Grinblatt, David L.

AbstractBackgroundAcute lymphoblastic leukemia (ALL) in adults is aggressive, with long‐term outcomes impacted by treatment resistance and toxicity. CD52 is expressed in most cases of B‐ and T‐lineage ALL. Alemtuzumab, a humanized immunoglobulin G1 monoclonal antibody that targets CD52, was identified as a potential agent to improve treatment efficacy without increasing toxicity.MethodsIn this phase 1/2 study (Cancer and Leukemia Group B [CALGB] 10102, NCT00061945), a course of single‐agent alemtuzumab was intercalated into CALGB 19802 backbone chemotherapy after the third course of intensive chemotherapy in those who were CD52+ at diagnosis. Phase 1 tested three dose levels of subcutaneous alemtuzumab (10, 20, and 30 mg 3 times weekly for 4 weeks/12 doses) and demonstrated that 30 mg was tolerable. Phase 2 established feasibility.ResultsThe study enrolled 295 evaluable patients (115 in phase 1, 180 in phase 2); 206 (69.8%) were CD52+. Among evaluable CD52+ patients, 43.7% (90/206) completed the first three treatment modules; 97.8% (88 of 90) were treated with alemtuzumab. Alemtuzumab was associated with cytomegalovirus viremia, which occurred in 23.3% (14 of 60) of patients during and 29.2% (19 of 65) after alemtuzumab treatment. With a median follow‐up of 101.2 months, median overall survival (OS) was 26.3 months (3‐year rate, 44%; 5‐year rate, 36%; 10‐year rate, 31%). Landmark analysis at the start of the fourth course of treatment demonstrated no difference in OS or disease‐free survival between patients who did and who did not receive alemtuzumab.ConclusionAlemtuzumab was feasible to administer in adults with ALL receiving intensive chemotherapy, but was without evidence of benefit.

Abstract Introduction: Non-Hodgkin lymphoma (NHL) constitutes ~40% of hematologic malignancies and, in 2020, resulted in 19,940 deaths in the USA. The most common NHL subtypes are diffuse large B-cell lymphoma (DLBCL), including primary mediastinal large B-cell lymphoma (PMBCL), and follicular lymphoma (FL). Although a majority of patients respond to standard-of-care therapy, many patients with NHL eventually relapse, highlighting the need for additional treatments. Real-world data regarding the safety and efficacy of emerging therapies in the relapsed/refractory (R/R) population, and the association between treatment patterns and patient outcomes, are limited. These data could provide unique insights to clinical and health-related quality of life (HRQoL) outcomes in patients with DLBCL, FL, or PMBCL treated with emerging therapies, especially novel options such as chimeric antigen receptor (CAR) T cell therapies. Methods: The Connect ® Lymphoma Disease Registry (NCT04982471) is a US-based, multicenter, prospective observational cohort study of patients with R/R NHL (DLBCL, FL, and PMBCL). Approximately 2100 patients ≥ 18 years of age from ~200 community oncology (~80%) or academic (~20%) sites will be enrolled over a ~3-year period. Patients with histologically confirmed NHL subtypes will be enrolled into 1 of 4 cohorts: first R/R DLBCL, second R/R DLBCL, first R/R FL, or first R/R PMBCL (Figure). Patients will be required to have begun second- (first R/R) or third- (second R/R) line systemic treatment within 60 days prior to enrollment. Patients receiving treatment for any active malignancy other than DLBCL, FL, or PMBCL at the time of enrollment, or who are diagnosed with any other malignancy in the 6 months prior to enrollment, will be excluded. All treatment and management decisions will be determined by the practicing clinicians. Patients may undergo hematopoietic stem cell transplantation, CAR T cell therapy, or other treatments at other sites while participating in this study. Patients will be followed from enrollment for up to 5 years or until death, withdrawal of consent, loss to follow-up, or study termination, whichever occurs first. Data collection will occur at enrollment (baseline) and then every ~3 months. The main objectives of the Connect ® Registry are to describe patient characteristics, practice patterns, and factors associated with treatment choice, sequencing, and effectiveness in NHL subtypes. Secondary objectives include describing treatment regimen safety, patient-reported outcomes (PROs) including HRQoL, and healthcare resource utilization outcomes. Exploratory objectives include tumor and blood biomarker evaluation and understanding the availability of social support and its impact on long-term treatment decision-making. Case report forms will be used to collect clinical and treatment data, including baseline demographics, clinical characteristics, treatment details and response, and socioeconomic factors. Outcome measures for efficacy will be progression-free survival, event-free survival, objective response rate, time to next treatment, and overall survival. The availability of social support will be assessed via a specific questionnaire administered at baseline. General (EQ-5D-5L) and disease-specific (FACT-Lym) questionnaires will also be administered. Patients may also optionally agree to release tumor biopsies and blood samples for biomarker analysis. Clinicians will be required to report serious adverse events (AEs), secondary primary malignancies, and confirmed COVID-19 infections within 24 hours. Non-serious AEs of interest include grade 1-3 cytokine release syndrome, grade 1-3 neurotoxicity, grade 3 colitis, grade 3 arrhythmia, grade 3 hemorrhage. Other AEs of interest to be collected include grade 3 hypogammaglobulinemia, prolonged grade 3 cytopenia, and grade 3 infections. Data collected in the Connect ® Registry will increase understanding of the association between emerging therapies and patient outcomes for R/R DLBCL, FL, and PMBCL. Study support: Bristol Myers Squibb Figure 1 Figure 1. Disclosures Flowers: Amgen: Research Funding; Janssen: Research Funding; Biopharma: Consultancy; Ziopharm: Research Funding; Burroughs Wellcome Fund: Research Funding; Nektar: Research Funding; Karyopharm: Consultancy; Iovance: Research Funding; Allogene: Research Funding; AbbVie: Consultancy, Research Funding; Cellectis: Research Funding; Pfizer: Research Funding; Sanofi: Research Funding; BeiGene: Consultancy; Kite: Research Funding; EMD: Research Funding; Genentech/Roche: Consultancy, Research Funding; Morphosys: Research Funding; Adaptimmune: Research Funding; Novartis: Research Funding; Epizyme, Inc.: Consultancy; Spectrum: Consultancy; Pharmacyclics/Janssen: Consultancy; Acerta: Research Funding; 4D: Research Funding; Denovo: Consultancy; Celgene: Consultancy, Research Funding; Guardant: Research Funding; Genmab: Consultancy; Gilead: Consultancy, Research Funding; Bayer: Consultancy, Research Funding; SeaGen: Consultancy; Cancer Prevention and Research Institute of Texas: CPRIT Scholar in Cancer Research: Research Funding; Takeda: Research Funding; National Cancer Institute: Research Funding; TG Therapeutics: Research Funding; Eastern Cooperative Oncology Group: Research Funding; Xencor: Research Funding; Pharmacyclics: Research Funding. Andorsky: Celgene/Bristol Myers Squibb: Research Funding; AbbVie: Consultancy; Celgene/Bristol Myers Squibb: Consultancy; AstraZeneca: Other: served on steering committees; Epizyme: Research Funding; AbbVie: Research Funding. Burke: SeaGen: Consultancy, Speakers Bureau; X4 Pharmaceuticals: Consultancy; Bristol Myers Squibb: Consultancy; Verastem: Consultancy; AstraZeneca: Consultancy; MorphoSys: Consultancy; Adaptive Biotechnologies: Consultancy; Roche/Genentech: Consultancy; Epizyme: Consultancy; Kura: Consultancy; AbbVie: Consultancy; Beigene: Consultancy, Speakers Bureau; Kymera: Consultancy. Cerhan: Genentech: Research Funding; NanoString: Research Funding; Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; Regeneron Genetics Center: Other: Research Collaboration. Grinblatt: Astellas Pharma, Inc.: Consultancy; Bristol Myers Squibb: Consultancy; Astra Zeneca: Consultancy; AbbVie: Consultancy. Toomey: Bristol Myers Squibb: Consultancy. Zelenetz: Gilead: Honoraria, Research Funding; Verastem: Honoraria; Novartis: Honoraria; MEI Pharma: Honoraria, Research Funding; SecuraBio: Honoraria; Abbvie: Honoraria, Research Funding; MorphoSys: Honoraria; Pharmacyclics: Honoraria; AstraZeneca: Honoraria; LFR: Other; Genentech/Roche: Honoraria, Research Funding; NCCN: Other; MethylGene: Research Funding; Beigene: Honoraria, Other, Research Funding; BMS/Celgene/JUNO: Honoraria, Other; Amgen: Honoraria; Gilead: Honoraria; Janssen: Honoraria. Sullivan: Bristol Myers Squibb: Current Employment, Current holder of individual stocks in a privately-held company. Flick: Bristol Myers Squibb: Current Employment. Kiselev: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company, Current holder of individual stocks in a privately-held company. Kaplan: Bristol Myers Squibb: Current Employment. Ahn: Bristol Myers Squibb: Current Employment.

AbstractHealth‐related quality of life (HRQoL) in patients with chronic lymphocytic leukemia (CLL) is important in guiding treatment decisions. However, the impact of CLL treatment initiation on HRQoL is unclear. We assessed HRQoL using the FACT‐Leu and EQ‐5D‐3L questionnaires in the Connect® CLL Registry, a large, US‐based, multicenter, prospective observational study of CLL patients enrolled between 2010 and 2014, prior to the introduction of novel therapies. Among 889 patients initiating first‐line therapy with chemoimmunotherapy or rituximab monotherapy, questionnaire completion rates were 95.7% and 95.8% at enrollment, and 70.8% and 69.4% at 12 months, for FACT‐Leu Total and EQ‐5D‐3L, respectively. For 849 patients completing all five FACT‐Leu components, average total scores were 135.7 at enrollment and 141.6 at 12 months. Among 526 patients with FACT‐Leu Total scores at enrollment and 12 months, clinically meaningful (≥11‐point) improvements or reductions were observed in 179 (34.0%) and 88 (16.7%) patients, respectively. Mean EQ‐5D‐3L index scores were 0.87 at enrollment and 12 months. Among 513 patients completing EQ‐5D‐3L at enrollment and 12 months, clinically meaningful (≥0.06‐point) improvements or reductions were observed in 125 (24.4%) and 116 (22.6%) patients, respectively. In the Connect® CLL Registry, HRQoL remained stable or slightly improved after 12 months of follow‐up.

Abstract Optimal treatment of chronic lymphocytic leukemia (CLL) remains unclear. The Connect CLL Registry, a United States–based multicenter prospective observational cohort study, enrolled 1494 patients between 2010 and 2014 from predominantly community-based settings. Patients were grouped by line of therapy (LOT) at enrollment. With a median follow-up of 46.6 months (range, 0-63.0 months), median overall survival (OS) was not reached in LOT1, 63.0 months (95% confidence interval [CI], 46.0-63.0 months) in LOT2, and 38.0 months (95% CI, 33.0-47.0 months) in LOT≥3. Bendamustine and rituximab (BR; 33.5%); fludarabine, cyclophosphamide, and rituximab (FCR; 21.4%); and rituximab monotherapy (18.5%) were the most common regimens across LOTs. Median event-free survival (EFS) was similar in patients treated with BR (59.0 months) and FCR (55.0 months) in LOT1; median OS was not reached. In multivariable analysis, BR or FCR vs other treatments in LOT1 was associated with improved EFS (hazard ratio [HR], 0.60; P < .0001) and OS (0.67; P = .0162). Using the Kaplan-Meier product limit, ibrutinib vs other treatments improved OS in LOT2 (HR, 0.279; P = .009), LOT3 (0.441; P = .011), and LOT≥4 (0.578; P = .043). Prognostic modeling of death at 2 years postenrollment identified 3 risk groups: low (mortality rate, 6.2%), medium (14.5%), and high (27.4%). The most frequent adverse events across LOTs were pneumonia (11.6%) and febrile neutropenia (6.2%). These data suggest that advantages of LOT1 FCR over BR seen in clinical trials may not translate to community practice, whereas receiving novel LOT2 agents improved outcomes. This trial was registered at www.clinicaltrials.gov as NCT01081015.

7086 Background: The HRQOL of patients (pts) with chronic lymphocytic leukemia (CLL) has not been adequately delineated across patient, disease and treatment characteristics. We evaluated HRQOL of CLL pts undergoing treatment in the United States (US) by age, gender and line of therapy. Methods: Data were collected in Connect CLL, a prospective observational US registry. Physicians provided data on demographics, clinical characteristics and line of therapy at enrollment. HRQOL was self-reported by pts at enrollment using the Functional Assessment of Cancer Therapy-Leukemia, an instrument that yields a leukemia-specific total HRQOL score (FACT-Leu) and a cancer-specific total HRQOL score (FACT-G). Mean total scores were analyzed by line of therapy, age and gender. Statistical significance was ascertained by ANOVA using SAS 9.2. Multivariate analyses were conducted to assess the relative association of line of therapy, age and gender with HRQOL. Results: Among 1,252 pts enrolled from 161 geographically diverse centers (90% community, 8% academic, 2% veterans/military), pts were predominantly male (63%), white (89%) with mean age 69 yrs. Pts were categorized by line of therapy at enrollment: First 61%, Second 18%, Third 11%, Higher 9%; and by age group: <65 33%, 65-74 35%, 75+ 32%. Univariate analyses suggested that the total FACT-Leu score was significantly better in men than women (P=0.004); in pts aged 65-74 vs younger or older pts (P=0.033); and in pts initiating first-line treatment vs pts receiving subsequent treatments (P=0.0002). Similar results were found with the FACT-G score except that gender differences were not statistically significant. Multivariate analysis confirmed that line of therapy (P=0.007), gender (P<0.0001), and age group (P=0.039) were each associated with significant differences in the FACT-Leu total score. Conclusions: Results from the Connect CLL Registry indicate that HRQOL is better among pts initiating first-line therapy compared to pts initiating subsequent treatments, and that this remains true when age and gender are considered. Future analyses should determine how HRQOL may change over time relative to treatment and treatment response.

6122 Background: Clinicians and investigators commonly use ECOG PS and clinician-reported patient (pt) fatigue as surrogates for HRQOL, a multi-faceted construct that comprehensively looks at the pt perspective on disease and well-being. Because limited data exist on the relationships between PS, fatigue, and HRQOL for CLL pts, we examined the associations between these measures, and 3 validated HRQOL instruments: the Functional Assessment of Cancer Therapy-Leukemia (FACT-Leu), EQ-5D, and Brief Fatigue Inventory (BFI). Methods: Data were collected in CONNECT CLL, a prospective US observational registry initiated in 2010. Patient demographics and clinical characteristics were provided by clinicians. Patient HRQOL was self-reported at enrollment using the FACT-Leu, EQ-5D, and BFI. Scores were analyzed by ECOG PS (0, 1, 2-4) and clinician-reported fatigue (yes, no). Differences in HRQOL scores were assessed by ANOVA. Results: HRQOL data were reported by 899 pts from 148 community, 10 academic, and 3 government centers. ECOG PS was available on 711 pts. Overall HRQOL, measured by mean FACT-Leu, FACT-G and EQ-5D Visual Analogue Scale (VAS), worsened with ECOG PS severity and was worse in pts with fatigue (all p<0.0001). All FACT-Leu domains except social/family were worse in pts with fatigue and those with higher ECOG PS. Mean EQ-5D pain/discomfort, mobility, self care and usual activities domain scores worsened in severity as ECOG worsened and for pts with fatigue (all p<0.011). BFI data indicated that global fatigue, fatigue severity and fatigue-related interference worsened by ECOG severity and were associated with clinician-reported fatigue (all p<0.0001). Conclusions: Initial CONNECT CLL results confirm that HRQOL worsens with worsening ECOG PS and was worse among pts with fatigue, especially in physical/functioning domains, pain/discomfort, and mobility. These results indicate that baseline ECOG PS and physician-rated fatigue are rapid assessments that predict robust measures of HRQOL. Future analyses are planned to examine how HRQOL, ECOG PS and fatigue change over time with changes in treatment and CLL disease status.

Abstract Introduction: CLL pts who qualify for participation in clinical trials are often thought of as a highly selected population. Therefore whether safety and efficacy data from these trials can be generalized to all CLL pts treated in the community setting is unknown. Prospective, observational studies can provide significant insight into pt and disease characteristics as well as practice patterns in different clinical settings. Here we report on baseline demographics and clinical characteristics for 1495 pts who participated in the Connect CLL observational study and were followed prospectively. Methods: Connect®CLL is a non study-specific intervention treatment registry which collects data on the management and outcomes of CLL pts in clinical, academic and community practices in the US. Clinical information was prospectively collected for pts treated in community (n=1312), academic (n=155), or government (n=28) centers in the US between March 2010 – Jan 2014. Pts eligible for treatment or on treatment not more than 2 months were eligible for enrollment. Here we report on the baseline demographics and clinical characteristics of a large CLL cohort stratified by AG, LOT and type of treatment center. Results: In total,1,495 pts were accrued with a median age at enrollment of 69 (range 22–99). Pts were Caucasian (92.2%), African American (6.9%), and male (63.7%). Median duration from diagnosis until initial therapy was 3.7 years (range 0-32). Age of enrolled pts was as follows; 527 pts age <65 years (AG1; 35%); 511 age 65–75 (AG2; 34%); and 457 age ≥75 (AG3; 31%) at the time of enrollment. Eight hundred and ninety-four pts (60%) were treated with front-line therapy (LOT1); 259 pts (17%) treated with second-line therapy (LOT2); and 342 pts (23%) treated beyond second-line therapy (LOT≥3). Patient age: Pt age was associated with significant variation in several clinical variables: Charlson comorbidity index (CCI) score ≥3 (AG 1-3 35/46/52%; p<0.0001), ECOG PS = 0 (AG1-3 60, 48, 33%, p<0.0001) and mean creatinine clearance (CrCl) decreased (AG 1-3 101/74/53 mL/min; p<0.0001). Line of therapy: Differences in baseline characteristics were observed between pts enrolled at LOT1 (previously untreated) and LOT2/≥3 (relapsed). Median age of pts accrued at LOT1 was 68 vs. 70 years for pts enrolled at LOT2/≥3 (p=0.007). ECOG PS = 0 was more frequent at LOT1 (50%) vs. LOT2/≥3 (42%) (p=0.0057). CCI ≥3 at LOT1 was 41% vs 48% at LOT2/≥3 (p=0.0072). When adjusted for differences in age, logistic regression also demonstrated significant differences in performance status (PS=0; p=0.02) and CCI (p=0.03) stratified by LOT. Treating institution: Baseline characteristics also differed by type of treating institution. Median age was 63 vs 70 at academic vs non-academic (p<0.0001). Pts treated at academic sites also had lower CCI (CCI≤2; 72.9% vs 54.2%, academic vs non-academic) and higher median CrCl (86.4 vs 71.4) (p=0.0017). In this registry, only 16% of patients under age 75 had CCI <= 2, CrCl >= 70 mL/min, ECOG 0-1; 18% of patients on LOT1 and 12% of pts on LOT=2 would satisfy these criteria. They represent 36% of eligible pts from academic treating institutions and 13% from community/government centers. Only 20% of patients on LOT1 would satisfy enrollment criteria for CLL8 (FCR vs. FC; Hallek; Lancet 2010) CLL 10 (BR vs FCR; NCT00769522). which did not have enrollment restrictions for age. Conclusions:Baseline characteristics of pts with CLL vary by age, LOT, and type of treatment center. In this large prospective observational study, our data confirms that older pts typically have a worse ECOG PS, more medical comorbidities, more advanced disease when initiating therapy and a lower probability of being treated at an academic medical center. Based on inclusion criteria used for entry in either CLL10 or CLL8, fewer than 20% of pts satisfy age, renal clearance, and fitness profile to be considered suitable for aggressive chemoimmunotherapy in the front line setting. This observation supports the notion that current clinical trial data might not always be applicable to the general CLL population seen in the community and argues for designing clinical trials that are more generalizable to the broader pt population. Disclosures Sharman: Gilead: Research Funding; Calistoga: Honoraria; Phamacyclics: Honoraria, Research Funding; Celgene: Consultancy, Research Funding; TG therapeutics: Research Funding; Roche: Research Funding. Mato:Millennium: Speakers Bureau; Celgene: Speakers Bureau; Genentech: Speakers Bureau. Kay:Celgene: Research Funding. Kipps:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Lamanna:Genentech-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; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Infinity: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Weiss:Celgene: Consultancy; Phamacyclics: Consultancy; Gilead: Consultancy. Nabhan:Celgene: Honoraria, Research Funding. Flinn:Celgene: Research Funding. Grinblatt:Celgene: Honoraria, Speakers Bureau. Kozloff:Celgene: Consultancy. Farber:Alexion: Equity Ownership, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Gilead: Speakers Bureau; Janssen/Pharmacyclics: Speakers Bureau; Seattle Genetics: Speakers Bureau; Genentech: Membership on an entity's Board of Directors or advisory committees. Sullivan:Celgene: Employment, Equity Ownership. Street:Celgene: Employment, Equity Ownership. Swern:Celgene: Employment, Equity Ownership. Flowers:TG Therapeutics: Research Funding; Phamacyclics: Research Funding; Acerta: Research Funding; Abbvie: Research Funding; Infinity: Research Funding; Lymphoma Research Foundation: Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; Spectrum: Research Funding; Gilead: Research Funding; Genentech: Unpaid consultancy Other; Millennium: Research Funding, Unpaid consultancy, Unpaid consultancy Other; Seattle Genetics: Consultancy; Prescription Solutions: Consultancy; Celgene: Unpaid consultancy Other.

Abstract Introduction: Rituximab (R) improves survival in CLL when added to intensive chemotherapy (such as fludarabine and cyclophosphamide [FCR]), and has been shown to improve progression-free survival when given as maintenance therapy following first- or second-line chemoimmunotherapy. However, early phase 2 studies demonstrated only modest activity of R monotherapy (R mono), particularly at standard dose, and its use as a single agent for pts with CLL has remained controversial. Here we describe the characteristics and outcomes of pts with CLL receiving R mono in a real-world setting. Methods: The Connect CLL registry (NCT01081015), a multicenter, prospective observational cohort study, enrolled 1,494 pts with CLL between 2010-2014 from 179 community, 17 academic, and 3 government sites throughout the USA. Pts were ≥ 18 years and were enrolled ≤ 2 months after initiating any line of therapy (LOT). Pts were treated according to individual physician/patient decision making, and adherence to IWCLL standards cannot be determined. Bone marrow biopsy and CT scans were at the physician's discretion; responses were physician assessed and not centrally reviewed. For this analysis, pts were stratified by first (LOT1) or subsequent LOT (LOT≥2), and by treatment with R mono or other treatments (Tx). Kaplan-Meier methods were used to estimate event-free survival (EFS; event defined as death, progression/relapse, or transformation). A log-rank test was used to evaluate differences in EFS. A multivariate analysis of EFS in LOT1 pts was performed using the Cox regression model. Results: Of the pts enrolled, 105 (11.8%) pts in LOT1 and 81 (13.4%) pts in LOT≥2 received R mono. Of the pts receiving other Tx, 620/784 pts (79%) in LOT1 and 333/524 pts (64%) in LOT≥2 received R in combination. In LOT1, pts receiving R mono were older than pts receiving other Tx (74 vs 67 years; P < 0.0001); in LOT≥2 median ages were comparable (71 vs 70 years). Pts receiving R mono were more likely to have Rai stage 0-1 CLL than pts receiving other Tx, both in LOT1 (63.9% vs 51.8%; P = 0.05) and LOT≥2 (70.4% vs 49.9%; P = 0.005). The proportion of pts receiving R mono vs other Tx with a CCI score of ≥ 4 was similar in LOT1 (25.7% vs 22.8%) and LOT≥2 (32.1% vs 28.4%). Median absolute lymphocyte count at enrollment was lower in pts on R mono vs other Tx in LOT1 (27.7 vs 46.1 x 109/L) but similar in LOT≥2 (35.6 vs 30.2 x 109/L). A lower proportion of pts receiving R mono had FISH/cytogenetics performed at enrollment than pts receiving other Tx in LOT1 (48.6% vs 67.0%; P = 0.0002) and LOT≥2 (30.9% vs 49.6%; P = 0.002). The most common Tx regimens in LOT1 were FCR (25.9%), bendamustine plus R ([BR] 21.0%), R mono (11.8%), fludarabine plus R ([FR] 6.3%), and chlorambucil (4.6%); and in LOT≥2, BR (27.6%), R mono (13.4%), FCR (8.6%), bendamustine (7.4%), FR (4.1%), and ofatumumab (4.0%). The most common reason to initiate treatment in any LOT was bone marrow failure (LOT1, 44.8% vs 39.3%; LOT≥2, 37.0% vs 31.5%; R mono vs other Tx). Duration of therapy was shorter for pts receiving R mono vs other Tx in LOT1 (1.4 vs 4.1 months) and LOT≥2 (1.6 vs 3.3 months). In LOT1, responses were lower in pts on R mono vs other Tx: overall response rate (ORR) was 38.1% vs 64.2% (complete response [CR], 16.2% vs 41.2%; P < 0.0001). In LOT≥2, ORR was 25.9% vs 24.6% for pts on R mono vs other Tx (CR, 9.9% vs 11.5%; P = 0.68). Partial response did not differ significantly between pts receiving R mono vs other Tx in LOT1 and LOT≥2. Pts receiving R mono in LOT1 had inferior median EFS vs other Tx (34 vs 50 months; log-rank P = 0.04); however, after adjusting for factors such as ECOG status and del(17p) status, there was no difference in EFS (HR 0.932; P = 0.79). In pts in LOT≥2, median EFS was similar for R mono and other Tx (15 months for both groups; P = 0.93). Conclusions: Pts receiving R mono as frontline CLL therapy were older than pts receiving other Tx. They also had lower stage disease and lower lymphocyte counts, a shorter duration of treatment, and inferior response rates. Pts receiving R mono in relapsed CLL, more closely approximated pts receiving other Tx in terms of age. Despite the shorter duration of therapy for pts receiving R mono in LOT1 and LOT≥2, both groups had similar ORR and EFS in LOT≥2. These data reinforce the idea that R mono is inadequate as frontline therapy in progressive CLL, and demonstrate the opportunity for improvement in relapsed/refractory disease with novel agents relative to traditional chemoimmunotherapy approaches. Disclosures Sharman: Celgene: Research Funding; Gilead: Research Funding; Pharmacyclics: Research Funding; Acerta: Research Funding; TG Therapeutics: Research Funding; Seattle Genetics: Research Funding. Davids:Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Membership on an entity's Board of Directors or advisory committees, Research Funding; Infinity: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie, Janssen, Gilead: Consultancy; Celgene Corporation: Consultancy. Farber:Seattle Genetics: Research Funding. Grinblatt:Celgene Corporation: Consultancy, Speakers Bureau. Lamanna:Gilead: Research Funding; AbbVie: Research Funding; Genentech: Research Funding; Infinity: Research Funding; Pronai: Research Funding; Celgene Corporation: Research Funding. Mato:TG Therapeutics: Consultancy; Abbvie: Research Funding; Acerta Pharma: Research Funding; Gilead Sciences: Research Funding; ProNAi: Research Funding; TG Therapeutics: Research Funding; Theradex: Research Funding; Pharmacyclics: Consultancy; Gilead Sciences: Consultancy; Abbvie: Consultancy. Nabhan:Astellas: Research Funding; Seattle Genetics: Research Funding; Cardinal Health: Consultancy; Infinity: Consultancy; Abbvie: Consultancy; Genentech: Consultancy, Research Funding; Celgene Corporation: Consultancy, Research Funding. Sullivan:Celgene Corporation: Employment, Equity Ownership. Flick:Celgene Corporation: Employment, Equity Ownership. Kiselev:Celgene Corporation: Employment, Equity Ownership. Bhushan:Celgene Corporation: Employment, Equity Ownership. Swern:Celgene: Employment, Equity Ownership. Flowers:Seattle Genetics: Research Funding; Optum Rx, Seattle Genetics, Genentech/Roche: Consultancy; Celgene Corporation: Consultancy, Honoraria; Spectrum, Janssen, Infinity, AbbVie, Acerta, Pharmacyclics, TG Therapeutics: Research Funding; Millennium: Consultancy, Research Funding; Gilead: Consultancy, Research Funding.

Abstract Abstract 2864 Introduction: Clinical trials have illuminated a number of unique treatment strategies for patients with CLL. The impact of these strategies on routine practice remains unknown as trial participants may not reflect the same population encountered outside of a clinical trial setting. Many questions remain regarding the sequencing of therapies based on age and performance status. By characterizing current patterns of care; patients, treating physicians, and regulatory agencies will be able to understand the current landscape of CLL treatment. The Connect® CLL registry was designed to report the natural history and real world management of patients receiving therapy for CLL. In this first report, we characterize the therapeutic approaches used for the treatment of patients with CLL of different age groups (i.e. < 65 years, 65–75 years, and ≥ 75 years) and with an ECOG PS status score of 0 compared to 1 or greater. Methods: Connect® CLL is a prospective, longitudinal, observational, multi-center registry conducted in community and academic research centers in the United States. At present, 237 sites are actively participating with a projected study enrollment of 1500 patients. Eligible patients are to be enrolled within 2 months of being initiated on any line of therapy; whether initial therapy or salvage therapy. Each patient will be followed for up to 60 months. Clinical data, physician choices, patient-reported health-related quality of life, response and survival are to be collected approximately every 3 months during participation. Results: A total of 607 patients have been enrolled (4% from academic sites) with a median age of 70 years. 198 were < 65 years old (age group 1), 187 were between 65–75 years old (age group 2), and 222 were ≥ 75 years old (age group 3). ECOG status varied across the three age groups, with an ECOG status score of ≥ 1 for 39%, 52%, and 70% of patients respectively. Treatment patterns varied across the age groups and by ECOG status in the 496 patients reporting therapies. The most commonly recorded first-line regimens independent of age included fludarabine (F) cyclophosphamide (C) and rituximab (R) (33%), bendamustine (B) +/− R (19%), F +/− R (15%), or investigational therapy (15%). For second-line regimens and beyond, the most frequently recorded regimen was B +/− R (30%), FCR (23%), other F-based regimens (13%), or investigational therapy (8%). The use of FCR for first-line treatment decreased significantly with increasing age group, (45%, 32%, 20%, for age group 1, 2, 3 respectively, p=0.04, spearman correlation) while use of F +/− R remained level across the age groups (14%, 15%, 15%, respectively). Compared to age group 1, first-line therapy with B +/− R in age groups 2 and 3 (15%, 22%, 21%, respectively) was higher but did not achieve statistical significance. B +/− R represented the most common treatment for all age groups (37%, 26%, 29%, respectively) as second line therapy but did not vary by age (P=0.35). The use of chlorambucil was infrequent in all age groups, but was more common in age group 3 patients compared to the others (P=0.01), in both first-line (2%, 4%, 12%, respectively) and subsequent lines of therapy (0%, 1%, 8%, respectively). Treatment assignments did not vary by ECOG PS score for patients in age group 1. First-line therapy for patients with an ECOG PS score of 0 in age groups 2 and 3 consisted of FCR (32% and 15%, respectively), F +/− R (19% and 15%, respectively), B +/− R (16% and 15%, respectively), and alkylating agents (3% and 23%, respectively). Patients in age groups 2 and 3 with ECOG PS score ≥ 1 received B +/− R regimen (33% and 22%, respectively), FCR (23% and 21%, respectively), F +/− R (14% and 10%, respectively) and alkylating agents (7% and 9%, respectively) as first-line therapy. Further description and clarification on the various treatment regimens based on the three age groups and by ECOG PS score will be presented at the meeting. Conclusion: The Connect® CLL Registry is the largest prospective, multicenter registry in the United States evaluating management for patients with CLL. With the currently available data, we characterize the extent to which age and performance status are associated with treatment selection in both first-line and subsequent lines of therapy in routine practice. As enrollment increases and additional follow-up is completed, the data will provide more extensive and real world overview of the current treatment strategies used in CLL patients. Disclosures: Sharman: Celgene - consulting: Consultancy; Pharmacyclics: Honoraria; Calistoga: Honoraria; Portola pharmaceuticals: Consultancy. Flowers:Consultancy: Celgene, Prescription Solutions, Spectrum (future), Seattle Genetics, Millennium (future), Genentech (unpaid): Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Weiss:Celgene: Consultancy. Grinblatt:Celgene: Honoraria, Speakers Bureau. Kay:Genenetech, Celgene, Hospira,: Research Funding. Kipps:Igenica: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Research Funding; Abbot Industries: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Genentech: Research Funding; GSK: Research Funding; Gilead Sciences: Research Funding; Amgen: Research Funding. Lamanna:Celgene Corporation: Advisory board. Pashos:United BioSource Corporation: Research Funding. Flinn:Celgene: Research Funding. Kozloff:Celgene: Consultancy. Lerner:Celgene Connect: Membership on an entity's Board of Directors or advisory committees. Swern:Celgene: Employment. Sullivan:Celgene: Employment. Street:Celgene: Employment. Keating:Celgene Connect: Membership on an entity's Board of Directors or advisory committees.

Abstract Abstract 2085 Introduction. Although advanced patient age is commonly used as a factor in selecting therapy for patients with chronic lymphocytic leukemia (CLL), based on presumed associations with functional status, limited data exist regarding the relationships between age and physical, emotional, social, and functional well being. We examined the relationships between age and these domains of health-related quality of life (HRQOL) for CLL patients treated in US community practices. Methods. Baseline data were collected as part of Connect CLL®, a prospective observational registry initiated in March 2010 involving centers in the US. Data on patient demographics and clinical characteristics were provided by clinicians. HRQOL was self-reported by patients in the clinic at enrollment. Patients completed 3 psychometrically validated instruments: the Brief Fatigue Inventory (BFI), EQ-5D, and Functional Assessment of Cancer Therapy-Leukemia (FACT-Leu). Standard analyses were conducted of each instrument given clinical characteristics at that time. Reported mean BFI, EQ-5D and FACT-Leu scores were analyzed by age group (<65, 65–74, >74). Statistical significance of score differences among sub-cohorts was ascertained by ANOVA using SAS 9.1. Results. Baseline HRQOL data were reported by 604 patients, enrolled from 161 centers. Patients were predominantly male (62%) and white (90%) with mean age at 69.9 (standard deviation [SD] 11.2) yrs. HRQOL scores by age group are presented: There were no significant differences between the age groups in fatigue as measured by the BFI, or differences in overall HRQOL as measured by the EQ-5D Visual Analogue Scale (VAS) or the FACT-G. Anxiety/depression and self care are EQ-5D domains that also did not vary by age. Although mobility was most impaired in the oldest age group compared to the two younger groups, usual activities and pain/discomfort were worse in both the younger and older cohorts compared to those 65–74 years of age. FACT-Leu results indicated that the social/family domain scores did not vary by age, but that physical, emotional, and functional domains did vary statistically with the oldest typically doing better than the 65–74 year olds, but not necessarily better than those <65. Conclusions. Initial results from the Connect CLL® Registry indicate that HRQOL does not worsen monotonically with older age. In this cohort, both the youngest and oldest age groups had worse HRQOL in certain domains, presenting an inverted v-shaped relationship. Future analyses should be conducted on: (1) how HRQOL may be affected over time with changes in disease; and, (2) how HRQOL may be influenced by alternative therapies. Results reported here should serve as a useful baseline reference. Disclosures: Pashos: Celgene: Membership on an entity's Board of Directors or advisory committees. Flowers:Genentech/Roche (unpaid): Consultancy; Celgene: Consultancy; Millennium/Takeda: Research Funding; Wyeth: Research Funding; Novartis: Research Funding. Weiss:Celgene: Membership on an entity's Board of Directors or advisory committees. Lamanna:Celgene: Membership on an entity's Board of Directors or advisory committees. Farber:Celgene: Membership on an entity's Board of Directors or advisory committees. Kipps:Igenica: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Research Funding; Abbot Industries: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Genentech: Research Funding; GSK: Research Funding; Gilead Sciences: Consultancy, Research Funding; Amgen: Research Funding. Lerner:Celgene: Membership on an entity's Board of Directors or advisory committees. Kay:Celgene: Membership on an entity's Board of Directors or advisory committees. Sharman:Celgene: Membership on an entity's Board of Directors or advisory committees. Grinblatt:Celgene: Membership on an entity's Board of Directors or advisory committees. Flinn:Celgene: Membership on an entity's Board of Directors or advisory committees. Kozloff:Celgene: Membership on an entity's Board of Directors or advisory committees. Swern:Celgene Corporation: Employment, Equity Ownership. Kahn:Celgene Corporation: Employment, Equity Ownership. Street:Celgene: Employment, Equity Ownership. Sullivan:Celgene: Employment, Equity Ownership. Keating:Celgene: Membership on an entity's Board of Directors or advisory committees.