Sharman, Jeff P.

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.

7519 Background: Acalabrutinib, a highly selective, potent, covalent Bruton tyrosine kinase (BTK) inhibitor, has a 24% overall response rate (ORR) as a single agent in R/R DLBCL. Pem targets PD-1, an immune checkpoint that limits anticancer responses. Pem showed responses in patients (pts) with Richter transformation who failed ibrutinib and can augment acalabrutinib activity in vitro. This study assessed acalabrutinib + Pem in R/R DLBCL. Methods: Pts with DLBCL, ≥1 prior chemoimmunotherapy and no prior allogeneic transplant received acalabrutinib 100 mg PO BID until progressive disease (PD) + Pem 200 mg/kg IV Q3W up to 2 y. Germinal center B-cell (GCB) vs non-GCB subtype was assessed by immunohistochemistry. Primary endpoint was safety. Results: Sixty-one pts (30 GCB; 31 non-GCB) were accrued, with a median age (range) of 67 y (30-85) and a median of 3 (1-8) prior therapies; 1 pt had prior autologous transplant. The most common Gr 3/4 adverse events (AEs) were neutropenia (15%) and anemia (11%). Gr 5 AEs were respiratory failure (n=3), sepsis, septic shock and abdominal abscess (n=1 each). All Gr atrial fibrillation was 5% (n=3), and major hemorrhage (≥ Gr 3) was 11% (4 gastrointestinal, 1 pulmonary, 1 epistaxis, 1 hematuria). Gr 3/4 immune-mediated events were elevated alanine aminotransferase (n=4), pneumonitis (n=2) and colitis (n=1). The ORR was 26% (Table) and was similar in GCB (27%) and non-GCB (26%) tumors. The median time on study was 5.2 mo (0.4-30.4+). Acalabrutinib/Pem discontinuations were due to PD (62%/56%) and AEs (15%/26%). As of June 2018, 10 pts remain on study; 6 on active therapy and 7 without PD. Conclusions: Acalabrutinib + Pem was well tolerated, with meaningful activity and some exceptional responders (>24 mo) in these R/R DLBCL pts. Randomized trials of the combination vs single agent are needed. Clinical trial information: NCT02362035. [Table: see text]

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.

8032 Background: Btk supports activation, survival, and proliferation of malignant B cells in CLL and B-NHL. AVL-292 is an oral, potent (IC50 < 0.5nM), selective small molecule covalent inhibitor of Btk. Methods: Patients (pts) with previously treated CLL or B-NHL were administered AVL-292 in escalating cohorts of 125, 250, or 400 mg po QD using a 3+3 design in continuous 28 day cycles until progressive disease (PD) or toxicity. Key objectives were safety, DLT, MTD, PK, and Btk occupancy. Plasma AVL-292 levels were assessed by LC-MS-MS. Btk occupancy by AVL-292 was assessed by covalent probe assay in peripheral blood mononuclear cells. Results: 12 pts have enrolled (3 each at 125 and 250 mg and 6 at 400 mg: 5M/7F; median age 68 years, range 45-79; median 2.5 prior therapies, range 1-10) including 8 CLL (2 with 17p-, 2 with 11q22-, 2 with both 17p-/11q22-; 2 mutated IGHV, 5 unmutated IGHV, 1 missing) and 4 B-NHL (1 diffuse large B cell lymphoma (DLBCL); 1 follicular (FL); 2 marginal zone (MZL)). Median time on treatment is 65 days, range 28-158. Ten of 12 pts continue on treatment: 1 pt (DLBCL) discontinued for PD after 1 cycle and 1 pt (FL) for DLT (Gr 4 plts; 400 mg QD). No other DLTs or grade 4 adverse events (AEs) have occurred and MTD has not been reached. Most frequent AEs reported include transient diarrhea, rash/skin infection, URI, nausea, and fatigue. Gr 3 AEs include 1 atrial fibrillation (not drug related) and 1 ANC low (probably drug related). To date, 8 of 8 CLL patients have stable disease (SD) with median 28% decrease from baseline lymph node measurement (range 3-40% decrease). Six of 8 pts with CLL experienced increased ALC in cycle 1: median increase 89.5% (range 50-212%). Two of 4 NHL pts have SD (both MZL), 1 PD (DLBCL), and 1 not evaluable due to DLT (FL). Full Btk occupancy was achieved with dose levels ≥ 250 mg. Multiple dose PK exposure (AUClast) was linear with no accumulation from Day 1 to 15. Conclusions: AVL-292 was well tolerated from 125-400 mg po QD and early efficacy analysis in CLL and B-NHL shows 10/11 efficacy evaluable pts with SD. Full Btk occupancy was achieved with ≥ 250 mg QD and PK was predictable with no accumulation. Dose escalation is ongoing and MTD cohort expansion is planned.

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.

Background Diffuse large B-cell lymphoma (DLBCL) is the most common non-Hodgkin's lymphoma (NHL) in adults. R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone) remains the standard of care for newly diagnosed DLBCL, with cure rates of 60-70%. However, more effective front-line options are needed to further improve outcomes, particularly in high-risk patients (Sehn LH, Gascoyne RD. Blood 2015;125:22). Approximately 15-20% of treatment-naïve patients with DLBCL have CD20-low expressing tumors, while CD19 is expressed in >90% of DLBCL. CD20-low DLBCL is associated with poor response to rituximab-based regimens (Johnson NA, et al. Blood 2009;113:3773; Prevodnik VK, et al. Diagnostic Pathol 2011;6:33). CD19 is a B-lymphocyte lineage-specific surface antigen that is widely expressed in mature B-cell malignancies, including DLBCL. CD19 functions as a positive regulator of B-cell receptor signaling and is important for B-cell activation and proliferation, and is, therefore, an attractive therapeutic target in addition to CD20. Tafasitamab (MOR208) is a humanized anti-CD19 monoclonal antibody with an engineered constant region (Fc) that enhances Fc-γ receptor binding affinity on effector cells, thereby enhancing antibody-dependent cellular cytotoxicity (ADCC) and phagocytosis (ADCP). Preliminary data in DLBCL cell lines suggest that combined targeting of CD19 and CD20 with tafasitamab and rituximab, respectively, could have synergistic cytotoxic effects. Monotherapy with tafasitamab has shown clinical activity and acceptable safety in a Phase I study in relapsed/refractory (R/R) chronic lymphocytic leukemia/small lymphocytic lymphoma (NCT01161511) and in a Phase IIa study in R/R NHL (NCT01685008). In patients with R/R DLBCL, treatment with single agent tafasitamab until progression led to a 26% objective response rate (ORR) with several long-term responses (Jurczak W, et al. Ann Oncol 2018; 29:1266). Preclinical in vitro and in vivo data have demonstrated increased combinatorial antitumor effects with tafasitamab and the immunomodulatory agent lenalidomide (LEN). In the Phase II, single-arm L-MIND study (NCT02399085) in patients with R/R DLBCL, treatment with tafasitamab/LEN achieved an ORR of 60%, a complete response (CR) rate of 42.5% and a median progression-free survival (PFS) of 12.1 months (Salles GA, et al. ICML 2019; Abstr 124). This combination received breakthrough therapy designation by the US Food and Drug Administration. Study design and methods First-MIND is a Phase Ib, open-label, multicenter, randomized trial of tafasitamab/R-CHOP or tafasitamab/LEN/R-CHOP in patients with newly diagnosed DLBCL (Figure 1). Patients must be aged ≥18 years, treatment naïve, with histologically confirmed DLBCL not otherwise specified and have intermediate- to high-risk disease (International Prognostic Index 2-5). Key exclusion criteria include known double- or triple-hit lymphoma, and transformed or composite lymphoma. Treatment consists of six 21-day cycles of tafasitamab (12 mg/kg intravenously [IV], on Days [D] 1, 8 and 15) in addition to R-CHOP (Arm A) or tafasitamab (12 mg/kg IV, on D1, 8 and 15) and LEN (25 mg orally, on D1-10) in addition to R-CHOP (Arm B). The trial includes a safety run-in phase and a main phase. In the safety run-in phase, 12 patients will be enrolled in each arm. If no unexpected safety signals suspected to be related to the addition of tafasitamab ± LEN to R-CHOP are observed, an additional 18 patients will be enrolled in each arm in the main phase. The primary objective of the trial is to assess safety; secondary objectives include evaluation of efficacy (ORR and PET-assessed CR rate at end of treatment, PFS, overall survival, event-free survival, time to next anti-lymphoma treatment), long-term safety and pharmacokinetics, and immunogenicity of tafasitamab in each arm. Exploratory objectives will include the assessment of biomarkers in peripheral blood (natural killer [NK] cell count, cell-free circulating tumor DNA) and tumor tissue (DLBCL cell of origin, NK cell or macrophage count/gene expression profile, CD19 and CD20 expression) that may be relevant to the mechanism of action and/or response to study treatment. As this is a Phase Ib study to primarily explore safety, no formal statistical hypothesis is considered for the sample size calculation; approximately 60 patients will be recruited across Europe and the US. Disclosures Burke: Gilead: Consultancy; Roche/Genentech: Consultancy; Celgene: Consultancy. André:Celgene: Other: Travel grants, Research Funding; Chugai: Research Funding; Takeda Millenium: Research Funding; Johnson & Johnson: Research Funding; Amgen: Other: Travel grants, Research Funding; Roche: Other: Travel grants, Research Funding; Abbvie: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; Bristol-Myers-Squibb: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees, Other: Travel grants. Cheson:Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Research Funding; Acerta: Consultancy, Research Funding; Kite: Research Funding; Epizyme: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Symbios: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Trillium: Research Funding; TG Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Seattle Genetics: Research Funding; Bristol Myers Squibb: Research Funding; Portola: Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Duell:Regeneron Pharmaceuticals, Inc.: Research Funding. Nowakowski:Genentech, Inc.: Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding; MorphoSys: Consultancy, Research Funding; Curis: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding. Rosenwald:MorphoSys: Consultancy. Salles:Roche, Janssen, Gilead, Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; BMS: Honoraria; Novartis, Servier, AbbVie, Karyopharm, Kite, MorphoSys: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Autolus: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Epizyme: Consultancy, Honoraria; Amgen: Honoraria, Other: Educational events; Merck: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Sharman:Acerta: Consultancy, Honoraria, Research Funding; TG Therapeutics: Consultancy, Honoraria, Research Funding; Pharmacyclics LLC, an AbbVie Company: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria, Research Funding; Genentech: Consultancy, Honoraria, Research Funding; AstraZeneca: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Research Funding. Staber:Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Takeda-Millenium: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Honoraria, Speakers Bureau; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; MSD: Honoraria, Speakers Bureau; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Trněný:Abbvie: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Gilead Sciences: Consultancy, Honoraria; Incyte: Consultancy, Honoraria; MorphoSys: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; F. Hoffmann-La Roche: Consultancy, Honoraria; Celgene: Consultancy; Janssen: Consultancy, Honoraria. Westin:Novartis: Other: Advisory Board, Research Funding; Juno: Other: Advisory Board; Unum: Research Funding; Curis: Other: Advisory Board, Research Funding; Genentech: Other: Advisory Board, Research Funding; Kite: Other: Advisory Board, Research Funding; Celgene: Other: Advisory Board, Research Funding; 47 Inc: Research Funding; MorphoSys: Other: Advisory Board; Janssen: Other: Advisory Board, Research Funding. Brugger:MorphoSys: Employment; AstraZeneca: Equity Ownership. Fingerle-Rowson:MorphoSys AG: Employment. Klanova:MorphoSys AG: Employment. Würth:MorphoSys AG: Employment. Truemper:Janssen Oncology: Consultancy; Nordic Nanovector: Consultancy; Takeda: Consultancy, Research Funding; Seattle Genetics, Inc.: Research Funding; Roche: Research Funding; Mundipharma: Research Funding.

Abstract Introduction: Several prognostic models for overall survival (OS) in chronic lymphocytic leukemia (CLL) have been developed, but none were derived for patients (pts) with relapsed or refractory (R/R) CLL treated in the era of novel agents. We used a comprehensive approach to derive and validate a novel risk model for OS in 2,475 pts with R/R CLL who received therapy in randomized phase 3 trials evaluating ibrutinib (IBR), idelalisib (IDELA), and venetoclax (VEN) vs control arms, or the Mayo Clinic CLL Database (MCCD). Methods: In collaboration with Janssen, Gilead, Pharmacyclics, and Genentech/Roche, the analysis included 2,475 pts from 6 multicenter randomized phase 3 trials or the MCCD. Trials included were: IBR plus bendamustine-rituximab (BR) vs placebo plus BR (HELIOS: NCT01611090), IBR vs ofatumumab (RESONATE: NCT01578707), IDELA plus BR vs placebo plus BR (Study 115: NCT01569295); IDELA plus rituximab vs placebo plus rituximab (Study 116: NCT01539512); IDELA plus ofatumumab vs ofatumumab (Study 119: NCT01659021); VEN plus rituximab vs BR (MURANO: NCT02005471). All pts had R/R CLL and required treatment by iwCLL criteria. The model-building dataset (n=969) included pts from HELIOS and RESONATE, and was randomly assigned to the IBR/chemoimmunotherapy (CIT) training dataset (n=727) and IBR/CIT internal-validation dataset(n=242). Three independent external validation datasets included IDELA/CIT (n=897), VEN/CIT (n=389), and MCCD (n=220). We applied univariate and multivariate analyses (MVA) to 28 candidate clinical/laboratory and genetic prognostic factors to derive the risk model in the training dataset. The primary endpoint was OS. We assessed the need for separate models for targeted agents by interactions with treatment in univariate analyses. We proceeded to develop a single model for all pts with R/R CLL, as only one candidate factor (del(13q), interaction p value <0.1) demonstrated a marginal differential effect. We evaluated cutoffs for dichotomized covariates and for definition of risk groups after the final factors were selected. We fit a Cox regression on the training and internal/external validation datasets using the risk categories as the covariate to test the difference among the groups, and calculated the C-statistic as a measure of discrimination. Results: Of 11 selected factors with a significant univariate effect on OS (p<0.1), 6 were independently prognostic in the MVA of OS (p<0.05): Baseline β2-microglobubulin (B2M), lactate dehydrogenase (LDH), hemoglobin (HGB), IGHV mutational status, number of prior therapies, and time from initiation of last therapy. We excluded number of prior therapies from the model, reasoning that its optimal cutoff might change with advances in CLL therapies. IGHV did not remain significant (p=0.0592) in MVA of 5 remaining prognostic factors. Notably, del(17p) was not independently prognostic for OS. The final risk model consisted of 4 prognostic factors: B2M ≥5 mg/L, LDH elevated, HGB <110 mg/L for women or <120 mg/L for men, and time from initiation of last therapy <24 months. Because hazard ratios for each factor were similar (range, 0.55-0.68) with overlapping confidence intervals, 1 point was assigned to each factor. The resulting score separated pts into low (score 0-1), intermediate (score 2-3), and high risk (score 4) groups. Our risk model was prognostic for OS in the IBR/CIT training dataset (C-statistic 0.74 [95% CI 0.60-0.85]; log-rank p<0.0001) and was validated in the IBR/CIT internal validation (C-statistic 0.79 [95% CI 0.56-0.97]; log-rank p<0.0001), as well as in all 3 external validations: IDELA/CIT dataset (CS=0.71, 95% CI 0.59-0.81; log-rank p<0.001); VEN/CIT dataset (CS=0.76, 95% CI 0.66-0.85; log-rank p=0.01); MCCD (CS=0.61, 95% CI 0.56-0.66; log-rank p<0.001). Conclusions: We present the first validated risk model for OS in R/R CLL in the era of targeted therapies. Our model consists of 4 readily available factors (B2M ≥5 mg/L, LDH elevated, HGB <110 mg/L for women or <120 mg/L for men, and time from initiation of last therapy <24 months), identifies 3 prognostic groups with significantly different OS, and has been validated for pts treated with all FDA approved targeted therapies: IBR, IDELA, and VEN. This identifies a well-defined cohort of pts with R/R disease with an unmet clinical need who are suitable for prospective trials targeting these pts. An exploratory analysis regarding prediction of MRD is ongoing. Figure. Figure. Disclosures Darif: Jannsen: Employment. Londhe:Jannsen: Employment. Xing:Gilead Sciences, Inc.: Employment. Mun:Genentech: Employment, Equity Ownership. Kay:Cytomx Therapeutics: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Infinity Pharm: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Acerta: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees. Shanafelt:Mayo Clinic: Patents & Royalties: Physician Well-being Index, Medical Student Well-being Index, Well-being index; GlaxoSmithKline: Research Funding; Genentech: Research Funding; Pharmacyclics: Research Funding; Janssen: Research Funding; Abbvie: Research Funding; Celgene: Research Funding. Furman:Loxo Oncology: Consultancy; Pharmacyclics LLC, an AbbVie Company: Consultancy; Sunesis: Consultancy; TG Therapeutics: Consultancy; Verastem: Consultancy; Gilead: Consultancy; Incyte: Consultancy, Other: DSMB; Acerta: Consultancy, Research Funding; Genentech: Consultancy; Janssen: Consultancy; AbbVie: Consultancy. Hillmen:Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Pharmacyclics: Research Funding; Alexion Pharmaceuticals, Inc: Consultancy, Honoraria; Novartis: Research Funding; Gilead Sciences, Inc.: Honoraria, Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Acerta: Membership on an entity's Board of Directors or advisory committees. Sharman:Acerta: Consultancy, Research Funding; Pharmacyclics, an AbbVie Company: Consultancy, Research Funding. Seymour:AbbVie: Consultancy, Honoraria, Research Funding; Celgene: Consultancy; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Genentech Inc: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Research Funding. Jones:Celgene: Employment, Equity Ownership. Ferrante:Jannsen: Employment. Dreiling:Gilead: Employment. Mobasher:F. Hoffmann-La Roche Ltd: Other: Ownership interests non-PLC; Genentech Inc: Employment. Stark:Genentech: Employment. Reddy:Actinium Pharmaceuticals: Employment, Equity Ownership; Pharmacyclics: Employment. Howes:Janssen: Employment. James:Pharmacyclics: Employment. Bhargava:Gilead: Employment. Zelenetz:Novartis/Sandoz: Consultancy; Abbvie: Research Funding; Celgene: Consultancy; Amgen: Consultancy; Gilead: Consultancy, Research Funding; AstraZeneca: Consultancy; Genentech/Roche: 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.