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Background: Multiple myeloma (MM) is typically diagnosed in patients (pts) aged 65-74 y (SEER: Myeloma. 2019); therefore, many pts present with concomitant metabolic disorders such as diabetes (18%-22% prevalence of type 2 diabetes [T2D; BMC Cancer. 2020;20:489]). Obesity (body mass index [BMI], ≥ 30 kg/m2) is associated with increased prevalence of T2D (Int J Clin Pract. 2007;61:737), and both are suggested risk factors for MM (Blood. 2012;119:4845; Bone Marrow Transpl. 2014;49:1009). Results from single-center, retrospective studies have shown poorer clinical features and survival outcomes in diabetic pts with MM vs their nondiabetic counterparts (Eur J Haematol. 2012;89:320, Br J Cancer. 2014;111:628). The Connect® MM Registry (NCT01081028) is a large, US, multicenter, prospective observational cohort study of largely community-based pts with NDMM. Reported here is a descriptive analysis assessing differences in baseline (BL) characteristics, treatment patterns, and survival outcomes in diabetic vs nondiabetic pts enrolled in the Connect MM Registry. Methods: Pts with NDMM (N = 3011) were enrolled at 250 community, academic, and government sites. Eligible pts were aged ≥ 18 y with symptomatic MM diagnosed ≤ 2 months (mo) pre-enrollment per International Myeloma Working Group criteria (Leukemia. 2009;23:3). Diabetic pts were defined as those with a history of diabetes and also receiving antidiabetic treatment at BL; those without a history of diabetes and not receiving antidiabetic treatment at BL were defined as nondiabetic pts. Descriptive statistics were used for BL characteristics and treatment regimens. Survival outcomes (progression-free survival [PFS] and overall survival [OS]) were analyzed using Cox regression and adjusted for covariates. Results: Of the 2845 pts included in this analysis, 467 (16%) were diabetic, and 2378 (84%) were nondiabetic. The median age was 69 y for diabetic pts and 66 y for nondiabetic pts, with fewer Black pts (12.2% vs 19.5%) in the nondiabetic group. The proportion of men was higher in the diabetic vs the nondiabetic group (61.9% vs 56.6%). Similar percentages of pts had ECOG PS of 0-1 in both groups (53.3% vs 55.3%). Obesity was more prevalent in diabetic vs nondiabetic pts (55.9% vs 30.4%). More diabetic pts had a history of hypertension requiring treatment vs nondiabetic pts (84.2% vs 52.5%). The prevalence of chromosomal abnormalities was comparable between the groups (within the limitation that data were missing in a substantial number of pts). Among MM-defining criteria, diabetic pts had a higher incidence of hypercalcemia (11.8% vs 8.5%), anemia (50.3% vs 46.5%), and increased creatinine (23.8% vs 19%), whereas measured kidney function was similar. A lower proportion of diabetic than nondiabetic pts received stem cell transplantation (SCT; 28.9% vs 41.5%) and triplet regimens during first induction (48.2% vs 52.8%%). The use of ≥ 2 novel agents during first line (1L) was lower in diabetic than nondiabetic pts (27.8% vs 34.6%), but use of a single novel agent (63.4% vs 60%) and alkylator in 1L (20.6% vs 22.4%) was comparable. The top five 1L regimens were similar for both groups, with lenalidomide + bortezomib + dexamethasone being the most common 1L regimen, and lenalidomide the most common maintenance therapy. Diabetic pts had significantly shorter adjusted median PFS (24.4 vs 31.5 mo; hazard ratio [HR], 1.24; P = 0.001; Fig. 1A) and median OS (60 vs 72.6 mo; HR, 1.29; P = 0.001; Fig. 1B) than nondiabetic pts. In a subgroup analysis by BMI, diabetic pts had significantly shorter OS than nondiabetic pts (for BMI < 30 [50.8 vs 73.1 mo; HR, 1.51; P = 0.0001] and BMI ≥ 30 [56.4 vs 78.6 mo; HR, 1.51; P < 0.0001]). Conclusions: Diabetic pts with NDMM had poorer BL features and were less likely to receive SCT and triplet regimens and/or aggressive upfront treatment. Regardless of BMI, diabetic pts had shorter median OS than nondiabetic pts, suggesting that diabetes might be a stronger factor for survival than obesity. These results support a previous analysis of the Connect MM Registry that identified history of diabetes as a predictive prognostic factor for poor OS (Br J Haematol. 2019;187:602). Limitations of this analysis include limited detail on the care/management of diabetes and steroid use/dosage (which can be challenging for glycemic control). These findings highlight the need to provide better supportive care for diabetes management in MM pts to improve survival. Disclosures La: Celgene BMS: Consultancy. Jagannath:BMS, Janssen, Karyopharm, Legend Biotech, Sanofi, Takeda: Consultancy. Ailawadhi:Amgen: Research Funding; Celgene: Honoraria; Takeda: Honoraria; Janssen: Research Funding; Pharmacyclics: Research Funding; Cellectar: Research Funding; BMS: Research Funding; Medimmune: Research Funding; Phosplatin: Research Funding. Durie:Amgen, Celgene, Johnson & Johnson, and Takeda: Consultancy. Gasparetto:Adaptive Biotechnologies: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company), Speakers Bureau; Karyopharm: Consultancy, Honoraria, Other: TRAVEL, ACCOMODATIONS, EXPENSES (paid by any for-profit health care company), Speakers Bureau; Janssen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; GSK: Consultancy, Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company); BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AbbVie: Consultancy, Honoraria. Hardin:Celgene Pharmaceutical Company: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: TRAVEL, ACCOMMODATIONS, EXPENSES. Lee:Sanofi: Consultancy; Janssen: Consultancy, Research Funding; GlaxoSmithKline: Consultancy, Research Funding; Genentech: Consultancy; Takeda: Consultancy, Research Funding; Regeneron: Research Funding; Genentech: Consultancy; Amgen: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Daiichi Sankyo: Research Funding. Narang:Maryland Oncology Hematology: Current Employment; Beigene: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; J&J: Consultancy, Honoraria. Omel:Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; BMS/Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Rifkin:McKesson: Current equity holder in publicly-traded company, Ended employment in the past 24 months, Other: Stock ownership; Takeda, Amgen, Celgene, BMS, Mylan, Coherus BioSciences, Fresenius: Consultancy; AbbVie: Other: Investigator in AbbVie sponsored clinical trials; Takeda, Amgen, BMS (Celgene): Membership on an entity's Board of Directors or advisory committees. Terebelo:Newland Medical Associates: Current Employment; BMS: Membership on an entity's Board of Directors or advisory committees. Toomey:Celgene/BMS: Membership on an entity's Board of Directors or advisory committees. Wagner:Celgene Inc.: Membership on an entity's Board of Directors or advisory committees; Connect Multiple Myeloma Registry: Membership on an entity's Board of Directors or advisory committees. Dhalla:BMS: Current Employment, Current equity holder in publicly-traded company. Liu:TechData Inc: Consultancy. Yang:BMS: Current Employment, Current equity holder in publicly-traded company. Joshi:Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company; Eisai Inc.: Ended employment in the past 24 months. Abonour:Takeda: Consultancy; Janssen: Honoraria, Research Funding; Celgene: Consultancy; BMS: Consultancy, Research Funding.

AbstractBackgroundThe critical‐period theory of menopausal hormone therapy (mHT) suggests that if menopausal hormone therapy begins shortly after menopause, it may have beneficial effects on brain structure and cognitive health. We investigated white matter integrity with diffusion tensor MRI (DTI) 3 years after the end of mHT trial in recently menopausal women who were randomized shortly after menopause.MethodParticipants of this study were enrolled in the Kronos Early Estrogen Prevention Study (aged 42–56 years; 5–36 months past menopause). Participants received the following treatments: 0.45 mg/d oral conjugated equine estrogen (oCEE, n=19); 50 μg/d transdermal 17β‐estradiol (tE2, n=22); or placebo (n=33) for 4 years. Oral progesterone (200 mg/d) was given to hormone therapy groups for 12 days each month. DTI was performed 3 years after the end of 4 years of hormone therapy (n=75), which corresponded to 7 years after randomization. Voxel‐based analysis was performed on DTI to evaluate fractional anisotropy (FA) and mean diffusivity (MD) differences between treatment groups (uncorrected p<0.001).ResultVoxel based analysis showed higher FA, a measure of white matter integrity, in the superior corona radiata, anterior limb of the internal capsule and splenium of the corpus callosum of participants treated with oCEE compared to placebo (p <0.001, Figure 1A). Furthermore, higher FA was observed in the superior corona radiata, anterior limb of internal capsule and thalamus in participants treated with tE2 compared to placebo (p <0.001, Figure 1B). There were no differences in FA findings between oCEE and tE2 groups, and no MD differences between treatments groups.ConclusionA relatively higher FA in a variety of white matter regions in the oCEE and tE2 groups compared to placebo suggest that mHT may have long‐term protective effects on white matter integrity. Previously, we had shown that women in the tE2 group preserved their dorsolateral prefrontal cortex volumes better than the placebo group over 7 years. Our findings suggest that the tracts that connect the dorsolateral prefrontal cortex and the thalamus such as the superior corona radiata and the anterior limb of internal capsule may particularly benefit from mHT.

AbstractAimThis study is a comprehensive review with the purpose of collecting the most relevant data in several sections including current treatment guidelines in the paediatric population.MethodsLiterature was systematically searched in different databases. Results were limited to 2019+ and English, French and Spanish language.ResultsChildren can exhibit mild and less severe COVID‐19 disease than adults and also have asymptomatic carriage of SARS‐CoV‐2, while severe disease is more frequently noted during infancy (<1 year). SARS‐CoV‐2 binds the angiotensin‐converting enzyme 2 (ACE‐2) receptor; age‐, racial‐, and gender‐specific differences in ACE‐2 expression need to be elucidated in order to explain the differential clinical profiles between children and adults. Multisystem inflammatory syndrome in children (MIS‐C) is an important condition to recognise in children. The decision to use antiviral or immunomodulatory therapy in a child or adolescent should be individualised based on the clinical scenario. Remdesivir is the only FDA‐approved therapy available for children older than 12 years old who require hospitalisation for COVID‐19.ConclusionFurther studies are urgently required to address prevention and treatment in at‐risk and infected children, especially with underlying comorbidities. The chapter on the overall impact of COVID‐19 in children has not yet been written. Nevertheless, SARS‐CoV‐2 has now joined a long list of human pandemics, which may forever change the world's history.

BACKGROUND AND OBJECTIVES: The effects of in utero methamphetamine exposure on behavioral problems in school-aged children are unclear. Our objective for this study was to evaluate behavior problems in children at aged 3, 5, and 7.5 years who were prenatally exposed to methamphetamine. METHODS: Subjects were enrolled in the Infant Development, Environment, and Lifestyle study, a longitudinal prospective study of prenatal methamphetamine exposure and child outcomes. Exposed and comparison groups were matched on birth weight, race, education, and health insurance. At ages 3, 5, and 7.5 years, 339 children (171 exposed) were assessed for behavior problems by using the Child Behavior Checklist. Generalized estimating equations were used to determine the effects of prenatal methamphetamine exposure, age, and the interaction of exposure and age on behavior problems. Caregiver psychological symptoms were assessed by using the Brief Symptom Inventory. RESULTS: Analyses adjusted for covariates revealed that relative to age 3, children at 5 years had less externalizing and aggressive behavior and more internalizing behavior, somatic complaints, and withdrawn behavior. By age 7.5, aggressive behavior continued to decrease, attention problems increased and withdrawn behavior decreased. There were no main effects for methamphetamine exposure and no interactions of exposure and age. Caregiver psychological symptoms predicted all behavior problems and the quality of the home predicted externalizing problems and externalizing syndrome scores. CONCLUSIONS: Behavioral effects longitudinally from ages 3 to 7.5 years were not associated with prenatal methamphetamine exposure, whereas caregiver psychological symptoms and the quality of the home were predictors of behavior problems.

Introduction: FL is the most common indolent non-Hodgkin lymphoma in the Western world. FL may cause disease-related symptoms, and patients with high-risk disease usually require systemic therapy. BR is commonly used as first-line therapy for high-risk FL, and the addition of bortezomib to a BR backbone has been studied (Evens A et al. Clin Can Res 2020). Little is known about how these therapeutic options impact patients' health-related quality of life (HRQL). To fill this gap, patient-reported outcomes (PROs) were administered to patients enrolled on E2408 to quantify symptom burden and effects of BR versus BVR induction on HRQL. Methods: Patients (n=258) randomized to receive 6 cycles of BR or BVR induction completed PROs assessing neurotoxicity (FACT/GOG-Ntx) at the beginning of each treatment cycle. Additional PROs measuring fatigue (FACT-F), lymphoma-specific concerns (FACT-Lym) and HRQL (Functional Assessment of Cancer Therapy-General; FACT-G) were completed at baseline, mid-treatment (MT; cycle 3/4) and end of induction (EOI; cycle 6). Paired t-test was used to assess PRO score changes from baseline to MT and EOI within BR or BVR group. Two-sample t-test was used to compare change scores between groups at MT and EOI, respectively. Univariate analyses with a linear model identified patient baseline characteristics and clinical factors (age, sex, stage, performance status, # extra nodal sites, FLIPI, GELF, bone marrow involvement, elevated LDH, palpable splenomegaly, B-symptoms, CRIS) associated with PRO change scores from baseline to EOI, adjusting for treatment group. A multivariate model was built with backward variable selection approach for each of the PROs. Results: As shown in Figure 1, compared with baseline, patients randomized to BVR reported significantly worse FACT/GOG-Ntx scores at cycle 4, which continued to end of induction (FACT/GOG-Ntx change scores -2.91 to -3.73; p &lt; 0.001). Neurotoxicity remained stable for patients treated with BR (Ntx change scores -0.02 to -0.55). FACT-Fatigue scores indicated worse fatigue at MT compared to baseline for patients receiving BVR (-2.7, p&lt;0.05), yet they remained stable for BR. FACT-Lym scores were significantly higher at MT (BR: 2.69, p&lt;0.001; BVR: 2.71, p=0.007) and end of induction (BR: 3.32, p&lt;0.001; BVR: 3.55, p&lt;0.001) compared to baseline, signifying a reduction in lymphoma-related symptoms in both arms. FACT-G scores were comparable between treatment arms at each time-point and did not change significantly from baseline to end of induction. Univariate analyses among all patients identified older age and the absence of palpable splenomegaly at baseline as associated with worse FACT-Lym, FACT-Fatigue, and FACT-G change scores, signifying less improvement in lymphoma-related symptoms, fatigue and HRQL from baseline to end of induction (p&lt;0.01). The presence of B-symptoms at baseline was associated with a greater reduction in lymphoma-related symptoms and fatigue from baseline to end of induction (p&lt;0.01). Higher ECOG performance status was only associated with higher FACT-Fatigue change score, suggesting more improvement in fatigue for those with worse performance status at baseline. A multivariate model generated similar results. Conclusions: Despite worse treatment-related symptoms throughout induction, the addition of bortezomib was associated with comparable overall HRQL to those treated with BR. Both treatments were associated with a reduction in lymphoma-related symptoms from baseline to end of induction, likely contributing to stable HRQL throughout treatment despite treatment-related symptoms. Findings also suggest that a subgroup of patients, particularly those who are older, may experience fewer improvements in lymphoma-related symptoms. This underscores the potential need for closer monitoring and clinical management of these patients. Collectively, results are likely to be encouraging for patients experiencing lymphoma-related symptoms, for whom the symptom burden associated with treatment may be worth the trade-off given the potential for improved disease-related symptom control. Disclosures Evens: Merck: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy, Honoraria; Pharmacyclics: Consultancy, Honoraria; MorphoSys: Consultancy, Honoraria; Research To Practice: Honoraria, Speakers Bureau; Epizyme: Consultancy, Honoraria, Research Funding; Mylteni: Consultancy, Honoraria; Novartis: Consultancy, Honoraria. Advani:Celgene, Forty Seven, Inc., Genentech/Roche, Janssen Pharmaceutical, Kura, Merck, Millenium, Pharmacyclics, Regeneron, Seattle Genetics: Research Funding; Astra Zeneca, Bayer Healthcare Pharmaceuticals, Cell Medica, Celgene, Genentech/Roche, Gilead, KitePharma, Kyowa, Portola Pharmaceuticals, Sanofi, Seattle Genetics, Takeda: Consultancy. Ansell:Trillium: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; AI Therapeutics: Research Funding; Takeda: Research Funding; Seattle Genetics: Research Funding; Bristol Myers Squibb: Research Funding; ADC Therapeutics: Research Funding. Winter:Norvartis: Consultancy, Other: DSMB; Ariad/Takeda: Consultancy; CVS/Caremark: Consultancy; Delta Fly Pharma: Consultancy; Amgen: Consultancy; Epizyme: Other: DSMB; Merck: Membership on an entity's Board of Directors or advisory committees, Other: advisory board; Karyopharm: Membership on an entity's Board of Directors or advisory committees, Other: advisory board. Cella:FACIT.org: Membership on an entity's Board of Directors or advisory committees, Other: President; Astellas: Consultancy, Honoraria; Pled Pharma: Research Funding; Janssen: Research Funding; Clovis: Research Funding; Alexion: Research Funding; Apellis: Consultancy; Pfizer: Consultancy, Research Funding; Novartis: Consultancy; Kiniksa: Consultancy; IDDI: Consultancy; BMS: Consultancy, Research Funding; ASAHI KASEI PHARMA CORP.: Consultancy; Oncoquest: Consultancy; Mei Pharma: Consultancy; Ipsen: Consultancy, Research Funding; Evidera: Consultancy; DSI: Consultancy, Research Funding; BlueNote: Consultancy; Abbvie: Consultancy, Research Funding; PROMIS Health Org: Membership on an entity's Board of Directors or advisory committees, Other. Kahl:ADC Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; BeiGene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche Laboratories Inc: Consultancy; Pharmacyclics LLC: Consultancy; Genentech: Consultancy; Celgene Corporation: Consultancy; AstraZeneca Pharmaceuticals LP: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy; Acerta: Consultancy, Research Funding. Wagner:Celgene Inc.: Membership on an entity's Board of Directors or advisory committees; Connect Multiple Myeloma Registry: Membership on an entity's Board of Directors or advisory committees.

SummaryAlthough new multiple myeloma (MM) therapies are effective in alleviating some disease‐associated symptoms (e.g. bone pain, fatigue, functional decline), they can result in additional toxicities, further impacting health‐related quality of life (HRQoL). Here, we compared HRQoL and safety of lenalidomide‐bortezomib‐dexamethasone [RVd (n = 445)], bortezomib‐melphalan‐prednisone [VMP (n = 77)] and Vd or VMP (n = 588) in patients with newly diagnosed MM (NDMM) from the Connect® MM Registry, a large, USA, multicentre, prospective observational cohort study. Functional Assessment of Cancer Therapy‐Multiple Myeloma subscale, EuroQol‐5D overall score and Bone Pain Inventory HRQoL scores were significantly improved with RVd versus Vd/VMP. Serious adverse event rates were similar in all groups. Treatment with RVd maintained HRQoL in this real‐world, largely community‐based population of patients with NDMM.

ABSTRACT Background There is only partial overlap in the genetic background of isolated rapid‐eye‐movement sleep behavior disorder (iRBD) and Parkinson's disease (PD). Objective To examine the role of autosomal dominant and recessive PD or atypical parkinsonism genes in the risk of iRBD. Methods Ten genes, comprising the recessive genes PRKN , DJ‐1 (PARK7) , PINK1 , VPS13C , ATP13A2 , FBXO7 , and PLA2G6 and the dominant genes LRRK2 , GCH1 , and VPS35 , were fully sequenced in 1039 iRBD patients and 1852 controls of European ancestry, followed by association tests. Results We found no association between rare heterozygous variants in the tested genes and risk of iRBD. Several homozygous and compound heterozygous carriers were identified, yet there was no overrepresentation in iRBD patients versus controls. Conclusion Our results do not support a major role for variants in these genes in the risk of iRBD. © 2020 International Parkinson and Movement Disorder Society

Abstract Background: Whether circulating polyunsaturated fatty acid (PUFA) levels are associated with pancreatic cancer risk is uncertain. Mendelian randomization (MR) represents a study design using genetic instruments to better characterize the relationship between exposure and outcome. Methods: We utilized data from genome-wide association studies within the Pancreatic Cancer Cohort Consortium and Pancreatic Cancer Case–Control Consortium, involving approximately 9,269 cases and 12,530 controls of European descent, to evaluate associations between pancreatic cancer risk and genetically predicted plasma n-6 PUFA levels. Conventional MR analyses were performed using individual-level and summary-level data. Results: Using genetic instruments, we did not find evidence of associations between genetically predicted plasma n-6 PUFA levels and pancreatic cancer risk [estimates per one SD increase in each PUFA-specific weighted genetic score using summary statistics: linoleic acid odds ratio (OR) = 1.00, 95% confidence interval (CI) = 0.98–1.02; arachidonic acid OR = 1.00, 95% CI = 0.99–1.01; and dihomo-gamma-linolenic acid OR = 0.95, 95% CI = 0.87–1.02]. The OR estimates remained virtually unchanged after adjustment for covariates, using individual-level data or summary statistics, or stratification by age and sex. Conclusions: Our results suggest that variations of genetically determined plasma n-6 PUFA levels are not associated with pancreatic cancer risk. Impact: These results suggest that modifying n-6 PUFA levels through food sources or supplementation may not influence risk of pancreatic cancer.

Abstract Background Black race is associated with worse outcomes in early breast cancer. We evaluated clinicopathologic characteristics, the 21-gene recurrence score (RS), treatment delivered, and clinical outcomes by race and ethnicity among women who participated in the Trial Assigning Individualized Options for Treatment. Methods The association between clinical outcomes and race (White, Black, Asian, other or unknown) and ethnicity (Hispanic vs non-Hispanic) was examined using proportional hazards models. All P values are 2-sided. Results Of 9719 eligible women with hormone receptor–positive, HER2-negative, node-negative breast cancer, there were 8189 (84.3%) Whites, 693 (7.1%) Blacks, 405 (4.2%) Asians, and 432 (4.4%) with other or unknown race. Regarding ethnicity, 889 (9.1%) were Hispanic. There were no substantial differences in RS or ESR1, PGR, or HER2 RNA expression by race or ethnicity. After adjustment for other covariates, compared with White race, Black race was associated with higher distant recurrence rates (hazard ratio [HR] = 1.60, 95% confidence intervals [CI] = 1.07 to 2.41) and worse overall survival in the RS 11-25 cohort (HR = 1.51, 95% CI = 1.06 to 2.15) and entire population (HR = 1.41, 95% CI = 1.05 to 1.90). Hispanic ethnicity and Asian race were associated with better outcomes. There was no evidence of chemotherapy benefit for any racial or ethnic group in those with a RS of 11-25. Conclusions Black women had worse clinical outcomes despite similar 21-gene assay RS results and comparable systemic therapy in the Trial Assigning Individualized Options for Treatment. Similar to Whites, Black women did not benefit from adjuvant chemotherapy if the 21-gene RS was 11-25. Further research is required to elucidate the basis for this racial disparity in prognosis.