow biopsies, treatment modalities and survival information. Autoimmunity (AI) was considered present if pts had evidence of positive serological testing (such as rheumatoid factor (RF), anti-nuclear antibodies (ANA), antineutrophil cytoplasmic antibodies (ANCA)) and/or were diagnosed with autoimmune diseases (such as rheumatoid arthritis, vasculitis, autoimmune hemolytic anemia (AIHA), immune thrombocytopenia (ITP)). IRB approval was obtained in accordance with Helsinki Declaration. Chi-Square, t-test and Anova were used for comparatives between groups, and Kaplan-Meier test was applied for survival estimates using JMP 9. 0 software. Results: A total of 134 adult pts were found to have LR-MDS at the time of their diagnosis. Sixty-six percent (89) were males, 13% (17) had antecedent hematological disease (AHD), and only 7% (9) had prior radio- or chemotherapy. Thirty-nine (29%) had evidence of AI. At the time of diagnosis, pts' median Hgb was 9. 3 g/dL, white blood cells (WBC) 4. 1×109/L, and platelets 151×109/L. On comparison, there was no difference between pts with AI (group 1) to the rest of the sample (group 2) (p = 0. 12, 0. 85 and 0. 23, respectively). Bone marrow cytogenetics were abnormal in 42% (56) pts, with 44 pts have one cytological anomaly, and only 2 have four anomalies. Twenty-four pts (18%) had RCUD, 60 (44%) RARS and 50 (37%) RCMD, as defined by World Health Organization (WHO) classification (Vardiman et al, 2008). Karyotype anomalies within the three WHO classes were found in 12/19 pts (63%), 15/52 pts (29%), and in 29/42 pts (70%), respectively. Of note, among those with karyotype anomalies, the mean number of cytogenetic abnormalities was significantly different across the three categories (F=6. 89, p=. 0014), with means of 0. 5, 0. 3, and 0. 9 respectively. Seven pts (5%) progressed into acute myeloid leukemia. Seventy percent of pts (94) remained as stable disease. Of the 134 pts studied, 39 (29%) were found to have evidence of AI, with 24/48 (50%) had abnormal serological tests, and 29/134 (21%) had an autoimmune disease. When tested, positive RF was found in 7/25 (28%), ANA in 14/42 (33%), anti dsDNA in 1/11 (9%), anti SS-A/-B in 2/3 (66%), ANCA in 1/12 (8%), anti-smooth muscle in 1/2 (50%), and anti-histone in 1 pt. As per autoimmune diseases, rheumatoid arthritis was identified in 6 pts (4%), vasculitides in 9 (7%), AIHA in 4 pts (3%), Sjögren syndrome in 3 (2%), myositis in 2 (1. 4%), ITP in 2 pts (1. 4%). There was no difference in AI frequency based on WHO classification (p 0. 17) or based on cytogenetic grouping (p 0. 37). Overall survival in pts with LR-MDS was found to be lower in group 1 as compared to group 2 but did not reach statistical significance (p=0. 109), with median survival of 40 months and 81 months, respectively. Conclusion: AI is a frequent finding in pts with LR-MDS, seen in up to 29% of pts. On comparison there was no difference in hematological parameters of both groups with or without AI (CBC, cytogenetics, and WHO classification). There was no survival difference in LR-MDS pts with AI compared to pts without AI. Larger size studies are needed to confirm our findings. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 423 Background: Cytogenetic abnormalities at diagnosis are seen in 20–70% of patients with myelodysplastic syndromes (MDS). The International Prognostic Scoring System -revised (IPSS-R) classifies these cytogenetic abnormalities into five prognostic groups: very good (del(11q), ΠY with overall survival (OS) of 61 months); good (normal, del(20q), del(5q), del(12p) with OS 49 months); intermediate (+8,7q-, i(17q),+19,+21 with OS 26 months); poor (der(3)q21/q26, −7, complex with 3 abnormalities with OS 16 months); and very poor (complex with >3 abnormalities with OS of 6 months) (Schanz J, JCO 2012, Greenberg P, Blood 2012). Monosomal karyotype (MK) is defined as the presence of two or more autosomal monosomies or a single monosomy associated with a structural abnormality. We have previously shown that MK identifies a prognostically worse subgroup of MDS patients with a complex karyotype (Patnaik M, Leukemia 2010). Objectives: Methods: The Mayo Clinic database for MDS was used to identify patients in whom bone marrow histologic and cytogenetic information was obtained at the time of diagnosis. WHO criteria were used for MDS diagnosis and leukemic transformation. Results: i) Patient characteristics: A total of 1,014 patients met the above-stipulated criteria. Median age of the cohort was 71 years (range: 18–98 years) with 684 (67%) males. 819 patients (81%) had primary MDS with 195 cases (19%) of therapy-related MDS. 759 patients (75%) are dead at a median follow-up of 18 months (range: 0–223 months) with leukemic transformation documented in 125 cases (12%). IPSS-R risk distribution was as follows: very low (n=149, 15%), good (n=261, 26%), intermediate (n=221, 22%), high (n=131, 13%), and very high (n=252, 25%). ii) IPSS-R karyotype (Entire cohort; n=1,014): The five cytogenetic groups by IPSS-R were as follows: very good (n=43, 4%), good (n=577, 57%), intermediate (n=187, 18%), poor (n=83, 8%), and very poor (n=124, 12%). We evaluated the prognostic impact of the above groups by Kaplan Meier and Cox proportional hazards analysis. OS for the five cytogenetic groups was as follows: good (36 months), very good (28 months), intermediate (20 months), poor (13 months), and very poor (6 months) (Figure 1). OS of patients with very good karyotype was significantly better than patients with very poor and poor karyotype (p<0.0001, RR 3.2 and p=0.04, RR 1.6 respectively) but similar to patients with intermediate and good karyotype (p=0.22 and 0.28 respectively). iii) IPSS-R karyotype (Primary MDS; n=819): Cytogenetic risk groups by IPSS-R were as follows: very good (n=38, 5%), good (n=512, 63%), intermediate (n=153, 19%), poor (n=46, 6%), and very poor (n=70, 9%). OS of the five groups was as follows: good (39 months), very good (23 months), intermediate (21.5 months), poor (14.5 months), and very poor (6.5 months). OS of patients with very good karyotype was significantly better than patients with very poor karyotype (p=0.0002, RR 2.5) but similar to patients with poor, intermediate and good karyotype (p=0.23, 0.26 and 0.18 respectively). iv) Monosomal karyotype: MK was identified in 153 (15%) cases of which 4 cases were intermediate, 42 poor, and 107 very poor by IPSS-R. OS of patients with MK was similar to those with very poor karyotype (6 months). In addition, OS of patients with very poor without MK was akin to patients with poor without MK (p=0.21). Furthermore, among primary MDS we identified 83 (8%) cases of MK of which 4 were intermediate, 21 were poor, and 58 very poor by IPSS-R. We confirmed that OS of patients with MK was similar to patients with very poor karyotype (6.5 months). Moreover, survival of patients with very poor without MK was similar to patients with poor without MK (p=0.51). Conclusions: In this independent analysis of 1,014 patients with MDS, IPSS-R cytogenetic risk characterization failed to discriminate between very good, good and intermediate prognostic groups. In addition, patients with very poor without MK have a similar prognosis to patients with poor without MK and should be included in the poor category whereas the presence of MK should warrant inclusion into the very poor risk category. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 2342 Poster Board II-319 PURPOSE: Numerous clinical and biologic parameters are able to predict time to first treatment (TFT) and overall survival (OS) for patients with CLL. The utility of prognostic testing in CLL patients may vary based on age at diagnosis given the higher mortality from other causes among older individuals. The goals of the present study were to i) evaluate differences in natural history of CLL patients based on age at diagnosis, ii) compare survival to age-matched individuals in the general population, and iii) determine the age-stratified utility of prognostic testing. METHODS: All 2487 CLL/SLL patients diagnosed between January 1995 and June 2008 and cared for in the Mayo Clinic Division of Hematology were categorized by age at diagnosis (<55 years, 55-64 years, 65-74 years, or ≥75 years) and evaluated for differences in clinical characteristics, TFT, and OS using chi-square tests. IGHV gene mutation analysis, ZAP-70 status, CD38 status, and cytogenetics abnormalities by interphase FISH testing were performed as part of clinical and/or research studies using methods previously described by our group. Cox regression was used to evaluate the ability of prognostic parameters to predict clinical outcome stratified by age at diagnosis. Patient survival was compared to that of the age matched Minnesota population. RESULTS: When grouped by age, 593 patients were age <55, 713 age 55-64, 748 age 65-74, and 433 age ≥75 at diagnosis. As of last follow-up, 268, 282, 296, and 108 patients in these age groups have been treated, respectively and 112, 171, 254, and 199 patients have died. Survival decreased as the age at diagnosis increased (p<0.001). OS of CLL patients was significantly shorter than that of the age-matched general population for patients age <55 years (p<0.001), 55-64 years (p<0.001), and 65-74 years (p<0.001) at diagnosis but not those ≥75 years (p=0.136). Among Rai stage 0 patients, survival was also shorter than that of the age-matched general population for CLL patients age <55 years (p<0.001), 55-64 years (p<0.001), and 65-74 years (p<0.001) but not those ≥ age 75 at diagnosis (p=0.07). No statistically significant differences were observed in CD38 status, IGHV mutation status, ZAP-70 status or the frequency of common cytogenetic abnormalities on FISH based on age at diagnosis category. Consistent with prior reports, all of these parameters were powerful predictors of TFT and OS for the overall cohort on univariate analysis (all p<0.001 for both TFT and OS). Given the variation in TFT and OS based on age at diagnosis, we next evaluated the utility of these prognostic parameters for predicting TFT and OS in each age category after adjusting for stage. CD38, IGHV mutation, and ZAP-70 each predicted TFT independent of stage for all age groups (all p <0.05). FISH results predicted TFT independent of stage for patients age 55-64 and 65-74 however did not reach statistical significance for those age <55 (p=0.18) or ≥75 (p=0.07). The utility of these parameters for predicting OS independent of stage was less consistent and varied by age. IGHV predicted OS independent of stage for patients <age 55 (p<0.001), 55-64 (p=0.007), and 65-74 (p'0.001) but was not a significant predictor of OS among those ≥75 (p=0.15). CD38, ZAP-70, and FISH each predicted survival independent of stage for only 2 of the 4 age categories (ZAP-70 for age <55 and 55-64; FISH for age <55 and 65-74; CD38 for 55-64 and ≥75). CONCLUSIONS: Survival of CLL patients is shorter than that of the age-matched general population for individuals age <75 at diagnosis regardless of disease stage. In contrast, survival does not differ from the age-matched general population among CLL patients ≥age 75 at diagnosis. Prognostic testing using CD38, IGHV mutation, and ZAP-70 is useful for predicting TFT independent of stage for CLL patients of all ages (including those ≥age 75) but has less value for predicting OS particularly as the age at diagnosis increases. IGHV appeared to be the best predictor of OS independent of stage among all patients age <75. Unexpectedly, prognostic testing had little utility for predicting OS independent of stage among patients age ≥75. These findings have important implications regarding the use of prognostic tests in patients with CLL as well as the use of test results to select patients for clinical trials testing early treatment for asymptomatic individuals. Disclosures: Shanafelt: Cephalon: Research Funding; Celgene: Research Funding; Polyphenon Pharma : Research Funding; Hospira: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Research Funding; Bayer Health Care Pharmaceuticals: Research Funding. Kay:Biogenc-Idec, Celgene, Genentech, genmab: Membership on an entity's Board of Directors or advisory committees; Genentech, Celgene, Hospira, Polyphenon Pharma, Sanofi-Aventis: Research Funding. Zent:Genentech, Bayer, Genzyme, Novartis: Research Funding.

Abstract Abstract 3790 Background: Chronic myelomonocytic leukemia (CMML) is a clonal stem cell disorder characterized by: persistent peripheral blood (PB) monocytosis (>1 × 10(9)/L), absence of BCR-ABL1 fusion, absence of rearrangement of the PDGFRA/B genes, <20% bone marrow (BM) & PB blasts, and dysplasia involving one or more myeloid cell lines. It is clinically considered to be an overlapping syndrome with myelodysplastic and myeloproliferative features. The natural history and prognostic features of CMML are not well defined with the MD Anderson prognostic score (MDAPS) and the Spanish risk stratification by cytogenetics being the two major prognostic tools currently being used in clinical practice. Methods: 227 patients with WHO defined CMML were seen at the Mayo Clinic from 1997 through 2007. All patients underwent bone marrow (BM) examination and cytogenetic evaluation at diagnosis. We evaluated the prognostic relevance of several clinical and laboratory parameters including those previously identified by the MDAPS (Blood 2002;99:840) and the Spanish cytogenetic risk stratification (Haematologica 2011;96:375). Results: Among the 227 study patients, 153 (67%) were males and median age was 71 years (range, 17–90 years). There were 192 (85%) patients with CMML-1 & the remainder had CMML-2. At a median follow-up of 15 months, 166 (73%) deaths and 33 (14.5%) leukemic transformations were documented. Median survivals were 22 months for CMML-1 and 14 months for CMML-2. In univariate analysis, significant risk factors for survival included decreased hemoglobin level, decreased platelet count and increased levels of white blood cells (WBC), absolute neutrophils (ANC), absolute monocytes (AMC), absolute lymphocytes (ALC), PB blasts, BM blasts and presence of circulating immature myeloid cells (IMC; inclusive of PB blasts). However, on multivariable analysis that included the aforementioned Spanish cytogenetic risk stratification, only increased AMC (>10 × 10(9)/L, RR 2.5, 95% CI 1.7–3.8), presence of circulating IMC (RR 2.0, 95% CI 1.4–2.7), decreased hemoglobin (<10 g/dL; RR 1.6, 99% CI 1.2–2.2), and decreased platelet count (<100 × 10(9)/L; RR 1.4, 99% CI 1.0–1.9) retained significance. Using these four independent risk factors, we prepared a new prognostic risk model that performed better than both the MDAPS and the Spanish cytogenetic risk models (Figure). The Mayo risk model was also predictive of leukemic transformation: high risk RR 4.9 (95% CI 1.9–12.8) and intermediate risk RR 2.6 (1.1–5.9). Individual parameters of independent significance for leukemic transformation included PB blast count and AMC >10 × 10(9)/L. Conclusions: Absolute monocyte count is the strongest predictor of survival in CMML. Other independent risk factors include circulating immature myeloid cells, anemia and thrombocytopenia. A risk model based on these four risk factors is effective in predicting both overall and leukemia-free survival and outperforms both the MDAPS and risk stratification by cytogenetics. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 1379 Background: Although chemoimmunotherapy (CIT) has substantially improved response rates, treatment free survival, and overall survival in patients with chronic lymphocytic leukemia (CLL), only 40–50% of patients achieve a complete remission and the majority have residual disease when evaluated using sensitive assays for minimal residual disease (MRD). While this observation created interest in consolidation therapy, previous alemtuzumab based consolidation trials have demonstrated excess morbidity/mortality. We conducted a lenalidomide based consolidation trial for patients with previously untreated CLL who received 6 cycles of induction with pentostatin, cyclophosphamide and rituximab (PCR). Methods: Eligible patients were previously untreated and had CLL in need of treatment according to the NCI-WG criteria (Blood 111:5446). Treatment schema consisted of 6 cycles of pentostatin (2 mg/m2), cyclophosphamide (600 mg/m2) and rituximab (375 mg/m2) given every 21 days (Blood 109:405). All patients completing 6 cycles of PCR, underwent complete restaging and evaluation for MRD using sensitive flow cytometry (Leukemia 21:956). Following restaging and adequate recovery of blood counts, patients received 6 mos of lenalidomide consolidation by continuous daily administration. The starting lenalidomide dose was 5 mg/day with escalation to 10 mg/day after the first cycle as tolerated. Patients again underwent complete restaging and MRD evaluation after 6 mos of lenalidomide. At the time of this restaging, MRD negative patients entered observation. Those with residual disease continued on lenalidomide and underwent repeat MRD assessment every 3 mos with cessation of lenalidomide when an MRD negative state achieved. Results: 45 patients were enrolled at Mayo Clinic between 3/2008 and 11/2009. 44 patients were eligible for treatment: 71% male, median age 65 (range: 44–78); intermediate Rai risk 61%; high Rai risk 39%. On prognostic testing 32% were CD38+, 52% Zap-70 +, 52% IGHV unmutated, and 16% had high risk FISH (del 17p13; del 11q22). 38 of 44 eligible patients (86%) completed 6 cycles of PCR induction. Adverse events deemed at least possibly related to PCR induction included 19 (43%) patients with grade 3+ hematologic toxicity and 9 (20%) with grade 3+ non-hematologic toxicity. The Overall response rate to induction was 98% with 15 CR/CRi, 3 CCR, 9 nPR, and 16 PR. Four patients with CR were also MRD negative at the completion of induction. Of 38 patients who completed induction, 34 initiated lenalidomide consolidation. Thus, by protocol intent to treat analysis, 34/44 (77%) patients starting CIT with PCR were able to receive consolidation therapy. The remaining patients were unable to initiate consolidation due to: failure to complete induction (6 patients), disease progression (1), adverse event (1) and patient refusal (2). Among the 34 patients who initiated consolidation, the median number of cycles of lenalidomide received was 5.5 (range: 1–19). Adverse events deemed at least possibly related to lenalidomide consolidation included 22 (65%) patients with grade 3+ hematologic toxicity and 4 (12%) with grade 3+ non-hematologic toxicity. Among the 34 patients who received at least 1 cycle of lenalidomide, 4 patients have improved the quality of their response to date with 11 patients still on lenalidomide at the time of this report. After median follow-up of 16 mos, 42/44 patients are alive and median duration of response has not been reached. To date 3/44 (7%) of patients have progressed to require additional treatment. Finally, since eligibility was nearly identical to our historic trial of PCR without lenalidomide consolidation, we compared the 44 patients in the present trial to the 64 patients previously treated on our PCR trial (Blood 109:405). Demographic and prognostic characteristics of the patients in the two studies were similar. With the caveat it represents comparison across phase II trials, the proportion of patients free of retreatment at 12 mos was 97% (95%CI: 91–100) for PCR-L vs. 78% (95%CI: 68–89) for PCR (Figure 1). Conclusion: We report here the first results of lenalidomide based consolidation for CLL patients receiving first-line CIT induction. Although lenalidomide consolidation appears to improve the quality of response and prolong time to retreatment, longer follow-up is necessary to determine the clinical benefit of this strategy. Disclosures: Shanafelt: Celgene: Research Funding; Hospira: Research Funding; Genentech: Research Funding. Off Label Use: Lenalidomide. Kay:Celgene: Research Funding; Hospira: Research Funding; Genentech: Research Funding.

Abstract BACKGROUND: Chronic lymphocytic leukemia (CLL) is one of the most common lymphoid malignancies, accounting for ~11% of all hematologic neoplasms. Over the last 15 years, a series of phase 3 trials have established that chemoimmunotherapy (CIT) with fludarabine, cyclophosphamide, and rituximab (FCR) improves both progression free survival (PFS) and overall survival (OS) compared with chemotherapy alone. FCR is the gold standard for young fit patients with treatment naïve CLL. In parallel with the advances in CIT, a profound increase in the understanding of CLL B-cell biology led to new therapeutic approaches.1 Among these, ibrutinib (an irreversible inhibitor of Bruton's Tyrosine Kinase [BTK]) has had the largest impact on clinical practice to date. Initial trials of ibrutinib demonstrated robust and durable efficacy in patients with relapsed/refractory disease. Subsequent phase 3 trials showed improved PFS and OS with ibrutinib relative to chlorambucil in previously untreated, older CLL patients. Despite these advances, the efficacy of ibrutinib as a first-line treatment for younger CLL patients (i.e. <70) relative to the most efficacious CIT regimens, such as FCR, is unknown. METHODS: Eligible patients were treatment-naive individuals with CLL who were age <70 and required therapy. Patients with deletion 17p- were excluded from participating given the poor response of these patients to FCR therapy. Participants were randomly assigned in a 2:1 ratio to receive ibrutinib (420 mg/day until disease progression) and rituximab (50 mg/m2 on day 1 of cycle 2; 325 mg/m2 on day 2 of cycle 2; 500 mg/m2 on day 1 of cycles 3-7) or six courses of intravenous fludarabine (25 mg/m2 ) and cyclophosphamide (250 mg/m2) days 1-3 with rituximab (50 mg/m2 on day 1 of cycle 1; 325 mg/m2 on day 2 of cycle 1; 500 mg/m2 on day 1 of cycles 2-6) every 28-days. The planned accrual was 519 patients. Hematologic toxicity was graded according to the 2008 IWCLL Working Group scale. All other adverse events were graded according to the NCI Common Toxicity Criteria (version 4). The primary endpoint was PFS with a secondary endpoint of overall survival (OS). Analysis was by intention to treat. The first planed interim analysis for PFS was scheduled to occur 24-27 months after full accrual with the first interim analysis for OS scheduled to occur if the boundary for PFS was crossed. The primary analysis was a stratified logrank test applied to all patients as randomized. Treatment effect p-values are one-sided. The study was approved by the Central Institutional Review Board for the National Cancer Institute, conducted in accordance with the principles of the Declaration of Helsinki, and registered with ClinicalTrials.gov (NCT02048813). RESULTS: A total of 529 patients were accrued between January 31, 2014 and June 9, 2016. 354 patients were assigned to ibrutinib and rituximab (IR) and 175 to FCR. Nineteen patients did not start protocol therapy. The first interim analysis was performed September 2018. With median follow-up of 33.4 months, we observed 77 PFS events and 14 deaths. The hazard ratio (HR) for PFS favored IR over FCR (HR=0.352; 95% CI 0.223-0.558; p<0.0001) which crossed the pre specified boundary. The HR for OS also favored the IR arm (HR=0.168, 95% CI 0.053-0.538; p=0.0003, pre-specified boundary for superiority p=0.0005). Kaplan-Meier estimates for PFS and OS are shown in Figure 1A and 1B. In subgroup analysis for PFS, IR was superior to FCR independent of age, sex, performance status, disease stage or the presence/absence of del11q23. With current follow-up, IR was also superior to FCR for IGHV unmutated patients (HR=0.262; 95% CI 0.137-0.498; p<0.0001) but not IGHV mutated patients (HR=0.435; 95% CI 0.140-0.1350; p=0.07). Grade 3 and 4 treatment-related adverse events were observed in 58% of IR and 72% of FCR treated patients (p=0.0042). Specifically, FCR was more frequently associated with grade 3 and 4 neutropenia (FCR: 69 [44%] of 158 vs. IR: 80 [23%] of 352; p<0·0001) and infectious complications (FCR: 28/158 [17.7%] vs. IR: 25/352 [7.1%]; p<0.0001). CONCLUSIONS: The combination of ibrutinib and rituximab provides superior PFS and OS relative to FCR for patients with previously untreated CLL age <70. These findings have immediate practice changing implications and establish ibrutinib-based therapy as the most efficacious first-line therapy for patients with CLL. Disclosures Shanafelt: Mayo Clinic: Patents & Royalties: Physician Well-being Index, Medical Student Well-being Index, Well-being index; Celgene: Research Funding; GlaxoSmithKline: Research Funding; Genentech: Research Funding; Abbvie: Research Funding; Pharmacyclics: Research Funding; Janssen: Research Funding. Kay:Janssen: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Cytomx Therapeutics: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Infinity Pharm: Membership on an entity's Board of Directors or advisory committees. O'Brien:Amgen: Consultancy; Astellas: Consultancy; Celgene: Consultancy; GlaxoSmithKline: Consultancy; Janssen: Consultancy; Aptose Biosciences Inc.: Consultancy; Vaniam Group LLC: Consultancy; Abbvie: Consultancy; Alexion: Consultancy; Kite Pharma: Research Funding; Regeneron: Research Funding; Acerta: Research Funding; Gilead: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; TG Therapeutics: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Sunesis: Consultancy, Research Funding. Barrientos:Pharmacyclics/AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Bayer: Membership on an entity's Board of Directors or advisory committees; astra Zeneca: Membership on an entity's Board of Directors or advisory committees. Erba:Seattle Genetics: Consultancy, Research Funding; Pfizer: Consultancy, Other: grant; Novartis: Consultancy, Speakers Bureau; Pfizer: Consultancy, Other: grant; Pfizer: Consultancy, Other: grant; Incyte: Consultancy, Speakers Bureau; Agios: Consultancy, Speakers Bureau; Agios: Consultancy, Speakers Bureau; Astellas: Research Funding; Janssen: Research Funding; Janssen: Research Funding; Amgen: Research Funding; Amgen: Research Funding; Novartis: Consultancy, Speakers Bureau; Astellas: Research Funding; Incyte: Consultancy, Speakers Bureau; Astellas: Research Funding; Pfizer: Consultancy, Other: grant; Novartis: Consultancy, Speakers Bureau; Juno: Research Funding; Juno: Research Funding; Novartis: Consultancy, Speakers Bureau; MacroGenics: Consultancy; MacroGenics: Consultancy; Amgen: Research Funding; Takeda/Millenium: Research Funding; Amgen: Research Funding; Takeda/Millenium: Research Funding; Seattle Genetics: Consultancy, Research Funding; Jazz: Consultancy, Speakers Bureau; Immunogen: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Jazz: Consultancy, Speakers Bureau; Seattle Genetics: Consultancy, Research Funding; Celgene: Consultancy, Speakers Bureau; Takeda/Millenium: Research Funding; Immunogen: Consultancy, Research Funding; Takeda/Millenium: Research Funding; Glycomimetics: Consultancy, Other: Chair, Data and Safety Monitoring Committee; Celgene: Consultancy, Speakers Bureau; MacroGenics: Consultancy; Daiichi Sankyo: Consultancy, Research Funding; MacroGenics: Consultancy; Glycomimetics: Consultancy, Other: Chair, Data and Safety Monitoring Committee; Daiichi Sankyo: Consultancy, Research Funding; Juno: Research Funding; Juno: Research Funding; Agios: Consultancy, Speakers Bureau; Agios: Consultancy, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; Jazz: Consultancy, Speakers Bureau; Immunogen: Consultancy, Research Funding; Jazz: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Immunogen: Consultancy, Research Funding; Glycomimetics: Consultancy, Other: Chair, Data and Safety Monitoring Committee; Celgene: Consultancy, Speakers Bureau; Daiichi Sankyo: Consultancy, Research Funding; Glycomimetics: Consultancy, Other: Chair, Data and Safety Monitoring Committee; Daiichi Sankyo: Consultancy, Research Funding. Stone:Juno: Consultancy; Macrogenics: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Research Funding; FujiFilm: Consultancy; Sumitomo: Consultancy; Ono/Theradex: Consultancy; Otzuka/Astex: Consultancy; Pfizer: Consultancy; Roche: Consultancy; AbbVie: Consultancy, Research Funding; Actinium: Membership on an entity's Board of Directors or advisory committees; Agios: Consultancy, Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees; Argenx: Membership on an entity's Board of Directors or advisory committees; Arog: Consultancy, Research Funding; Astellas: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Consultancy; Celator / Jazz: Consultancy; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cornerstone: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees. Tallman:ADC Therapeutics: Research Funding; Daiichi-Sankyo: Other: Advisory board; BioSight: Other: Advisory board; AbbVie: Research Funding; Cellerant: Research Funding; AROG: Research Funding; Orsenix: Other: Advisory board.