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AbstractBackgroundHigh titers of cold agglutinins jeopardize the quality of an apheresis product meant for autologous or allogeneic transplant. Management of transplant patients with cold agglutinin disease (CAD) is often experience‐based and under reported, yet decisions must be made quickly to optimize product management and patient outcomes. There remains a lack of data quantifying cell recovery and viability when using various warming methodologies.Study Design and MethodsTo expand the published experimental data on this subject, our human cellular therapy lab compared cellular recoveries and viabilities after manipulation of cryopreserved apheresis products through various warming methodologies: (1) extended warming in a water bath, (2) warming via blood warmer and infusion pump, and (3) warming in a water bath followed by infusion pump as a control to assess potential shear stress effects.ResultsThe presented studies demonstrate that all methods of product warming produce the same rates of recovery of total and viable cells across vital cell types prior to patient administration. Statistically, use of an extended water bath protocol provided a marginal benefit in recovery of total nucleated cells, though this effect is diminished when products are held for an extended period to simulate a delay in administration.DiscussionThese results can inform decisions to improve patient care and minimize product manipulation and loss. Centers are encouraged to use this information to guide proactive measures to establish a standard operating procedure to manage CAD cases.

The NCCN Guidelines for Lung Cancer Screening recommend criteria for selecting individuals for screening and provide recommendations for evaluation and follow-up of lung nodules found during initial and subsequent screening. These NCCN Guidelines Insights focus on recent updates to the NCCN Guidelines for Lung Cancer Screening.

6591 Background: BMT CTN 1101 was a Phase III randomized controlled trial evaluating the comparative effectiveness of unrelated umbilical cord blood (UCB) versus HLA-haploidentical related donor bone marrow (haplo-BM) cell sources for hematopoietic cell transplantation (HCT) in patients with high-risk hematologic malignancies (leukemias, lymphomas). We report results of an economic evaluation conducted as part of the clinical trial. Methods: 368 patients (90% of planned accrual) enrolled from 33 centers in the U.S. were randomly assigned to unrelated UCB (n=186) or haplo-BM (n=182) transplant. Healthcare utilization and costs were estimated using propensity-score matched cohorts of BMT patients in the OptumLabs Data Warehouse for trial participants <65 years, and Medicare claims for trial participants ≥65 years. Cost-effectiveness was calculated from payer perspectives (commercial, Medicare) over a 20-year time horizon from time of transplant. Weibull models (best fit based on AIC/BIC) were used to extrapolate survival from 5-year trial follow-up data. Trial participant surveys (EQ-5D) were used to derive health state utilities for estimating Quality-Adjusted Life Years (QALYs). One-way and probabilistic sensitivity analyses were conducted to assess uncertainty in results. Outcomes were discounted at 3% annually. Results: At 5-year follow-up, overall survival was 42% for haplo-BM versus 36% for UCB (P=.06). Over a 20-year time horizon, haplo-BM is expected to be more effective and more costly for <65 year-olds and in ≥65 year-olds it is expected to be more effective and less costly. In one-way uncertainty analyses, for persons <65, the cost/QALY result was most sensitive to life years and health state utilities. For persons ≥65, life years were more influential than costs and health state utilities. Using probabilistic sensitivity analysis, for persons <65 there was a 43% chance that haplo-BM was cost-effective using a willingness to pay threshold of $150k/QALY and 52% at a $200K/QALY threshold. Conclusions: Results from a large national clinical trial indicate that compared to UCB, haplo-BM was moderately cost-effective for patients aged <65 years, and less costly and more effective for persons ≥65 years. Haplo-BM is a fair value choice for commercially insured patients with high-risk leukemia and lymphoma who require HCT. For Medicare enrollees, haplo-BM is a preferred choice when considering costs and outcomes. [Table: see text]

AbstractLeukocyte adhesion deficiency type II (LAD II, also known as SLC35C1‐congenital disorder of glycosylation) is an autosomal recessive disorder characterized by growth and cognitive impairment, peripheral neutrophilia, recurrent infections, and the Bombay blood phenotype. A subset of patients with a milder presentation has been described with short stature and developmental delay but minimal immune and hematologic features. Some patients with LAD II benefit from oral fucose therapy, though this has not been previously studied in patients with milder disease. In this study, we describe two new patients from separate families with the milder variant of LAD II and review the published literature on this rare disorder. We demonstrate improvement in speech and cognition, CD15 expression, and core fucosylation of serum glycoproteins after 27 months of oral fucose supplementation in one patient. These patients further support the stratification of this disorder into distinct subtypes, a classical severe and an attenuated variant, and provide preliminary evidence of benefit of fucose therapy in the latter group.

AbstractBackground and objectivePleuroscopy with pleural biopsy has a high sensitivity for malignant pleural effusion (MPE). Because MPEs tend to recur, concurrent diagnosis and treatment of MPE during pleuroscopy is desired. However, proceeding directly to treatment at the time of pleuroscopy requires confidence in the on‐site diagnosis. The study's primary objective was to create a predictive model to estimate the probability of MPE during pleuroscopy.MethodsA prospective observational multicentre cohort study of consecutive patients undergoing pleuroscopy was conducted. We used a logistic regression model to evaluate the probability of MPE with relation to visual assessment, rapid on‐site evaluation (ROSE) of touch preparation and presence of pleural nodules/masses on computed tomography (CT). To assess the model's prediction accuracy, a bootstrapped training/testing approach was utilized to estimate the cross‐validated area under the receiver operating characteristic curve.ResultsOf the 201 patients included in the study, 103 had MPE. Logistic regression showed that higher level of malignancy on visual assessment is associated with higher odds of MPE (OR = 34.68, 95% CI = 9.17–131.14,p < 0.001). The logistic regression also showed that higher level of malignancy on ROSE of touch preparation is associated with higher odds of MPE (OR = 11.63, 95% CI = 3.85–35.16,p < 0.001). Presence of pleural nodules/masses on CT is associated with higher odds of MPE (OR = 6.61, 95% CI = 1.97–22.1,p = 0.002). A multivariable logistic regression model of final pathologic status with relation to visual assessment, ROSE of touch preparation and presence of pleural nodules/masses on CT had a cross‐validated AUC of 0.94 (95% CI = 0.91–0.97).ConclusionA prediction model using visual assessment, ROSE of touch preparation and CT scan findings demonstrated excellent predictive accuracy for MPE. Further validation studies are needed to confirm our findings.

Abstract Background: The use of immunotherapeutic agents in multiple myeloma (MM) has shown improvements in clinical outcomes, emphasizing the role the host immune system plays in disease control. In recognition of this relationship, efforts aimed at identifying biomarkers of immune surveillance in MM have identified prognostic value in the peripheral absolute lymphocyte (ALC) and absolute monocyte (AMC) counts at various stages of disease and following autologous stem cell transplant (ASCT), with lower ALC and AMC serving as a surrogate for immune dysregulation and correlating with inferior progression free (PFS) and overall survival (OS). With ASCT remaining the standard of care in the treatment of MM, we sought to examine whether CD3 content of the apheresis product during stem cell collection could be used as a biomarker for immune competence and whether it influences outcomes. Methods: A retrospective study was conducted on 1086 MM patients who underwent stem cell (CD34) collection with available CD3 data and subsequent ASCT at our institution. We recorded the total absolute CD3 and CD34 cell count upon completion of mobilization, with a higher CD3 count serving as a surrogate for immune competence. In addition to investigating the absolute CD3 count, we calculated the CD3/CD34 ratio given variation in the CD34 goals. Patients were dichotomized based on whether their absolute CD3 and CD3/CD34 ratio values were above or below medians. A Kaplan-Meier model was used to compare median PFS and OS between groups. A cox proportional hazards model was used to determine its prognostic impact, adjusting for ISS stage 3, high risk FISH, achievement of CR near day 100, and maintenance therapy received post-ASCT. Results: The median length of follow-up from date of ASCT for the entire cohort (N=1086) was 34.1 months (range: 0.26-157 months) and the median time from stem cell collection to ASCT was 9 days (range: 3-3143 days). The most common mobilizing regimen was Neupogen and plerixafor (N=425, 39%) and 694 (64%) patients received ASCT in the first line setting. The median absolute total CD3 count was 4.3 x 10^6/kg (range: 0.1-21.9) with 542 patients above and 544 patients at or below the median. The median absolute total CD34 count was 8.53 x 10^6/kg (range: 0.2-37.0) and median CD3/CD34 ratio was 0.50 (range: 0.01-15), with 536 patients above and 550 patients at or below the median ratio. The median PFS among patients with a CD3 count &gt; 4.25 x 10^6/kg was 23.1 vs. 16.9 months among patients with CD3 count ≤ 4.25 x 10^6/kg (p&lt;0.0001) and median OS was 65.3 months vs. 41.6 months (p&lt;0.0001), respectively. A similar trend was observed when dividing patients based on CD3/CD34 ratio, with median PFS of 22.4 vs. 17.5 months (p=.0003) and median OS of 61.5 vs. 45.7 months (p=.0001), both favoring the cohort with a CD3/CD34 ratio &gt; 0.5 (Figure 1). The prognostic value among patients with a CD3/CD34 ratio &gt; 0.5 was retained after adjusting for ISS stage III, high risk FISH features, and use of maintenance therapy as follows: PFS HR: 0.73 (95% CI: 0.62-0.86; p=0.0002); OS 0.71 (95% CI: 0.59-0.88; p=0.001). Conclusions: Our study demonstrates that patients who have higher CD3 content in their apheresis product have better PFS and OS following ASCT. These findings reveal a possible role for using absolute CD3 and CD3/CD34 ratios in the apheresis product as a surrogate marker for immune competence and in predicting clinical outcomes. Figure 1 Figure 1. Disclosures Gertz: Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; Aurora Biopharma: Other: Stock option; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Ionis Pharmaceuticals: Other: Advisory Board. Dingli: GSK: Consultancy; Sanofi: Consultancy; Janssen: Consultancy; Alexion: Consultancy; Apellis: Consultancy; Novartis: Research Funding. Dispenzieri: Takeda: Research Funding; Pfizer: Research Funding; Alnylam: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy; Janssen: Consultancy, Research Funding. Kapoor: Sanofi: Research Funding; Takeda: Research Funding; Ichnos Sciences: Research Funding; Glaxo SmithKline: Research Funding; Regeneron Pharmaceuticals: Research Funding; AbbVie: Research Funding; Karyopharm: Research Funding; Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding. Kumar: Novartis: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Antengene: Consultancy, Honoraria; Tenebio: Research Funding; Amgen: Consultancy, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; BMS: Consultancy, Research Funding; Oncopeptides: Consultancy; Carsgen: Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche-Genentech: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Consultancy; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding.

Abstract BACKGROUND: Our group recently reported on the results of Blood and Marrow Transplant (BMT) Clinical Trials Network (CTN) 1101 a randomized comparison between double umbilical cord blood (dUCB) and haploidentical bone marrow (haplo) with post-transplant cyclophosphamide (ptCy) in the nonmyeloablative setting that showed similar progression free survival (PFS) between the two treatment groups, but lower non-relapse mortality (NRM) and better of overall survival (OS) in the haplo arm. In this secondary analysis we sought to investigate if transplant center experience with haplo and or cord blood HCT had an impact on outcomes. PATIENTS AND METHODS: All patient randomized in BMT CTN 1101 were included. In order to determine the transplant center experience with either haplo or dUCB we queried the Center for International Blood and Marrow Transplant Research (CIBMTR) for number of transplants with each platform in the year prior to initiation of the study. Centers were then grouped as dUCB center (&gt; 10 dUCB, n=117, 10 centers), Haplo center (&gt;10 haplo and ≤10 dUCB, n=110, 2 centers), and ≤10 haplo and ≤10 dUCB HCTs (other center, n=140, 21 centers). Further analysis considered the alternative cut-off for haplo (&gt; 5 vs ≤ 5) experience, and considered the outcomes based on the donor experience vs. others (e.g. dUCB &gt; 10 vs. ≤ 10; haplo &gt; 5 vs. ≤ 5). RESULTS: The effect of center experience on HCT outcomes shown in Figure, below . After adjusting for age, Karnofsky performance score and, disease risk index we found that there was no difference in outcomes between haplo and dUCB for centers that were experienced with dUCB or had limited to no experience with either dUCB or haplo. In contrast, in centers that were primarily experienced with haplo had better outcomes with this donor type, as compared to dUCB. The higher risk of treatment failure (relapse or death) and overall mortality in dUCB in haplo experienced centers was driven by significantly higher risk of relapse. We then considered the transplant experience with each of the donor types separately. In transplant centers that had performed &gt; 10 dUCB, there were similar outcomes for recipients of both dUCB and haplo. Similarly, centers that had ≤ 5 haplo HCTs had no difference in outcomes between donor types suggesting an overlap with centers that had performed &gt; 10 dUCB HCTs. Overall mortality was higher among dUCB recipients in centers that had performed ≤ 10 dUCB. Notably, the hazard ratio of non-relapse mortality favored haplo in all four donor experience type of transplant center, albeit not statistically significant. CONCLUSION: Except for dUCB recipients in centers with &lt; 10 dUCB/year had worse overall mortality, primarily driven by relapse, the transplant center experience in the year prior to the initiation of BMT CTN 1101 had limited impact on the outcomes of this randomized clinical trial. Figure 1 Figure 1. Disclosures Brunstein: NANT: Research Funding; FATE: Research Funding; GamidaCell: Research Funding; BlueRock: Research Funding; AlloVir: Consultancy. Costa: Amgen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding; Sanofi: Consultancy, Honoraria, Speakers Bureau; Pfizer: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria. Cutler: Deciphera: Consultancy; Cimeio: Consultancy; Editas: Consultancy; Kadmon: Consultancy; Pfizer: Consultancy; Mallinckrodt: Consultancy; CareDx: Consultancy; Incyte: Consultancy; Omeros: Consultancy; Syndax: Consultancy; Mesoblast: Consultancy; Jazz: Consultancy. Horowitz: Sobi: Research Funding; Regeneron: Research Funding; Orca Biosystems: Research Funding; Tscan: Research Funding; Xenikos: Research Funding; Miltenyi Biotech: Research Funding; Stemcyte: Research Funding; Medac: Research Funding; Vor Biopharma: Research Funding; Kite/Gilead: Research Funding; Janssen: Research Funding; Pharmacyclics: Research Funding; Kiadis: Research Funding; Seattle Genetics: Research Funding; Mesoblast: Research Funding; GlaxoSmithKline: Research Funding; Sanofi: Research Funding; Pfizer, Inc: Research Funding; Omeros: Research Funding; Magenta: Consultancy, Research Funding; Jazz Pharmaceuticals: Research Funding; Vertex: Research Funding; Genentech: Research Funding; Takeda: Research Funding; Novartis: Research Funding; Shire: Research Funding; Gamida Cell: Research Funding; Daiicho Sankyo: Research Funding; CSL Behring: Research Funding; Chimerix: Research Funding; Bristol-Myers Squibb: Research Funding; bluebird bio: Research Funding; Astellas: Research Funding; Amgen: Research Funding; Allovir: Consultancy; Actinium: Research Funding. Horwitz: Gamida Cell: Research Funding. McGuirk: Novartis: Research Funding; Magenta Therapeutics: Consultancy, Honoraria, Research Funding; EcoR1 Capital: Consultancy; Pluristem Therapeutics: Research Funding; Novartis: Research Funding; Bellicum Pharmaceuticals: Research Funding; Astelllas Pharma: Research Funding; Gamida Cell: Research Funding; Fresenius Biotech: Research Funding; Allovir: Consultancy, Honoraria, Research Funding; Juno Therapeutics: Consultancy, Honoraria, Research Funding; Kite/ Gilead: Consultancy, Honoraria, Other: travel accommodations, expense, Kite a Gilead company, Research Funding, Speakers Bureau. Rezvani: US Department of Justice: Consultancy; Kaleido: Other: One-time scientific advisory board; Nohla Therapeutics: Other: One-time scientific advisory board; Pharmacyclics-Abbvie: Research Funding. Rybka: Spark Therapeutics: Consultancy; Merck: Consultancy. Vasu: Kiadis, Inc.: Research Funding; Boehringer Ingelheim: Other: Travel support; Seattle Genetics: Other: travel support; Omeros, Inc.: Membership on an entity's Board of Directors or advisory committees.

AbstractBackgroundDaratumumab (Dara), an anti‐CD38 monoclonal antibody for hematologic malignancies, interferes with routine blood bank testing, specifically affecting the antibody screen and identification panels. In 2016, the AABB recommended performing a baseline phenotype or genotype before a patient (Pt) begins taking anti‐CD38 to avoid this interference and potential problems with transfusion. The objective of this study was to assess red blood cell (RBC) utilization and subsequent incidence of alloimmunization to the transfused RBCs in patients receiving Dara.Methods and MaterialsWe monitored 244 patients taking Dara to determine their red blood cell transfusions and incidence of clinically significant antibody formation before and following administration of Dara. Poisson generalized estimating equations with log link were used comparing the post‐Dara incidence and prevalence to those prior, with significance defined as p < .05.ResultsFrom September 1, 2015 to December 22, 2018, 244 patients on Dara were identified, of which 145 patients (59.4%) received a red blood cell transfusion. Antibody screens were performed on 97 of the 145 patients at least 2 weeks following RBC transfusion. Four of the total transfused patients (2.8% total, 4.1% patients with follow‐up antibody screen testing) formed new clinically significant alloantibodies, which was not significantly different from Asare's hematologic incidence (p = .98/p = .49).ConclusionsThis study showed our patients on Dara did not form alloantibodies following RBC transfusion at a higher incidence than similar patient populations.