Shanafelt, Tait D.

BACKGROUND: Chemoimmunotherapy with fludarabine, cyclophosphamide, and rituximab (FCR) has been the standard therapy for younger patients with CLL. FCR therapy is particularly effective in patients with immunoglobulin heavy chain variable region (IGHV) mutated CLL. Approximately half of IGHV mutated patients are progression free 8 years after FCR therapy. At the ASH 2018 meeting, we reported the initial results of the ECOG 1912 (E1912) trial, a phase 3 trial comparing the FCR regimen to the combination of ibrutinib and rituximab (IR) for previously untreated CLL patients age 70 or younger who required therapy. With median follow-up of approximately 34 months, the trial demonstrated both a progression-free survival (PFS) and an overall survival (OS) benefit relative to FCR. On sub-set analysis by IGHV mutation status, the difference in PFS was statistically significant for IGHV unmutated patients but, with current follow-up, not IGHV mutated patients. Here, we present updated results for PFS in the E1912 trial. METHODS: As previously reported, eligible patients were treatment-naive individuals with CLL age 70 or younger. Patients with deletion 17p- were excluded from participating in the E1912 trial given their known poor response to FCR therapy. Patients were randomly assigned in a two-to-one ratio to receive ibrutinib (420 mg/day until disease progression or unacceptable toxicity) and rituximab (50 mg/m2 on day 1 of cycle 2, 325 mg/m2 on day 2 of cycle 2, and then 500 mg/m2 on day 1 of cycles 3-7) or six courses of intravenous fludarabine (25 mg/m2 days 1-3), cyclophosphamide (250 mg/m2 days 1-3) and rituximab (50 mg/m2 on day 1 of cycle 1, 325 mg/m2 on day 2 of cycle 1, and then 500 mg/m2 on day 1 of cycles 2-6) every 28-days. Adverse events (AEs) were graded according to the NCI Common Toxicity Criteria (version 4). Dose adjustments for cytopenias were based on the IWCLL CLL Working Group grading scale. The primary endpoint of the trial was PFS with OS a secondary endpoint. Analysis was by intention to treat. RESULTS: With median follow-up of 45 months, 257 (73%) of 354 patients randomized to IR remain on ibrutinib. With extended follow-up, grade 3 and above treatment-related AEs were observed in 70% of IR and 80% of FCR treated patients (OR=0.56; 95% CI 0.34 - 0.90; p=0.013). Among IR-treated patients, the median time on treatment is currently 43 months (range=0.2-61). Among the 95 patients who have discontinued ibrutinib, the reason for discontinuation was progression or death in 23 (7% of patients who started IR; 24% of those who discontinued treatment), AE or complication in 48 (14% of patients who started IR; 51% of those who discontinued treatment), and withdrawal of consent or other reasons in 24 (7% of patients who started IR; 25% of those who discontinued treatment). On multivariable Cox regression adjusting for Timed Up and Go test score, Cumulative Illness Rating Scale (CIRS) score, age, gender, ECOG performance status, creatinine clearance, and baseline anemia/thrombocytopenia, only CIRS score (range 0 - 14) predicted discontinuation of ibrutinib for a reason other than progression or death (HR=1.13 per unit increase; 95% CI 1.03 - 1.23; p=0.009). Among the 72 patients who discontinued ibrutinib for a reason other than progression or death, the median time on ibrutinib was 15.1 months (range 0.2-58.2 months). The median time from ibrutinib discontinuation to disease progression or death was 23 months. With current follow-up, we observed 110 PFS events. The hazard ratio (HR) for PFS favored IR over FCR (HR=0.39; 95% CI 0.26-0.57; p<0.0001). Updated analysis of OS will be presented. On sub-group analysis by IGHV mutation status, IR was superior to FCR for IGHV unmutated patients (HR=0.28; 95% CI 0.17-0.48; p<0.0001). With current follow-up the difference is not significant in IGHV mutated patients (HR=0.42; 95% CI 0.16-1.16; p=0.086). Kaplan-Meier estimates for PFS are shown in Figure 1. CONCLUSIONS: Although less than 7% of ibrutinib treated patients progressed while on therapy, roughly 1 in 5 patients have discontinued ibrutinib for a reason other than progression or death. The only parameter significantly associated with discontinuation for a reason other than progression was increased baseline CIRS score. With extended follow-up, the combination of ibrutinib and rituximab continues to provide superior PFS compared to FCR for younger patients with previously untreated CLL. Disclosures Shanafelt: Pharmacyclics: Research Funding; Patent: Patents & Royalties: US14/292,075 on green tea extract epigallocatechin gallate in combination with chemotherapy for chronic lymphocytic leukemia; Polyphenon E International: Research Funding; Merck: Research Funding; Abbvie: Research Funding; Genentech: Research Funding; Celgene: Research Funding; Glaxo-SmithKline: Research Funding; Hospira: Research Funding; Cephalon: Research Funding. Kay:MorphoSys: Other: Data Safety Monitoring Board; Infinity Pharmaceuticals: Other: DSMB; Celgene: Other: Data Safety Monitoring Board; Agios: Other: DSMB. O'Brien:Janssen: Consultancy, Honoraria; Pharmacyclics LLC, an AbbVie Company: Consultancy, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria; Astellas: Consultancy; Aptose Biosciences, Inc: Consultancy; Amgen: Consultancy; Alexion: Consultancy; Acerta: Research Funding; Eisai: Consultancy; Gilead: Consultancy, Research Funding; GlaxoSmithKline: Consultancy; Verastem: Consultancy; Celgene: Consultancy; Sunesis: Consultancy, Research Funding; TG Therapeutics: Consultancy, Research Funding; Vaniam Group LLC: Consultancy; Regeneron: Research Funding; Kite: Research Funding. Barrientos:AbbVie: Consultancy, Research Funding; AstraZeneca: Consultancy; Genentech: Consultancy; Bayer: Consultancy; Gilead: Consultancy; Janssen: Honoraria; Pharmacyclics LLC, an AbbVie Company: Consultancy, Research Funding; Sandoz: Consultancy; Oncternal Therapeutics: Research Funding. Coutre:Astellas: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Research Funding; Astra Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees; Acerta: Research Funding; Gilead: Research Funding; BeiGene: Other: Travel, Accommodations, Expenses & Data Safety Monitoring Committee; Genentech: Consultancy. Barr:Pharmacyclics LLC, an AbbVie company: Consultancy, Research Funding; Gilead: Consultancy; Verastem: Consultancy; Genentech: Consultancy; Seattle Genetics: Consultancy; Merck: Consultancy; Celgene: Consultancy; Janssen: Consultancy; AbbVie: Consultancy; Astra Zeneca: Consultancy, Research Funding; TG Therapeutics: Consultancy, Research Funding. Cashen:Celgene: Other: Speaker's Bureau; Seattle Genetics: Other: Speaker's Bureau; Novartis: Other: Speaker's Bureau. Mato:AstraZeneca: Consultancy, Research Funding; AbbVie: Consultancy, Research Funding; Sunesis: Consultancy, Research Funding; Celgene: Consultancy; Johnson & Johnson: Consultancy, Research Funding; TG Therapeutics: Consultancy, Other: DSMB member , Research Funding; LOXO: Consultancy, Research Funding; DTRM Biopharma: Research Funding; Genentech: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; Gilead: Research Funding; Acerta: Consultancy; Janssen: Consultancy. Erba:Amgen: Consultancy; MacroGenics: Consultancy, Other: Lecture fees, Research Funding; MacroGenics: Consultancy, Other: Lecture fees, Research Funding; Novartis: Consultancy, Research Funding, Speakers Bureau; Novartis: Consultancy, Research Funding, Speakers Bureau; Jazz Pharmaceuticals: Consultancy, Speakers Bureau; Agios: Consultancy, Speakers Bureau; Agios: Consultancy, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; Jazz Pharmaceuticals: Consultancy, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; ImmunoGen: Consultancy, Research Funding; Astellas Pharma: Consultancy; Astellas Pharma: Consultancy; Amgen: Consultancy; GlycoMimetics: Consultancy, Other: Chair, data and safety monitoring board, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Celgene: Consultancy, Other: chair, AML Registry Scientific Steering Committee, Speakers Bureau; ImmunoGen: Consultancy, Research Funding; AbbVie: Consultancy, Other: Chair, IRC for phase III studies, Research Funding; GlycoMimetics: Consultancy, Other: Chair, data and safety monitoring board, Research Funding; Covance: Other: Fees for serving as chair on an independent review board for AbbVie Phase III studies; Covance: Other: Fees for serving as chair on an independent review board for AbbVie Phase III studies; AbbVie: Consultancy, Other: Chair, IRC for phase III studies, Research Funding; Celgene: Consultancy, Other: chair, AML Registry Scientific Steering Committee, Speakers Bureau; Pfizer: Consultancy; Pfizer: Consultancy; Seattle Genetics: Consultancy; Seattle Genetics: Consultancy; Daiichi Sankyo: Consultancy, Research Funding. Stone:Arog Pharmaceuticals: Consultancy, Honoraria, Research Funding; Otsuka-Astex Pharmaceuticals: Consultancy; Fujifilm: Consultancy; AstraZeneca: Consultancy; Celator Pharmaceuticals: Consultancy; Abbvie: Consultancy, Research Funding; Ono Pharmaceutical-Theradex Oncology: Consultancy; Cornerstone Pharmaceuticals: Consultancy; Daiichi Sankyo: Consultancy; Takeda: Other: Fees for serving on a data and safety monitoring board ; Orsenix: Consultancy; MacroGenics: Consultancy; Jazz Pharmaceuticals: Consultancy; Agios: Consultancy, Research Funding; Stemline Therapeutics: Consultancy; Pfizer: Consultancy; Celgene: Consultancy, Other: Fees for serving on a steering committee, and fees for serving on a data and safety monitoring board; Novartis: Consultancy, Research Funding; Actinium Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Astellas Pharma: Membership on an entity's Board of Directors or advisory committees; Argenx: Other: Fees for serving on a data and safety monitoring board ; Roche: Consultancy. Tallman:Jazz Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Oncolyze: Consultancy, Membership on an entity's Board of Directors or advisory committees.

Clinician burnout and patient experience are important issues that are often considered separately. New measures of resilience may influence both. We explored relationships among clinician resilience, burnout, and patient experience. Analysis included 490 physicians who completed surveys measuring burnout and resilience (decompression and activation) and had at least 30 patient experience surveys available for analysis. Burnout was measured with 2 items from the Maslach Burnout Inventory (MBI) which were part of the organization’s ongoing measurement of clinician experience. Resilience was measured with 8 items from 2 Press Ganey validated subscales related to clinicians’ ability to decompress from work and their experience of feeling of activation and connection to purpose while at work. Clinicians reporting more frequent symptoms of burnout based on the MBI items reported less ability to decompress ( r for individual measures ranged from −.183 to −.475, P < .01) and less feeling of activation ( r for individual measures ranged from −.116 to −.401, P < .01). Individual elements of decompression and activation were significantly associated with patient experience. In terms of activation, feeling that one’s work makes a difference ( r ranged from .121 to .159, P < .05) and believing one’s work to be meaningful ( r ranged from .102 to .135, P < .05) were positively associated with patient experience with their care provider. However, elements of decompression such as being able to free one’s mind from work ( r ranged from −.092 to −.119, P < .05) and being able to disconnect from work communications such as e-mails ( r ranged from −.094 to −.130, P < .05) were negatively associated with patient experience with their care providers. Patient and provider experience are intertwined in that clinician resilience is associated with both burnout and patient experience, but individual mechanisms of resilience may be beneficial for the clinician but not for the patient.

Abstract BACKGROUND: Chronic lymphocytic leukemia (CLL) is a heterogeneous B cell malignancy with patients being categorized into disease subsets based on several key biologic parameters, e.g., mutation status (mutated, M; or unmutated, UM) of the immunoglobulin heavy chain variable region (IGHV), acquired chromosomal abnormalities, and expression of CD38 and CD49d. Furthermore, about one third of CLL patients express stereotyped B cell receptors and/or may acquire high risk common mutations in genes such as NOTCH1 and SF3B1 suggesting ongoing genetic evolution as drivers of disease development. Critical to this concept, those CLL patients with trisomy 12 (T12) defects have a higher incidence of mutations in NOTCH1 and often have a stereotyped receptor. However, T12 patients may have a variable clinical course that appears to be unrelated to these 2 drivers suggesting an additional, possibly non-coding genetic component that may further impact disease progression in these patients. One potentially relevant genetic factor that could influence T12 clinical course is long non-coding RNAs (lncRNAs). LncRNAs are transcripts longer than 200 nucleotides that can affect a number of cellular processes. Importantly, lncRNAs have been implicated in various cancers including malignant hematopoiesis indicating they could be therapeutic targets and/or clinically useful biomarkers. METHODS: To pursue a role for lncRNAs in T12 we used v3.0 Arraystar Human LncRNA Microarrays to assess the global profile of lncRNA expression in CLL with an emphasis on patients with T12. Two cohorts of 6 patients with T12 were selected for comparison: one defined as progressive with a short time to treatment (TTT) (treatment ≤1 year after diagnosis) and one as indolent (no treatment > 5 years after diagnosis). Each cohort included 3 patients with M and 3 with UM IGHV status. RNA from normal CD5+ and CD5- B cells was included as a control. To compensate for the small sample size in each cohort, a significant difference in lncRNA expression between the groups was defined as a fold change (FC) ≥5.0, p-value ≤0.05 and false discovery rate (FDR) ≤ 0.05. RESULTS: An initial global comparison of CD5+/CD5- normal B cells vs all CLL samples found that 609 lncRNAs were differentially expressed using the criteria listed above with 158 lncRNAs having a FC>10. Notable lncRNAs in this group included: LOC541472 (down in CLL and associated with the IL-6 gene), D63785 (up in CLL and associated with TBC1D3C, an oncoprotein), CTC-459I6.1 (up in CLL and associated with RASGRF2) and AC002480.5 (down in CLL and associated with STEAP1B, shown to be overexpressed in prostate cancer). We next evaluated T12 samples and identified 90 candidate lncRNAs that may discriminate between progressive and indolent T12 cases. Within this group were 11 lncRNAs with a FC > 10, 5 of which have no known associated gene. Of those associated with known genes, 3 were ultra-conserved region encoding lncRNAs down-regulated in progressive T12 patients (TTT ≤1 yr) and linked to hephaestin-like protein 1 precursor, pannexin-1, and tubulin beta-3 chain isoform 1. Of potential high relevance we found that the lncRNA LPP-AS1 was down-regulated in progressive T12 patients (TTT ≤1 yr) and known to be associated with the LIM-containing lipoma preferred partner (LPP) gene (p=0.028; FDR=0.03 and FC=18.3). Looking specifically at IGHV M progressive T12 patients (T12M≤1 yr) vs IGHV M indolent T12 patients (T12M>5 yrs), we again found the LPP-AS1 lncRNA was highly down-regulated in T12M≤1 (p=0.00046; FDR=0.006 and FC=34.5) but it was not found to be differentially expressed in the UM T12≤1 yr vs UM T12>5 yr comparison. The LPP gene has been shown to play a role in cell-cell adhesion, motility and signaling, and is often the fusion partner for the mixed lineage leukemia (MLL) gene in secondary acute leukemia. Furthermore, LLP may play a role in breast cancer cell invasion. LPP-AS1 may be participating in IGHV M T12 progression by affecting LPP and thus influencing migration through the lymph node microenvironment. CONCLUSION: While candidate lncRNAs in T12 CLL need to be validated, the LPP-AS1 lncRNA shows promise as a possible marker and potential treatment target for those patients with T12 and M IGHV that may progress rapidly. Further studies are needed to evaluate the impact of lncRNAs on clinical outcome of T12 CLL patients. Disclosures Shanafelt: Hospiria: Research Funding; Pharmacyclics/Jannsen: Research Funding; Cephalon: Research Funding; Celgene: Research Funding; glaxoSmithKline: Research Funding; Genetech: Research Funding; Polyphenon E Int'l: Research Funding. Kay:Celgene: Research Funding.

Abstract The IGHV4-34 gene is very frequent (~10%) in the B cell receptor immunoglobulin (BcR IG) gene repertoire of chronic lymphocytic leukemia (CLL). Over 30% of IGHV4-34 CLL cases can be assigned to different subsets with stereotyped BcR IG. The largest is subset #4 which represents ~1% of all CLL and ~10% of IGHV4-34 CLL and is considered a prototype for indolent disease. The BcR IG of a great majority (~85%) of IGHV4-34 CLL cases carry a significant load of somatic hypermutation (SHM), often with distinctive SHM patterns. This holds especially true for stereotyped subsets and is suggestive of particular modes of interactions with the selecting antigen(s). In detail, subsets #4 and #16, both involving IgG-switched cases (IgG-CLL), exhibit the greatest sequence similarity in SHM profiles, whereas they differ in this respect from IgM/D subsets #29 and #201. Prompted by these observations, here we explored the extent that these subset-biased SHM profiles in different IGHV4-34 stereotyped subsets were reflected in distinct demographics, clinical presentation, genomic aberrations and outcomes. Within a multi-institutional series of 20,331 CLL patients, 1790 (8.8%) expressed IGHV4-34 BcR IG. Following established bioinformatics approaches for the identification of BcR IG stereotypy, 573/1790 IGHV4-34 CLL cases (32%) were assigned to stereotyped subsets; of these, 340 cases (19% of all IGHV4-34 CLL and 60% of stereotyped IGHV4-34 cases) belonged to subsets #4, #16, #29 and #201, all concerning IGHV-mutated CLL (M-CLL). Clinicobiological information was available for 275/340 patients: #4, n=150; #16, n=44; #29, n=39; and #201, n=42. Comparisons between subsets revealed no differences in gender and age distribution. Interestingly, however, 36-43% of each subset cases were young for CLL (defined as patients aged ≤55 years), which is higher compared to general CLL cohorts, where young patients generally account for ~25% of cases. In contrast, significant differences were identified between subsets regarding: (i) disease stage at diagnosis, with >90% of IgG subsets #4 and #16 diagnosed at Binet stage A versus 83% in subset #201 and 74% in subset #29 (p=0.029); (ii) CD38 expression, ranging from 1% in subset #4 to 10% in subset #201 (p=0.013); (iii) the distribution of del(13q), peaking at a remarkable 92% in subset #29 versus only 37% in subset #16 (p<0.0001). Regarding other genomic aberrations, they were either absent (NOTCH1 mutations) or rare (SF3B1 mutations, trisomy 12, del(11q), TP53 aberrations due to either del(17p) and/or TP53 mutations). The sole exception concerned a high frequency (14%) of TP53 aberrations in subset #29 (p<0.05 compared with the other subsets), which is notable for M-CLL cases in general. Time to first treatment (TTFT) could be analyzed in 228 cases. IgG subsets #4 and #16 had significantly (p=0.036) longer TTFT (median TTFT: not yet reached) compared to the IgM/D subsets #29 and #201 (median TTFT: 11 and 12 years, respectively). In conclusion, we have identified distinct clinicobiological profiles for different stereotyped IGHV4-34 M-CLL subsets, highlighting subsets #4 and #16 as particularly indolent, which is important for both medical and social reasons, especially considering that a significant proportion of patients in these subsets are diagnosed at younger ages. Our findings support the notion that BcR IG stereotypy refines prognostication in CLL, superseding the crude immunogenetic distinction based on SHM load only. Additionally, the observed heterogeneity suggests that not all M-CLL are equal, prompting further research into the underlying biological background with the ultimate aim of tailored patient management. Disclosures Tausch: Gilead: Other: Travel support. Shanafelt:Glaxo-Smith_Kline: Research Funding; Genentech: Research Funding; Celgene: Research Funding; Polyphenon E Int'l: Research Funding; Hospira: Research Funding; Janssen: Research Funding; Pharmactckucs: Research Funding; Cephalon: Research Funding. Niemann:Gilead: Consultancy; Janssen: Consultancy; Roche: Consultancy; Novartis: Other: Travel grant. Langerak:InVivoScribe: Patents & Royalties: Licensing of IP and Patent on BIOMED-2-based methods for PCR-based Clonality Diagnostics.; DAKO: Patents & Royalties: Licensing of IP and Patent on Split-Signal FISH. Royalties for Dept. of Immunology, Erasmus MC, Rotterdam, NL; Roche: Other: Lab services in the field of MRD diagnostics provided by Dept of Immunology, Erasmus MC (Rotterdam). Hallek:Celgene: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; AbbVie: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Roche: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Boehringher Ingelheim: Honoraria, Other: Speakers Bureau and/or Advisory Boards; Pharmacyclics: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Mundipharma: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Janssen: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Gilead: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding. Ghia:Janssen Pharmaceuticals: Research Funding.

Abstract Background: Multiple Myeloma (MM) patients have a substantially reduced Health related Quality of Life (HQOL) at diagnosis (dx) due to disease related symptoms like bone pain (58%) and fatigue (32%). HQOL monitoring is becoming increasingly important, owing to improved survival and the impact of treatment-related toxicity. As a result HQOL assessments are increasingly being used in clinical trials, but the literature regarding the relationship between HQOL and outcomes in MM is sparse. We used the Mayo Clinic “Hematology Patient Reported Symptom Screen” (HPRSS) to assess the impact of HQOL on outcomes in newly dx patients with MM. Methods:We retrospectively reviewed charts of 453 patients with newly dx MM seen at Mayo Clinic, Rochester from 2009 to 2014. All patients who visit Mayo clinic hematology clinic complete a 3-point questionnaire (HPRSS) on pain, fatigue and quality of life (QOL) (scored on a scale of 0-10; with 0 being the least fatigue or pain and 10 being the best QOL). Pain, fatigue and QOL scores documented at the time of dx and at 6 months were collected. JMP version 10 was used for the data analysis. Results: The median age at diagnosis was 67 years (range, 33-95); 60% were male. The estimated median OS for the cohort was 21 m (95% CI19, 23); 387 (85%) of the patients were alive at last follow up and the median OS for the population was not reached. The median (IQR) scores for pain, fatigue and QOL were 4 (2, 6), 3 (1, 5), and 7 (5, 9), respectively. First, we examined the relationship between each of the scores (dichotomized at the median) and the baseline characteristics. Higher fatigue scores were associated with lower Hb and serum albumin and higher beta 2 microglobulin, LDH and marrow plasmacytosis. Higher pain scores were seen in female patients, and associated with higher B2M, serum calcium and lytic bone lesions. Lower QOL scores were associated with lower absolute lymphocyte count and serum albumin levels. Next, we examined the relationship between the scores and the OS from diagnosis. The overall survival was inferior for patients with higher pain scores, fatigue scores and lower QOL scores (Figure). In a multivariable analysis, fatigue scores were most strongly associated with survival outcome. Patients with adverse scores in two or more of pain, fatigue and QOL had significantly inferior outcomes (Figure). In univariate analysis, age, B2M, LDH, FISH high risk and the presence of two or more adverse scores were all significantly associated with poorer OS. In a multivariable analysis, age, LDH and the presence >=2 adverse scores were all associated with shorter OS. Of the 453 patients included in the study, 222 patients had pain, fatigue and QOL scores at 6 month from diagnosis. At 6 months, the median (IQR) scores for pain, fatigue and QOL were 2 (1, 5), 4 (2, 5), and 7 (5, 9), respectively; suggesting improved pain, worsened fatigue and static QOL scores. Improvement in the scores by at least one point was seen in 50%, 49% and 38% for the fatigue, pain and QOL scores. While the pain and fatigue scores at 6 months correlated inversely with OS, improvements in the scores in any of the three were not associated with any improved outcomes. Conclusion: A simple, patient reported scoring system for pain, fatigue, and overall perceived QOL at the time of diagnosis is a powerful predictor of survival outcomes in patients with newly diagnosed MM and should be considered routinely in clinical practice. The results of these patient reported measures can be utilized to develop risk-adapted trials in patients with MM. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Abstract Introduction: Monoclonal B cell lymphocytosis (MBL) is an asymptomatic expansion of clonal CD19+/CD5+ B cells with less than 5x109/L cells in the peripheral blood and without other manifestations of chronic lymphocytic leukemia (CLL). Approximately 1% of MBL evolves to CLL requiring therapy per year; thus it is critical to develop more precise tools to identify which MBL will progress to CLL and require treatment. Patients and Methods: In this study, we performed targeted deep sequencing (TDS) on 49 high-count MBL individuals (median B-cell count 3.7x109/L; range 0.8-4.9x109/L) and explored the mutation status of 20 driver genes recurrently mutated in CLL. We analyzed the clonal evolution in 45 of these 49 MBLs by screening 2-4 sequential samples (average time between samples 56 months, range 10-119 months). At last follow-up, 19 cases (39%) had progressed to Rai>0, and 10 cases (20%) required treatment. Tumor and germ line DNAs were isolated from sorted CD5+/CD19+ and CD5-/CD19- cell populations, respectively. Overall, 154 samples from 49 MBL cases (105 tumor and 49 germ line) were screened using semiconductor sequencing technology. The latter genetic information was integrated with relevant clinical and biological parameters, and we evaluated the effect of driver mutations and clonal expansion on time to CLL progression and time to treatment (TTT). Results and Discussion: Our cohort consisted in 17 women and 32 men, with a median age of 66 years (range: 44-80). Five cases presented secondary diseases, including melanoma, lung and bladder cancer. Clinical and biological parameters were collected, including IGHV mutation status (mutated 66%, unmutated 34%), ZAP70 and CD49 expression (25% each). At presentation, 46% of cases had del(13q), 27% trisomy 12, 6% del(11q), and 4% del(17p). Overall, we found somatic non-synonymous mutations in 23 of 49 MBLs (47%) at the initial time point including 22% of cases with more than one mutated driver gene. The average depth of coverage was 730x, thus allowing the identification of small subclonal mutations. Recurrent mutations were found in most of the drivers: CHD2, DDX3X (8% of cases), FBXW7, NOTCH1, SF3B1 (6% each), ATM, BCOR, BIRC3, BRAF, KRAS, MED12, MYD88 and ZMYM3 (4% each). Furthermore, ITPKB, POT1, SAMHD1 and XPO1 were mutated in only one case, whereas no mutations were found in HIST1H1E, RIPK1 and TP53. In 4 individuals, we found two mutations in the same gene (BRAF, DDX3X, KRAS and SAMHD1). Genes that are known to be associated with disease progression in CLL were either mutated with significantly lower incidence (NOTCH1, SF3B1) or not mutated (TP53). Mutations were detected on average 45 months (range 9-73) prior to progression to CLL Rai>0 indicating the early origin of most driver gene mutations in the MBL/CLL continuum. The presence of driver mutations in MBL was associated with shorter TTT (median TTT: present: 96 months vs. not present: not reached, HR: 5.52, 95% CI: 1.2-26.2, P =0.015). Next, we looked at clonal expansion of driver mutations over time (defined as >2-fold change in the allelic frequency of driver mutations between time points). Of 20 MBLs with mutations at baseline who had sequential samples available, 10 cases showed clonal expansion. Seven out of 10 MBLs who required therapy showed clonal expansion, which was detected on average 15 months (range 6-30 month) prior to treatment. Finally, the detection of clonal expansion was significantly associated with reduced TTT (median TTT: clonal expansion: 21 months vs. no clonal expansion: 84 months, HR: 7.79, 95% CI: 1.94-31.3, P <0.001). Conclusion: We have confirmed the existence of recurrent mutations in most CLL putative driver genes at the premalignant MBL stage many years before progression to CLL. Furthermore, the early identification of driver mutations and its clonal expansion predicts a shorter TTT. Of note, clonal evolution under selective pressure has recently been linked to the onset of CLL progression after therapy. In this study, we characterized the clonal dynamics in the pre-malignant stages of the disease and underlined its impact on clinical outcome. Despite the relatively small size of the cohort, these findings suggest that the sequential monitoring of MBL individuals with a simple and reliable technique, such as TDS, will be at least of prognostic use and thus its incorporation in the disease stratification and clinical management should be further tested. Disclosures Fonseca: Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding; Applied Biosciences: Membership on an entity's Board of Directors or advisory committees; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding; Millennium: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding; Binding Site: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding; Onyx/Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding; Bayer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding. Kay:Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Research Funding; Tolero Pharma: Research Funding; Genentech: Research Funding; Celgene Corporation: Membership on an entity's Board of Directors or advisory committees, Research Funding; Hospira: Research Funding.

Abstract Introduction. CLL primarily affects elderly individuals who frequently have comorbid health conditions. It is typically assumed non-CLL-related etiologies will be the ultimate cause of death for most CLL patients, particularly those with comorbid conditions at diagnosis. Methods. Between 9/2002 and 11/2014, 1174 patients with newly diagnosed CLL were enrolled in a prospective cohort study evaluating the natural history of CLL. Comorbidities were prospectively recorded at the time of diagnosis. Comorbidities arising during the course of disease were not considered for this analysis. Standardized longitudinal follow-up was performed in all patients every 6 months for the first 3 years after diagnosis and annually thereafter through 04/2015. Internal and external medical records, death certificates, and information from next of kin were centrally reviewed to determine cause of death, using a standardized protocol. Categorical and continuous variables were evaluated using the c2 or Fisher exact tests and the Mann-Whitney test, as appropriate. Results. Baseline characteristics at time of CLL diagnosis are shown in the Table. Over 80% of patients had 2 or more comorbidities at diagnosis (median 3, range 0-11). After a median follow up of 5 years, 224 (19%) patients have died. The cause of death could be accurately determined in 183 (82%) of these patients. The cause of death was due to CLL in 135 (74%), including 84 (46%) CLL progressions, 14 (8%) infections, and 37 (20%) other cancers. Death was due to non-CLL-related causes (such as congestive heart failure, stroke or chronic obstructive pulmonary disease) in the remaining 48 (26%) patients. On univariable analysis, age and number of comorbid health conditions were not related to whether or not the cause of death was related/unrelated to CLL. The only specific co-morbid condition at diagnosis that predicted for non-CLL related death was stroke (8% vs 1%, p=0.04). Unmutated IGHV was the only prognostic factor thatpredicted greater likelihood of CLL-related death (70% vs 50%, p=0.03). Conclusions. The majority of patients with CLL have multiple comorbidities at time of diagnosis. Despite this fact, CLL progression and/or CLL-related complications are the primary cause of death. The number and type of comorbidities at diagnosis have minimal relationship to whether or not the ultimate cause of death was CLL-related. In contrast, the CLL-specific characteristic IGHV status (but interestingly not FISH defects) correlates with cause of death. Collectively, these findings illustrate the need for more effective CLL therapy, particularly treatments that can be tolerated by patients with comorbid health conditions. It is hoped the signaling inhibitors may help address this unmet need. Table. Number (%), median [range] N=1174 Age (years) 63 [23-89] Males Females 791 (67) 383 (33) Creatinine-Clearance > (mL/min) 86 [10-252] B2M (mg/dL) 2.3 [1.1-13.2] Rai stage 0 I-II III-IV 604 (52) 512 (38) 54 (10) CD49d positive negative 277 (30) 638 (70) CD38 positive negative 332 (30) 780 (70) ZAP70 positive negative 380 (37) 650 (63) IGHV unmutated mutated 394 (44) 506 (56) FISH del13q negative +12 del11q del17p 395 (40) 175 (18) 276 (28) 90 (9) 50 (5) Comorbid health conditions Other cancers 237 (20) Stroke 38 (3) Cardiac disease 326 (28) Hypertension 472 (40) Respiratory 210 (18) Endocrinologic 165 (14) Diabetes 118 (10) Hyperlipidemia 485 (41) Rheumatologic 489 (42) Gastrointestinal 384 (33) Genitourinary 412 (35) Psychiatric 197 (17) DVT/PE 33 (3) Substance abuse 58 (5) Sexually transmitted disease 35 (3) Obesity 376 (32) # of Comorbidities 0 1 2 3 4 > 4 66 (6) 148 (13) 203 (17) 220 (19) 206 (17) 331 (28) Disclosures Kay: Hospira: Research Funding; Genentech: Research Funding; Celgene Corporation: Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Research Funding; Tolero Pharma: Research Funding. Cerhan:Kite Pharma: Research Funding.

Abstract Background: Monoclonal B-cell lymphocytosis (MBL) is characterized by the presence of a circulating population of clonal B-cells where the total B-cell count is <5 × 109/L and criteria for the diagnosis of other lymphoproliferative disorders are not present. In most patients the immunophenotype is similar to that of chronic lymphocytic leukemia with co-expression of CD19 and CD5. The natural history of MBL is unclear. We used the Mayo Clinic hematopathology database to identify patients with MBL and abstracted clinical information on natural history and prognostic parameters from clinical and research records. Methods: After IRB review and approval, we reviewed the hematopathology records of 2292 patients seen at Mayo Clinic between August 1998 and May 2006 who had a clonal B-cell population on flow cytometry phenotypically consistent with CLL and fewer than <5 × 109/L B-cells. Clinical records were then reviewed to identify patients who fulfilled the criteria for MBL (no evidence of other lymphoproliferative disorders, no adenopathy on exam). Patient characteristics, prognostic parameters, and clinical outcomes were abstracted from the clinical and research records of these patients. Cox regression analysis was used to evaluate association between prognostic markers and time to treatment. Results: A total of 118 patients meeting the criteria for MBL were identified. Median age at the time of MBL diagnosis was 69.4 years (range 39.0 – 91.4). A slight male preponderance was observed (54% male). CD38 status was available for 106 (90%) patients of whom 20% were CD38 positive using the 30% threshold to classify CD38. Cytogenetic analysis by fluorescent in situ hybridization (FISH) was available in 58 (49%) patients. Using the hierarchical classification system of Dohner and colleagues, 26 (44.8%) were 13q-, 10 (17.2%) were trisomy 12, 2 (3.4%) were 11q-, 1 (1.7%) was 17p-, and 19 were (32.8%) no defect was detected. ZAP-70 status was available for 32 patients of whom 22% were ZAP-70+ positive. IgVH gene mutation status was only available for 15 (12.7%) patients of whom 40% were unmutated. Time from MBL diagnosis to treatment is shown in Figure 1. Survival free of treatment was 92.7% (95%CI: 86.8–99.1%) at 1 year, 90.9% (95%CI: 84.2–98.2%) at 2 years, and 87.5% (95% CI: 78.7–97.4%) at 5 years. While age (p=0.68) and gender (p=0.14) were not found to be associated with time to treatment (TTT), CD38 status showed a strong relationship with TTT (p<0.001, HR: 22.7, 95% CI: 3.4–239.6). Conclusion: The distribution of prognostic parameters (e.g. CD38, FISH) in patients with MBL appears similar to that of patients with early stage CLL. We observed a low rate of progression, with 5 year survival free of treatment greater than 87%. TTT among newly diagnosed MBL patients was associated with the CD38 status of clonal B-cells. Figure Figure