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Background The relative benefits of haploidentical HCT using PTCy compared to traditional matched-sibling donor, traditional unrelated donor and umbilical cord blood (UCB) allogeneic HCT for adult acute lymphoblastic leukemia (ALL) is still being defined. Methods We performed a retrospective analysis using the Center for International Blood and Marrow Transplant Research (CIBMTR) database comparing post-HCT outcomes of haploidentical donors with PTCy to HLA-identical sibling donors, 8/8 HLA-MUDs, 7/8 HLA-MUDs, and UCB. Outcomes were overall survival (OS) leukemia-free survival (LFS), relapse, non-relapse mortality (NRM), grade 2-4 and grade 3-4 acute graft-versus-host disease (aGVHD), and chronic GVHD (cGVHD). Eligible patients were adults with ALL in complete remission (CR1, CR2, or CR3) undergoing first allogeneic HCT from 2013 to 2017. Key exclusion included not receiving PTCy for haploidentical HCT and ex vivo T-cell depleted or CD34-selected grafts. Cox proportional hazards multivariable regression analysis was used to compare the treatment groups. Results 4201 patients were studied: 393 haploidentical donor (92 centers), 1627 HLA-identical sibling donor (206 centers), 1646 8/8 HLA-MUD (181 centers), 230 7/8 HLA-MUD (90 centers), and 305 UCB (79 centers). Groups were well matched, however, notable differences between included race, time from diagnosis to HCT (CR1 only), conditioning regimen intensity, donor age, graft source for non-cord (peripheral blood or bone marrow), GVHD prophylaxis modality, and the use of in vivo T-cell depletion. Compared to other groups, haploidentical HCT had the lowest percentage of non-Hispanic white patients (43% vs. 49-74%), was more likely to use reduced-intensity conditioning (42% vs 17-25%), and was more likely to use bone marrow (41% vs. 14-29%). In multivariate analysis comparing haploidentical to matched-sibling donor HCT, no differences were observed in OS, LFS, NRM, relapse, or aGVHD. Compared to haploidentical HCT, the risk of cGVHD was significantly higher with matched-sibling donor HCT (D/R sex match F/M, HR 2.59, P<0.001, D/R sex match, other, HR 1.37, P=0.003). Comparing haploidentical to 8/8 HLA-MUD HCT, no differences were seen in OS, LFS, relapse, or Grade 2-4 aGVHD but 8/8 HLA-MUD HCT was associated with increased incidences of NRM (HR 1.42, P=0.02), grade 3-4 aGVHD (HR 1.59, P=0.005), and cGVHD (HR D/R sex match F/M, HR 2.91, P<0.001, D/R sex match, other, HR 1.38, P=0.001). Comparing haploidentical to 7/8 HLA-MUD HCT, no differences were seen in LFS or relapse but 7/8 HLA-MUD HCT was associated with worse OS (HR 1.38, P=0.01) and increased incidences of NRM (HR 2.13, P=<0.001), grade 2-4 aGVHD (HR 1.33, P=0.04) , grade 3-4 aGVHD (HR 1.86, P=0.003), and cGVHD (HR 1.72, P=<0.001). Comparing haploidentical to UCB HCT, no differences were seen in late OS (>18 months), late LFS, relapse, or cGVHD. Compared to haploidentical HCT, UCB HCT was associated with worse early OS (≤18 months, HR 1.93, P<0.001), worse early LFS (HR 1.40, P=0.007) and increased incidences of NRM (HR 2.08, P<0.001), grade 2-4 aGVHD (HR 1.83, P<0.001), and grade 3-4 aGVHD (HR 1.97, P<0.001). Similar outcomes were observed in sensitivity analyses restricting cohorts to (1) MA conditioning with peripheral blood stem cells and (2) calcineurin inhibitor-based GVHD prophylaxis for matched-sibling, unrelated donor, and UCB HCT. Conclusions For OS and LFS, haploidentical HCT using PTCy for adult ALL was superior to traditional HCT using 7/8 HLA-MUDs and UCB but equivalent to traditional HCT using matched-sibling donors and 8/8 HLA-MUDs. Results were consistent across all subgroups. Haploidentical HCT had a lower incidence of aGVHD compared to 8/8 HLA-MUD, 7/8 HLA-MUD, and UCB HCT and a lower incidence of cGVHD compared to matched-sibling donor, 8/8 HLA-MUD, and 7/8 HLA-MUD HCT. Based on these data, haploidentical HCT with PTCy results in similar survival with less GVHD compared to traditional matched-sibling and 8/8 HLA-matched donor HCT and is the superior alternative donor option for adult patients with ALL needing allogeneic HCT in CR. Figure Disclosures Wieduwilt: Leadiant: Research Funding; Shire: Research Funding; Merck: Research Funding; Macrogeneics: Research Funding; Amgen: Research Funding; Daiichi Sankyo: Membership on an entity's Board of Directors or advisory committees. de Lima:Incyte: Other: Personal Fees, advisory board; BMS: Other: Personal Fees, advisory board; Pfizer: Other: Personal fees, advisory board, Research Funding; Celgene: Research Funding; Kadmon: Other: Personal Fees, Advisory board. Kebriaei:Novartis: Other: Served on advisory board; Pfizer: Other: Served on advisory board; Kite: Other: Served on advisory board; Ziopharm: Other: Research Support; Amgen: Other: Research Support; Jazz: Consultancy. Hourigan:Merck: Other: Research Support (CRADA); Sellas: Other: Research Support (CRADA). Weisdorf:FATE Therapeutics: Consultancy; Incyte: Research Funding.

Background: Allogeneic HCT continues to be the optimal consolidation strategy for many patients with AML. Cytogenetic and molecular abnormalities are known to influence post-transplant outcomes. We tested the prognostic ability of a modified (mELN) classification system based on available CIBMTR genetic data, to predict post-transplant outcomes. Methods: Adult patients with a diagnosis of AML in first complete remission (CR1) with available pre-transplant cytogenetic and molecular mutational data, receiving a first allogeneic HCT from 2013-2017, were included. Patients were stratified according to mELN genetic classification in three distinct groups: favorable (Fav), intermediate (IM) and adverse (Adv). Clinical outcomes following HCT were compared among groups after adjusting for significant patient, disease, and transplant-related variables. The primary endpoint was disease free survival (DFS). Secondary endpoints were overall survival (OS), non-relapse mortality (NRM), cumulative incidence of relapse, acute GVHD, and chronic GVHD. Cox proportional hazard models were used to compare endpoints among mELN risk groups, age groups and genetic subsets within the adverse-risk group. Results: Demographic characteristics are summarized in Table 1. 2289 patients (Fav, n=181; IM n=1185; and Adv n=923) met the inclusion criteria. Median follow-up for survivors was 35 months. Importantly, 41% of transplant recipients (n=936) were >60 years, 76% (n=1743) had de novo AML and 48% (n=1111) received a myeloablative conditioning regimen. Univariate analysis (UVA) demonstrated significant differences in 2-year OS (Fav: 67.7%, IM: 64.9% and Adv: 53.9%; p<0.001); DFS (Fav: 57.8%, IM: 55.5% and Adv: 45.3; p<0.001) and relapse (Fav: 28%, IM: 27.5% and Adv: 37.5%; p<0.001) There were no significant differences in NRM (p=0.467) or the incidence of acute (p=0.423) and chronic GVHD (p=0.442) among mELN groups. Initial multivariate analysis (MVA) of mELN risk groups indicated that there was no significant difference in clinical outcomes between the Fav and IM risk groups. Thus, these groups were combined for subsequent analyses. Adv risk (vs. Fav/IM) led to significantly worse OS (HR 1.39 [1.24-1.57] p=<0.001), DFS (HR 1.32 [1.18-1.48] p=<0.001), and relapse (HR 1.42 [1.23-1.63] p=<0.001) (Table 2). This mELN classification effectively stratified both younger (<60 y/o) and older (>60 y/o) patients for OS (Adv vs. Fav/IM HR for <60: 1.43 [1.21-1.69] p<0.001; >60: 1.44 [1.21-1.72] p<0.001), DFS (Adv HR for <60: 1.31 [1.12-1.53] p<0.001; >60: 1.41 [1.19-1.66] p<0.001) and relapse (Adv HR for <60: 1.44 [1.20-1.74] p<0.001, >60: 1.42 [1.15-1.76] p=0.001). NRM was higher for older patients (>60 y/o) in both the Fav/IM (HR 1.40 [1.10-1.78] p=0.007) and Adv-risk cohorts (HR 1.59 [1.18-2.13] p=0.002). Genetic subset comparisons within the adverse-risk group showed that patients carrying monosomy 5, del(5q) or monosomy 7 had inferior 2-year OS (42.6%, p<0.001) and DFS (35.2%, p<0.001), as well as higher rates of relapse (45%, p= 0.002) when compared to other patients within the Adv-risk cohort (OS 60%, DFS 50.8%, relapse 33.5%). Conclusion: Stratification using mELN criteria resulted in clear prognostic separation of OS, DFS and relapse in this large cohort of AML patients undergoing allogeneic HCT. While Fav and IM groups had similar OS, DFS and relapse rates; patients in the Adv risk group had the highest risk of relapse and inferior DFS/OS. However, the majority of patients in all cohorts had favorable outcomes for HCT in CR1. Our findings confirm the value of a combined genetic prognostic model in the AML HCT setting and justify the use of this stratification system in future HCT trials. Correlation of genetic subtypes with other important transplant variables, such as conditioning intensity and pre-transplant MRD status deserves further evaluation. There remains a subset of Adv-risk patients for which post-transplant outcomes continue to be poor, even when transplanted in CR1. Novel peri-transplant pre-emptive/therapeutic strategies are urgently needed for this high-risk cohort. Disclosures de Lima: Celgene: Research Funding; Pfizer: Other: Personal fees, advisory board, Research Funding; BMS: Other: Personal Fees, advisory board; Incyte: Other: Personal Fees, advisory board; Kadmon: Other: Personal Fees, Advisory board. Komanduri:Kiadis: Consultancy; Takeda: Consultancy; Celgene: Consultancy; Atara: Consultancy, Membership on an entity's Board of Directors or advisory committees; Adaptimmune: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Kite/Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees. Kebriaei:Ziopharm: Other: Research Support; Jazz: Consultancy; Kite: Other: Served on advisory board; Amgen: Other: Research Support; Novartis: Other: Served on advisory board; Pfizer: Other: Served on advisory board. Bhatt:National Marrow Donor Program: Research Funding; Rigel Pharmaceuticals: Other; Jazz: Research Funding; Agios: Other: Personal Fees; Incyte: Other: Personal Fees, Research Funding; Takeda: Other: Personal Fees; Partner Therapeutics: Other: Personal Fees; Pfizer: Other, Research Funding; CSL Behring: Other; Tolero Pharmaceuticals: Research Funding; Oncoceutics: Other: Drug support for a trial; Partnership for health analytic research, LLC: Other: Personal Fees; Omeros: Other: Personal Fees; Abbvie: Other: Personal Fees, Research Funding. Saad:Orcabio: Other: research support; Kadmon: Other: research support; Amgen: Other: research support; Incyte Pharmaceuticals: Other: Personal Fees; Magenta Therapeutics: Other: Personal Fees. Copelan:Amgen: Membership on an entity's Board of Directors or advisory committees. Defilipp:Incyte: Research Funding; Regimmune: Research Funding; Syndax Pharmaceuticals: Consultancy. Nishihori:Karyopharm: Other: Research support to institution; Novartis: Other: Research support to institution. Weisdorf:Incyte: Research Funding; FATE Therapeutics: Consultancy.

Abstract To evaluate the racial and ethnic differences in prevalence of germline pathogenic variants (PVs) and the effect of race and ethnicity on breast cancer (BC) risk among carriers, results of multigene testing of 77 900 women with BC (non-Hispanic White [NHW] = 57 003; Ashkenazi-Jewish = 4798; Black = 6722; Hispanic = 5194; and Asian = 4183) were analyzed, and the frequency of PVs in each gene were compared between BC patients (cases) and race- and ethnicity-matched gnomAD reference controls. Compared with NHWs, BRCA1 PVs were enriched in Ashkenazi-Jews and Hispanics, whereas CHEK2 PVs were statistically significantly lower in Blacks, Hispanics, and Asians (all 2-sided P < .05). In case-control studies, BARD1 PVs were associated with high risks (odds ratio > 4.00) of BC in Blacks, Hispanics, and Asians; ATM PVs were associated with increased risk of BC among all races and ethnicities except Asians, whereas CHEK2 and BRIP1 PVs were associated with increased risk of BC among NHWs and Hispanics only. These findings suggest a need for personalized management of BC risk in PV carriers based on race and ethnicity.

Maternal–fetal surgery is a rapidly evolving specialty, and significant progress has been made over the last 3 decades. A wide range of maternal–fetal interventions are being performed at different stages of pregnancy across multiple fetal therapy centers worldwide, and the anesthetic technique has evolved over the years. The American Society of Anesthesiologists (ASA) recognizes the important role of the anesthesiologist in the multidisciplinary approach to these maternal–fetal interventions and convened a collaborative workgroup with representatives from the ASA Committees of Obstetric and Pediatric Anesthesia and the Board of Directors of the North American Fetal Therapy Network. This consensus statement describes the comprehensive preoperative evaluation, intraoperative anesthetic management, and postoperative care for the different types of maternal–fetal interventions.

As a critical factor in the built environment, lighting presents considerable influence on occupants. Previous research across static lighting conditions has found that both illuminance and correlated color temperature (CCT) affect occupants’ physiological and psychological functioning. However, little research has been conducted on the non-visual impacts of dynamic lighting with daily variation in illuminance and CCT levels. The purpose of this study is to better understand the impact of dynamic lighting on office occupants’ health, well-being and experience at a living lab. Fifteen participants were recruited to work in three office modules for four months. Four lighting conditions were designed and implemented in this study, including two static lighting conditions and two dynamic lighting conditions with a specific predefined control scheme. A prototype lighting system with enhanced control capabilities was configured and implemented to ensure the desired lighting environment protocol. Both objective methods and subjective surveys were used to assess the behavioral and physiological outcomes of interest, including mental stress, sleep, productivity, satisfaction, mood, visual comfort and perceived naturalness. The results showed that the daytime behavioral impacts were either positive or mixed. Specifically, a significant alertness increase was observed in the afternoon, indicating a potential solution to reduce the natural feelings of sleepiness during the workday. There was also a marginal benefit for mood. The nighttime impacts include a significant decrease in perceived sleep quality and sleep time after subjects were exposed to dynamic lighting. No significant differences were observed for mental stress, productivity, visual comfort, or perceived naturalness. The findings present additional insights into the non-visual impacts of dynamic lighting and give recommendations for further investigations.

Abstract Chronic lymphocytic leukemia (CLL) is characterized by the existence of subsets of patients with (quasi)identical, stereotyped B-cell receptor (BcR) immunoglobulins. Patients in certain major stereotyped subsets often display remarkably consistent clinicobiological profiles, suggesting that the study of BcR immunoglobulin stereotypy in CLL has important implications for understanding disease pathophysiology and refining clinical decision-making. Nevertheless, several issues remain open, especially pertaining to the actual frequency of BcR immunoglobulin stereotypy and major subsets, as well as the existence of higher-order connections between individual subsets. To address these issues, we investigated clonotypic IGHV-IGHD-IGHJ gene rearrangements in a series of 29 856 patients with CLL, by far the largest series worldwide. We report that the stereotyped fraction of CLL peaks at 41% of the entire cohort and that all 19 previously identified major subsets retained their relative size and ranking, while 10 new ones emerged; overall, major stereotyped subsets had a cumulative frequency of 13.5%. Higher-level relationships were evident between subsets, particularly for major stereotyped subsets with unmutated IGHV genes (U-CLL), for which close relations with other subsets, termed “satellites,” were identified. Satellite subsets accounted for 3% of the entire cohort. These results confirm our previous notion that major subsets can be robustly identified and are consistent in relative size, hence representing distinct disease variants amenable to compartmentalized research with the potential of overcoming the pronounced heterogeneity of CLL. Furthermore, the existence of satellite subsets reveals a novel aspect of repertoire restriction with implications for refined molecular classification of CLL.

Background: Abdominal aortic aneurysm (AAA) is an important cause of cardiovascular mortality; however, its genetic determinants remain incompletely defined. In total, 10 previously identified risk loci explain a small fraction of AAA heritability. Methods: We performed a genome-wide association study in the Million Veteran Program testing ≈18 million DNA sequence variants with AAA (7642 cases and 172 172 controls) in veterans of European ancestry with independent replication in up to 4972 cases and 99 858 controls. We then used mendelian randomization to examine the causal effects of blood pressure on AAA. We examined the association of AAA risk variants with aneurysms in the lower extremity, cerebral, and iliac arterial beds, and derived a genome-wide polygenic risk score (PRS) to identify a subset of the population at greater risk for disease. Results: Through a genome-wide association study, we identified 14 novel loci, bringing the total number of known significant AAA loci to 24. In our mendelian randomization analysis, we demonstrate that a genetic increase of 10 mm Hg in diastolic blood pressure (odds ratio, 1.43 [95% CI, 1.24–1.66]; P =1.6×10 −6 ), as opposed to systolic blood pressure (odds ratio, 1.06 [95% CI, 0.97–1.15]; P =0.2), likely has a causal relationship with AAA development. We observed that 19 of 24 AAA risk variants associate with aneurysms in at least 1 other vascular territory. A 29-variant PRS was strongly associated with AAA (odds ratio PRS , 1.26 [95% CI, 1.18–1.36]; P PRS =2.7×10 −11 per SD increase in PRS), independent of family history and smoking risk factors (odds ratio PRS+family history+smoking , 1.24 [95% CI, 1.14–1.35]; P PRS =1.27×10 −6 ). Using this PRS, we identified a subset of the population with AAA prevalence greater than that observed in screening trials informing current guidelines. Conclusions: We identify novel AAA genetic associations with therapeutic implications and identify a subset of the population at significantly increased genetic risk of AAA independent of family history. Our data suggest that extending current screening guidelines to include testing to identify those with high polygenic AAA risk, once the cost of genotyping becomes comparable with that of screening ultrasound, would significantly increase the yield of current screening at reasonable cost.

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.

Purpose Intensity‐modulated proton therapy (IMPT) is sensitive to uncertainties from patient setup and proton beam range, as well as interplay effect. In addition, respiratory motion may vary from cycle to cycle, and also from day to day. These uncertainties can severely degrade the original plan quality and potentially affect patient’s outcome. In this work, we developed a new tool to comprehensively consider the impact of all these uncertainties and provide plan robustness evaluation under them. Methods We developed a comprehensive plan robustness evaluation tool that considered both uncertainties from patient setup and proton beam range, as well as respiratory motion simultaneously. To mimic patients' respiratory motion, the time spent in each phase was randomly sampled based on patient‐specific breathing pattern parameters as acquired during the four‐dimensional (4D)‐computed tomography (CT) simulation. Spots were then assigned to one specific phase according to the temporal relationship between spot delivery sequence and patients’ respiratory motion. Dose in each phase was calculated by summing contributions from all the spots delivered in that phase. The final 4D dynamic dose was obtained by deforming all doses in each phase to the maximum exhalation phase. Three hundred (300) scenarios (10 different breathing patterns with 30 different setup and range uncertainty scenario combinations) were calculated for each plan. The dose‐volume histograms (DVHs) band method was used to assess plan robustness. Benchmarking the tool as an application’s example, we compared plan robustness under both three‐dimensional (3D) and 4D robustly optimized IMPT plans for 10 nonrandomly selected patients with non‐small cell lung cancer. Results The developed comprehensive plan robustness tool had been successfully applied to compare the plan robustness between 3D and 4D robustly optimized IMPT plans for 10 lung cancer patients. In the presence of interplay effect with uncertainties considered simultaneously, 4D robustly optimized plans provided significantly better CTV coverage (D 95% , P = 0.002), CTV homogeneity (D 5% ‐D 95% , P = 0.002) with less target hot spots (D 5% , P = 0.002), and target coverage robustness (CTV D 95% bandwidth, P = 0.004) compared to 3D robustly optimized plans. Superior dose sparing of normal lung (lung D mean , P = 0.020) favoring 4D plans and comparable normal tissue sparing including esophagus, heart, and spinal cord for both 3D and 4D plans were observed. The calculation time for all patients included in this study was 11.4 ± 2.6 min. Conclusion A comprehensive plan robustness evaluation tool was successfully developed and benchmarked for plan robustness evaluation in the presence of interplay effect, setup and range uncertainties. The very high efficiency of this tool marks its clinical adaptation, highly practical and versatile nature, including possible real‐time intra‐fractional interplay effect evaluation as a potential application for future use.