Citations

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 BACKGROUND Treatment options and prognosis are limited for patients with high grade glioma (pwHGG), underscoring the importance of patient and caregiver understanding to prioritize goals of care and quality of life (QOL). Although addressed by multiple providers, patients and caregivers may experience discordance in understanding the prognosis. This may be related to patient/caregiver perception, cognitive decline as a result of the tumor and/or treatment, or failure by the clinician to clearly articulate this information under emotional circumstances. AIMS: To evaluate the longitudinal perception of prognosis of patients compared to their caregivers and their providers during the adjuvant treatment of newly diagnosed HGG. METHODS After IRB approval, 16 pwHGG, their caregivers and their providers reported an overall survival estimate at each monthly visit during adjuvant treatment, as part of a larger survey. Options included “weeks,” “weeks to several months,” “several months to years,” “indefinite number of years”, or “I do not wish to answer.” RESULTS Seven of the sixteen patient/caregiver clusters have completed the appropriate duration of the study with the remaining completing in November. The perception of the patient differs from the caregiver at almost each visit. Regardless of the counseling provided by provider, the perception of both tends to change at each visit and can vary from dismal to overtly optimistic. There does not appear to be discrepancy between the neuro-oncology and palliative care provider’s perception of prognosis. CONCLUSION Newly diagnosed pwHGG and caregivers vary in their perception of prognosis, deviating not only from each other but also differing at each visit throughout the course of their illness. The providers’ perception appeared to remain consistent but often varied from that of the patient and caregiver. Providers need to be aware that prognostic understanding appears to fluctuate throughout the course of illness and cannot be clarified via a single discussion.

Abstract BACKGROUND Early involvement of palliative care (PC) in patients with metastatic cancer has been associated with improved quality of life (QOL). Patients with high grade glioma (pwHGG) and their caregivers have unique needs such that similar results are anticipated in this population but cannot be extrapolated. Recognizing that pwHGG often require a caregiver early in the course of disease, this patient population also experiences significant personal and caregiver distress that has been given limited attention and resources. AIM: To assess the feasibility of implementation of a novel patient reported outcomes (PRO) quality of life (QOL) tool administered by smart device in routine office visit (OV) and early integration of palliative care (PC) for pwHGG and their caregivers to improve QOL for both. DESIGN: Prospective, single-center cluster-randomized pilot conducted for 6 months during completion of adjuvant therapy for newly diagnosed high grade glioma. After informed consent was obtained, 15 pwHGG and their caregivers were randomized to: routine OV with basic QOL survey; OV with PROQOL; or PC consultation, in addition to OV with PROQOL. RESULTS Two elderly patients with declining performance status transitioned to hospice after initial visit, and one moved out of state prior to adjuvant visits. Thus far 5/15 patients/caregivers have successfully completed the pilot with the 6 remaining participants due to complete in November 2019. DISCUSSION The PROQOL appears to be easily integrated into OV without significant patient, caregiver, or provider burden. Providers confirmed utility in prioritizing symptoms and concerns. Thus far, it appears that patients (and caregivers) appeared to benefit from the PROQOL and PC support as evidenced by longitudinal improvement in QOL scores over the control group. CONCLUSIONS A unique PROQOL tool and early PC can be easily integrated into practice, and may improve the QOL of pwHGG and their caregivers.

Abstract BACKGROUND Conventional magnetic resonance imaging (MR) guides patient care in GBM. However, there is mounting awareness that MR enhancement is non-specific reflecting either tumor progression or non-tumoral inflammatory changes. Histological evaluation of GBM is held as the gold standard for disease assessment. However, the invasiveness of this methodology and the sample sparsity limit its usefulness. Methods to infer histological underpinnings of MRI are needed to improve clinical care. METHODS A transfer learning mixed effects model based on T1Gd and FLAIR MR voxel based image features trained and cross-validated to predict FPKM values of CD68, CASP3, CD8A and IL13RA2. Training data included RNAseq from 38 image-localized biopsies from 15 newly-diagnosed GBM patients. These models were then applied to two independent patients, chosen based on therapy and the quality of image registration, at three different time points, just prior to receiving IL13RA2 targeted CAR-T therapy for rGBM, after 2 cycles and after 4 cycles, resulting in a voxel-based prediction of the relative expression levels of these genes. RESULTS Cross-validation of the proposed machine learning models demonstrated a Pearson Correlation coefficient between predicted and observed FPKM values of 0.89 (CD68), 0.92 (CASP3), 0.93 (CD8A), and 0.88 (IL13RA2). When the models were applied to the two CAR-T patients, CD68-modeled expression levels were seen to increase throughout therapy for one patient, while remaining stable for the other. Survival from first CAR-T infusion was, respectively, 412 and 83 days suggesting that the increased CD68 was indicative of therapeutic effectivity. Further, the spatial activity predictions were consistent with expected therapeutic action as the correlation coefficient between CASP3 and the product of IL13R2 and CD8A expression was 0.81, suggesting the T-cells targeting IL13RA2 were inducing cell death. CONCLUSIONS Preliminary results with our model highlights the potential of spatially resolved radiomic maps to provide insight into regional therapeutic effectivity.

Abstract INTRODUCTION The impact of treatment on both the quality and the quantity of life, i.e. the ‘net clinical benefit’, should be considered to facilitate shared decision making. Two methods that combine survival and health-related quality of life (HRQoL) data: Quality Adjusted Effect Sizes (QASES) and Joint Modelling (JM) were applied to gain insight in the net clinical benefit. METHODS The net clinical benefit in one RCT (EORTC 26951 comparing radiotherapy (RT) + PCV chemotherapy versus RT alone) was calculated as a proof of concept for other trials. With the QASES method, effect sizes for differences in survival and HRQoL between treatment arms were calculated. JM allows simultaneous modeling of a longitudinal outcome (HRQoL), and a time-to event outcome (survival). HRQoL scales/items that were selected for primary analysis in the main study were also selected for this analysis: fatigue, global health, social functioning, communication deficit, seizures, physical functioning, and nausea/vomiting. RESULTS 288/386 patients completed baseline HRQoL forms and were included in the analysis. Overall survival (OS) was significantly longer with combined treatment (42.3 vs. 30.6 months). The percentage of patients who experienced a clinically relevant deterioration (≥10 points) in nausea/vomiting, fatigue, social functioning and global health up to one year after treatment compared to baseline was larger in the RT+PCV arm. QASES corresponded to a reduction in the median OS difference from 9.7 months up till 5.5 months, given equal weights to OS and HRQoL. JM analyses resulted in a theoretical loss of treatment effect in OS of 2–6% when adjusting for HRQoL. CONCLUSION Both methods showed that adjusting for the impact of treatment on a relevant HRQoL parameter reduced the survival benefit in the experimental treatment arm compared to standard treatment arm. Applying these methods may facilitate communicating the impact of treatment to patients in clinical practice.

Abstract Background Cardiovascular implantable electronic device (CIED) infections are associated with significant morbidity, mortality, and cost. There is limited evidence on antibiotic prophylactic strategies to prevent CIED infection. Recently, the TYRX Envelope, which elutes a combination of rifampin and minocycline for a minimum of 7 days, was shown to significantly reduce major CIED infections in the WRAP-IT trial. We sought to characterize the pathogens among patients who experienced an infection in the current era. Methods All patients undergoing CIED replacement, upgrade, revision, or de novo cardiac resynchronization therapy (CRT-D) received standard of care antibiotic prophylaxis and were randomized 1:1 to receive TYRX or not. The primary endpoint was major CIED infection within 12 months of the procedure. Major infection was defined as an infection resulting in (1) system extraction or revision, (2) long-term suppressive antibiotic therapy, or (3) death. Data were analyzed using the Cox proportional hazards regression model. Results A total of 6,983 patients were randomized worldwide with 3,495 randomized to receive an envelope and 3,488 randomized to the control. At 12 months, 25 major infections (0.7%) were observed in the envelope group and 42 major infections (1.2%) in the control group, resulting in a 40% reduction of major infections (HR: 0.60, 95% CI: 0.36–0.98, P = 0.04). Of 63 infections assayed, causative pathogens were identified in 36 infections whereas cultures were negative in 27 cases. Staphylococcus species (n = 22) were the predominate pathogens and a 53% reduction was observed with the use of TYRX (Figure 1). Moreover, there was only 1 CIED pocket infection with Staphylococcus species in the envelope group compared with 14 pocket infections in the control group. A comparison of timing of infection in the envelope group showed the presence of 11 endocarditis/bacteremia infections at 103 ± 84 days compared with 14 pocket infections presenting at 70 ± 78 days from the procedure. Conclusion In this large randomized trial, the use of the TYRX Envelope containing rifampin and minocycline resulted in a significant reduction of major CIED infections and was effective against staphylococcal species, which are the predominant cause of pocket infections. Disclosures All Authors: No reported Disclosures.

Abstract Background: Modern clinical practice places time restrictions on the amount of information and processing that can be done in a typical office visit. Meeting patient needs within the healthcare system is challenging, contributing to patient (pt) and clinician dissatisfaction and potential suboptimal outcomes. We developed an electronic point-of-care case management system for cancer patients. The system's goal is to obtain patient-reported quality of life (PROQOL) outcomes and provide clinicians with information regarding QOL issues to address. We tested this system in a prospective randomized study against usual care (UC). The primary objective was to determine if PROQOL system would improve mean QOL over time. Methods: Eligible pts were adults with multiple myeloma (MM) or light amyloidosis (AL), seen at Mayo Clinic. Pts were randomized 2:1 to PROQOL system or usual care. PROQOL system was offered prior to every visit. Pts select from various categories about their single biggest concern, and receive a printed list of actionable resources based on selected concern. Clinicians also receive the PROQOL results to review with pts. Providers and pts randomized to PROQOL completed a "was it worth it survey" (WIWI). An 8 item Linear Analogue Self-Assessment was used to assess QOL, the primary endpoint. Secondary endpoints included distribution of choices of most important concern and their relationship to demographic and clinical variables. The study was powered to detect a 0.5 standard deviation difference in QOL between groups. Results: There were 233 patients enrolled (171 MM, 62 AL) in this study between July 1, 2016 and April 17, 2018. Median age was 65 years (range 31-87), and 59% were male. Median time from diagnosis to study consent was 37 months (PROQOL 36.3 versus UC 39.6). Median follow up for all patients was 15 months (range: 0.7-22 months), and median follow up for PROQOL pts was 16 months and 14 months for UC pts (p=0.027). There were 25 pts that have died since enrollment and 208 alive. No statistical significant difference in QOL between PROQOL and UC (median QOL 7 vs 7, p=0.75). The most prevalent main concerns selected were Physical Health (37%) and Cancer and Diagnosis (27%), the pattern remained even when pts were given the option to pick a second major concern 26% and 20% respectively. No other concern was listed more than 8% at baseline. All category selections and percentages are shown in the Figure. The average time to complete the instrument was 6 minutes. Pts found the PROQOL system was worth their time (75%), they would choose it again (87%) and recommend it to others (82%). Eighty-two percent of clinicians did not think the PROQOL tool negatively impacted their practice and 75% believed they may see improvement in pt wellbeing. Discussion: The PROQOL system was well received by pts and clinicians but did not improve QOL relative to UC in this study. The PROQOL demonstrates that majority of patients strongly desire more information regarding ongoing therapy, clinical trials, prognosis and toxicity. Further investigation is needed to understand whether communication is limited by time or mechanism of information delivery, such as verbal or written, or whether it should be undertaken in a separate allied health care visit. Figure. Figure. Disclosures Gertz: spectrum: Consultancy, Honoraria; Abbvie: Consultancy; Research to Practice: Consultancy; annexon: Consultancy; Medscape: Consultancy; Physicians Education Resource: Consultancy; Amgen: Consultancy; janssen: Consultancy; Alnylam: Honoraria; Teva: Consultancy; Apellis: Consultancy; Ionis: Honoraria; celgene: Consultancy; Prothena: Honoraria. Kumar:Novartis: Research Funding; Celgene: 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; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; KITE: 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, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding. Dingli:Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.; Millennium Takeda: Research Funding; Millennium Takeda: Research Funding; Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.. Lacy:Celgene: Research Funding. Dispenzieri:Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding.