Street, Thomas K.

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.

8037 Background: Advances in the treatment of MM have greatly improved clinical outcomes for patients (pts). SPM occurrence has been observed in early and late stage MM as well as with increasing age. US SEER Cancer Registry reports a background incidence rate of SPM 2.1/100 person-yrs (PY) among persons ≥ 65 yrs of age. However, incidence of SPM in MM pts and the relationship to therapy still warrants further exploration. Methods: Connect MM is a US-based observational registry designed to characterize pts with newly diagnosed MM from 266 US sites. Initiated in Sep 2009, patient data were collected at baseline and each subsequent quarter with a standardized form. On Dec 14, 2011, Connect MM reached full enrollment at 1,500 pts. Results: As of Jan 13, 2012, preliminary retrospective SPM data is available for 1015 pts. Median age was 67 yrs, 56.8% male, and median follow-up was 10.6 mo (0.03-24.9 mo). 12 pts (7 male) with median age of 68.5 yrs developed SPM. Median time to SPM was 8.5 mo (0.8-17.7 mo) after treatment initiation. 11 invasive SPM were observed - 4 hematological (heme): 1 AML, 1 MDS, 1 CMML and 1 DLBCL, and 7 solid: 2 melanoma skin, 1 bronchus, 1 breast, 1 prostate, 1 tonsil, and 1 gastric carcinoid. Also, 1 pt had non-melanoma skin cancer (NMSC), and 1 pt with invasive skin cancer also had NMSC. Of the 4 pts developing heme SPM, 3 had bortezomib (BORT), 1 had thalidomide (THAL), 1 had lenalidomide (LEN), 2 had melphalan (MEL), and all 4 pts had steroids. Of the 7 pts who developed solid tumor SPM, 5 had BORT, 5 had LEN, 2 had doxorubicin, 1 had MEL, 5 had steroids, 1 had irradiation, and 1 had not received MM treatment. 2 pts with prior history of invasive malignancy developed solid tumor SPM (1 pt also developed NMSC).1 pt who received irradiation developed NMSC. Early overall incidence of invasive SPM was 1.21/100 PY (95% CI 0.60, 2.16) for all pts and 1.20/100 PY (95% CI 0.44,2.62) for pts ≥ 65 yrs of age. Conclusions: This preliminary analysis shows that SPM occurred at an expected rate in this disease specific registry of patients with NDMM and appeared to occur irrespective of MM treatment administered. Incidence rates of SPM may increase over time as patients receive transplantation and alkylators. Prospective observation will continue.

e18556 Background: Studies in the United States (US) have identified variation in incidence and survival of multiple myeloma (MM) patients of different races, and noted that MM is the most common hematologic cancer among African Americans. This analysis evaluated whether health-related quality of life (HRQOL) of patients in the US varies by race as they initiate treatment having been newly diagnosed with active, symptomatic MM. Methods: Data were collected in Connect MM, a prospective US observational registry begun in September 2009. Data on patient demographics and clinical characteristics were provided by clinicians. HRQOL was reported by patients at enrollment within 2 months of diagnosis. Patients completed the Brief Pain Inventory (BPI), EQ-5D, and Functional Assessment of Cancer Therapy-Multiple Myeloma (FACT-MM). Mean reported scores for BPI, EQ-5D and FACT-MM were analyzed by patient race. Statistical significance was ascertained by ANOVA using SAS 9.1. Results: Baseline HRQOL data were reported by 1144 patients (enrolled in 228 centers) of whom 82% were White, 13% Black, and 6% Other race. The cohorts did not differ statistically by ECOG status or by multiple myeloma stage (assessed by either the International Staging System or the Durie and Salmon system). Compared to non-Blacks, Black patients reported less anxiety/depression on the EQ-5D (p=0.030) and better emotional well-being on the FACT-MM (p=0.003). No other statistically significant differences were noted between cohorts on the BPI, other EQ-5D domains (mobility, self care, usual activities, pain/discomfort), or other FACT-MM domains (physical, social/family, functional, and MM-specific considerations). Conclusions: Initial results from the Connect MM Registry indicate that baseline HRQOL prior to initiation of treatment may vary by patient race with respect to emotional well-being, and specifically anxiety/depression. These results serve as a baseline reference for future analyses. As patients in the Connect MM Registry proceed through therapy, analyses should be conducted of patients by race, among other characteristics and factors, to determine whether it may be associated with subsequent clinical outcomes and HRQOL over time.

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 Abstract 3150 Introduction. Affordability of health care in the United States (US), and the impact of patient insurance coverage on it have been shown to be associated with the delivery and timeliness of access to care. With increasing costs of novel therapies in hematology and oncology, this concern has been raised in hematologic cancers. This analysis evaluates whether the health-related quality of life (HRQOL) of patients with active, symptomatic multiple myeloma (MM) patients in the US varies by their insurance coverage as they initiate treatment. Methods. Baseline data were collected in Connect MM®, a prospective observational registry initiated in September 2009 involving centers in the US. Data on patient demographics and clinical characteristics were provided by clinicians. HRQOL was reported by patients in the clinic at enrollment, within two months of diagnosis. Patients completed 3 psychometrically validated instruments: the Brief Pain Inventory (BPI), EQ-5D, and Functional Assessment of Cancer Therapy-Multiple Myeloma (FACT-MM). Standard analyses were conducted of each instrument given clinical characteristics at that time. Patients were characterized as to the main source of their insurance coverage: Medicare, Medicaid or Commercial. The Medicare cohort included those with supplemental commercial coverage, and the Medicaid cohort included those with dual Medicare-Medicaid coverage. Reported mean BPI, EQ-5D and FACT-MM scores were analyzed by patient insurance coverage. Statistical significance of score differences among sub-cohorts was ascertained by ANOVA using SAS 9.1. Results. HRQOL data and insurance status were reported by 863 patients, enrolled from 189 centers. Patients were predominantly male (57%) and white (82%) with mean age at 67.0 (standard deviation [SD] 11.3) yrs. HRQOL scores by insurance status are presented: Overall FACT-MM results indicate that Medicaid insurance status is associated with greater decrement in baseline HRQOL compared to the other groups. Statistically significant differences are noted in the FACT-G general cancer HRQOL score, and its physical, social/family and emotional component scores. BPI data (on a scale of 0 [no pain] to 10 [worst pain] indicate that average pain may be worse among Medicaid patients compared to either Medicare or commercially insured patients. There are no statistically significant differences on EQ-5D scores (on a scale of 1 [no problem] to 2 [some problems] to 3 [incapacity] between cohorts based on insurance status. Conclusions. Initial results from the Connect MM® Registry indicate that HRQOL at baseline prior to initiation of treatment is worse among Medicaid patients compared to those with either Medicare or commercial coverage. This should be investigated to determine whether Medicaid patients are accessing care later in disease progression than others covered by Medicare or commercial insurance. Furthermore, future analyses should be conducted of patients by insurance coverage to determine whether status may be associated with access to medical care, subsequent clinical outcomes, and HRQOL over time. Results reported here should serve as a baseline reference. Disclosures: Pashos: Celgene: Membership on an entity's Board of Directors or advisory committees. Durie:Celgene: Membership on an entity's Board of Directors or advisory committees. Rifkin:Celgene: Membership on an entity's Board of Directors or advisory committees. Terebelo:Celgene: Membership on an entity's Board of Directors or advisory committees. Gasparetto:Celgene: Membership on an entity's Board of Directors or advisory committees. Mehta:Celgene: Membership on an entity's Board of Directors or advisory committees. Toomey:Celgene: Membership on an entity's Board of Directors or advisory committees. Abonour:Celgene: Membership on an entity's Board of Directors or advisory committees. Fonseca:Celgene: Membership on an entity's Board of Directors or advisory committees. Narang:Celgene: Membership on an entity's Board of Directors or advisory committees. Shah:Celgene: Membership on an entity's Board of Directors or advisory committees. Swern:Celgene Corporation: Employment, Equity Ownership. Sullivan:Celgene: Employment, Equity Ownership. Street:Celgene: Employment, Equity Ownership. Khan:Celgene: Employment, Equity Ownership.

Abstract Abstract 5070 Introduction. Studies in the United States (US) have identified variation in incidence and survival of multiple myeloma (MM) patients of different races, and noted that MM is the most common hematologic cancer among African Americans. This analysis was conducted to evaluate whether the health-related quality of life (HRQOL) of patients in the US as they initiate treatment with active, symptomatic MM varies by race. Methods. Data were collected in Connect MM®, a prospective observational registry begun in September 2009 involving centers in the US. Data on patient demographics and clinical characteristics were provided by clinicians. HRQOL was reported by patients in the clinic at enrollment, within two months of diagnosis. Patients completed 3 psychometrically validated instruments: the Brief Pain Inventory (BPI), EQ-5D, and Functional Assessment of Cancer Therapy-Multiple Myeloma (FACT-MM). Standard analyses were conducted of each instrument. Reported mean BPI, EQ-5D and FACT-MM scores were analyzed by patient race. Statistical significance of score differences was ascertained by ANOVA using SAS 9.1 in two ways: (1) among three different racial categories (White, Black and Other), and (2) between Blacks and non-Blacks. Hispanic/Latino patients and Asian patients comprise most of the Other cohort. Results. HRQOL data at baseline were reported by 916 pts, enrolled from 189 centers. Of these patients, 82% were White, 12% were Black, and 5% were of another race (Other). Among evaluable patients, the different race groups did not differ statistically by ECOG status or multiple myeloma stage (measured by either the International Staging System or the Durie and Salmon system). The three racial groups differed by age, with the mean (SD) age of Blacks (63 (11)) and Others (63 (13)) being less than that of Whites (68 (11), p<0.0001). Gender was trending, but not statistically significantly different, between races, with males comprising 58% of Whites, 52% of Blacks, and 46% of Others (p=0.1803). HRQOL scores by race are presented here: Overall FACT-MM results indicate that baseline HRQOL does not vary between races, as the main summary scores do not differ statistically, although the FACT-MM Total scores of Blacks and Whites are trending higher than those of Others. Only the emotional and social/family domain scores of the FACT-MM vary statistically, as Blacks show a worse mean score in the social/family domain and a better score in the emotional domain. BPI data (on a scale of 0 [no pain] to 10 [worst pain] do not show a statistically significant difference between races, and the same is true of the five EQ-5D domains (measured on a scale of 1 [no problem] to 2 [some problems] to 3 [incapacity]. Conclusions. Initial results from the Connect MM® Registry indicate that HRQOL at baseline prior to initiation of treatment does not vary by patient race. As such, these results may serve as a baseline reference for future analyses. In particular, as patients proceed through therapy, analyses should be conducted of patients by race, among other factors, to determine whether it may be associated with subsequent clinical outcomes and HRQOL over time. Disclosures: Pashos: Celgene: Membership on an entity's Board of Directors or advisory committees. Durie:Celgene: Membership on an entity's Board of Directors or advisory committees. Rifkin:Celgene: Membership on an entity's Board of Directors or advisory committees. Terebelo:Celgene: Membership on an entity's Board of Directors or advisory committees. Gasparetto:Celgene: Membership on an entity's Board of Directors or advisory committees. Mehta:Celgene: Membership on an entity's Board of Directors or advisory committees. Toomey:Celgene: Membership on an entity's Board of Directors or advisory committees. Abonour:Celgene: Membership on an entity's Board of Directors or advisory committees. Fonseca:Celgene: Membership on an entity's Board of Directors or advisory committees. Narang:Celgene: Membership on an entity's Board of Directors or advisory committees. Shah:Celgene: Membership on an entity's Board of Directors or advisory committees. Swern:Celgene Corporation: Employment, Equity Ownership. Sullivan:Celgene: Employment, Equity Ownership. Street:Celgene: Employment, Equity Ownership. Khan:Celgene: Employment, Equity Ownership.

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.

Abstract Abstract 4591 Introduction: Clinicians and investigators appreciate the value of measuring HRQOL for monitoring CLL and the impact of treatments, and commonly use ECOG performance status (PS) and clinician-reported patient fatigue as surrogates for HRQOL in clinical practice. However, limited data exist on the relationships between PS, fatigue, and HRQOL in CLL patients (pts) undergoing treatment in clinical practices. We examined the associations between these measures and 3 psychometrically validated, patient-reported, HRQOL instruments: the Brief Fatigue Inventory (BFI), EQ-5D, and Functional Assessment of Cancer Therapy-Leukemia (FACT-Leu). Methods: Data were collected as part of Connect CLL®, a prospective observational registry initiated in March 2010 involving US practices. Data on pt demographics and clinical characteristics were provided by clinicians. HRQOL was self-reported by pts at enrollment using the BFI, EQ-5D, and FACT-Leu. Mean BFI, EQ-5D and FACT-Leu scores were analyzed by ECOG PS and clinician-reported fatigue. Differences in HRQOL scores between sub-cohorts were assessed by ANOVA. Results: HRQOL data were reported by 604 pts enrolled from 10 academic, 148 community, and 3 government centers. Pts were predominantly male (62%) and white (90%); mean age was 70 (standard deviation 11) years. BFI data (scale: 0 [no fatigue] - 10 [worst fatigue]) indicated that on average pts report that global fatigue, fatigue severity and fatigue-related interference worsen by ECOG severity (Table 1) and are statistically associated with clinician-reported fatigue (Table 2). Mean EQ-5D overall HRQOL as measured by a Visual Analogue Scale (VAS) from 0 (worst) to 100 (best) worsens by ECOG severity and is significantly worse in pts with fatigue. Mean EQ-5D domain scores (scale: 1 [no problem], 2 [some problems], 3 [incapacity]) indicated that pain/discomfort, mobility and usual activities increase in severity as ECOG worsens and in pts with fatigue. FACT-Leu domains except social/family were statistically worse with worse ECOG PS and in pts with fatigue. Conclusions: Initial results from Connect CLL® indicate that HRQOL worsens with worsening ECOG PS, especially in physical / functioning domains, pain/discomfort, and mobility, and worsens across multiple domains among pts whose physicians reported fatigue. Future analyses should be conducted on how HRQOL, PS and fatigue may change over time with changes in CLL, and how they are influenced by therapies. These results may serve as 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.