Nabhan, Chadi

Abstract Abstract 680 Cytogenetics play an essential role in determining the prognosis of patients with AML. However, there is still no validated cytogenetics grouping scheme that specifically applies to patients undergoing allogeneic stem cell transplantation, which hampers accurate prognostication and risk stratification. We studied 821 adult patients (median age 41, range 18–74) who underwent SCT between 1999 and 2004 for AML (excluding APL) in CR1 or CR2 and who were reported to the CIBMTR from centers with >20 patients meeting study criteria. 75% of patients received a myeloablative conditioning. 496 patients had a normal karyotype. The primary cytogenetics reports were manually reviewed for 92% of the patients with an abnormal karyotype. We compared the ability of the 6 existing grouping schemes (MRC, CALGB, EORTC/GIMEMA, SWOG/ECOG, DFCI, and Monosomal Karyotype (MK) classifications) to stratify patients, using both the Akaike Information Criterion in multivariable models and the C-statistic. Among all existing schemes, the DFCI system provided a marginally superior stratification for overall and leukemia-free survival. We also built a new classification using individual cytogenetic abnormalities in a Cox model that included other significant covariates (performance status, therapy-related disease, conditioning intensity, graft source, donor match, duration of CR1, and gender match). This CIBMTR scheme (see Table), which is similar to the DFCI scheme except for the inclusion of patients with t(8;21) in the intermediate group, could stratify patients into 3 groups with similar treatment-related mortality but significantly different overall survival, leukemia-free survival, and incidence of relapse. This scheme appeared to apply to both patients in CR1 and in CR2 (see FiguresF2). This transplant-specific scheme could be adopted for prognostication purposes and to stratify patients with karyotypic abnormalities entering transplantation clinical trials. Future studies may clarify the relative outcome of patients with t(8;21) and refine this scheme with the inclusion of molecular abnormalities. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 2877 Background: Racial disparity has been well documented in a number of cancers but the impact of race on CLL in the contemporary era is unclear. While preliminary evidence suggests that Black (B) patients (pts) have worse survival than their White (W) counterparts (Shenoy et al, Clin Lymph Myleoma Leuk, 12/2011), the importance of sex, age, socioeconomic status (SES), and whether the wide use of single use or combined therapy with R in CLL over the last decade plus has affected overall survival (OS) have not been fully explored. Further, outcome of Hispanic (H) and Asian/Pacific Islanders (A/PI) CLL pts has not been fully studied. Methods: We examined population based survival data from SEER 13 (1993–2008) for CLL within and across various races. We also investigated the impact of sex, age, and socioeconomic status (SES) on their clinical outcome. Outcomes were examined over two consecutive 8-year (yr) periods: Era-1 (1993–2000) and Era-2 (2001–2008) with the assumption of R therapy in CLL patients being more frequent after 2001 (market research data not shown). Results: We identified 24,964 pts [W =21,363 (85.5%), H =1,197 (4.7%), B =1,709 (6.8%), and A/PI =695 (2.7%)]. Differences were notable for a greater male predominance among A/PI [62% vs. 57% (B), 56% (H), 58% (W); P=0.03]; a higher proportion of pts >80 among W [22% vs. 17% (H), 15% (B), 16% (A/PI); P<0.001], and higher SES among A/PI and W pts compared to B and H (P<0.001). OS for all patients was significantly better in Era-2 vs. Era-1 at 5-yrs (65% vs. 60.4%, P<0.0001). This improvement was statistically significant in all races except A/PI pts (P=0.71) (Table). Improved survival across eras was also noted in all age groups (<50 (P<0.00001), 50–59 (P=0.007), 60–69 (P<0.0001), 70–79 (P<0.0001), >80 yrs (P<0.0001)). Further, improved OS was noted in the two SES classes evaluated (0–15% and 15.1–30% below poverty line respectively). While there were no statistical differences between males and females within either era, improvement in OS was noted in both sexes in Era-2 versus Era-1 (P<0.0001). We subsequently compared OS within and across races (Table). Despite the fact that OS improved in all races, W pts continued to have better OS in Era-2. In Era-1, while W pts had better OS than B and H pts, the OS is similar between W and A/PI. Although OS improved in all SES classes, patients with higher SES continued to have better OS in Era-2 (P<0.0001 for both). Conclusions: The OS of CLL pts has improved in the contemporary era for both sexes, all age groups, and all races except A/PI individuals. The improvement in outcome in Era-2 might be partially explained by increased use of R and other novel agents that became available after 2001. Despite the broad nature of these improvements, racial and SES differences in the survival persist and deserve further validation and pursuit of the causes. Disclosures: Shanafelt: Genentech: Research Funding; GlaxoSmith Klein: Research Funding; Teva/Cephalon: Research Funding; Celgene: Research Funding. Kay:Genentech: Research Funding; Glaxosmith Klein: Research Funding.

Abstract Background: Contemporary approaches to non-Hodgkin lymphoma (NHL) and chronic lymphocytic leukemia (CLL) incorporate chemo-immunotherapy, biologic combinations, and immune modulating agents; toxicities in elderly pts (³65 years) receiving these therapies are not well studied. Further, clinical and biologic factors predicting these toxicities in pts receiving biologic therapy remain undefined. Methods: We reviewed data on NHL and/or CLL pts treated prospectively on 14 studies by the Alliance for Clinical Trials in Oncology from 2004-2014 (Table 1). Toxicity was assessed per the NCI CTCAE at the time of trial enrollment, and the probabilities of experiencing grade 3 and grade 4 hematologic (hem) and non-hematologic (non-hem) toxicities were modeled as a function of age (³65 years vs. < 65), time on study, treatment (biologics only vs. biologic + chemotherapy), gender, race, LDH, performance status (PS), stage, and an age-by-treatment interaction using logistic regression. Results: A total of 1199 pts (409 age ³ 65; 790 age < 65; 736=CLL and 463=NHL) were included. Among these patients, 493 received only biologic therapy (166 age ³ 65; 327 age < 65; 104 CLL; 389 NHL), and 706 received biologic + chemotherapy (243 age ³ 65; 463 age < 65; 632 CLL; 74 NHL). Among CLL pts (259 pts ³ 65), the effect of age on the probability of experiencing a grade 3 heme toxicity differed by treatment type (age-by-treatment interaction p = 0.047). Specifically, the adjusted odds ratio (OR) (age ³ 65 vs. < 65) for pts receiving only biologic therapy was 3.075 (95% CI: 1,15-8.25), and that for pts receiving biologic + chemotherapy was 1.044 (95% CI: 0.69 - 1.57). Similar results were seen in CLL pts for grade 4 heme toxicities (age-by-treatment interaction p = 0.033; biologic OR 6.937, 95% CI: 1.76-27.35; biologic + chemo OR 1.484, 95% CI: 1.04-2.13). No such interactions were found in CLL pts for grade 3 and 4 non-hem toxicities; however, older pts had significantly higher odds of experiencing a grade 3 non-hem toxicity than younger pts (adjusted OR 1.40; p = 0.047; 95% CI: 1.004-1.96). No age group differences were found in CLL pts for grade 4 non-hem toxicity. Similar analyses were performed for NHL pts (150 pts ³ 65), but no significant age group differences were found. Among CLL pts, women had significantly higher odds of experiencing a grade 3 heme toxicity than men (OR 2.01; p = 0.0007); no difference in grade 3 non-hem or any grade 4 toxicity was noted. Non-Caucasian CLL pts had higher odds of experiencing a grade 4 non-hem toxicity than Caucasians (OR 2.892; p = 0.0029), but no other toxicity differences were found. Worse PS was associated with increased toxicities (OR 1.871; p = 0.0009: grade 3 heme; OR 1.647; p = 0.0025: grade 3 non-hem; OR 1.410; p = 0.0448: grade 4 heme, and OR 1.931; p = 0.0252: grade 4 non-hem). CLL pts with advanced stage disease had higher odds of experiencing a heme toxicity (grade 3: OR 1.95; p = 0.0007, grade 4: OR 1.451; p = 0.0329), but no stage associations were found for non-hem toxicities. Among NHL pts, men had significantly higher odds of experiencing a grade 4 hematologic toxicity than women (OR 4.351; p = 0.0169), but no other toxicity differences were found. An increase in LDH was associated with significantly higher odds of experiencing grade 3 non-hem and grade 4 heme toxicities (grade 3 non-heme: OR 1.633; p = 0.021, grade 4 heme: OR 2.039, p = 0.0182), but no such effect was found for grade 3 heme or grade 4 non-hem. Worse PS was associated with higher odds of experiencing grade 3 toxicities (heme: OR 2.025; p = 0.0344, non-hem: OR 2.458; p = 0.0013), but no such differences were found for grade 4 toxicities. No significant stage or race effects were found in NHL patients. Conclusion: In pts ³65 years who have CLL or NHL, we identified several clinical and disease-related factors as potential predictors of developing grade 3 and/or 4 heme and non-hem toxicities (Table 2). A prognostic model is being constructed to predict toxicities in these under-studied pts to guide management and monitoring. Further, the impact of these toxicities on outcomes is being analyzed and will be presented at the meeting. Disclosures Hurria: Celgene: Other: Research; Optum Health Care SOlutions: Consultancy, Other: Conference panel, research; Boehringer Ingelheim Pharmaceuticals: Consultancy; Sanofi: Consultancy; Carevive: Consultancy; Novartis: Other: Research; GTx, Inc: Consultancy. Bartlett:Gilead: Consultancy. Cheson:Gilead: Research Funding; Acerta: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding. Nabhan:Infinity: Consultancy; Abbvie: Consultancy; Cardinal Health: Consultancy; Seattle Genetics: Research Funding; Genentech: Consultancy, Research Funding; Astellas: Research Funding; Celgene Corporation: Consultancy, Research Funding.

Abstract Introduction The natural history of patients (pts) with CLL varies considerably. Some pts may have asymptomatic, indolent disease, while others may require therapy soon after diagnosis. Clinical staging systems cannot identify early-stage pts at risk for inferior survival. Genetic and molecular markers can provide additional information regarding prognosis and response prediction, however their utilization is limited in routine practice (Mato, ASCO 2015) and results can be conflicting. There is a need to identify characteristics of early-stage CLL pts at highest risk of early progression and/or death. Such characteristics, if readily available and reproducible, may identify such pts as candidates for early-intervention studies; particularly in the era of kinase inhibitor therapy. The Connect CLL registry is the largest prospective study describing real-world management of a diverse cohort of 1494 CLL pts. In this analysis, we evaluate key factors that are associated with early CLL-associated mortality in clinical practice. Methods Connect CLL is a multicenter, observational cohort study aimed at understanding patterns of CLL management without a study-specific intervention. Eligible pts were adults with a clinical diagnosis of CLL, enrolled between 2010-2014 at 179 community (n=1311), 17 academic (n=155), and 3 government (n=28) sites within ≤ 2 months of initiating either a first line of therapy (LOT1), or a second-line or subsequent LOT (LOT≥2). The goal of this analysis was to assess potential predictors of death occurring within 18 months following initiation of frontline therapy (LOT1). Because CLL usually presents as an indolent disease associated with a prolonged clinical course, we chose to define early mortality as any death occurring ≤ 18 months following enrollment. Univariate logistic regression was performed against potential predictor variables including several clinical characteristics and comorbid conditions, race, treatment (Tx) site, insurance type, geographic region, presence of prior malignancies, genetic prognostic factors (FISH and cytogenetics) at enrollment, cell surface markers (Zap70, CD38), reasons for Tx initiation and Tx choice for LOT1 (BR or FCR). IgVH mutation status and genetic mutations (P53, Notch1, etc.) were not included as these tests were not readily performed in community practice. Predictors that were found to be significant at the 0.15 significance level were included in the multivariable logistic regression using a stepwise variable selection process, to identify factors associated with early mortality. Results 1344 pts completed 18 months of follow-up (n=1111) or died (n=233) within the first 18 months of study enrollment. Of these, 801 pts were enrolled in LOT1 (median time from diagnosis to LOT1 was 1.3 yrs; IQR, 0.1-3.7 yrs). 82 of 801 pts (10.2%) died within 18 months of LOT1 initiation; 41% of pts with available clinical information who died, were defined as early-stage (Rai stage 0-1). Of 26 potential predictors evaluated, 12 were associated with early mortality among LOT1 pts at the 0.15 significance level in univariate analyses including site, race, age>75, CD-38, del(17p), ECOG PS, CCI group, RAI stage, creatinine clearance, insurance status, reasons for Tx initiation, anemia and lymphocytosis. In multivariable logistic regression analyses we identified 4 independent predictors of mortality within 18 months of LOT1 initiation (Table): pt age, CD38 expression, baseline decreased hemoglobin (as a reason for Tx initiation), and race. Conclusions In CLL pts with Rai stage 0-1, we have identified 4 factors which are associated with increased risk of death within 18 months of initiation of frontline therapy. Interestingly, neither choice of FCR vs BR chemoimmunotherapy nor the presence of del(17p)/del(11q) were predictors of early mortality. Using these results, we are currently designing a model to predict early mortality in early-stage pts. Once validated, these results may provide a framework for trials targeting the "early stage, symptomatic" CLL pts for novel interventions. Table. Multivariable Analysis: Predictors of Early Mortality Odds ratio estimate 95% CI P -value LOT1, n=781 Age ≥75 years, yes vs no 2.2 1.4-3.5 0.0012 CD38 expression, positive vs negative/not specified 1.8 1.1-2.9 0.0182 Anemia as reason for treatment, yes vs no 2.1 1.3-3.4 0.0040 Race, other vs Caucasian 1.9 1.0-3.8 0.0501 Disclosures Farber: Gilead: Speakers Bureau; Genentech: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene Corporation: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Honoraria, Speakers Bureau; Pharmacyclics: Honoraria, Speakers Bureau. Mato:TG Therapeutics: Research Funding; Genentech: Consultancy; AbbVie: Consultancy, Research Funding; Pronai Pharmaceuticals: Research Funding; Gilead: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; Celgene Corporation: Consultancy, Research Funding; Janssen: Consultancy. Nabhan:Celgene Corporation: Honoraria, Research Funding. Kipps:Pharmacyclics Abbvie Celgene Genentech Astra Zeneca Gilead Sciences: Other: Advisor. Flowers:Spectrum: Research Funding; Pharmacyclics: Research Funding; Infinity Pharmaceuticals: Research Funding; OptumRx: Consultancy; Gilead Sciences: Research Funding; Spectrum: Research Funding; Genentech: Research Funding; Onyx Pharmaceuticals: Research Funding; Acerta: Research Funding; OptumRx: Consultancy; Gilead Sciences: Research Funding; AbbVie: Research Funding; Pharmacyclics: Research Funding; Seattle Genetics: Consultancy; Onyx Pharmaceuticals: Research Funding; Genentech: Research Funding; Millennium/Takeda: Research Funding; Celegene: Other: Unpaid consultant, Research Funding; Janssen: Research Funding; Infinity Pharmaceuticals: Research Funding; Acerta: Research Funding; AbbVie: Research Funding; Seattle Genetics: Consultancy; Celegene: Other: Unpaid consultant, Research Funding; Janssen: Research Funding; Millennium/Takeda: Research Funding. Kay:Pharmacyclics: Research Funding; Hospira: Research Funding; Genentech: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharma: Research Funding; Celgene Corporation: 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 Corporation: 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. Grinblatt:Celgene Corporation: Consultancy, Honoraria, Speakers Bureau. Kozloff:Celgene: Consultancy, Speakers Bureau; Genentech: Consultancy, Speakers Bureau; Roche: Consultancy, Speakers Bureau; AbbVie: Consultancy. Sullivan:Celgene Corporation: Employment, Equity Ownership. Flick:Celgene Corporation: Employment, Equity Ownership. Kiselev:Celgene Corporation: Consultancy. Bhushan:Celgene Corporation: Employment, Equity Ownership. Swern:Celgene Corporation: Employment, Equity Ownership. Sharman:TG Therapeutics, Inc.: Research Funding; Celgene Corporation: Consultancy, Research Funding; Gilead: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Research Funding; Calistoga: Honoraria; Roche: Research Funding; Pharmacyclics: Consultancy, Honoraria, Research Funding.

Abstract Introduction: Results of several large clinical trials have demonstrated inferior outcomes when CLL patients (pts) with del(17p), or to a lesser extent del(11q), are treated with chemoimmunotherapy. Despite recent advances in targeted therapies, management of unfavorable-risk CLL pts remains challenging. The Connect CLL registry is the largest prospective study describing real-world management of a diverse cohort of CLL pts. Here we describe the management of genetically unfavorable-risk CLL pts enrolled in the Connect CLL Registry, and test associations between del(17p)/del(11q) mutations and treatment choice, timing of therapy, and outcomes. Methods: Connect CLL is a longitudinal, multicenter, observational cohort study of 1,494 CLL pts enrolled between 2010-2014 at 179 community (n=1,311), 17 academic (n=155), and 3 government (n=28) sites within ≤ 2 months of initiating any line of therapy (LOT). For this study, pts were categorized into 3 risk-groups based on FISH or cytogenetic results at enrollment: unfavorable risk [either del(17p)/del(11q) positive]; favorable risk [absence of del(17p)/del(11q)]; and unknown risk (testing not performed). Analyses were stratified by LOT at enrollment (LOT1 vs LOT≥2). The risk of an EFS defining event was compared across risk-groups stratified by LOT, including only pts who had been followed for ≥ 2 years (yr) or those who had an EFS defining event (death, progression/relapse, transformation) within 2 yr, using multivariable (MV) logistic regression. Logistic regression analyses of 18 potential predictors were performed, and significant predictors (0.10 significance level) were then included in a MV logistic regression model to identify factors associated with inferior 2 yr EFS. Results: Of 1,494 pts enrolled, 225 had unfavorable risk [del(17p), n = 94; del(11q), n = 131], 621 favorable risk, and 648 unknown risk. For pts enrolled at LOT1 (n = 889), 141 had unfavorable risk, 425 favorable risk, and 323 unknown risk. Baseline characteristics for unfavorable-risk pts in LOT1 included: median age 69 yr (62% age ≥ 65 yr); 91% White; 53% Rai stage ≥ 2; 86% community sites; 0.9 yr median time from dx to LOT1; 8% family history CLL. With the exception of age, unfavorable-risk pts treated at LOT1 with FCR (median age 63) and BR (median age 74) had similar demographic characteristics. Median time from dx to LOT1 was 1.0, 1.3, and 2.0 yr for unfavorable risk, favorable, and unknown-risk pts, respectively (P < 0.001 for comparison of the 3 risk-subgroups). Reasons for initiating treatment in unfavorable-risk pts were lymphadenopathy (42%), bone marrow failure (36%), and lymphocytosis (33%) (similar across the 3 risk-subgroups). The three most common therapies for unfavorable-risk pts in LOT1 were FCR (36%), BR (21%), and FR (6%). Favorable-risk (FCR 26%, BR 24%, and R 10%) and unknown-risk pts (FCR 22%, BR 18%, and R 17%) were treated similarly in LOT1. Median time from dx to LOT≥2 was 3.5 yr in unfavorable-risk pts (vs 4.1 yr in favorable and 4.6 yr in unknown risk pts; P = 0.04 for comparison of the 3 risk-groups). For unfavorable-risk pts in LOT≥2, BR (26%), R (11%), and FCR (10%) were most commonly prescribed. At any LOT, only 10% of unfavorable-risk pts participated in a clinical trial and 4% underwent allogeneic SCT. Overall, 33% (LOT1) and 68% (LOT≥2) of pts experienced an EFS defining event within 2 yrs. Pts with unfavorable risk (vs favorable risk) had significantly worse outcomes, with a higher-risk of death/progression/relapse/transformation within 2 yr (LOT1: 42% vs 29%, respectively, P = 0.008; and LOT≥2: 80% vs 61%, P = 0.004). Unfavorable-risk pts treated with either FCR or BR at LOT1 had similar risk of an EFS defining event (odds ratio [OR] 0.9, CI 0.6-1.5). Results from MV analyses of LOT1 pts identified unfavorable risk (OR 1.9; 95% CI 1.1-3.1; P = 0.0168) and age ≥ 75 years (OR 2.6; 95% CI 1.5-4.3; P = 0.007) as independent predictors of inferior EFS at 2 yr. Conclusions: Although similar treatment approaches were used among the 3 risk-subgroups, pts with unfavorable-risk CLL had inferior outcomes at LOT1 and LOT≥2. These results, from a real-world setting, validate the findings for unfavorable risk pts from large clinical trials. These data underscore the importance of performing genetic risk stratification on all CLL pts, and support consideration of clinical trials and/or B cell receptor targeted agents for unfavorable risk CLL pts when treatment is considered. Disclosures Mato: Janssen: Consultancy; AbbVie: Consultancy, Research Funding; Genentech: Consultancy; Pronai Pharmaceuticals: Research Funding; Celgene Corporation: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; Gilead: Consultancy, Research Funding; TG Therapeutics: Research Funding. Nabhan:Celgene Corporation: Honoraria, Research Funding. Flowers:Celegene: Other: Unpaid consultant, Research Funding; Celegene: Other: Unpaid consultant, Research Funding; Spectrum: Research Funding; Infinity Pharmaceuticals: Research Funding; OptumRx: Consultancy; Onyx Pharmaceuticals: Research Funding; Janssen: Research Funding; AbbVie: Research Funding; Seattle Genetics: Consultancy; Onyx Pharmaceuticals: Research Funding; Pharmacyclics: Research Funding; Gilead Sciences: Research Funding; Genentech: Research Funding; Acerta: Research Funding; Genentech: Research Funding; Janssen: Research Funding; Millennium/Takeda: Research Funding; Infinity Pharmaceuticals: Research Funding; Spectrum: Research Funding; Millennium/Takeda: Research Funding; Pharmacyclics: Research Funding; OptumRx: Consultancy; Gilead Sciences: Research Funding; AbbVie: Research Funding; Seattle Genetics: Consultancy; Acerta: Research Funding. Kay:Pharmacyclics: Research Funding; Genentech: Research Funding; Tolero Pharma: 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; Hospira: Research Funding. Kipps:Pharmacyclics Abbvie Celgene Genentech Astra Zeneca Gilead Sciences: Other: Advisor; Pharmacyclics Abbvie Celgene Genentech Astra Zeneca Gilead Sciences: Other: Advisor. Grinblatt:Celgene Corporation: Consultancy, Honoraria, Speakers Bureau. 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; Infinity: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Kozloff:Genentech: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Roche: Consultancy, Speakers Bureau; AbbVie: Consultancy. Sullivan:Celgene Corporation: Employment, Equity Ownership. Flick:Celgene Corporation: Employment, Equity Ownership. Kiselev:Celgene Corporation: Consultancy. Bhushan:Celgene Corporation: Employment, Equity Ownership. Swern:Celgene Corporation: Employment, Equity Ownership. Sharman:Gilead: Consultancy, Honoraria, Research Funding, Speakers Bureau; Calistoga: Honoraria; Roche: Research Funding; TG Therapeutics, Inc.: Research Funding; Celgene Corporation: Consultancy, Research Funding; Pharmacyclics: Consultancy, Honoraria, Research Funding; Janssen: Research Funding.

Abstract Introduction: The median age at diagnosis for CLL pts in the US is 72 years. As clinical trials in CLL have largely enrolled younger pt populations, data on disease and pts' characteristics, patterns of care, prognosis, and molecular features in aged CLL pts are limited. With this in mind, we conducted a prospective study to update critical demographic data and patterns of care for aged CLL pt. Patients and Methods: Connect®-CLL is a US-based prospective, longitudinal, multi-center, observational registry that is aimed at understanding patterns of CLL management without a study-specific intervention. We enrolled pts treated at an academic (n=155) or community (n=1340) setting between 2010 and 2014. Eligible pts were adults with a clinical diagnosis of CLL who required therapy 2 or less months after enrollment. Data on demographics, baseline characteristics, and treatment selection are presented here using descriptive statistics. Continuous variables are reported using appropriate measures of dispersion and central tendency (means, medians, ranges and standard deviations) while categorical variables are summarized as number and percentage of the analysis population. Results: Of 1495 enrolled pts, 457 (30.5%) were ≥75 years (57.3% males, 94.2% white). Rai stage III/IV was noted in 33% and B symptoms (predominantly fatigue (58.4%)) were observed in 68.1%. These and other clinical baseline characteristics appeared similar to pts younger than 75 years except that older pts had more prior malignancies (33.5% vs. 19.8%) and co-morbidities (69.3% vs. 53.6%). Cardiac, neurologic, and renal disorders were the most common morbidities in pts ≥75 years (11.5%, 8.8%, and 4.6% respectively). Imaging studies were performed in 157 (60.2%) older pts and in 416 (65.7%) pts less than 75 years prior to initial therapy. Percentage of pts with bulky nodes (> 5 cm) by imaging was similar in the two groups, 19.3% overall. Prognostic biomarker data were available on 247 pts (178 (72%) <75 years; 69 (28%) ≥75 years). While a higher proportion of older pts had CD38+ CLL (55.1% vs. 40.5%, P=0.038), the proportions of patients with ZAP-70+ CLL were similar between the two groups. In total, 137 (9%) older and 378 (25%) younger pts had 17p and 11q analysis by FISH at enrollment prior to first-line therapy. Of these, 27.0% of pts ≥75 years and 20.6% of pts <75 years had a deletion of either 17p or 11q (P=0.125). Out of all pts enrolled in the registry, 894 (60%) received first-line treatment (261 (29%) pts ≥75 years and 633 (71%) <75 years) as their indication for study entry. Amongst these treated pts, interim analysis shows (data cutoff date: 25 June 2014) progressive marrow failure was more commonly used as the indication for therapy in older pts compared to younger pts (52.1% vs. 38.5%; P<0.001), while splenomegaly was a more common cause for therapy in younger pts (16% vs. 9%; P<0.01). Rai stage III/IV at time of first therapy was 46% and 49% for younger and older pts, respectively. Progressive lymphocytosis was used as the indication for therapy in one third of pts regardless of age. Seventy-four percent of older CLL pts received first-line therapies containing rituximab (R) vs. 85% in pts <75 years (P<0.0001). R-bendamustine was the most common first-line regimen for CLL pts ≥75 (23.4%) while FCR was more commonly given to pts <75 years (32.5%). R-monotherapy was used in 18.8% of older pts versus 9.5% in pts <75 years (P<0.0001). Of note, approximately 25% of CLL pts ≥75 years did not receive R-based regimens for initial therapy. Conclusions: Connect®-CLL is the largest prospective, multicenter CLL registry in the United States. CLL Pts ≥75 years more frequently overexpress CD38 and may more commonly demonstrate high risk cytogenetics by FISH, although the difference did not reach statistical significance. Pts ≥75 years also more commonly had co-morbid diseases, and surprisingly 25% did not receive first-line R-based therapy. CLL pts are rarely included in front-line clinical trials (<3%). Given that novel therapies are increasingly available for CLL patients a continued analysis is warranted to determine their use in elderly vs younger patients as well. A longer follow up is needed to evaluate the impact of these findings on outcomes. Disclosures Nabhan: Celgene: Honoraria, Research Funding. Off Label Use: Lenalidomide in CLL. Kay:Celgene: Research Funding. Mato:Genentech, Celgene, Millenium: Speakers Bureau. Grinblatt:Celgene: Honoraria, Speakers Bureau. Kipps:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Lamanna:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Weiss:Celgene: Consultancy. Flinn:Celgene: Research Funding. Swern:Celgene: Employment, Equity Ownership. Street:Celgene: Employment, Equity Ownership. Kristen:Celgene: Employment, Equity Ownership. Flowers:Celgene, Prescription Solutions, Seattle Genetics, Millennium (unpaid), Genentech (unpaid) : Consultancy; Gilead, Spectrum, Millennium, Janssen: Research Funding.

Key Points Early progression of disease within 2 years of initial therapy independently predicts inferior survival in CLL. Early progression of disease is a robust clinical end point and a useful posttreatment risk stratification tool.

Abstract Introduction: Our current understanding of CLL biology and optimal therapies is based on clinical trials that have largely enrolled White patient populations. Whether these findings are applicable to Hispanic or non-White patients is unknown but critical to evaluate given the growing numbers of minority patients in the U.S. While retrospective studies have suggested inferior outcomes in non-White patients, prospective data on these disparities are lacking. Patients and Methods: We utilized the Mayo Clinic CLL database to better understand variations in disease characteristics, molecular differences, and treatment selections between non-Hispanic White patients and those not in this category (referred to hereafter as “other race”). After excluding 49 patients with missing diagnosis date and another 490 patients with missing race and/or ethnicity, the remaining 4104 cases within the registry were included in the analysis. Comparisons by race were made using Chi-square or Wilcoxon rank sum tests for qualitative or quantitative variables, respectively. Overall survival (OS) was calculated from diagnosis until death or last known alive date; time to first treatment (TTFT) was calculated from diagnosis until treatment date or date last known to be untreated. OS and TTFT were displayed via Kaplan-Meier plots, and differences in OS and TTFT by race were calculated using log-rank statistics. Individuals who were enrolled in early intervention trials (n=61) were excluded from analyses involving treatment. Results: In total, 4104 CLL patients were identified: 4011 (97.7%) non-Hispanic Whites and 93 (2.3%) other races. Median age at CLL diagnosis was younger for other race patients (59 vs. 63 years; p=0.002), while gender and stage distributions were comparable between both groups. Serum β-2-microglobulin and absolute lymphocyte counts at diagnosis were similar but more other race patients had elevated LDH (29.5% vs. 16.1%; p=0.02). Cytogenetic data by FISH were available for 1884 non-Hispanic Whites and 46 other race patients; poor-risk cytogenetics (17p and/or 11q deletions) were present in 23.9% of other race and 13.5% of non-Hispanic White patients, respectively (p=0.04). No statistically significant differences were observed for CD38, ZAP-70, or IGHV by race TTFT was similar for both non-Hispanic Whites and other race patients (4.6 vs. 5.5 years, respectively; p=0.12). First-line treatment selection was similar for both groups (Table). . With a median follow-up of 12.1 years, median overall survival was 9.3 years for other race and 12.2 years in non-Hispanic White patients (P=0.15; Figure). Conclusions: This prospective data supports the notion that CLL might be biologically different between non-Hispanic White and other race patients with less favorable FISH present in the latter group. Despite the observation that TTFT and type of first therapy are similar between both groups, the trend towards shorter OS in other race patients argues that other factors might contribute to outcome differences, such as disease biology, access to care, co-morbidities, and socioeconomic considerations. Further studies with larger cohorts are warranted. Table: First-line treatment selection among treated individual by racial First-line Treatment Non-Hispanic Whites(n=1875) Other race(n=41) Chemoimmunotherapy Purine analogue-based Alkylator-based 675 (36.0) 495 (26.4) 180 (9.6) 15 (35.6) 9 (22.0) 6 (14.6) Purine analogue -monotherapy 157 (8.4) 4 (9.8) Alkylator monotherapy 610 (32.5) 9 (22.0) PA+Alkylator 41 (2.2) 1 (2.4) Antibody alone 190 (10.1) 6 (14.6) Other 202 (10.8) 6 (14.6) Figure: Overall survival in CLL cases stratified by race Figure:. Overall survival in CLL cases stratified by race Disclosures Nabhan: Genentech: Honoraria, Research Funding, Speakers Bureau; Celgene: Honoraria, Research Funding; Janssen: Honoraria, Speakers Bureau. Kay:Celgene: Research Funding. Shanafelt:Genentech: Research Funding; GlaxoSmithKline: Research Funding; Celegene: Research Funding; Cephalon: Research Funding; Pharmacyclics/Jannsen: Research Funding; Hospira: Research Funding; Polyphenon E Int'l: Research Funding.

Abstract The majority of pts with newly diagnosed CLL are classified with Rai stage 0 or 1 disease and typically experience an indolent clinical course. However, little is known regarding the reasons for initiating therapy in this population or patterns of initial treatment in the contemporary era of our practicing community. We utilized data from the Connect CLL registry, a US-based multi-center, prospective observational cohort study that is aimed at understanding patterns of CLL management without a study-specific intervention. Eligible pts were adults with a clinical diagnosis of CLL who initiated therapy ≤2 months prior to enrollment, and were enrolled from academic (n=155), community (n=1311), or government (n=28) sites between 2010-2014. Descriptive statistics were applied to examine data on demographics, baseline characteristics, treatment selection, early treatment outcomes, and reasons for initiating therapy that were reported for pts with Rai 0/1 CLL receiving first-line therapy. Multivariable logistic regression models were constructed to evaluate predictors of complete response (CR) and event-free survival (EFS) defined as the occurrence of the first of disease progression, relapse or death within 24 months of enrollment. Among 684 pts who received first-line therapy at enrollment and for whom Rai stage was available, 363 had Rai 0/1 CLL. This group had a median age of 68 years (range 41-90); 94% were white, 60% male, 98% insured, and 93% were treated in community practices; 47% had Rai stage 0 disease (54% Binet A); 33% had ≥1 constitutional symptoms; 96% had ECOG performance status of 0 or 1; 35% had conventional cytogenetics and 53% had FISH analysis performed. Among pts for whom cytogenetic or FISH analysis were performed, 159 (72%) were abnormal, of them 37 pts (23%) had del(11q), 104 pts (65%) had del(13q), 33 pts (21%) had trisomy 12, and 20 pts (13%) had del(17p) by conventional cytogenetics and/or FISH, including 8% with del(17p) by FISH. The median time from diagnosis to initiation of therapy was 2.5 years (range 0-20 years) for Rai 0/1 pts compared with 0.5 years for pts enrolled with Rai stage ≥2 (range 0-32). The most common reasons for initiating therapy (with >1 reason possible) in Rai 0/1 CLL were: bulky or progressive or lymphadenopathy (40%), progressive lymphocytosis (39%), any disease-related symptom (weight loss, fatigue, fever, night sweats; 28%), anemia (20%), and thrombocytopenia (15%); 42% of pts had >1 reason for initiation. The most common first-line regimens used in this cohort were: fludarabine/cyclophosphamide/rituximab (FCR; 29%), bendamustine/rituximab (BR; 20%), and rituximab alone (12%). Of the 317 pts who either responded to treatment during the first 24 months of enrollment or were followed ≥24 months, 143 pts (45%) achieved CR (investigator assessed as per protocol) and 264 (83%) achieved CR or partial response. Female gender (odds ratio [OR] = 2.22), treatment with BR or FCR (OR = 3.41), and time from diagnosis to therapy (OR = 0.92; with each year increase in time from diagnosis to initiation of therapy, relative odds of CR decreases by 8%), were independent predictors of CR. Of the 311 evaluable pts, 82 pts (26%) experienced an EFS event during the 24 months on study, of which 19 (23%) were deaths and 48 (59%) were progressions. Age ≥75 years (OR = 4.46), lymphocytosis as a reason for therapy initiation (OR = 1.89), and male gender (OR = 1.73) were independent predictors of an EFS event within 24 months. The Connect CLL registry represents the largest comprehensive prospective cohort of CLL pts collected from multiple practices across the US. In concordance with other studies, pts with Rai 0/1 initiated therapy approximately 2.5 years following CLL diagnosis and included a cohort of pts with poor prognostic FISH characteristics. Although chemoimmunotherapy was associated with a significantly higher likelihood of CR, progressive lymphocytosis as a reason for initiating therapy (and not any form of treatment) was more likely to predict an early EFS event. Approaches using novel agents or combination therapies aimed towards addressing pts with progressive lymphocytosis should be considered in future studies. Disclosures Flowers: Seattle Genetics: Consultancy; OptumRx: Consultancy; AbbVie: Research Funding; Pharmacyclics: Research Funding; Gilead Sciences: Research Funding; Genentech: Research Funding; AbbVie: Research Funding; Celegene: Other: Unpaid consultant, Research Funding; Spectrum: Research Funding; Onyx Pharmaceuticals: Research Funding; Spectrum: Research Funding; Acerta: Research Funding; Gilead Sciences: Research Funding; Janssen: Research Funding; Infinity Pharmaceuticals: Research Funding; Infinity Pharmaceuticals: Research Funding; Janssen: Research Funding; Millennium/Takeda: Research Funding; Onyx Pharmaceuticals: Research Funding; Pharmacyclics: Research Funding; Acerta: Research Funding; Millennium/Takeda: Research Funding. Nabhan:Celgene Corporation: Honoraria, Research Funding. Kay:Pharmacyclics: Research Funding; Genentech: Research Funding; Celgene Corporation: Membership on an entity's Board of Directors or advisory committees, Research Funding; Hospira: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharma: Research Funding. Mato:AbbVie: Consultancy, Research Funding; Janssen: Consultancy; Celgene Corporation: Consultancy, Research Funding; Pronai Pharmaceuticals: Research Funding; Pharmacyclics: Consultancy, Research Funding; TG Therapeutics: Research Funding; Gilead: Consultancy, Research Funding; Genentech: Consultancy. 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 Corporation: 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. Grinblatt:Celgene Corporation: Consultancy, Honoraria, Speakers Bureau. Kipps:Pharmacyclics Abbvie Celgene Genentech Astra Zeneca Gilead Sciences: Other: Advisor; Pharmacyclics Abbvie Celgene Genentech Astra Zeneca Gilead Sciences: Other: Advisor. Kozloff:Roche: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Genentech: Consultancy, Speakers Bureau; AbbVie: Consultancy. Sullivan:Celgene Corporation: Employment, Equity Ownership. Flick:Celgene Corporation: Employment, Equity Ownership. Kiselev:Celgene Corporation: Consultancy. Bhushan:Celgene Corporation: Employment, Equity Ownership. Swern:Celgene Corporation: Employment, Equity Ownership. Sharman:TG Therapeutics, Inc.: Research Funding; Gilead: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Research Funding; Calistoga: Honoraria; Celgene Corporation: Consultancy, Research Funding; Pharmacyclics: Consultancy, Honoraria, Research Funding; Roche: Research Funding.

Abstract Abstract 3708 Background: There are few prospective studies on disease characteristics, patterns of care, response, and outcomes in elderly FL patients (pts) in the US. The NLCS is a Genentech-sponsored prospective multicenter registry study that collects this information without study-specific treatment. We utilized the NLCS database to better understand the impact of age on FL outcome. Patients and Methods: All evaluable pts with FL histology in the NLCS were included except pts with FL plus other lymphoma histology or pts who progressed before first treatment or before being assigned to watchful waiting (WW). Using Pearson Chi-Square tests, associations of age groups (≤60, 61–70, >70) with disease characteristics and overall response (ORR) were examined. Median PFS and OS by treatment regimen were estimated using Kaplan-Meier methods for each age group. Cox proportional hazards regression adjusted for baseline factors (grade, number of nodal sites, LDH, Hgb, stage, performance status (PS), bone marrow (BM) involvement, race, and treatment center type) were used to assess treatment differences in PFS and OS and the significance of age by treatment interactions. Results: Of 2,647 pts, 47% (n=1,254) were ≤60 yrs, 25% (n=666) were 61–70 yrs, and 27% (n=727) were >70 yrs (min age of 22; max of 97). Compared with pts ≤60 yrs, pts 61–70 and >70 were more likely to be white (93% >70, 92% 61–70, and 88% ≤60, P=.02 and .02 respectively), have stage I/II disease (37% >70, 36% 61–70, and 29% ≤60, P=.0008 and .0003), have <5 nodal sites (73% >70, 69% 61–70, and 61% ≤60, P=.001 and <.0001), and have poor-risk FLIPI (53% >70, 51% 61–70, and 15% ≤60, P<.0001 and <.0001). Compared with pts ≤60, elderly pts (>70) were more likely to have FL grade 3 (24% vs 18%, P=.01). While there were no differences in geographic distribution by age, elderly pts were more likely to receive therapy at community practices (86%) versus academic institutions than pts ≤60 (77%, P<.0001) or 61–70 (81%, P=.004). Treatments varied significantly by age (P<.0001). More elderly pts were observed compared to pts ≤60 (23% vs19%). When treated, elderly pts (22%) were more likely to receive rituximab (R) monotherapy compared with patients aged 61–70 (12%) or ≤60 (10%). When chemotherapy alone or plus R was given, elderly pts were less likely to receive anthracyclines (45% vs 65% (61–70) and 68% (≤60)). Among all variables, only grade 3 histology predicted anthracycline use in all age groups. Lack of BM involvement predicted anthracycline use for younger pts (≤60 and 61–70). Of those ≤60, white pts were more likely to receive anthracyclines, and of those 61–70, those with ≥5 nodal sites were more likely to receive anthracyclines. ORRs were similar across age groups receiving similar regimens with R plus chemo providing the highest ORR. Adjusting for baseline factors, treatment (WW, R, R-Chemo, or other) benefit varied for each age group in terms of PFS (P=.02), with treatment outcomes being most differentiated among younger pts (Table). PFS appeared shorter in elderly pts regardless of the treatment received. No significant interaction between age and efficacy of anthracycline in terms of PFS or OS was observed (P-values >.65), but the overall effect of anthracycline for all pts was beneficial for PFS (HR=0.80, P=.02) and OS (HR=0.67, P=.003). Median OS was 8 years for elderly and not reached for others. After adjusting for baseline factors, no significant differences in treatment impact by age on OS were seen. Elevated LDH, reduced Hgb, stage III/IV, PS ≥1, and BM involvement were all significantly associated with shortened OS. These factors were also significantly associated with treatment choice, as worse-prognosis elderly pts were more likely to receive either R or R+chemo than WW or other treatment. Conclusions: FL pts >70 yrs more commonly received R alone and less commonly received anthracyclines when treated with chemotherapy. The impact of anthracyclines on PFS did not vary by age, but differences in PFS for other treatment regimens showed a stronger association among younger pts Disclosures: Nabhan: Genentech: Research Funding, Speakers Bureau. Byrtek:Genentech, Inc., a member of the Riche Group: Employment, Equity Ownership. Dawson:Genentech, Inc., a member of the Riche Group: Employment, Equity Ownership. Link:Genentech, Inc., a member of the Riche Group: Consultancy; Celgene: Consultancy; Spectrum: Consultancy. Friedberg:Genentech: Consultancy. Cerhan:Genentech: National LymphoCare Scientific Advisory Board Other. Flowers:Celgene: Consultancy; Prescription Solutions: Consultancy; Seattle Genetics: Consultancy; Millennium: Consultancy, Research Funding; Genentech: Consultancy; GIlead: Research Funding; Spectrum: Research Funding; Janssen: Research Funding; Lymphoma Research Foundation: Membership on an entity's Board of Directors or advisory committees.