Using Targeted Transcriptome and Machine Learning of Pre- and Post-Transplant Bone Marrow Samples to Predict Acute Graft-versus-Host Disease and Overall Survival after Allogeneic Stem Cell Transplantation.

Acute graft-versus-host disease (aGvHD) remains a major cause of morbidity and mortality after allogeneic hematopoietic stem cell transplantation (HSCT). We performed RNA analysis of 1408 candidate genes in bone marrow samples obtained from 167 patients undergoing HSCT. RNA expression data were used in a machine learning algorithm to predict the presence or absence of aGvHD using either random forest or extreme gradient boosting algorithms. Patients were randomly divided into training (2/3 of patients) and validation (1/3 of patients) sets. Using post-HSCT RNA data, the machine learning algorithm selected 92 genes for predicting aGvHD that appear to play a role in PI3/AKT, MAPK, and FOXO signaling, as well as microRNA. The algorithm selected 20 genes for predicting survival included genes involved in MAPK and chemokine signaling. Using pre-HSCT RNA data, the machine learning algorithm selected 400 genes and 700 genes predicting aGvHD and overall survival, but candidate signaling pathways could not be specified in this analysis. These data show that NGS analyses of RNA expression using machine learning algorithms may be useful biomarkers of aGvHD and overall survival for patients undergoing HSCT, allowing for the identification of major signaling pathways associated with HSCT outcomes and helping to dissect the complex steps involved in the development of aGvHD. The analysis of pre-HSCT bone marrow samples may lead to pre-HSCT interventions including choice of remission induction regimens and modifications in patient health before HSCT.

SOHO State of the Art Updates and Next Questions: Treatment Evolution of Mantle Cell Lymphoma: Navigating the Different Entities and Biological Heterogeneity of Mantle Cell Lymphoma in 2024.

Progress in mantle cell lymphoma (MCL) has led to significant improvement in outcomes of patients even in the real world (RW) setting albeit to a lesser degree. In parallel to the demonstration of benefit using combination therapy with rituximab plus high-dose cytarabine (R-AraC) as well as dose intensive therapy-autologous stem cell transplantation (DIT-ASCT) consolidation and maintenance, it became clear over the last 2 decades that MCL is a highly heterogenous disease at the molecular level, explaining differences observed in clinical behavior and response to therapy. While clinical prognostic factors and models have helped stratify patients with distinct outcomes, they failed to help guide therapy. The identification of molecular high-risk (HR) features, in particular, but not only, p53 aberrations (including mutations and deletions [del]), as well as complex karyotype (CK), has allowed to identify subsets of patients with poorer outcomes (median overall survival [OS] <2 years) regardless of conventional therapies used. The constant pattern of relapse seen in MCL has fueled sustained and productive efforts, with 7 novel agents approved in the United States (US), showing high and durable efficacy even in HR and chemo-refractory patients and likely curing a subset of patients in the relapsed or refractory (R/R) setting. Progress in diagnostics, in particular next-generation sequencing (NGS), which is accessible in routine practice nowadays, can help recognize patients with HR features, well beyond MIPI or Ki-67 prognostication, although the impact on decision making is still unclear. The era of integrating novel agents into our prior standard of care (SOC) has begun with a confirmed benefit, for example, ibrutinib (Ib) in the TRIANGLE study, defining the first new potential SOC in younger patients in over 30 years. Expanding on novel agents, either in combination, sequentially or to replace chemotherapy altogether, using biological doublets or triplets has led to a median progression-free survival (PFS) in excess of 72 months, certainly competitive with prior SOC and will continue to reshape the management of MCL patients. Achieving minimal residual disease negative (MRD-ve) status is becoming a new endpoint in MCL, and customizing maintenance and/or de-escalation/consolidation strategies is within reach, although it will require prospective, built-in MRD-based approaches, with the goal of eliminating subclinical disease and not simply delaying time to relapse. Taking into account the biological diversity of MCL is now feasible in routine clinical practice and has already helped recognize what not to do for HR patients (i.e., avoid intensive induction chemotherapy and/or ASCT for p53 mutated patients) as well as identify promising novel options. Ongoing and future work will help expand on these dedicated approaches, to further improve the management and outcomes of all MCL patients.

Assessment of the trueness of additively manufactured mol3% zirconia crowns at different printing orientations with an industrial and desktop 3D printer compared to subtractive manufacturing.

OBJECTIVES: This study endeavours to investigate the effect of printing orientation on the trueness of additively manufactured molar zirconia crowns. The areal surface roughness and the characteristics of the marginal regions of the crowns were also considered. METHODS: Twelve molar crowns were manufactured at 0°, 45°, and, 90° printing orientations in a Lithoz and AON zirconia printer, respectively. Twelve milled crowns were used as a comparison. Samples were scanned and analysed in metrology software to determine the trueness of the groups. Regions of interest were defined as the margins, intaglio surface and contact points. Areal surface roughness and print layer thickness were further analysed using a confocal laser scanning microscope. RESULTS: The results indicate that there are clear differences between the investigated desktop (AON) and industrial (Lithoz) 3D printer. The 45° Lithoz group is the only sample group showing no significantly different results in trueness for all regions analysed compared to the milled group. Areal surface roughness analysis indicates that the print layers in the marginal regions are within clinically tolerable limits and surface characteristics. CONCLUSIONS: The printing orientation for zirconia crowns is critical to trueness, and differences are evident between different AM apparatuses. Considerations for design and orientation between different apparatuses should therefore be considered when utilising direct additive manufacturing processes. The areal surface roughness of the marginal regions is within acceptable clinical limits for all manufacturing processes and print orientations considered. CLINICAL SIGNIFICANCE: The materials and apparatuses for additive manufacturing of zirconia crowns are now clinically acceptable from the perspective of the trueness of a final crown for critical functional surfaces and areal surface roughness of the marginal regions.

Treatment Outcomes with Standard of Care in Relapsed/Refractory Diffuse Large B-Cell Lymphoma: Real-World Data Analysis.

INTRODUCTION: Despite new therapies for relapsed or refractory (R/R) diffuse large B-cell lymphoma (DLBCL), treatments with chemotherapy, single-agent rituximab/obinutuzumab, single-agent lenalidomide, or combinations of these agents continue to be commonly used. METHODS: This retrospective study utilized longitudinal data from 4226 real-world electronic health records to characterize outcomes in patients with R/R DLBCL. Eligible patients were diagnosed with DLBCL between January 2010 and March 2022 and had R/R disease treated with ≥ 1 prior systemic line of therapy (LOT), including ≥ 1 anti-CD20-containing regimen. RESULTS: A total of 573 patients treated with ≥ 1 prior LOT were included (31.2% and 13.4% with ≥ 2 and ≥ 3 prior LOTs, respectively). Median duration of follow-up was 7.7 months. Most patients (57.1%) were male; mean standard deviation (SD) age was 63 (14.7) years. Overall and complete response rates (95% confidence interval (CI) were 52% (48-56) and 23% (19-27). Median duration of response and duration of complete response were 3.5 and 18.4 months. Median progression-free and overall survival (95% CI) was 3.0 (2.8-3.3) and 12.9 (10.1-16.9) months, respectively. Patients with a higher number of prior LOTs, primary refractoriness, refractoriness to last LOT, refractoriness to last anti-CD20-containing regimen, and prior CAR T exposure had worse outcomes (i.e., challenging-to-treat R/R DLBCL) compared with those without these characteristics. CONCLUSIONS: Outcomes in patients with R/R DLBCL treated with chemotherapy, single-agent rituximab/obinutuzumab, single-agent lenalidomide, or combinations of these agents remain poor, especially for those with challenging-to-treat R/R DLBCL. These findings underscore the unmet need for new, safe, and effective therapies, especially for challenging-to-treat R/R DLBCL populations.

Humoral and cellular immune responses against SARS-CoV-2 post-vaccination in immunocompetent and immunocompromised cancer populations.

Cancer patients are at risk for severe coronavirus disease 2019 (COVID-19) outcomes due to impaired immune responses. However, the immunogenicity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination is inadequately characterized in this population. We hypothesized that cancer vs non-cancer individuals would mount less robust humoral and/or cellular vaccine-induced immune SARS-CoV-2 responses. Receptor binding domain (RBD) and SARS-CoV-2 spike protein antibody levels and T-cell responses were assessed in immunocompetent individuals with no underlying disorders (n = 479) and immunocompromised individuals (n = 115). All 594 individuals were vaccinated and of varying COVID-19 statuses (i.e., not known to have been infected, previously infected, or "Long-COVID"). Among immunocompromised individuals, 59% (n = 68) had an underlying hematologic malignancy; of those, 46% (n = 31) of individuals received cancer treatment <30 days prior to study blood collection. Ninety-eight percentage (n = 469) of immunocompetent and 81% (n = 93) of immunocompromised individuals had elevated RBD antibody titers (>1,000 U/mL), and of these, 60% (n = 281) and 44% (n = 41), respectively, also had elevated T-cell responses. Composite T-cell responses were higher in individuals previously infected with SARS-CoV-2 or those diagnosed with Long-COVID compared to uninfected individuals. T-cell responses varied between immunocompetent vs carcinoma (n = 12) cohorts (P < 0.01) but not in immunocompetent vs hematologic malignancy cohorts. Most SARS-CoV-2 vaccinated individuals mounted robust cellular and/or humoral responses, though higher immunogenicity was observed among the immunocompetent compared to cancer populations. The study suggests B-cell targeted therapies suppress antibody responses, but not T-cell responses, to SARS-CoV-2 vaccination. Thus, vaccination continues to be an effective way to induce humoral and cellular immune responses as a likely key preventive measure against infection and/or subsequent more severe adverse outcomes. IMPORTANCE: The study was prompted by a desire to better assess the immune status of patients among our cancer host cohort, one of the largest in the New York metropolitan region. Hackensack Meridian Health is the largest healthcare system in New Jersey and cared for more than 75,000 coronavirus disease 2019 patients in its hospitals. The John Theurer Cancer Center sees more than 35,000 new cancer patients a year and performs more than 500 hematopoietic stem cell transplants. As a result, the work was undertaken to assess the effectiveness of vaccination in inducing humoral and cellular responses within this demographic.

Phase 1b dose-finding study of rituximab, lenalidomide, and ibrutinib (R2I) in patients with relapsed/refractory mantle cell lymphoma.

Mantle cell lymphoma (MCL) is a rare non-Hodgkin lymphoma that frequently becomes chemoresistant over time. The distinct mechanisms of ibrutinib and lenalidomide provided a judicious rationale to explore the combination with anti-CD20 immunotherapy. In this phase 1b study (NCT02446236), patients (n = 25) with relapsed/refractory MCL received rituximab with escalating doses of lenalidomide (days 1-21) and ibrutinib 560 mg (days 1-28) of 28-day cycles. The MTD for lenalidomide was 20 mg; most common grade ≥3 adverse events were skin rashes (32%) and neutropenic fever (24%). The best ORR was 88%, CR rate was 83%, and median duration of response (DOR) was 36.92 months (95% CI 33.77, 51.37). Responses were seen even in refractory patients or with high-risk features (e.g. blastoid variant, TP53 mutation, Ki-67 > 30%). R2I was safe and tolerable in patients with R/R MCL.

Crop Disease Identification by Fusing Multiscale Convolution and Vision Transformer.

With the development of smart agriculture, deep learning is playing an increasingly important role in crop disease recognition. The existing crop disease recognition models are mainly based on convolutional neural networks (CNN). Although traditional CNN models have excellent performance in modeling local relationships, it is difficult to extract global features. This study combines the advantages of CNN in extracting local disease information and vision transformer in obtaining global receptive fields to design a hybrid model called MSCVT. The model incorporates the multiscale self-attention module, which combines multiscale convolution and self-attention mechanisms and enables the fusion of local and global features at both the shallow and deep levels of the model. In addition, the model uses the inverted residual block to replace normal convolution to maintain a low number of parameters. To verify the validity and adaptability of MSCVT in the crop disease dataset, experiments were conducted in the PlantVillage dataset and the Apple Leaf Pathology dataset, and obtained results with recognition accuracies of 99.86% and 97.50%, respectively. In comparison with other CNN models, the proposed model achieved advanced performance in both cases. The experimental results show that MSCVT can obtain high recognition accuracy in crop disease recognition and shows excellent adaptability in multidisease recognition and small-scale disease recognition.

Identifying an optimal fludarabine exposure for improved outcomes after axi-cel therapy for aggressive B-cell non-Hodgkin lymphoma.

Fludarabine is one of the most common agents given for lymphodepletion before CD19 chimeric antigen receptor T cells, but its optimal therapeutic intensity is unknown. Using data from a multicenter consortium, we estimated fludarabine exposure (area under the curve [AUC]) using a population pharmacokinetic (PK) model in 199 adult patients with aggressive B-cell non-Hodgkin lymphomas who received commercial axicabtagene ciloleucel (Axi-cel). We evaluated the association of estimated fludarabine AUC with key outcomes, aiming to find an AUC that optimized efficacy and tolerability. We identified low (<18 mg × hour/L [mgh/L]), optimal (18-20 mgh/L), and high (>20 mgh/L) AUC groups for analyses; the 6-month cumulative incidences of relapse/progression of disease (relapse/POD) by AUC groups were 54% (45%-62%), 28% (15%-44%), and 30% (14%-47%), respectively; and the 1-year progression-free survival (PFS) rates were 39% (31%-48%), 66% (52%-84%), and 46% (30%-70%) and the overall survival (OS) rates were 58% (50%-67%), 77% (64%-92%), and 66% (50%-87%), respectively. In multivariable analyses compared with low AUC, an optimal AUC was associated with the highest PFS (hazard ratio [HR], 0.52; 0.3-0.91; P = .02) and lowest risk of relapse/POD (HR, 0.46; 0.25-0.84; P = .01) without an increased risk of any-grade cytokine release syndrome (HR, 1.1; 0.7-1.6; P = .8) or and immune effector cell-associated neurotoxicity syndrome (ICANS) (HR, 1.36; 0.83-2.3; P = .2). A high AUC was associated with the greatest risk of any-grade ICANS (HR, 1.9; 1.1-3.2; P = .02). Although the main cause of death in all groups was relapse/POD, nonrelapse-related deaths, including 3 deaths from ICANS, were more frequent in the high AUC group. These findings suggest that PK-directed fludarabine dosing to achieve an optimal AUC may result in improved outcomes for patients receiving axi-cel.

Exploring Research on the Construction and Application of Knowledge Graphs for Aircraft Fault Diagnosis.

Fault diagnosis is crucial for repairing aircraft and ensuring their proper functioning. However, with the higher complexity of aircraft, some traditional diagnosis methods that rely on experience are becoming less effective. Therefore, this paper explores the construction and application of an aircraft fault knowledge graph to improve the efficiency of fault diagnosis for maintenance engineers. Firstly, this paper analyzes the knowledge elements required for aircraft fault diagnosis, and defines a schema layer of a fault knowledge graph. Secondly, with deep learning as the main method and heuristic rules as the auxiliary method, fault knowledge is extracted from structured and unstructured fault data, and a fault knowledge graph for a certain type of craft is constructed. Finally, a fault question-answering system based on a fault knowledge graph was developed, which can accurately answer questions from maintenance engineers. The practical implementation of our proposed methodology highlights how knowledge graphs provide an effective means of managing aircraft fault knowledge, ultimately assisting engineers in identifying fault roots accurately and quickly.

Combining cell-free RNA with cell-free DNA in liquid biopsy for hematologic and solid tumors.

Current use of liquid biopsy is based on cell-free DNA (cfDNA) and the evaluation of mutations or methylation pattern. However, expressed RNA can capture mutations, changes in expression levels due to methylation, and provide information on cell of origin, growth, and proliferation status. We developed an approach to isolate cell-free total nucleic acid (cfDNA) and used targeted next generation sequencing to sequence cell-free RNA (cfRNA) and cfDNA as new approach in liquid biopsy. We demonstrate that cfRNA is overall more sensitive than cfDNA in detecting mutations. We show that cfRNA is reliable in detecting fusion genes and cfDNA is reliable in detecting chromosomal gains and losses. cfRNA levels of various solid tumor biomarkers were significantly higher (P < 0.0001) in samples from solid tumors as compared with normal control. Similarly, cfRNA lymphoid markers and cfRNA myeloid markers were all higher in lymphoid and myeloid neoplasms, respectively as compared with control (P < 0.0001). Using machine learning we demonstrate cfRNA was highly predictive of diagnosis (AUC >0.98) of solid tumors, B-cell lymphoid neoplasms, T-cell lymphoid neoplasms, and myeloid neoplasms. In evaluating the host immune system, cfRNA CD4:CD8B and CD3D:CD19 ratios in normal controls were as expected (median: 5.92 and 6.87, respectively) and were significantly lower in solid tumors (P < 0.0002). This data suggests that liquid biopsy combining analysis of cfRNA with cfDNA is practical and may provide helpful information in predicting genomic abnormalities, diagnosis of neoplasms and evaluating both the tumor biology and the host response.

The impact of immunosuppressive agents on immune checkpoint inhibitor efficacy in patients with advanced melanoma: A real-world, multicenter, retrospective study.

BACKGROUND: Immune-related adverse events (irAEs) associated with immune checkpoint inhibitors (ICIs) are often managed via immunosuppressive agents (ISAs); however, their impact on ICI efficacy is not well studied. The impact of the use of ISAs on ICI efficacy in patients with advanced melanoma was therefore investigated. METHODS: This is a real-world, multicenter, retrospective cohort study of patients with advanced melanoma who received ICIs (n = 370). Overall survival (OS) and time to treatment failure (TTF) from the time of ICI initiation were compared among patients in subgroups of interest by unadjusted and 12-week landmark sensitivity-adjusted analyses. The association of irAEs and their management with OS and TTF were evaluated using univariate and multivariable Cox proportional hazards regression models. RESULTS: Overall, irAEs of any grade and of grade ≥3 occurred in 57% and 23% of patients, respectively. Thirty-seven percent of patients received steroids, and 3% received other ISAs. Median OS was longest among patients receiving both (not reached [NR]), shorter among those receiving only systemic steroids (SSs) (84.2 months; 95% CI, 40.2 months to NR), and shortest among those who did not experience irAEs (10.3 months; 95% CI, 6-20.1 months) (p < .001). Longer OS was significantly associated with the occurrence of irAEs and the use of SSs with or without ISAs upon multivariable-adjusted analysis (p < .001). Similar results were noted with anti-programmed death 1 (PD-1) monotherapy and combination anti-PD-1 plus anti-cytotoxic T-lymphocyte antigen 4 (CTLA-4) therapy, and with 12-week landmark sensitivity analysis (p = .01). CONCLUSIONS: These findings in patients with melanoma who were treated with ICIs suggest that the use of SSs or ISAs for the management of irAEs is not associated with inferior disease outcomes, which supports the use of these agents when necessary.

Green winner determination method based on environmental performance and minimum adjustment consensus in 4PL transportation service procurement.

Due to the intensified environmental protection consciousness of enterprises and consumers, the green winner determination (GWD) considering environmental performance becomes very important for the 4PL transportation service procurement. In this paper, a new GWD method is studied, which considers different types of attributes including those related to environmental performance and the consensus reaching process (CRP). To characterize multiple types of attributes, linguistic terms, interval numbers, and crisp numbers are combined. To achieve an acceptable consensus level among linguistic evaluations given by different experts, a minimum adjustment consensus model is constructed. And on this basis, an interactive CRP is proposed. Integrating the heterogeneous information addressing process and the CRP, a HC-VIKOR method is developed to promote the 4PL's operational efficiency and service quality. Further, a numerical example is designed to demonstrate the effectiveness of the proposed method. Sensitivity analysis reveals that both the acceptable consensus threshold and the weight of group utility have a significant influence on the winner determination result. Comparison analysis shows that the proposed method outperforms the existing methods. Our study not only extends the traditional winner determination but also provides decision support for the 4PL to provide transportation services efficiently.

Differential Diagnosis of Hematologic and Solid Tumors Using Targeted Transcriptome and Artificial Intelligence.

Diagnosis and classification of tumors is increasingly dependent on biomarkers. RNA expression profiling using next-generation sequencing provides reliable and reproducible information on the biology of cancer. This study investigated targeted transcriptome and artificial intelligence for differential diagnosis of hematologic and solid tumors. RNA samples from hematologic neoplasms (N = 2606), solid tumors (N = 2038), normal bone marrow (N = 782), and lymph node control (N = 24) were sequenced using next-generation sequencing using a targeted 1408-gene panel. Twenty subtypes of hematologic neoplasms and 24 subtypes of solid tumors were identified. Machine learning was used for diagnosis between two classes. Geometric mean naïve Bayesian classifier was used for differential diagnosis across 45 diagnostic entities with assigned rankings. Machine learning showed high accuracy in distinguishing between two diagnoses, with area under the curve varying between 1 and 0.841. Geometric mean naïve Bayesian algorithm was trained using 3045 samples and tested on 1415 samples, and showed correct first-choice diagnosis in 100%, 88%, 85%, 82%, 88%, 72%, and 72% of acute lymphoblastic leukemia, acute myeloid leukemia, diffuse large B-cell lymphoma, colorectal cancer, lung cancer, chronic lymphocytic leukemia, and follicular lymphoma cases, respectively. The data indicate that targeted transcriptome combined with artificial intelligence are highly useful for diagnosis and classification of various cancers. Mutation profiles and clinical information can improve these algorithms and minimize errors in diagnoses.

Anti-spike antibody response to the COVID vaccine in lymphoma patients.

Patients with hematologic malignancies have poor outcomes from COVID infection and are less likely to mount an antibody response after COVID infection. This is a retrospective study of adult lymphoma patients who received the COVID vaccine between 12/1/2020 and 11/30/2021. The primary endpoint was a positive anti-COVID spike protein antibody level following the primary COVID vaccination series. The primary vaccination series was defined as 2 doses of the COVID mRNA vaccines or 1 dose of the COVID adenovirus vaccine. Subgroups were compared using Fisher's exact test, and unadjusted and adjusted logistic regression models were used for univariate and multivariate analyses. A total of 243 patients were included in this study; 72 patients (30%) with indolent lymphomas; 56 patients (23%) with Burkitt's, diffuse large B-cell lymphoma (DLBCL), and primary mediastinal B-cell lymphoma (PMBL) combined; 55 patients (22%) with chronic lymphocytic leukemia or small lymphocytic lymphoma (CLL/SLL); 44 patients (18%) with Hodgkin and T-cell lymphomas (HL/TCL) combined; 12 patients (5%) with mantle cell lymphoma; and 4 patients (2%) with other lymphoma types. One-hundred fifty-eight patients (65%) developed anti-COVID spike protein antibodies after completing the primary COVID vaccination series. Thirty-eight of 46 (83%) patients who received an additional primary shot and had resultant levels produced anti-COVID spike protein antibodies. When compared to other lymphoma types, patients with CLL/SLL had a numerically lower seroconversion rate of 51% following the primary vaccination series whereas patients with HL/TCL appeared to have a robust antibody response with a seropositivity rate of 77% (p = 0.04). Lymphoma patients are capable of mounting a humoral response to the COVID vaccines. Further studies are required to confirm our findings, including whether T-cell immunity would be of clinical relevance in this patient population.

Improved Survival of Lymphoma Patients with COVID-19 in the Modern Treatment and Vaccination Era.

Lymphoma patients are at greater risk of severe consequences from COVID-19 infection, yet most reports of COVID-19-associated outcomes were published before the advent of COVID-19 vaccinations and monoclonal antibodies (mAbs). In this retrospective study, we report the real-world outcomes of 68 lymphoma or CLL patients who developed COVID-19 infection during the omicron surge in the US. We found that 34% of patients were hospitalized as a result of COVID-19 infection. The death rate due to COVID-19 was 9% (6/68) in the overall population and 26% (6/23) in hospitalized patients. During the preintervention COVID-19 era, the mortality rate reported in cancer patients was 34%, which increased to 60.2% in hospitalized patients. Thus, the death rates in our study were much lower when compared to those in cancer patients earlier in the pandemic, and may be attributed to modern interventions. In our study, 60% (18/30) of patients with serology data available did not develop anti-COVID-19 spike protein antibodies following vaccination. Most patients (74%, 17/23) who were hospitalized due to COVID-19 infection did not receive COVID-19 mAb treatment. Our results pointed to the importance of humoral immunity and the protective effect of COVID-19 mAbs in improving outcomes in lymphoma patients.

Reliability of Cell-Free DNA and Targeted NGS in Predicting Chromosomal Abnormalities of Patients With Myeloid Neoplasms.

Introduction: Cytogenetic analysis is important for stratifying patients with various neoplasms. We explored the use of targeted next generation sequencing (NGS) in detecting chromosomal structural abnormalities or copy number variations (CNVs) in patients with myeloid neoplasms. Methods: Plasma cell-free DNA (cfDNA) from 2821 myeloid or lymphoid neoplasm patients were collected. cfDNA was sequenced using a 275 gene panel. CNVkit software was used for analyzing and visualizing CNVs. Cytogenetic data from corresponding bone marrow (BM) samples was available on 89 myeloid samples. Results: Of the 2821 samples, 1539 (54.5%) showed evidence of mutations consistent with the presence of neoplastic clones in circulation. Of these 1539 samples, 906 (59%) showed abnormalities associated with myeloid neoplasms and 633 (41%) with lymphoid neoplasms. Chromosomal structural abnormalities in cfDNA were detected in 146 (16%) myeloid samples and 76 (12%) lymphoid samples. Upon comparison of the myeloid samples with 89 BM patients, NGS testing was able to reliably detect chromosomal gain or loss, except for fusion abnormalities. When cytogenetic abnormalities were classified according to prognostic classes, there was a complete (100%) concordance between cfDNA NGS data and cytogenetic data. Conclusions: This data shows that liquid biopsy using targeted NGS is reliable in detecting chromosomal structural abnormalities in myeloid neoplasms. In specific circumstances, targeted NGS may be reliable and efficient to provide adequate information without the need for BM biopsy considering broad mutation profiling can be obtained through adequate sequencing within the same test. Overall, this study supports the use of liquid biopsy for early diagnosis and monitoring of patients with myeloid neoplasms.

A multicenter retrospective study of polatuzumab vedotin in patients with large B-cell lymphoma after CAR T-cell therapy.

Polatuzumab vedotin (PV) is an antibody-drug conjugate targeting CD79b that is approved for patients with relapsed/refractory large B-cell lymphoma (LBCL). Patients who relapse after chimeric antigen receptor (CAR) T-cell therapy were not included in the registration study, and reports of PV use after CAR T cells are limited. This multicenter retrospective analysis included patients with LBCL who relapsed or progressed after CAR T-cell therapy and subsequently received PV with or without rituximab and bendamustine between July 2019 and May 2021. Response to treatment and progression were assessed based on the 2014 Lugano criteria. Fifty-seven patients were included in the study: 18 (32%) patients were primary refractory to CAR T-cell therapy, and 34 (60%) patients received PV-based therapy immediately after CAR T-cell therapy. PV was combined with rituximab in 54 (95%) patients and administered with bendamustine in 35 (61%) patients. A response was achieved in 25 (44%) patients, including complete remission in 8 (14%). No significant association between baseline characteristics and response was observed. After a median follow-up of 47 weeks (95% confidence interval [CI], 40-54), 46 (81%) patients had disease progression or died, and the median progression-free survival was 10 weeks (95% CI, 5-15). On a multivariate analysis, bone marrow involvement (hazard ratio, 5.2; 95% CI, 1.8-15; P = .003) and elevated lactate dehydrogenase levels (hazard ratio, 5.0; 95% CI, 1.4-16; P = .01) were associated with shorter progression-free survival. Studies aimed at better characterizing the intrinsic mechanism of resistance and identifying optimal consolidation strategies for these patients are warranted.

Validation of a Population-Based Data Source to Examine National Cancer Clinical Trial Participation.

Importance: The Centers for Medicare & Medicaid Services requires health care organizations to report the National Clinical Trial (NCT) identifier on claims for items and services related to clinical trials that qualify for coverage. This same NCT identifier is used to identify clinical trials in the ClinicalTrials.gov registry. If linked, this information could facilitate population-based analyses of clinical trial participation and outcomes. Objective: To evaluate the validity of a linkage between fee-for-service (FFS) Medicare claims and ClinicalTrials.gov through the NCT identifier for patients with cancer enrolled in clinical trials. Design, Setting, and Participants: This cohort study included 2 complementary retrospective analyses for a validation assessment. First, billing data from 3 health care institutions were used to estimate the missingness of the NCT identifier in claims by calculating the proportion of known participants in cancer clinical trials with no NCT identifier on any submitted Medicare claims. Second, the Surveillance Epidemiology and End Results-Medicare data set, which includes a subset of all FFS Medicare beneficiaries for whom health insurance claims are linked with cancer registry data, was used to identify adult patients diagnosed with cancer between 2006 and 2015 with an NCT identifier in claims corresponding to an interventional cancer clinical trial. To estimate the accuracy of the NCT identifier when present, the proportion of NCT identifiers that corresponded to trials that were aligned with the patients' known primary or secondary diagnoses was calculated. Data were analyzed from March 2020 to March 2021. Exposures: An NCT identifier present in Medicare claims. Main Outcomes and Measures: The main outcome was participating in a clinical trial relevant to patient's cancer diagnosis. Results: A total of 1 171 816 patients were included in analyses. Across the 3 participating institutions, there were 5061 Medicare patients enrolled in a clinical trial, including 3797 patients (75.0%) with an NCT identifier on at least 1 billing claim that matched the clinical trial on which the patient was participating. Among 1 171 816 SEER-Medicare patients, 29 138 patients (2.5%) had at least 1 claim with a value entered in the NCT identifier field corresponding to 32 950 unique patient-NCT identifier pairs. There were 26 694 pairs (81.0%) with an NCT identifier corresponding to a clinical trial registered in ClinicalTrials.gov, of which 10 170 pairs (38.1%) were interventional cancer clinical trials. Among these, 9805 pairs (96.4%) were considered appropriate. Conclusions and Relevance: In this cohort study, this data linkage provided a novel data source to study clinical trial enrollment patterns among Medicare patients with cancer on a population level. The presence of the NCT identifiers in claims for Medicare patients participating in clinical trials is likely to improve over time with increasing adherence with the Centers for Medicare & Medicaid Services mandate.

Clotting events among hospitalized patients infected with COVID-19 in a large multisite cohort in the United States.

INTRODUCTION: COVID-19 infection has been hypothesized to precipitate venous and arterial clotting events more frequently than other illnesses. MATERIALS AND METHODS: We demonstrate this increased risk of blood clots by comparing rates of venous and arterial clotting events in 4400 hospitalized COVID-19 patients in a large multisite clinical network in the United States examined from April through June of 2020, to patients hospitalized for non-COVID illness and influenza during the same time period and in 2019. RESULTS: We demonstrate that COVID-19 increases the risk of venous thrombosis by two-fold compared to the general inpatient population and compared to people with influenza infection. Arterial and venous thrombosis were both common occurrences among patients with COVID-19 infection. Risk factors for thrombosis included male gender, older age, and diabetes. Patients with venous or arterial thrombosis had high rates of admission to the ICU, re-admission to the hospital, and death. CONCLUSION: Given the ongoing scientific discussion about the impact of clotting on COVID-19 disease progression, these results highlight the need to further elucidate the role of anticoagulation in COVID-19 patients, particularly outside the intensive care unit setting. Additionally, concerns regarding clotting and COVID-19 vaccines highlight the importance of addressing the alarmingly high rate of clotting events during actual COVID-19 infection when weighing the risks and benefits of vaccination.