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Background: The rapid reduction in tumor burden by the oral B-cell lymphoma-2 inhibitor venetoclax (Ven) poses a risk of tumor lysis syndrome (TLS) for patients (pts) with chronic lymphocytic leukemia (CLL). The approved 5-week Ven dose ramp-up, along with prophylaxis and monitoring, effectively mitigate this risk of TLS but also introduce some logistical challenges to starting the drug. Moreover, the long ramp-up period may lead to clinical deterioration while pts are receiving lower doses, particularly for those with rapid disease progression after B-cell receptor pathway inhibitor (BCRi) therapy. Accelerated Ven dose ramp-up has been explored in a limited number of prior studies, including the prospective M14-032 trial (Jones et al. Lancet Oncol 2018) and a single-center retrospective study (Koenig et al. ASH 2019); these studies had conflicting results with regard to the risk of TLS. We conducted a multicenter study to systematically characterize the safety profile and feasibility of an accelerated Ven ramp-up schedule in pts with previously treated CLL. Methods: This is a retrospective chart review from 4 large academic US medical centers of 36 pts with relapsed/refractory CLL and a documented ramp-up period of <5 weeks (duration at treating physician's discretion). The study period was defined from 1 month before to 1 month after ramp-up. TLS risk before Ven initiation was assessed per the label. Safety endpoints included the proportion of pts who experienced Grade ≥3 adverse events (AEs), TLS per Howard criteria (laboratory, clinical, or any reported TLS), and/or metabolic abnormalities observed during ramp-up. Feasibility of accelerated ramp-up was measured by assessing the proportion of pts who reached the target 400-mg dose or an alternative stable dose, defined as continuous/stable Ven dosing for ≥1 month after ramp-up. Descriptive statistics were calculated. Results: The median age at Ven initiation was 67.5 years (range 53-84) and 58.3% of pts had deletion 17p or TP53 mutation (Table 1). Pts were heavily pretreated (median of 3 lines of prior therapy [range 1-7]) and 88.9% had prior BCRi therapy; 27 pts (75.0%) had BCRi as immediate prior line of therapy before Ven. Before Ven initiation, 7 pts (19.4%) were at high risk of TLS, 13 (36.1%) at medium risk of TLS, and 15 (41.7%) at low risk of TLS; 1 unknown. Last line of therapy was discontinued in 30 pts (83.3%). Twenty-one pts (58.3%) received Ven monotherapy, 11 (30.6%) received Ven plus rituximab, 1 (2.8%) received Ven plus obinutuzumab, and 3 (8.3%) received Ven plus other (including ibrutinib, duvelisib, or idelalisib). Thirty-three pts (91.7%) underwent accelerated ramp-up as an inpatient, with a median hospital stay of 11 days (range 3-28). A stable dose of Ven was reached by 34 pts (94.4%), with median time of 15 days (range 3-66) to stable dose. Twenty-eight of these 34 pts (82.4%) reached the full 400 mg as their stable dose, with median time of 19.5 days (range 11-66). Overall, 15 pts (41.7%) experienced Grade ≥3 AEs and 4 (11.1%) discontinued Ven during ramp-up (2 pts due to clinical TLS, and 1 patient each due to persistent cytopenias and enrollment in hospice care). Seven pts (19.4%) had TLS (5 [13.9%] laboratory, 2 [5.6%] clinical), and 9 pts (25.0%) developed a metabolic abnormality only that did not meet Howard criteria for TLS (Table 2). Both pts with clinical TLS received Ven ramp-up while hospitalized; 1 high risk and 1 medium risk at baseline. Life-threatening (Grade 4) acute kidney injury and hypovolemic shock were reported for both. Of those pts with TLS, 4 (57.1%) required supportive medications. All AEs of TLS (including clinical events) resolved. Conclusion: In this multicenter study exploring accelerated Ven ramp-up, 82% of pts reached a stable dose of Ven 400 mg. TLS was observed in 19% of pts, including 2 pts with clinical TLS, which in both cases was reversible. Our data suggest that although the risk of TLS with an accelerated ramp-up appears to be greater than with 5-week Ven ramp-up per label, an accelerated Ven ramp-up schedule appears feasible at experienced academic centers with close inpatient monitoring. This dosing regimen may be beneficial for relapsed CLL pts with aggressive disease, particularly those progressing immediately after BCRi therapy. While promising, the approach cannot be routinely recommended until results are validated in a prospective clinical trial. Disclosures Davids: BeiGene: Consultancy; AstraZeneca: Consultancy, Research Funding; Adaptive Biotechnologies: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Ascentage Pharma: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; TG Therapeutics: Consultancy, Research Funding; Verastem: Consultancy, Research Funding; AbbVie: Consultancy; Eli Lilly: Consultancy; MEI Pharma: Consultancy, Research Funding; Bristol Myers Squibb: Research Funding; Novartis: Consultancy, Research Funding; Sunesis: Consultancy; Gilead Sciences: Consultancy; Zentalis: Consultancy; Syros Pharmaceuticals: Consultancy; Research to Practice: Honoraria; Merck: Consultancy; Surface Oncology: Research Funding. Shadman:TG therapeutics: Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Meyers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees; Verastem: Consultancy, Membership on an entity's Board of Directors or advisory committees; ADC Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Atara Biotherapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cellectar: Consultancy, 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; Mustang Bio: Research Funding; BeiGene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Sunesis: Research Funding; Gilead: Research Funding; MophoSys: Consultancy, Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sound Biologics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Acerta Pharma: Ended employment in the past 24 months. Parikh:GlaxoSmithKline: Honoraria; AbbVie: Honoraria, Research Funding; Ascentage Pharma: Research Funding; Genentech: Honoraria; Verastem Oncology: Honoraria; Janssen: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding; TG Therapeutics: Research Funding; Merck: Research Funding; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding. Ujjani:MorphoSys: Consultancy; Genentech: Consultancy, Honoraria; Atara: Consultancy, Honoraria; Gilead/Kite: Consultancy, Research Funding; Verastem Oncology: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria, Research Funding; AstraZeneca: Consultancy, Honoraria, Research Funding. Chen:AbbVie: Other: Institutional research grants, Research Funding. Johnson:AbbVie: Other: Institutional research grants, Research Funding. Jiang:AbbVie: Current Employment, Other: may hold stock or options. Llamas:AbbVie: Current Employment, Other: may hold stock or options. Feng:AbbVie: Current Employment, Other: may hold stock or options. Khan:ICON plc: Current Employment, Other: a company contracted by AbbVie for this study. Lamanna:MingSight: Other: Institutional research grants, Research Funding; Oncternal, Verastem, TG Therapeutics: Other: Institutional research grants, Research Funding; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Columbia University Medical Center: Current Employment; Juno: Other: Institutional research grants, Research Funding; Octapharma: Research Funding; Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Institutional research grants, Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bei-Gene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Institutional research grants, Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Institutional research grants, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Institutional research grants, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Loxo: Research Funding. OffLabel Disclosure: "Venetoclax is a BCL-2 inhibitor indicated: for treatment of adult patients with chronic lymphocytic leukemia (CLL) or small lymphocytic lymphoma (SLL); in combination with azacitidine, or decitabine, or low-dose cytarabine to treat adults with newly-diagnosed acute myeloid leukemia (AML) in adults who are age 75 years or older, or who have comorbidities that preclude use of intensive induction chemotherapy. CLL/SLL: Dosing with venetoclax begins with a 5-week ramp-up."

Background: The tumor microenvironment (TME) of MM is characterized by an immunosuppressive milieu fostering MM growth. The impact of tumor associated macrophages (TAM) has not been well-studied in the MM TME. We evaluated the bone marrow biopsies (BMBx) obtained at the initial diagnosis of MM and evaluated the correlation between the number of CD68+ macrophages and clinical parameters and outcomes. Methods: We evaluated the BMBx at initial diagnosis of 34 consecutive MM patients (pts) diagnosed between 2007-2016 at Mayo Clinic Florida. Immunohistochemistry (IHC) was performed with an anti-CD68 (KP1) antibody to identify and count CD68+ TAMs. Survival was analyzed with the Kaplan-Meier method. Chi-square tests were performed to study the correlation between the number of CD68+ TAMs and various clinical parameters. Results: Nineteen (56%) pts were male, 29 (85%) were caucasian. Median age at MM diagnosis was 58.5 years (95% CI 57-63), 18 (53%) pts has ISS I/II disease, 13 (38%) pts had ISS III disease, 3 (9%) has unknown ISS. Eight (24%) had high risk cytogenetics; 4(12%) had del17p, 2 (6%) had t(14;16), 1(3%) had 1q amplification, 3 (9%) had t(4;14). Eight (24%) had t(11;14). Twenty nine (85%) pts underwent autologous transplantation, 11(32%) received maintenance therapy. Overall response rate (≥partial response) to induction therapy was 100%. The ≥ very good partial response (VGPR) rate was 73.5%. Median number of induction cycles was 4.5 (95% CI 4.8-8.3). Twelve (35%) pts received lenalidomide (R)-dexamethasone (D) induction (RD), 9 (26%) received bortezomib (V)-cyclophosphamide(C)-D (VCD) induction, 7 (21%) received VRD induction, 5(15%) received VD induction and 1(3%) received CRD induction. The median follow-up was 92 months (m) (95% CI 85-99) The median progression free survival (mPFS) of the pt population was 40m (95% CI 27-68) and the median overall survival (mOS) was 96m (95% CI 81-126). Mean CD68+ TAM count was 12.5% (95% CI 8.1-16). There was a trend towards improved PFS for patients with ≥5% vs. <5% CD68+ TAM (47m vs. 36m, p=0.055) and there was improved OS for patients with ≥5% vs. <5% CD68+ TAM (101m vs. 73m, p=0.042, Figure 1) in their initial diagnostic BMBx. Pts with high risk cytogenetics did not have a significantly different CD68+ TAM (8.6%vs.12.8%, p=0.363) compared to those with standard risk cytogenetics. Pts with ISS I/II disease were more likely to have ≥5% CD68+ TAM in their diagnosis BMBx compared to patients with ISS III disease, χ²=8.58, p=0.003. Pts who achieved ≥VGPR to induction therapy were more likely to have ≥5% CD68+ TAM in their diagnosis BMBx compared to those who achieved <VGPR; χ²=5.35, p=0.020. Pts who received R-based induction and had ≥5% CD68+ TAM in their diagnosis BMBx had superior OS (96m vs. 62m, p=0.044) compared to those with <5%.This finding was not seen in patients who received V-based induction (p=0.33). Conclusion: Pts with ≥5% CD68+ TAM in their initial diagnostic BMBx are more likely to have deeper responses to induction therapy as well as superior OS. In pts induced with an R-based regimen, increased CD68+ TAM was associated with significantly better OS raising the possibility of a therapeutic and mechanistic role of TAM in R-related therapeutic effect. ≥5% CD68+ TAM were noted in patients with lower risk disease as defined by ISS stage but not by cytogenetics. Further exploration of the role of TAM in the biology of MM and its impact on clinical and therapeutic outcomes is warranted. Disclosures Alhaj Moustafa: Acrotech: Consultancy. Tun:DTRM Biopharma: Research Funding; Acrotech: Research Funding; Bristol-Myers Squibb: Research Funding; Celgene: Research Funding; Mundipharma: Research Funding; Curis: Research Funding; TG Therapeutics: Research Funding.

Introduction: Population studies have identified genes with germline polymorphisms associated with acute myeloid leukemia (AML) risk and outcome. However, somatic mutations in these genes have not been reported in an AML clinical population and whether they are associated with epidemiologic exposures, clinical AML phenotypes and outcome after therapy. Methods: We systemically interrogated PubMed database (1998-2018), to identify genes with germline polymorphisms associated with AML risk, response to chemotherapy or outcome. To determine the prevalence and relevance of somatic mutations in these genes in an unselected AML population, we performed an analysis using Whole-Exome Sequencing (WES) on remnant diagnostic cytogenetic pellets from 98 patients from the Mayo Clinic AML Epidemiology Cohort, a detailed and highly-annotated cohort of 295 consecutive AML patients treated at Mayo Clinic Florida & Arizona between October, 2000 and December, 2011. Patient characteristics are shown in Table 1. Samples were sequenced at a depth of ~100 million paired-end 100bp reads using Agilent SureSelectXT Human All Exon V5 + UTRs target enrichment kit. Sequencing reads were aligned to human reference genome, and somatic mutations including non-synonymous and truncating single nucleotide variants and small INDELs were identified and filtered using Exome Sequencing Project, 1000 genome, HapMap, & Mayo Clinic internal biobank genetic variants database. Copy number aberrations were identified & filtered using public copy number polymorphism databases. The association analyses were performed at the gene level, with a primary endpoint of whether a given patient harbored a somatic mutation in any genes linked to AML risk or outcome in literature, and to determine the associations of these mutations with epidemiologic exposures, AML phenotype and clinical outcomes. Results: From the literature search, we identified 77 unique genes with known germline polymorphisms associated with AML risk, response to chemotherapy or outcome. Fifty-eight of these were found to be somatically mutated in our WES dataset, with subsequent analysis focusing on the 11 genes (ABCB1, CYP1A1, CYP2B6, EPHX1, ERCC1, ERCC2, ERCC5, JAK2, MEFV, MTRR, and TERT) that had greater than 5 patients with nonsynonymous somatic mutations in the given gene. Significant associations with epidemiologic exposures and outcomes were noted in patients with somatic mutations in ERCC2, CYP1A1 and ERCC5 genes. Table 2 shows a comparison of patient characteristics and associations according to the presence of somatic mutations in these genes. Patients with mutations in CYP1A1 had a significantly younger age at AML diagnosis (Median: 51.7 vs. 71.0 years, P=.02) and significantly shorter OS in age-adjusted analysis (HR=4.45, P=.003). The former is a novel finding, whereas the latter is consistent with previous reports. Patients with mutations in ERCC2 more commonly used statins (66.7% vs. 21.7%, P=.03). Patients with ERCC5 mutations had a lower rate of tobacco use (20.0% vs. 54.5%, P=.049). In unadjusted analysis, there was a significant association between presence of somatic mutations in JAK2 and poorer survival after AML diagnosis (HR=2.83, P=.017), but this attenuated and did not retain significance when adjusting for age at AML diagnosis (HR=2.22, P=.067). Conclusion: Our exploratory study describes a novel association of CYP1A1 somatic nonsynonymous mutations with age of AML onset, as well as novel associations of ERCC2 and ERCC5 mutations with epidemiologic exposures in an unselect cohort of patients with AML. We confirm the association of CYP1A1 with inferior overall survival after AML diagnosis. These findings suggest that some genes associated with AML risk may also harbor somatic mutations that are clinically relevant. These results will guide a planned confirmatory prospective study to determine frequency and impact of both germline and somatic mutations of risk genes in AML patients, and may contribute to a better understanding leukemia risk assessment and potentially to prevention strategies. Disclosures Finn: Jazz Pharmaceuticals: Speakers Bureau; Celgene: Speakers Bureau; Seattle Genetics: Speakers Bureau. Cerhan:BMS/Celgene: Research Funding; NanoString: Research Funding. Foran:Revolution Medicine: Consultancy; Servier: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Boehringer Ingelheim: Research Funding; H3Biosciences: Research Funding; Xencor: Research Funding; Trillium: Research Funding; Takeda: Research Funding; Kura Oncology: Research Funding; Aptose: Research Funding; Aprea: Research Funding; Actinium: Research Funding; Agios: Honoraria, Research Funding.

Background: B-cell maturation antigen (BCMA) is widely expressed on normal plasma cells and malignant plasma cells in multiple myeloma (MM). MEDI2228 is an antibody-drug conjugate (ADC) that targets the extracellular domain of human BCMA with preferential binding to membrane-bound versus circulating soluble BCMA. The ADC is comprised of a fully human antibody to BCMA, site- specifically conjugated to a DNA cross-linking pyrrolobenzodiazepine (PBD) dimer via a protease-cleavable linker. After cell surface binding to BCMA, MEDI2228 is internalized and cleaved in the lysosomal compartment, releasing the active PBD, which cross-links DNA and leads to apoptotic cell death. We report the results from a phase 1, first-in-human, open-label, dose-escalation and expansion trial (NCT03489525) that evaluated the safety, pharmacokinetics (PK), and clinical activity of MEDI2228 in patients (pts) with relapsed/refractory MM (R/R MM). Methods: Eligible pts were ≥18 years old with confirmed R/R MM as defined by International Myeloma Working Group consensus criteria, had measurable disease, and had an Eastern Cooperative Oncology Group performance status ≤1. Pts had to have progressed after treatment with three classes of standard-of-care anti-myeloma drugs, including proteasome inhibitors (PIs), immunomodulatory drugs (IMiDs), and monoclonal antibodies (mAbs). Dose escalation was based on an accelerated titration design, with an mTPI-2 algorithm. During dose escalation, MEDI2228 was administered in sequentially ascending dose levels (0.0125, 0.025, 0.05, 0.1, and 0.2 mg/kg) intravenously every 3 weeks (Q3W). Due to dose-limiting toxicities (DLTs), the dose was de-escalated from 0.2 mg/kg to an intermediate dose level of 0.14 mg/kg. The primary endpoint was safety and tolerability. Secondary endpoints included assessment of preliminary efficacy, PK, and immunogenicity. Results: As of May 15, 2020, 82 pts received MEDI2228 during dose escalation and expansion. All pts had received prior therapy with an IMiD, PI, and mAb: lenalidomide, 76 (94%); pomalidomide, 68 (84%); bortezomib, 77 (95%); carfilzomib, 64 (79%); and daratumumab, 71 (87%). Pts received between 2-11 lines of prior regimens. At 0.2 mg/kg, 2 pts experienced DLTs (grade 3/4 thrombocytopenia) without bleeding; no DLTs were reported for other dose levels. The maximum tolerated dose was 0.14 mg/kg Q3W. Treatment-related adverse events (TEAEs) occurring in ≥20% of pts in the 0.14 mg/kg cohort were photophobia (53.7%), thrombocytopenia (31.7%), rash (29.3%), increased gamma-glutamyltransferase (24.4%), dry eye (19.5%), and pleural effusion (19.5%). No reports of keratopathy or visual acuity loss were observed in the 0.14 mg/kg cohort. The TEAE profiles at lower-dose levels were similar but with lower incidences compared with the 0.14 mg/kg level. Efficacy was demonstrated at all dose levels (dose, objective response rate [ORR], [n]): 0.0125 mg/kg, 33.3% [1/3]; 0.025 mg/kg, 16.7% [1/6]; 0.05 mg/kg, 33.3% [3/9]; 0.10 mg/kg, 27.8% [5/18]; 0.14 mg/kg, 61.0% [25/41]; 0.2 mg/kg, 40.0%, [2/5]. In the 0.14 mg/kg cohort, ORR was 61.0% (95% confidence interval [CI]: 44.5%, 75.8%); there were 10 (24.4%) very good partial responses (VGPRs), 15 (36.6%) partial responses, and 3 (7.3%) minimal responses. Four of the VGPR pts were immunofixation negative. Most (90.2%) pts in the 0.14 mg/kg cohort had received prior daratumumab. Median duration of response (DOR) in the 0.14 mg/kg cohort was not reached. MEDI2228 exhibited linear PK at doses of ≥0.05 mg/kg Q3W that was minimally impacted by circulating levels of soluble BCMA at baseline. There was no difference in BCMA expression by IHC in the bone marrow of responders compared with nonresponders. Thirty-six pts in the 0.14 mg/kg cohort discontinued treatment due to adverse events (n=24), progressive disease (n=8), patient decision (n=2), investigator decision (n=1), or death (n=1). Conclusion: MEDI2228 is a BCMA-targeted ADC that demonstrated clinical efficacy at all dose levels explored. MEDI2228 0.14 mg/kg Q3W had a manageable safety profile and an ORR of 61% in a heavily pretreated population with myeloma that is R/R post PI, IMiD, and mAb therapies. Disclosures Kumar: Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Tenebio: Other, Research Funding; Merck: Consultancy, Research Funding; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genecentrix: Consultancy; Novartis: Research Funding; Kite Pharma: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; BMS: Consultancy, Research Funding; Karyopharm: Consultancy; MedImmune: Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Sanofi: Research Funding; Carsgen: Other, Research Funding; Cellectar: Other; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Dr. Reddy's Laboratories: Honoraria; Adaptive Biotechnologies: Consultancy. Bhutani:Sanofi Genzyme: Consultancy; Takeda: Other: Clinical trial funding to institute, Speakers Bureau; BMS: Other: Clinical trial funding to institute, Speakers Bureau; Amgen: Speakers Bureau; MedImmune: Other: Clinical Trial Funding to Institute; Prothena: Other: Clinical Trial Funding to Institute; Janssen: Other: Clinical Trial Funding to Institute. Spencer:Roche: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Other: Grant/Research Support; Servier: Consultancy, Other: Grant/Research Support; Janssen: Consultancy, Honoraria, Other: Grant/Research Support, Speakers Bureau; Haemalogix: Consultancy, Honoraria, Other: Grant/Research Support; Abbvie: Consultancy, Honoraria, Other: Grant/Research Support; Pfizer: Consultancy, Honoraria; Takeda: Honoraria, Other, Speakers Bureau; Secura Bio: Consultancy, Honoraria; TheraMyc: Consultancy, Honoraria; Antegene: Consultancy, Honoraria; BMS: Honoraria, Other: Grant/Research Support, Research Funding, Speakers Bureau; Pharmamar: Other. Ailawadhi:Cellectar: Research Funding; Pharmacyclics: Research Funding; Janssen: Research Funding; Takeda: Honoraria; Amgen: Research Funding; Celgene: Honoraria; Phosplatin: Research Funding; Medimmune: Research Funding; BMS: Research Funding. Kalff:Amgen: Honoraria; Janssen: Honoraria; Roche: Honoraria; Celgene: Honoraria; CSL: Honoraria. Pore:AstraZeneca: Current Employment, Current equity holder in publicly-traded company. Gibson:AstraZeneca: Current Employment, Other: Paid as a clinical scientist contractor. Wang:AstraZeneca: Current Employment, Current equity holder in publicly-traded company. Cheng:Astrazeneca: Current Employment, Current equity holder in private company. Williams:AstraZeneca: Current Employment, Current equity holder in publicly-traded company. Kinneer:AstraZeneca: Current Employment, Current equity holder in publicly-traded company, Other: Personal fees; BCMA Monoclonal Antibody-Drug Conjugate: Patents & Royalties: Pending. Zonder:Intellia: Membership on an entity's Board of Directors or advisory committees, Other: Personal fees; Alnylam: Membership on an entity's Board of Directors or advisory committees, Other: Personal fees; Oncopeptide: Membership on an entity's Board of Directors or advisory committees, Other: Personal fees; Amgen: Membership on an entity's Board of Directors or advisory committees, Other: Personal fees; BMS: Consultancy, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Other: Personal fees; Janssen: Consultancy, Other: Personal fees; Prothena: Consultancy; Caelum: Consultancy; Celgene: Research Funding. Larsen:Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen Oncology: Honoraria, Membership on an entity's Board of Directors or advisory committees. Yee:Amgen: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; GSK: Consultancy; Janssen: Consultancy; Karyopharm: Consultancy; Oncopeptide: Consultancy; Sanofi: Consultancy; Takeda: Consultancy, Research Funding. Dimopoulos:Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Personal fees, Research Funding, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Personal fees, Research Funding, Speakers Bureau; BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Personal fees; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Personal fees, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Personal fees, Speakers Bureau.

AbstractThe purpose of this analysis was to develop and validate computable phenotypes for heart failure (HF) with preserved ejection fraction (HFpEF) using claims‐type measures using the Rochester Epidemiology Project. This retrospective study utilized an existing cohort of Olmsted County, Minnesota residents aged ≥ 20 years diagnosed with HF between 2007 and 2015. The gold standard definition of HFpEF included meeting the validated Framingham criteria for HF and having an LVEF ≥ 50%. Computable phenotypes of claims‐type data elements (including ICD‐9/ICD‐10 diagnostic codes and lab test codes) both individually and in combinations were assessed via sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) with respect to the gold standard. In the Framingham‐validated cohort, 2,035 patients had HF; 1,172 (58%) had HFpEF. One in‐patient or two out‐patient diagnosis codes of ICD‐9 428.3X or ICD‐10 I50.3X had 46% sensitivity, 88% specificity, 84% PPV, and 54% NPV. The addition of a BNP/NT‐proBNP test code reduced sensitivity to 35% while increasing specificity to 91% (PPV = 84%, NPV = 51%). Broadening the diagnostic codes to ICD‐9 428.0, 428.3X, and 428.9/ICD‐10 I50.3X and I50.9 increased sensitivity at the expense of decreasing specificity (diagnostic code‐only model: 87% sensitivity, 8% specificity, 56% PPV, 30% NPV; diagnostic code and BNP lab code model: 61% sensitivity, 43% specificity, 60% PPV, 45% NPV). In an analysis conducted to mimic real‐world use of the computable phenotypes, any one in‐patient or out‐patient code of ICD‐9 428/ICD‐10 150 among the broader population (N = 3,755) resulted in lower PPV values compared with the Framingham cohort. However, one in‐patient or two out‐patient instances of ICD‐9 428.0, 428.9, or 428.3X/ICD‐10 150.3X or 150.9 brought the PPV values from the two cohorts closer together. While some misclassification remains, the computable phenotypes defined here may be used in claims databases to identify HFpEF patients and to gain a greater understanding of the characteristics of patients with HFpEF.

The increasing use of gastrointestinal endoscopic procedures has led to the recognition by histopathologists of non‐conventional (or special‐type) dysplasias of the gastrointestinal tract. These lesions can be recognised in association with prevalent underlying gastrointestinal conditions, such as Barrett oesophagus, chronic atrophic gastritis, and inflammatory bowel disease. The diagnosis of these special types can be challenging, and their biological behaviours are not fully characterised. The aim of this review is to provide a global view of non‐conventional dysplastic lesions observed in the various segments of the tubular gastrointestinal tract and describe their salient features. Furthermore, as the clinical implications of these various subtypes have not been broadly tested in practice and are not represented in most management guidelines, we offer guidance on the best management practices for these lesions.

Abstract Aging is a physiological decline in both structural homeostasis and functional integrity, progressively affecting organismal health. A major hallmark of aging is the accumulation of senescent cells, which have entered a state of irreversible cell cycle arrest after experiencing inherent or environmental stresses. Although cellular senescence is essential in several physiological events, it plays a detrimental role in a large array of age‐related pathologies. Recent biomedical advances in specifically targeting senescent cells to improve healthy aging, or alternatively, postpone natural aging and age‐related diseases, a strategy termed senotherapy, have attracted substantial interest in both scientific and medical communities. Challenges for aging research are highlighted and potential avenues that can be leveraged for therapeutic interventions to control aging and age‐related disorders in the current era of precision medicine.

Abstract Aims Baduanjin (eight silken movements), a traditional Chinese exercise, is an alternative to the most common cardiac rehabilitation programmes due to their scarcity and unaffordability in China. The aim of this study was to measure the intensity and energy expenditure during Baduanjin and to determine the relative oxygen consumption (VO2) and heart rate (HR) responses of Baduanjin compared with maximal capacity in patients with chronic heart failure. Methods and results Twenty participants (age: 65 ± 10 years, male: n = 17) with New York Heart Association II–III volunteered for this study. Participants were examined during two separate sessions, with 1–2 weeks between sessions. During session one, a symptom-limited cardiopulmonary exercise testing was performed on a cycle ergometer for measurement of maximal exercise capacity. Additionally, participants were taught Baduanjin exercise from a professional coach and were required to do it at home until the second session when their technique was confirmed by the coach. During session two, participants performed one 9 min round of Baduanjin with continuous measurement of VO2 and HR. Measurements obtained during the Baduanjin were compared with data obtained during cardiopulmonary exercise testing. While performing Baduanjin, the mean VO2 and HR were 7.1 ± 1.2 mL/kg/min and 86.1 ± 15.2 b.p.m., respectively. Compared with the cardiopulmonary exercise test, the VO2 was 44% of their VO2max and 67% of their HRmax, categorizing Baduanjin as a moderate-intensity exercise. The average energy expenditure during Baduanjin was 23.3 ± 4.4 kcal. Additionally, the VO2 and HR responses during Baduanjin both exhibited a bimodal pattern. Conclusions The results suggest that Baduanjin is a moderate-intensity aerobic exercise that could be an effective and safe exercise modality for home-based cardiac rehabilitation.

AbstractIntroductionWe sought to assess longitudinal electronic health records (EHRs) using machine learning (ML) methods to computationally derive probable Alzheimer's Disease (AD) and related dementia subphenotypes.MethodsA retrospective analysis of EHR data from a cohort of 7587 patients seen at a large, multi‐specialty urban academic medical center in New York was conducted. Subphenotypes were derived using hierarchical clustering from 792 probable AD patients (cases) who had received at least one diagnosis of AD using their clinical data. The other 6795 patients, labeled as controls, were matched on age and gender with the cases and randomly selected in the ratio of 9:1. Prediction models with multiple ML algorithms were trained on this cohort using 5‐fold cross‐validation. XGBoost was used to rank the variable importance.ResultsFour subphenotypes were computationally derived. Subphenotype A (n = 273; 28.2%) had more patients with cardiovascular diseases; subphenotype B (n = 221; 27.9%) had more patients with mental health illnesses, such as depression and anxiety; patients in subphenotype C (n = 183; 23.1%) were overall older (mean (SD) age, 79.5 (5.4) years) and had the most comorbidities including diabetes, cardiovascular diseases, and mental health disorders; and subphenotype D (n = 115; 14.5%) included patients who took anti‐dementia drugs and had sensory problems, such as deafness and hearing impairment.The 0‐year prediction model for AD risk achieved an area under the receiver operating curve (AUC) of 0.764 (SD: 0.02); the 6‐month model, 0.751 (SD: 0.02); the 1‐year model, 0.752 (SD: 0.02); the 2‐year model, 0.749 (SD: 0.03); and the 3‐year model, 0.735 (SD: 0.03), respectively. Based on variable importance, the top‐ranked comorbidities included depression, stroke/transient ischemic attack, hypertension, anxiety, mobility impairments, and atrial fibrillation. The top‐ranked medications included anti‐dementia drugs, antipsychotics, antiepileptics, and antidepressants.ConclusionsFour subphenotypes were computationally derived that correlated with cardiovascular diseases and mental health illnesses. ML algorithms based on patient demographics, diagnosis, and treatment demonstrated promising results in predicting the risk of developing AD at different time points across an individual's lifespan.