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Background: Cerebrovascular disease is often the consequence of cardiac disease. Our aim was to examine associations of biomarkers of cardiovascular disease, high sensitivity troponin T (hs-cTnT), NT-proBNP, and galectin-3, with cerebrovascular signs: lacunar infarcts, lobar and subcortical microhemorrhages, cortical infarcts, and white matter hyperintensity (WMH) volume. We also examined total cortical and Alzheimer’s Disease (AD) signature region volumes. Methods: We conducted a cross-sectional analysis of 1748 ARIC participants from the 2011-2013 exam who had biomarker measurements, completed a brain MRI, and did not have a clinical history of stroke. We used linear regression to model brain volumes, modeled as Z scores, and logistic regression for all other outcomes; biomarkers were log transformed. We repeated analyses excluding persons with coronary heart disease, atrial fibrillation, and heart failure. Results: The mean age of participants was 76, 62% were female, and 21% were Black. All biomarkers were associated with total cortical volume. Each standard deviation increase in log hs-cTnT was associated with lower total cortical volume (adjusted beta = -0.08, 95% CI: -0.12, -0.05); results for the other biomarkers were similar (Figure). All biomarkers were associated with lobar microhemorrhages. Hs-cTnT and NT-proBNP were associated with WMH volume, but galectin-3 was not. No biomarker was associated with subcortical microhemorrhages or cortical infarcts. Results were similar in persons without coronary heart disease, atrial fibrillation, or heart failure (conditions associated with cerebral thromboembolism). Conclusions: In persons free of clinical cardiovascular disease, biomarkers of cardiac stretch, strain, and fibrosis were associated cerebral small vessel disease and reduced cortical volume, but not in a specific pattern suggestive of AD pathogenesis. This suggests subclinical vascular insults affect brain structure through mixed pathogenic processes.

AbstractPurposeThe purpose of this analysis was to determine the cost‐effectiveness of a Collaborative Care Model (CCM)‐based, centralized telecare approach to delivering rehabilitation services to late‐stage cancer patients experiencing functional limitations.MethodsData for this analysis came from the Collaborative Care to Preserve Performance in Cancer (COPE) trial, a randomized control trial of 516 patients assigned to: (a) a control group (arm A), (b) tele‐rehabilitation (arm B), and (c) tele‐rehabilitation plus pharmacological pain management (arm C). Patient quality of life was measured using the EQ‐5D‐3L at baseline, 3‐month, and 6‐month follow‐up. Direct intervention costs were measured from the experience of the trial. Participants’ hospitalization data were obtained from their medical records, and costs associated with these encounters were estimated from unit cost data and hospital‐associated utilization information found in the literature. A secondary analysis of total utilization costs was conducted for the subset of COPE trial patients for whom comprehensive cost capture was possible.ResultsIn the intervention‐only model, tele‐rehabilitation (arm B) was found to be the dominant strategy, with an incremental cost‐effectiveness ratio (ICER) of $15 494/QALY. At the $100 000 willingness‐to‐pay threshold, this tele‐rehabilitation was the cost‐effective strategy in 95.4% of simulations. It was found to be cost saving compared to enhanced usual care once the downstream hospitalization costs were taken into account. In the total cost analysis, total inpatient hospitalization costs were significantly lower in both tele‐rehabilitation (arm B) and tele‐rehabilitation plus pain management (arm C) compared to control (arm A), (P = .048).ConclusionThe delivery of a CCM‐based, centralized tele‐rehabilitation intervention to patients with advanced stage cancer is highly cost‐effective. Clinicians and care teams working with this vulnerable population should consider incorporating such interventions into their patient care plans.

Abstract Purpose: Genomic alterations in DNA damage repair (DDR) genes other than BRCA may confer synthetic lethality with PARP inhibition in metastatic castration-resistant prostate cancer (mCRPC). To test this hypothesis, the phase II TRITON2 study of rucaparib included patients with mCRPC and deleterious non-BRCA DDR gene alterations. Patients and Methods: TRITON2 enrolled patients who had progressed on one or two lines of next-generation androgen receptor–directed therapy and one taxane-based chemotherapy for mCRPC. Key endpoints were investigator-assessed radiographic response per modified RECIST/PCWG3 and PSA response (≥50% decrease from baseline). Results: TRITON2 enrolled 78 patients with a non-BRCA DDR gene alteration [ATM (n = 49), CDK12 (n = 15), CHEK2 (n = 12), and other DDR genes (n = 14)]. Among patients evaluable for each endpoint, radiographic and PSA responses were observed in a limited number of patients with an alteration in ATM [2/19 (10.5%) and 2/49 (4.1%), respectively], CDK12 [0/10 (0%) and 1/15 (6.7%), respectively], or CHEK2 [1/9 (11.1%) and 2/12 (16.7%), respectively], including no radiographic or PSA responses in 11 patients with confirmed biallelic ATM loss or 11 patients with ATM germline mutations. Responses were observed in patients with alterations in the DDR genes PALB2, FANCA, BRIP1, and RAD51B. Conclusions: In this prospective, genomics-driven study of rucaparib in mCRPC, we found limited radiographic/PSA responses to PARP inhibition in men with alterations in ATM, CDK12, or CHEK2. However, patients with alterations in other DDR-associated genes (e.g., PALB2) may benefit from PARP inhibition. See related commentary by Sokolova et al., p. 2439

178 Background: The phase 2 TRITON2 study (NCT02952534) is evaluating the PARP inhibitor rucaparib in pts with mCRPC and a deleterious germline or somatic alteration in BRCA ( BRCA pts) or 1 of 13 other DNA damage repair (DDR) genes. Methods: Eligible pts had progressed on 1–2 lines of androgen receptor-directed therapy and 1 taxane-based chemotherapy. Deleterious DDR gene alterations were identified from central testing of plasma and/or tissue samples by Foundation Medicine or from local testing. Results: As of Jul 2, 2019 (visit cutoff), 98 BRCA pts had received rucaparib; median (range) duration of follow-up was 13.0 (4.1–25.8) mo. Confirmed objective response rate (ORR) in BRCA pts (with investigator-assessed measurable disease) and PSA response rates (in pts with and without measurable disease) are shown in the Table. A biallelic alteration was observed in 81.4% (35/43) of BRCA pts for whom zygosity could be determined, and pts with homozygous BRCA loss (20.4%; 20/98) demonstrated high ORR (66.7% [95% CI, 38.4-88.2]; 10/15) and PSA response rates (75.0% [95% CI, 50.9-91.3]; 15/20). The safety profile in BRCA pts was consistent with the overall TRITON2 pt population. Conclusions: Results from TRITON2 showed antitumor activity with rucaparib in pts with mCRPC and a deleterious BRCA alteration. Responses were observed in patients with germline or somatic alterations in BRCA1 or BRCA2. The activity of rucaparib in these and additional genomic subgroups (e.g., based on zygosity, plasma genomic testing, or co-occurring alterations) will be reported. Clinical trial information: NCT02952534. [Table: see text]

Introduction: With the expanding use of CAR-T cell therapy, which is associated with serious adverse effects (AEs), there is a need to characterize the patient's experience over time to guide patient/provider education, and help optimize symptom management. This study reports on longitudinal evaluation of patient-reported quality of life (QOL) and symptom burden of CAR-T cell therapy compared with established forms of cellular therapy i.e autologous stem cell transplant (autoSCT) and allogeneic SCT (alloSCT). Methods: Patients with hematologic malignancies were prospectively recruited in three cohorts: CAR-T, autoSCT and alloSCT. The primary endpoint was change in QOL from baseline, using the FACT-G questionnaire. Secondary endpoints were patient-reported AEs (PRO-AEs) using 7 items from the PRO-CTCAE and assessment of cognition/memory using the NeuroQOLv2 questionnaire. PRO-CTCAE data was graded using a composite score (combining frequency, severity, and interference) and rates, using a method adjusting for pre-existing baseline symptoms, were compared using Fisher's exact test. We also evaluated the time profile of PRO-AEs using the Toxicity over Time (ToxT) approach, a longitudinal approach to AE analysis (Thanarajasingam Lancet Onc 2016). Patients completed questionnaires at baseline, week 2 and monthly thereafter. Results: From 07/2018 to 06/2019, 93 patients were recruited (CAR-T: 20; autoSCT: 37; alloSCT: 36). At data cut-off, week 2 and months 1, 2 and 3 data were available in 74, 62, 46 and 35 patients, respectively. There was no difference in patient age across the 3 groups (median age 63, range 23-77; p=0.26). Baseline QOL by FACT-G total score (mean=83.4, SD=14.7; p=0.77), side effect bother by FACT-G GP5 (66/93 [71%] a little bit or less; p=0.72), activities and function (70/93 [75%] fairly normal activities or no limitations; p=0.68) and cognition by NeuroQOL t-score (mean=52.2, SD=8.13; p=0.39) were similar across 3 groups at baseline. The CAR-T group experienced significantly less worsening in QOL (FACT-G) than both autoSCT and alloSCT groups (Fig. 1a). Worsening in overall QOL nadired at week 2, after which QOL gradually returned to baseline in all groups. When comparing changes from baseline in overall QOL, statistically significant differences between groups were evident at week 2 (CAR-T vs autoSCT p<0.001; vs alloSCT p<0.001), month 1 (CAR-T vs autoSCT p=0.02; vs alloSCT p=0.003), month 2 (CAR-T vs autoSCT p=0.02; vs alloSCT p=0.001) and month 3 (CAR-T vs autoSCT p=NS; vs alloSCT p=0.03). Results for physical (Fig. 1b) and functional well-being (WB) were similar, with significantly less QOL worsening at week 2 in CAR-T vs autoSCT and alloSCT groups. The most common PRO-AEs (Table 1) in the CAR-T group were decreased appetite (59%), diarrhea (53%) and fatigue (44%). There was no statistically significant difference in the PRO-AEs between CAR-T and autoSCT groups. However, patients undergoing alloSCT had significantly higher proportion of PRO-AEs vs the CAR-T group, except for neuropathy and sad feelings. AutoSCT and alloSCT groups had significant worsening of FACT-G side effect bother (GP5) at week 2, which was significantly different from that of the CAR-T group, following which the side effect bother gradually returned to baseline. (Fig. 1c) This was the first application of ToxT to PRO-CTCAE data (graphs not shown). Bar charts of maximum grade frequency and stream plots of mean grade over time demonstrate that mouth sores, fatigue, diarrhea and decreased appetite peak at week 2 and improve by month 3, and are of lesser severity in the CAR-T vs autoSCT and alloSCT groups. The trajectory of maximum grade across all PRO-AEs was similar by group as overall side effect burden by FACT-G GP5. Heatmap visualization demonstrated significant intra-patient variability and allowed inspection of data completeness. No difference in cognition and memory was observed across the three groups over the first three months. (Fig. 1d) Conclusion: This study is the first to our knowledge to provide comprehensive PRO data comparing QOL, patient-reported AEs and cognition in CAR-T cell therapy vs. auto- and alloSCT, and the first application of ToxT to PRO-CTCAE data. Short-term QOL, including physical and functional WB domains was better in the CAR-T group vs. SCT groups. These data can serve as a guide for patient education and symptom management in CAR-T cell therapy. Co-senior authors: SKK & ACD Disclosures Paludo: Celgene: Research Funding; Celgene: Research Funding; Verily Life Sciences: Research Funding; Verily Life Sciences: Research Funding. Gertz:Johnson and Johnson: Speakers Bureau; Celgene: Consultancy; Appellis: Consultancy; Amyloidosis Foundation: Research Funding; DAVA oncology: Speakers Bureau; Physicians Education Resource: Consultancy; Amgen: Consultancy; Janssen: Consultancy; Abbvie: Other: personal fees for Data Safety Monitoring board; Medscape: Consultancy, Speakers Bureau; Prothena Biosciences Inc: Consultancy; Teva: Speakers Bureau; Research to Practice: Consultancy; Annexon: Consultancy; Alnylam: Consultancy; International Waldenstrom Foundation: Research Funding; Ionis/Akcea: Consultancy; Spectrum: Consultancy, Research Funding; i3Health: Other: Development of educational programs and materials; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Proclara: Membership on an entity's Board of Directors or advisory committees; Springer Publishing: Patents & Royalties. Dispenzieri:Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Alnylam: Research Funding. Ansell:Trillium: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding. Bennani:Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Adicet Bio: Other: Advisory board; Adicet Bio: Other: Advisory board; Purdue Pharma: Other: Advisory board; Purdue Pharma: Other: Advisory board; Seattle Genetics: Other: Advisory board; Seattle Genetics: Other: Advisory board; Seattle Genetics: Other: Advisory board; Kite Pharma: Other: Advisory board; Adicet Bio: Other: Advisory board; Kite Pharma: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Kite Pharma: Other: Advisory board; Purdue Pharma: Other: Advisory board. Kumar:Takeda: Research Funding; Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding.

Targeted agents have greatly improved outcomes for patients (pts) with chronic lymphocytic leukemia (CLL) and other B cell lymphomas; however, single agents have been limited by intolerance, resistance and depth/durability of responses. Current novel targeted agent combinations may improve depth of response, but such "full dose" strategies have been associated with significant AEs, dose reductions/interruptions and discontinuations. Our in vitro & in vivo screening/optimization studies identified that concurrent inhibition of BTK & mTOR targets plus IMiD at low doses of each inhibitor can synergistically kill B-cell malignancies and may address drug-resistance. DTRM-555 is an optimized oral triplet combination of a novel BTK inhibitor DTRMWXHS-12 (DTRM-12) with everolimus (EV) & pomalidomide (POM). This once daily therapy was tested in a stepwise, phase I, US multicenter study in patients with highest unmet medical needs including r/r CLL, Richter's transformation (RT) of CLL, DLBCL, transformed B-cell lymphomas. We conducted a 3+3 design phase I, first human trial exploring DTRM-555 in pts ≥18 years, ECOG PS ≤1 with CLL, B-cell NHL, or Hodgkin lymphoma (HL) with no available standard therapy (NCT02900716). Our goal was to determine optimal doses for triplet combination therapy through 3 escalating phases of study: DTRM-12 in escalating doses (50, 100, 200, & 300 mg/day) in Part Ia, DTRM-12 at 200 mg or 300 mg & EV at 5 mg (doublet or DTRM-505) in Part Ib Arm A while DTRM-12 at 200 mg or 300 mg, EV at 5 mg & POM at 2 mg in Part Ib Arm B. For all arms, treatment was administered for 21 consecutive days of a 28-day cycle, until disease progression or unacceptable toxicity. Safety was the primary endpoint, and the dose-limiting toxicity (DLT) period was cycle 1. Secondary endpoints included response (iwCLL 2018 or Cheson 2014), progression free survival, duration of response and pharmacokinetics. Intra-patient migration between arms (Mono to doublet to triplet) was permitted if subsequent doses were tolerated. The trial commenced 9/27/2016 and completed enrollment 7/25/2019. Thirty-three pts were enrolled, including 2 screen failures and 4 intra-cohort migrations, with r/r DLBCL (n=8), CLL/SLL (n=5), RT (n=6), FL (n=5), MCL (n=4), MZL/LPL (n=3), HL (n=2). 30 of 31 treated pts were evaluated: 8 pts participated in phase Ia (DTRM-12) while 23 pts were treated on phase Ib combinations (DTRM-505 & DTRM-555). Baseline characteristics: 70% male (n=23), median age 70 years (range 46-94) and 94% white. Median prior therapies were 3 (range 1-10), 53% had been treated with ≥1 prior targeted agent (i.e., CD19/CD3 bispecific antibody, obtinutuzumab, pembrolizumab, nivolumab, ibrutinib, venetoclax, PI3k-i), CAR-T or HSCT. 35% pts were previously treated with ibrutinib. Table 1 describes Grade (Gr) 3 and 4 AEs (all causality, stratified by treatment arm). Regarding safety, AEs were manageable, with a total of 5 DLTs were observed: 2 (Gr 3 febrile neutropenia, URI) in part Ib arm A, 3 (Gr 4 thrombocytopenia, Gr 3 diarrhea, G3 febrile neutropenia) in Part Ib arm B. No MTD was reached for the mono & doublet arms, with the MTD of the triplet determined to be DTRM-12 200 mg, EV 5 mg, & POM 2 mg. Spider plot (Figure 1a) shows the clinical response for individual CLL and lymphoma pts treated with mono, doublet and triplet therapies. Depth and durability of response improved with combination therapies (vs. mono). Of note, 48% of all patients had a ≥50% reduction in sum of the products of lymph node diameters. Representative PET-CT scans are in Figure 1b-c. Responses in multi-refractory pts are ongoing (including 15+ mos in a pt with r/r DLBCL and 5+ mos PR in a pt aged > 90 yrs with r/r DLBCL; 4+ & 13+ mos PRs in two pts with RT). DTRM-12 plasma concentrations were unaffected by EV & POM (Once Daily Oral Therapies) in Figure 1d. The clinical trial met its primary endpoint as the triple combination DTRM-555 had an acceptable safety profile. Dose dependent drug levels with minimal inter-pt variations were observed in all arms, supporting once daily oral administration of this low-dose combination therapy. Encouraging clinical activity was observed in several high-risk, multi-refractory CLL and lymphoma pts, including those previously treated with ibrutinib. Thus synthetic lethality is a viable treatment approach. A phase II US expansion study is underway targeting pts with transformed lymphomas (follicular or prior CLL) and r/r DLBCL cohorts. Table 1. Disclosures Mato: AbbVie: Consultancy, Research Funding; Sunesis: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; Johnson & Johnson: Consultancy, Research Funding; Celgene: Consultancy; AstraZeneca: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; Gilead: Research Funding; Acerta: Consultancy; Janssen: Consultancy; TG Therapeutics: Consultancy, Other: DSMB member , Research Funding; LOXO: Consultancy, Research Funding; DTRM Biopharma: Research Funding. Schuster:DTRM Biopharma: Research Funding. Foss:Mallinckrodt: Consultancy; Acrotech: Consultancy; miRagen: Consultancy; Seattle Genetics: Consultancy, Other: fees for non-CME/CE services ; Eisai: Consultancy; Spectrum: Other: fees for non-CME/CE services . Isufi:Novartis: Consultancy; Astra Zeneca: Consultancy; Celgene: Consultancy. Ding:Merck: Research Funding; DTRM Biopharma: Research Funding. Brander:Novartis: Consultancy; MEI: Research Funding; Pharmacyclics LLC, an AbbVie Company: Consultancy; BeiGene: Research Funding; AstraZeneca: Consultancy, Research Funding; Acerta: Research Funding; Tolero: Research Funding; AbbVie: Consultancy, Honoraria, Research Funding; Genentech: Consultancy, Honoraria, Research Funding; Teva: Consultancy, Honoraria; TG Therapeutics: Consultancy, Honoraria, Research Funding; DTRM Biopharma: Research Funding. Tun:Mundi-pharma: Research Funding; TG Therapeutics: Research Funding; Curis: Research Funding; DTRM Biopharma: Research Funding; Celgene: Research Funding; BMS: Research Funding. He:DTRM Biopharma: Employment, Equity Ownership. Kearney:DTRM Biopharma: Employment, Equity Ownership. Gui:DTRM Biopharma: Employment, Equity Ownership. Anderson:Theradex: Employment. Roeker:AbbVie: Equity Ownership; Abbott Laboratories: Equity Ownership. Huntington:Bayer: Consultancy, Honoraria; AbbVie: Consultancy; Celgene: Consultancy, Research Funding; Genentech: Consultancy; Pharmacyclics: Honoraria; DTRM Biopharm: Research Funding. OffLabel Disclosure: Everolimus in B cell lymphomas and CLL Pomalidomide in B cell lymphomas and CLL

Background Artificial Intelligent Virtual Assistants (AIVA) is a segment of artificial intelligence that is rapidly developing. However, its utilization to address patients' frequently asked questions remains unexplored. Methods We developed an AIVA to answer questions related to 10 frequent topics asked by plastic surgery patients in our institution. Between July 27, 2018, and August 10 of 2018, we recruited subjects with administrative positions at our health care institution to chat with the virtual assistant. They asked, with their own words, 1 question for each topic and filled out a satisfaction questionnaire. Postsurvey analysis of questions and answers allowed assessment of the virtual assistant's accuracy. Results Thirty participants completed the survey. The majority was female (70%), and the mean age was 27.76 years (SD, 8.68 [19–51] years). The overall accuracy of the plastic surgery AIVA was 92.3% (277/294 questions), and participants considered the answer correct in 83.3% of the time (250/294 answers). Most of the participants considered the AIVA easy to use, answered adequately, and could be helpful for patients. However, when asked if this technology could replace a human assistant, they stayed neutral.