Citations

Background: Periprosthetic joint infections (PJIs) following total hip arthroplasty (THA) and total knee arthroplasty (TKA) are associated with substantial morbidity. A better understanding of the costs of PJI treatment can inform prevention, treatment, and reimbursement strategies. The purpose of the present study was to describe direct inpatient medical costs associated with the treatment of hip and knee PJI. Methods: At a single tertiary care institution, 176 hips and 266 knees that underwent 2-stage revisions for the treatment of PJI from 2009 to 2015 were compared with 1,611 hips and 1,276 knees that underwent revisions for aseptic indications. In addition, 84 hips and 137 knees that underwent irrigation and debridement (I&D) with partial component exchange were compared with 39 hips and 138 knees that underwent partial component exchange for aseptic indications. Line-item details of services billed during hospitalization were retrieved, and standardized direct medical costs were calculated in 2018 inflation-adjusted dollars. Results: The mean direct medical cost of 2-stage revision THA performed for the treatment of PJI was significantly higher than that of aseptic revision THA ($58,369 compared with $22,846, p < 0.001). Similarly, the cost of 2-stage revision TKA performed for the treatment of PJI was significantly higher than that of aseptic revision TKA ($56,900 compared with $24,630, p < 0.001). Even when the total costs of aseptic revisions were doubled for a representative comparison with 2-stage procedures, the costs of PJI procedures were 15% to 28% higher than those of the doubled costs of aseptic revisions (p < 0.001). The mean direct medical cost of I&D procedures for PJI was about twofold higher than of partial component exchange for aseptic indications. Conclusions: The direct medical costs of operative treatment of PJI following THA and TKA are twofold higher than the costs of similar aseptic revisions. The high economic burden of PJI warrants efforts to reduce the incidence of PJI. Reimbursement schemes should account for the high costs of treating PJI in order to ensure sustainable patient care. Level of Evidence: Economic Level IV . See Instructions for Authors for a complete description of levels of evidence.

Background: Increased parasympathetic activity is thought to play important roles in syncope events of patients with vasovagal syncope (VVS). However, direct measurements of the vagal control are difficult. The novel deceleration capacity (DC) of heart rate measure has been used to characterize the vagal modulation. This study aimed to assess vagal control in patients with VVS and evaluate the diagnostic value of the DC in VVS. Methods: Altogether, 161 consecutive patients with VVS (43±15 years; 62 males) were enrolled. Tilt table test was positive in 101 and negative in 60 patients. Sixty-five healthy subjects were enrolled as controls. DC and heart rate variability in 24-hour ECG, echocardiogram, and biochemical examinations were compared between the syncope and control groups. Results: DC was significantly higher in the syncope group than in the control group (9.6±3.3 versus 6.5±2.0 ms, P <0.001). DC was similarly increased in patients with VVS with a positive and negative tilt table test (9.7±3.5 and 9.4±2.9 ms, P =0.614). In multivariable logistic regression analyses, DC was independently associated with syncope (odds ratio=1.518 [95% CI, 1.301–1.770]; P =0.0001). For the prediction of syncope, the area under curve analysis showed similar values when comparing single DC and combined DC with other risk factors ( P =0.1147). From the receiver operator characteristic curves for syncope discrimination, the optimal cutoff value for the DC was 7.12 ms. Conclusions: DC>7.5 ms may serve as a good tool to monitor cardiac vagal activity and discriminate VVS, particularly in those with negative tilt table test.

Background: An artificial intelligence (AI) algorithm applied to electrocardiography during sinus rhythm has recently been shown to detect concurrent episodic atrial fibrillation (AF). We sought to characterize the value of AI–enabled electrocardiography (AI-ECG) as a predictor of future AF and assess its performance compared with the CHARGE-AF score (Cohorts for Aging and Research in Genomic Epidemiology–AF) in a population-based sample. Methods: We calculated the probability of AF using AI-ECG, among participants in the population-based Mayo Clinic Study of Aging who had no history of AF at the time of the baseline study visit. Cox proportional hazards models were fit to assess the independent prognostic value and interaction between AI-ECG AF model output and CHARGE-AF score. C statistics were calculated for AI-ECG AF model output, CHARGE-AF score, and combined AI-ECG and CHARGE-AF score. Results: A total of 1936 participants with median age 75.8 (interquartile range, 70.4–81.8) years and median CHARGE-AF score 14.0 (IQR, 13.2–14.7) were included in the analysis. Participants with AI-ECG AF model output of >0.5 at the baseline visit had cumulative incidence of AF 21.5% at 2 years and 52.2% at 10 years. When included in the same model, both AI-ECG AF model output (hazard ratio, 1.76 per SD after logit transformation [95% CI, 1.51–2.04]) and CHARGE-AF score (hazard ratio, 1.90 per SD [95% CI, 1.58–2.28]) independently predicted future AF without significant interaction ( P =0.54). C statistics were 0.69 (95% CI, 0.66–0.72) for AI-ECG AF model output, 0.69 (95% CI, 0.66–0.71) for CHARGE-AF, and 0.72 (95% CI, 0.69–0.75) for combined AI-ECG and CHARGE-AF score. Conclusions: In the present study, both the AI-ECG AF model output and CHARGE-AF score independently predicted incident AF. The AI-ECG may offer a means to assess risk with a single test and without requiring manual or automated clinical data abstraction.

Abstract: Title: Architecture of sample preparation and data governance of Immuno-genomic data collected from bone marrow and peripheral blood samples obtained from multiple myeloma patients In multiple myeloma (MM), the interactions between malignant plasma cells and the bone marrow microenvironment is crucial to fully understand tumor development, disease progression, and response to therapy. The core challenge in understanding those interactions has been the establishment of a standard process and a standard model for handling the data quality workflow and the underlying data models. Here we present the Platform (Figure 1), an integrated data flow architecture designed to create data inventory and process tracking protocols for multi-dimensional and multi-technology immune data files. This system has been designed to inventory and track peripheral blood and bone marrow samples from multiple myeloma subjects submitted for immune analysis under the MMRF Immune Atlas initiative (figure 2), and the processing and storage of Single Cell RNA-seq (scRNA-seq) and Mass Cytometry time-of-flight (CyTOF) data files derived from these immune analyses. While these methods have been previously applied on both tumor and immune populations in MM [2,3], this level of multi-institutional and multi-technology is unique. The Cloud Immune-Precision platform contains standardized protocols and bioinformatics workflows for the identification and categorization of immune cell populations and functional states based upon scRNA-seq gene signatures (ref: Bioinformatics manuscript in submission) and CyTOF protein signatures. Upon further expansion, it will contain high dimensional scRNAseq and CyTOF immune data from both bone marrow and peripheral blood samples from myeloma patients enrolled in the Multiple Myeloma Research Foundation (MMRF) CoMMpass study (NCT01454297) [1] (Figure 3). The architecture covers the automation of data governance protocols, data transformation and ETL model developments that will create an immune proteomic and profiling database and its integration into clinical and genomics databases: e.g. the MMRF CoMMpass clinical trial. This large-scale data integration will establish a cutting-edge Immune-Precision central platform supporting large scale, immune-focused advanced analytics in multiple myeloma patients. This platform will allow researchers to interrogate the relationships between immune transcriptomic and proteomic signatures and tumor genomic features, and their impact on clinical outcomes, to aid in the optimization of therapy and therapeutic sequencing. Furthermore, this platform also promotes the potential to (further) elucidate the mechanisms-of-action of approved and experimental myeloma therapies, drive biomarker discovery, and identify new targets for drug discovery. Figure 1: Cloud Immune-Precision Platform (Integrated data flow architecture designed to create data inventory and process tracking protocols for multi-dimensional and multi-technology immune data files) Figure 2: Sample tracking process architecture Figure 3: Data file creation and repository process tracking References: 1- Settino, Marzia et al. "MMRF-CoMMpass Data Integration and Analysis for Identifying Prognostic Markers." Computational Science - ICCS 2020: 20th International Conference, Amsterdam, The Netherlands, June 3-5, 2020, Proceedings, Part III vol. 12139 564-571. 22 May. 2020, doi:10.1007/978-3-030-50420-5_42 2- Ledergor, Guy et al. "Single cell dissection of plasma cell heterogeneity in symptomatic and asymptomatic myeloma." Nature medicine vol. 24,12 (2018): 1867-1876. doi:10.1038/s41591-018-0269-2 3- Hansmann, Leo et al. "Mass cytometry analysis shows that a novel memory phenotype B cell is expanded in multiple myeloma." Cancer immunology research vol. 3,6 (2015): 650-60. doi:10.1158/2326-6066.CIR-14-0236-T Figure 1 Disclosures Bhasin: Canomiiks Inc: Current equity holder in private company, Other: Co-Founder. Dhodapkar:Amgen: Membership on an entity's Board of Directors or advisory committees, Other; Celgene/BMS: Membership on an entity's Board of Directors or advisory committees, Other; Janssen: Membership on an entity's Board of Directors or advisory committees, Other; Roche/Genentech: Membership on an entity's Board of Directors or advisory committees, Other; Lava Therapeutics: Membership on an entity's Board of Directors or advisory committees, Other; Kite: Membership on an entity's Board of Directors or advisory committees, Other.

Deregulated transcription and cell cycle control are hallmarks of cancer that are especially frequent in multiple myeloma (MM). Largely non-overlapping sets of cyclin-dependent kinases (CDKs) regulate cell division and RNA polymerase II (Pol II)-dependent transcription; and targeting of cell cycle CDKs has been long pursued as an attractive therapeutic strategy. Among CDKs, CDK7 presents a unique therapeutic opportunity as it functions as a CDK activating kinase (CAK), licensing the activity of cell cycle CDKs, and also serves as a core component of the general transcription factor TFIIH. Here we elucidated the biological role of CDK7 and its transcriptional regulatory landscape in MM, using genetic as well chemical approaches, including tools for CDK7 rapid protein degradation (dTAG) and the selective covalent inhibitor YKL-5-124 that targets a cysteine residue (C312) located outside of the kinase domain. We have observed that CDK7 inhibition via YKL-5-124 robustly inhibited the phosphorylation of the CDK1, 2 and 4 activation loops in a representative panel of MM cell lines at concentrations as low as 50 nM. This reduction was not observed in MM cells expressing a resistant mutation in the reactive cysteine (C312S). Consistent with decrease of CAK activity, we observed G1 arrest and S phase loss after CDK7 inhibition, which was also associated with a rapid and transient loss of Ser2 and Ser5 phosphorylation of the RNA Pol2 C-terminal domain. To understand the effect of CDK7 inhibition on MM cell growth and viability, we evaluated activity of YKL-5-124 across a large panel of 25 MM cell lines and observed a significant inhibition of MM cell proliferation, with a significantly lower IC50 compared to PHA-activated normal donor peripheral blood mononuclear cells (PBMCs), suggesting a specific sensitivity of MM cells to CDK7 inhibition. Longer exposure to YKL-5-124 caused apoptotic cell death in MM cells; however treatment with an inactive analog or in cells expressing the C312S mutation failed to inhibit MM cell proliferation, confirming that the antiproliferative potency of YKL-5-124 resides in its unique characteristic to covalently bind to C312 domain. Importantly, CDK7 inhibition impaired primary MM cells proliferation alone and when cultured in the presence of BM microenvironment. Selective pharmacological degradation of endogenously tagged CDK7 confirmed impact of CDK7 inhibition on MM cell proliferation via inhibition of CDK7 transcriptional and cell cycle activities. To complement the pharmacological studies, we have established MM cells to express inducible CRISPR/Cas9 constructs encoding 4 independent small guide RNAs targeting CDK7, resulting in the reduction of the abundance of CDK7 protein by 20-60% which was sufficient to inhibit MM cell viability over time, phenocopying pharmacologic inhibition of CDK7. These results support the view that CDK7 is a pharmacologically relevant target for MM. Gene expression analysis after CDK7 inhibition in MM1S and H929 cells revealed that transcripts for only a subset of genes were substantially affected by treatment with low dose of YKL-5-124, showing a strong leading-edge enrichment for downregulation of E2F expression program, cell cycle, DNA damage, and MYC targets. We have indeed confirmed a potent reduction in phosphorylation of RB protein, with consequent decrease of E2F activity in MM cells confirmed using E2F-driven luciferase reporter. These data suggest significant role for CDK7 in the CDK-pRB-E2F pathway in MM, which was strengthened by the observation of a positive correlation between expression of CDK7 and expression of E2F target genes in primary MM cells (n=409). Finally, we have evaluated the in vivo effect of CDK7 inhibition in several murine models of human MM. In the localized subcutaneous model, and the disseminated MM model where treatment with YKL-5-124 decreased tumor burden and improved survival. The effect of CDK7 inhibition explored in an aggressive, genetically engineered model of Myc-dependent MM, revealed evidence of response by decline in measurement of monotypic serum immunoglobulins. In conclusion, our study demonstrates that CDK7 contributes to the 'transcriptional addiction' and the cell cycle deregulation frequently observed in MM and represents an attractive molecular vulnerability to be exploited therapeutically. Disclosures Anderson: Millenium-Takeda: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Sanofi-Aventis: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Oncopep and C4 Therapeutics.: Other: Scientific Founder of Oncopep and C4 Therapeutics.; Celgene: Membership on an entity's Board of Directors or advisory committees. Munshi:Takeda: Consultancy; Karyopharm: Consultancy; AbbVie: Consultancy; Amgen: Consultancy; Legend: Consultancy; Adaptive: Consultancy; Janssen: Consultancy; C4: Current equity holder in private company; OncoPep: Consultancy, Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties; BMS: Consultancy. Fulciniti:NIH: Research Funding.

Compared with traditional bulk sequencing technologies, single-cell technologies have advantages to evaluate cellular heterogeneity and investigate the evolution of cellular subpopulations from the tumor and microenvironment. Application of single-cell sequencing in Multiple Myeloma (MM) is especially beneficial given MM is a highly heterogeneous disease with uncontrolled clonal expansion of plasma cells. Single-cell RNA sequencing (scRNA-seq) has been previously utilized to understand this hematopoietic malignancy in both tumor and immune populations in MM (Ledergor G. et al., 2018, Zavidij, O. et al., 2020). Mass cytometry (CyTOF) has also been used to identify the expansion of novel memory B cells in MM. (Hansmann, L. et al., 2015). Among the various single cell techniques, cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) is a multimodal approach with simultaneous quantification of single-cell transcriptomes and surface proteins. Since these three single-cell approaches enable the identification of cell types, cell states and characterization of cellular heterogeneity at transcriptomic and/or protein levels, understanding the concordance of the measurements among these three modalities is of great interest. We applied scRNA-seq, CyTOF and CITE-seq on four baseline samples of CD138-negative 'immune cell' fractions from patients enrolled in the MMRF CoMMpass study (NCT01454297). Two subjects were fast progressors (PFS &lt; 18 months) and two subjects were non-progressors (PFS not reached). With multi-center collaboration coordinated by Multiple Myeloma Research Foundation (MMRF), each sample was subject to scRNA-seq and CyTOF by 3 independent centers. All sites received aliquots of the same sample. On average, 1,060 immune cells were detected in each sample using scRNA-seq and &gt;64K CD45+ cells were detected using CyTOF. CITE-seq was performed in one center and 4,805 CD138-negative immune cells were identified on average. To compare cell type abundance between scRNA-seq, CyTOF and CITE-seq, we calculated the cell subset frequency of each immune population relative to the CD45+ populations. Overall, all three approaches were concordant while there is a stronger concordance between scRNA-seq and CyTOF. Cell type abundance is especially consistent for B cells, monocytes/macrophages, and plasmacytoid dendritic cells (pDC) among the 3 methods. For the same patient of interest, natural killer (NK) cell frequency was detected at the lowest level in CyTOF relative to scRNA and CITE-seq. The T cell population showed the highest discrepancy among techniques, with highest abundance in scRNA-seq followed by CyTOF and lowest abundance in CITE-seq. Interestingly, CITE-seq detected far less CD4 T cells compared to the other two techniques while CD8 T cell frequency did not show drastic differences. In addition to cell type abundance, we further examined the concordance of expression of cell type signature genes between scRNA-seq and CyTOF. Overall, expression between RNA-level and protein-level is positively correlated with typical cell type markers highly expressed in both techniques, especially in the following cell populations: CD8+ T cells (CD3, CD8), NK cells (CD56, GranzymeB/GZMB, NKG2A/KLRC1), B cells (CD19, CD38), Monocytes (CD14, CD11c/ITGAX, CD33). To note, although the concordance in CD4+ T cells is generally good, we found the expression of CD4 is higher in CyTOF compared to scRNA-seq whereas CD127/IL7R tends to be overexpressed in scRNA-seq. This could explain why IL7R is often identified as a differentially expressed gene (DEG) in CD4+ T cell population while CD4 is barely seen in DEG list in scRNA-seq analysis. It is also interesting to notice that the expression of most NK cell markers has strong concordance between scRNA-seq and CyTOF except NKG2D/KLRK1, which has much higher expression in CyTOF relative to scRNA-seq. Our preliminary results suggested good concordance of immune cell type abundance identified in CyTOF, scRNA-seq and CITE-seq as well as concordant expression of some canonical cell type markers between RNA level and protein level. This work provides the field with reference data sets and shows more detailed examination of NK and T cell subsets is needed when handling single cell sequencing with different modalities. Disclosures Dhodapkar: Roche/Genentech: Membership on an entity's Board of Directors or advisory committees, Other; Lava Therapeutics: Membership on an entity's Board of Directors or advisory committees, Other; Kite: Membership on an entity's Board of Directors or advisory committees, Other; Janssen: Membership on an entity's Board of Directors or advisory committees, Other; Celgene/BMS: Membership on an entity's Board of Directors or advisory committees, Other; Amgen: Membership on an entity's Board of Directors or advisory committees, Other. Kumar:MedImmune: Research Funding; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Carsgen: Other, Research Funding; Merck: Consultancy, Research Funding; Adaptive Biotechnologies: Consultancy; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Kite Pharma: Consultancy, Research Funding; Novartis: Research Funding; Sanofi: Research Funding; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Tenebio: Other, Research Funding; Karyopharm: Consultancy; BMS: Consultancy, Research Funding; Genecentrix: Consultancy; Cellectar: Other; Dr. Reddy's Laboratories: Honoraria. Gnjatic:Neon Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees; OncoMed: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Research Funding; Genentech: Research Funding; Immune Design: Research Funding; Agenus: Research Funding; Janssen R&D: Research Funding; Pfizer: Research Funding; Takeda: Research Funding; Regeneron: Research Funding; Merck: Consultancy, Membership on an entity's Board of Directors or advisory committees. Bhasin:Canomiiks Inc: Current equity holder in private company, Other: Co-Founder.

AbstractMolecular prognostic factors for individualized treatment of squamous cell carcinoma (SCC) are poorly defined. Our study developed and validated a novel molecular tools aid in preinguinal and postinguinal lymphadenectomy risk stratification in node‐positive penile SCC. Patients with node‐positive penile SCC who underwent inguinal or ilioinguinal lymphadenectomy were divided into three cohorts: a discovery set, a development set and a validation set. The local ethics committee approved the study. The primary endpoint was cancer‐specific survival (CSS). At the discovery stage, 17 CpG sites were significantly associated with CSS. In the development set, we constructed a 3‐CpG‐based prognostic score for survival prediction. The hazard ratio (HR) of the panel (dichotomized using the optimal cutoff) was 5.8 in the multivariate analyses (P < .001). The addition of the methylation score significantly improved the pN‐stage C‐index from 0.70 to 0.79 (incremental C = 0.09, P < .001). In the validation set, the methylation panel showed a HR of 9.9 in the multivariate analyses. The addition of the molecular marker improved the pN‐stage C‐index from 0.69 to 0.78 (incremental C = 0.09, P < .001). The methylation score remarkably separated survival curves in different pN stages, which indicate that the tool can be applied to tailor the treatment in both preinguinal and postinguinal lymphadenectomy settings. We developed and validated a prognostic methylation panel for node‐positive penile SCC. The tool may aid in the risk stratification of the population with heterogeneous outcomes and needs prospective validation. Patients in high‐risk group may benefit from more aggressive therapy or clinical trials.

Background: Patients with atrial fibrillation and severely decreased kidney function were excluded from the pivotal non–vitamin K antagonist oral anticoagulants (NOAC) trials, thereby raising questions about comparative safety and effectiveness in patients with reduced kidney function. The study aimed to compare oral anticoagulants across the range of kidney function in patients with atrial fibrillation. Methods and Results: Using a US administrative claims database with linked laboratory data, 34 569 new users of oral anticoagulants with atrial fibrillation and estimated glomerular filtration rate ≥15 mL/(min·1.73 m 2 ) were identified between October 1, 2010 to November 29, 2017. The proportion of patients using NOACs declined with decreasing kidney function—73.5%, 69.6%, 65.4%, 59.5%, and 45.0% of the patients were prescribed a NOAC in estimated glomerular filtration rate ≥90, 60 to 90, 45 to 60, 30 to 45, 15 to 30 mL/min per 1.73 m 2 groups, respectively. Stabilized inverse probability of treatment weighting was used to balance 4 treatment groups (apixaban, dabigatran, rivaroxaban, and warfarin) on 66 baseline characteristics. In comparison to warfarin, apixaban was associated with a lower risk of stroke (hazard ratio [HR], 0.57 [0.43–0.75]; P <0.001), major bleeding (HR, 0.51 [0.44–0.61]; P <0.001), and mortality (HR, 0.68 [0.56–0.83]; P <0.001); dabigatran was associated with a similar risk of stroke but a lower risk of major bleeding (HR, 0.57 [0.43–0.75]; P <0.001) and mortality (HR, 0.68 [0.48-0.98]; P =0.04); rivaroxaban was associated with a lower risk of stroke (HR, 0.69 [0.51–0.94]; P =0.02), major bleeding (HR, 0.84 [0.72–0.99]; P =0.04), and mortality (HR, 0.73 [0.58–0.91]; P =0.006). There was no significant interaction between treatment and estimated glomerular filtration rate categories for any outcome. When comparing one NOAC to another NOAC, there was no significant difference in mortality, but some differences existed for stroke or major bleeding. No relationship between treatments and falsification end points was found, suggesting no evidence for substantial residual confounding. Conclusions: Relative to warfarin, NOACs are used less frequently as kidney function declines. However, NOACs appears to have similar or better comparative effectiveness and safety across the range of kidney function.