National Center For Advancing Translational Sciences Research Articles

Machine learning with electrocardiograms to optimize mortality risk stratification in patients with suspected acute coronary syndrome

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Heart, Lung, and Blood Institute (NHLBI) and National Center for Advancing Translational Sciences (NCATS). Background The importance of risk stratification in patients with suspected acute coronary syndrome (ACS) extends beyond diagnosis and immediate treatment. It influences the precision of care delivery and the allocation of resources to those at highest risk of adverse events. Purpose We sought to evaluate the prognostic value of electrocardiogram (ECG) feature-based machine learning models to risk-stratify long-term mortality in those with suspected ACS. Methods This was a multicenter prospective observational cohort study of consecutive, non-traumatic patients evaluated at the emergency department for suspected ACS. The derivation cohort included 4,015 patients from a University Medical Center (age 59±16 years, 47% women, 80% training with 10-fold cross-validation and 20% testing). Ascertainment of all-cause death was based on numerous data sources, including the Centers for Disease Control and Prevention’s National Death Index registry. We trained six machine learning methods for survival analysis using 73 morphological ECG features from presenting prehospital 10-second 12-lead ECGs. We used predicted risk scores in a variational Bayesian Gaussian mixture model to define three risk groups corresponding to low, moderate, and high-risk and compared the resulting classification performance against the HEART score. The external testing cohort included 3,095 patients from a University (age 59±15 years, 44% women). Results The mortality rate was 20.3% in the derivation cohort after an average follow-up period of 3.53 years (IQR 1.75 - 5.32). Extra Survival Trees outperformed other forecasting models during cross-validation. In the internal testing cohort, the derived risk groups were significantly predictive of survival (Kaplan-Meier log-rank test statistic = 121.14, p<0.001), outperforming the classification performance using the HEART score (Figure 1). Our machine learning-based risk stratification model detected >90% of death events missed by low-risk HEART score (Figure 2). Ruling-out the low-risk group, it achieved a negative predictive value of 93.4% with a sensitivity of 85.9% (compared to 89.0% and 75.0%, respectively, for the HEART score). This classification performance generalized well to our external testing cohort. Compared to those in the low-risk group, patients at moderate (OR = 3.62 [1.35-9.74]) and high (OR = 6.12 [2.38-15.75]) risk had significantly higher odds of 30-day cardiovascular death (n=109, 3.5%). Conclusions Using only features from the 10-second 12-lead ECG, we derived and externally validated a machine learning model that stratifies the mortality risk of patients during long-term follow up. This model outperformed current standard of care based on the HEART score. Future work should validate the potential of this decision-support tool in influencing treatment plans and resource allocation.Figure 1.Clustering performanceFigure 2.Sankey diagram

Abstract 4301: Increasing the therapeutic vulnerability of heterogenous cell phenotypes within prostate cancer

Abstract Phenotype heterogeneity is a hallmark of prostate adenocarcinoma and is a major source of recurrent disease. We tested pre-clinical therapies to eradicate phenotypically distinct cell populations derived from the parental DU145WT prostate cancer cell line. The derived cell lines are called DU145AA, DU145J7, and DU145G6. The DU145AA variant is a non-aggressive cell population while the DU145J7 and DU145G6 are aggressive phenotypes that invade through muscle and metastasize to bone. Flow cytometry analysis documented the phenotypic plasticity of the DU145 cell variants since DU145 aggressive lines expressed 1.3-fold increases in matrix metalloprotease 14 surface expression and a 2-fold increase in tri-methyl Histone H3 at lysine 27 as compared to the DU145WT parent line. The DU145AA non-aggressive line expressed an epithelial cell-cell lineage phenotype with up to 2-fold increases in E-cadherin, claudin 4, claudin 7, and a unique cytokeratin 6A expression and a 2-fold loss of Zinc finger E-box-binding homeobox 1, EVL, and Kindlin 2. A collaboration with the National Center for Advancing Translational Science (NCATS) resulted in the identification of pharmacological agents active in eradicating DU145J7 and DU145G6 cells as compared to the DU145WT population. The agents were selected from a quantitative high-throughput screen of 10,677 combined investigative and approved anti-cancer agents using the Cell Titer-Glo Luminescent Cell Viability assay. We independently validated 31 compounds from the assay that have 2-fold, or greater, differences in concentration to inhibit 50% cell growth (IC50) between the wild-type and aggressive variants of DU145 cells. The top 10 hits were tested for the efficacy of different combinations to eradicate defined admixtures of aggressive and non-aggressive phenotypes, including the DU145AA cells, to model tumor heterogeneity. Tested compounds with differential sensitivity between aggressive and non-aggressive cells were those inhibiting histone deacetylase (vorinostat, fimepinostat, and pracinostat), proteasomes (bortezomib, delanzomib, ixazomib), topoisomerases (gimatecan and daunorubicin), and other compounds identified independently by us targeting nicotinamide phosphoribosyl transferase (FK866) and DNA (bleomycin). Using admixtures of tumor cell phenotypes, we determined optimal combinations of compounds that would selectively eradicate the sub-populations. The results suggest that determination of phenotypes within tumor populations may eliminate the heterogenous tumor and prevent recurrent disease. Funding was provided by the University of Arizona Cancer Center (NCI-P30 CA23074 and NCI-R01 CA159406) and by the Partnership in Native American Cancer Prevention at the University of Arizona (U54CA143924) and Northern Arizona University (U54CA143925). Collaborators at NCATS were supported by the intramural research program. Citation Format: Allan I. Paxson, Loren H. Chang, Kendra D. Marr, Jaime M. Gard, Colin S. Nelson, Abhijeet Kapoor, William L. Harryman, Juan J. Marugan, Mark J. Henderson, Tino W. Sanchez, Anne E. Cress. Increasing the therapeutic vulnerability of heterogenous cell phenotypes within prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4301.

Neutralizing IFN-γ autoantibodies are rare and pathogenic in HLA-DRB1*15:02 or 16:02 individuals.

BACKGROUNDWeakly virulent environmental mycobacteria (EM) can cause severe disease in HLA-DRB1*15:02 or 16:02 adults harboring neutralizing anti-IFN-γ autoantibodies (nAIGAs). The overall prevalence of nAIGAs in the general population is unknown, as are the penetrance of nAIGAs in HLA-DRB1*15:02 or 16:02 individuals and the proportion of patients with unexplained, adult-onset EM infections carrying nAIGAs.METHODSThis study analyzed the detection and neutralization of anti-IFN-γ autoantibodies (auto-Abs) from 8,430 healthy individuals of the general population, 257 HLA-DRB1*15:02 or 16:02 carriers, 1,063 patients with autoimmune disease, and 497 patients with unexplained severe disease due to EM.RESULTSWe found that anti-IFN-γ auto-Abs detected in 4,148 of 8,430 healthy individuals (49.2%) from the general population of an unknown HLA-DRB1 genotype were not neutralizing. Moreover, we did not find nAIGAs in 257 individuals carrying HLA-DRB1* 15:02 or 16:02. Additionally, nAIGAs were absent in 1,063 patients with an autoimmune disease. Finally, 7 of 497 patients (1.4%) with unexplained severe disease due to EM harbored nAIGAs.CONCLUSIONThese findings suggest that nAIGAs are isolated and that their penetrance in HLA-DRB1*15:02 or 16:02 individuals is low, implying that they may be triggered by rare germline or somatic variants. In contrast, the risk of mycobacterial disease in patients with nAIGAs is high, confirming that these nAIGAs are the cause of EM disease.FUNDINGThe Laboratory of Human Genetics of Infectious Diseases is supported by the Howard Hughes Medical Institute, the Rockefeller University, the St. Giles Foundation, the National Institutes of Health (NIH) (R01AI095983 and U19AIN1625568), the National Center for Advancing Translational Sciences (NCATS), the NIH Clinical and Translational Science Award (CTSA) program (UL1 TR001866), the French National Research Agency (ANR) under the "Investments for the Future" program (ANR-10-IAHU-01), the Integrative Biology of Emerging Infectious Diseases Laboratory of Excellence (ANR-10-LABX-62-IBEID), ANR-GENMSMD (ANR-16-CE17-0005-01), ANR-MAFMACRO (ANR-22-CE92-0008), ANRSECTZ170784, the French Foundation for Medical Research (FRM) (EQU201903007798), the ANRS-COV05, ANR GENVIR (ANR-20-CE93-003), and ANR AI2D (ANR-22-CE15-0046) projects, the ANR-RHU program (ANR-21-RHUS-08-COVIFERON), the European Union's Horizon 2020 research and innovation program under grant agreement no. 824110 (EASI-genomics), the Square Foundation, Grandir - Fonds de solidarité pour l'enfance, the Fondation du Souffle, the SCOR Corporate Foundation for Science, the Battersea & Bowery Advisory Group, William E. Ford, General Atlantic's Chairman and Chief Executive Officer, Gabriel Caillaux, General Atlantic's Co-President, Managing Director, and Head of business in EMEA, and the General Atlantic Foundation, Institut National de la Santé et de la Recherche Médicale (INSERM) and of Paris Cité University. JR was supported by the INSERM PhD program for doctors of pharmacy (poste d'accueil INSERM). JR and TLV were supported by the Bettencourt-Schueller Foundation and the MD-PhD program of the Imagine Institute. MO was supported by the David Rockefeller Graduate Program, the Funai Foundation for Information Technology (FFIT), the Honjo International Scholarship Foundation (HISF), and the New York Hideyo Noguchi Memorial Society (HNMS).

Prediction and Experimental Evaluation of the hERG Blocking Potential of Drugs Showing Clinical Signs of Cardiotoxicity

Background: A large scale experimental validation conducted at the National Center for Advancing Translational Sciences (NCATS/NIH, USA) confirmed the predictions of our 3D-SDAR model of hERG blockage and phospholipidosis induction. It was demonstrated that both hERG blockage and phospholipidosis induction are driven by a common three-center toxicophore composed of two aromatic rings and an amino group. This work extends our earlier efforts by predicting the hERG blocking potential of pharmaceuticals from two additional datasets: i) one comprised of 106 drugs with reported clinical signs of cardiotoxicity from the AZCERT database and ii) a dataset of 54 FDA-approved tyrosine kinase inhibitors (TKIs). Methods: A bagging-like 3D-SDAR algorithm aggregating predictions from 100 randomized models was used to predict the hERG blocking potential of all 160 drugs. All 106 drugs from the AZCERT dataset were further evaluated for their hERG inhibition at NCATS using a thallium flux assay. Results: Comparison of the predicted hERG class against the results of the thallium flux qHTS assay resulted in an overall predictive accuracy of 0.736 and the area under the ROC curve of 0.780. Factors such as the generation of false negatives by the thallium flux assay, proximity to the cut-off, use of conformations that may differ from the biologically relevant ones, and the lack of structurally similar compounds in the modeling set could explain the somewhat reduced predictive performance compared to that of the original model. The original 3D-SDAR model was also used to evaluate the TKIs ability to block hERG. Comparing our predictions to class assignments based on IC50 values with a 30 μM cut-off, an accuracy of 0.850, sensitivity of 0.906, and specificity of 0.625 were achieved. Conclusion: 3D-SDAR provides a reliable platform for the prediction of hERG blockage. Particular attention should be paid to all investigational new drugs containing our three-center hERG toxicophore, especially those having highly flexible molecules. Particular scrutiny should be given to the tyrosine kinase inhibitors, which represent a therapeutic class possessing all structural characteristics previously associated with an increased potential to block hERG.

Seminar: Extracellular Vesicles as Mediators of Environmental Stress in Human Disease.

Extracellular vesicles (EVs), membrane-bound particles containing a variety of RNA types, DNA, proteins, and other macromolecules, are now appreciated as an important means of communication between cells and tissues, both in normal cellular physiology and as a potential indicator of cellular stress, environmental exposures, and early disease pathogenesis. Extracellular signaling through EVs is a growing field of research for understanding fundamental mechanisms of health and disease and for the potential for biomarker discovery and therapy development. EVs are also known to play important roles in mediating the effects of exposure to environmental stress. This seminar addresses the application of new tools and approaches for EV research, developed in part through the National Institutes of Health (NIH) Extracellular RNA Communication Program, and reflects presentations and discussions from a workshop held 27-28 September 2021 by the National Institute of Environmental Health Sciences (NIEHS) and the National Center for Advancing Translational Sciences (NCATS) on "Extracellular Vesicles, Exosomes, and Cell-Cell Signaling in Response to Environmental Stress." The panel of experts discussed current research on EVs and environmental exposures, highlighted recent advances in EV isolation and characterization, and considered research gaps and opportunities toward identifying and characterizing the roles for EVs in environmentally related diseases, as well as the current challenges and opportunities in this field. The authors discuss the application of new experimental models, particularly organ-on-chip (OOC) systems and in vitro approaches and how these have the potential to extend findings in population-based studies of EVs in exposure-related diseases. Given the complex challenges of identifying cell-specific EVs related to environmental exposures, as well as the general heterogeneity and variability in EVs in blood and other accessible biological samples, there is a critical need for rigorous reporting of experimental methods and validation studies. The authors note that these efforts, combined with cross-disciplinary approaches, would ensure that future research efforts in environmental health studies on EV biomarkers are rigorous and reproducible. https://doi.org/10.1289/EHP12980.

Report of the Assay Guidance Workshop on 3-Dimensional Tissue Models for Antiviral Drug Development.

The National Center for Advancing Translational Sciences (NCATS) Assay Guidance Manual (AGM) Workshop on 3D Tissue Models for Antiviral Drug Development, held virtually on 7-8 June 2022, provided comprehensive coverage of critical concepts intended to help scientists establish robust, reproducible, and scalable 3D tissue models to study viruses with pandemic potential. This workshop was organized by NCATS, the National Institute of Allergy and Infectious Diseases, and the Bill and Melinda Gates Foundation. During the workshop, scientific experts from academia, industry, and government provided an overview of 3D tissue models' utility and limitations, use of existing 3D tissue models for antiviral drug development, practical advice, best practices, and case studies about the application of available 3D tissue models to infectious disease modeling. This report includes a summary of each workshop session as well as a discussion of perspectives and challenges related to the use of 3D tissues in antiviral drug discovery.

Areas of strength and opportunities for growth in translational science education and training: Results of a scoping review from the NCATS Education Branch.

Translational science education and training (E&T) aims to prepare the translational workforce to accelerate progress along the translational pipeline toward solutions that improve human health. In 2020-2021, the National Center for Advancing Translational Sciences (NCATS) Education Branch conducted a scoping review of the E&T literature with this focus. The review used the methodological framework proposed by Arksey and O'Malley. PubMed, Education Resources Information Center (ERIC), and Embase were searched, and forward citations conducted. Screening of titles, abstracts, and full text identified 44 included articles. Data extraction facilitated analysis of E&T content, audiences, modalities, evaluations, and recommendations. The NCATS Translational Science Principles were used to identity described or recommended E&T content. Twenty-nine articles described a translational science E&T opportunity or its evaluation, and another 15 articles offered recommendations for translational science E&T. The most prevalent NCATS Translational Science Principles were boundary-crossing partnerships (77%) and cross-disciplinary team science (75%). Among publications describing E&T opportunities, the most reported modalities were experiential learning (64%) and courses (61%) and the most reported participants were graduate students (68%) and postdoctoral fellows (54%). About half of these articles (n = 15) reported an evaluation, covering a range of proximal to distal outcomes. Recommendations emphasized the value of translational science E&T across training and career stages and the use of varied modalities to reach diverse audiences. This review highlights strengths and opportunities for growth in translational science E&T. Enhancements to content, expansion of participants and modalities, and rigorous evaluations will contribute to building a highly qualified, diverse translational science workforce.

Weight cycling may induce lipid handling in mast cells

Abstract Weight cycling worsens diabetes risk in both humans and mice. We recently found that weight loss and weight cycling induce many immunological changes in the adipose tissue of mice by single cell RNA-sequencing. We also found a substantial increase in adipose mast cells with weight cycling, but not weight loss. The purpose of this study was to confirm and characterize the changes in mast cells with weight cycling. However, using flow cytometry (cKit+FcER1+) and Toluidine blue staining, we found that adipose mast cells are greatest in the weight loss group, in contrast to our prior study using single cell RNA-sequencing. Upon further analysis, we found two unique mast cell populations in our single cell sequencing dataset: one that we consider traditional mast cells and one with lower expression of mast cell surface and protease genes and elevated expression of lipid handling and antigen presentation genes. The second fraction appeared similar to lipid-associated macrophages and accounted for most of the mast cells in the weight cycled group. By flow cytometry, we confirmed the %CD9+, MHCII (I-A/I-E)+, and CD74+ mast cells were highest in weight cycled mice. We also found two mast cell populations in human subcutaneous adipose tissue that appear similar to the murine populations in our dataset, with one population significantly correlating with weight variability. Together, these data suggest that weight cycling may induce a population of lipid-associated mast cells. We next aim to to induce lipid handling in bone marrow derived mast cells by repeated exposure to adipose conditioned media in order to understand the mechanisms which induce lipid handling. This project was funded by a Veterans Affairs Merit Award 5I01BX002195 to AHH. AHH is also supported by a Career Scientist Award from the Veterans Affairs (IK6 BX005649). HLC was funded by an American Heart Association Postdoctoral Fellowship (20POST35120547), MAC was funded by an NIH F31 Predoctoral Fellowship (1F31DK123881), and both were previously supported by the Molecular Endocrinology Training Program (T32 DK07563). Additionally, the human mast cell work was funded by VICTR grants to HLC and MM. The Vanderbilt Institute for Clinical and Translational Research (VICTR) is funded by the National Center for Advancing Translational Sciences (NCATS) Clinical Translational Science Award (CTSA) Program, Award Number 5UL1TR002243-03.

0828 Greater sleep variability is associated with higher systemic inflammation in type 2 diabetes

Abstract Introduction Circadian misalignment increased systemic inflammation in sleep experiments and in those performing shift work. Milder degree of circadian misalignment such as day-to-day shift in sleep timing, i.e. sleep variability, was related to inflammation in population studies. Further, other sleep disturbances and glycemic control can contribute to inflammation. This pilot study explored if sleep variability was associated with inflammation in type 2 diabetes (T2D). Methods Subjects included 35 non-shift working T2D patients with and without diabetic retinopathy (DR) who were participating in a clinical study (NCT04547439). Sleep pattern was assessed by 14-day actigraphy, yielding sleep duration and efficiency. Standard deviation of sleep duration across the night was used to represent sleep variability. Sleep apnea severity was assessed by an overnight home monitor. Neuropathy pain, statin use, serum creatinine, low-density lipoprotein (LDL), HbA1C and by high-sensitivity c-reactive protein (hs-CRP) were collected. Spearman’s correlation analyses and multiple regression analysis (using natural-log transformed values) were performed to establish an independent association between sleep variability and hs-CRP. Results Mean (SD) age was 54.3 (6.4) years, 54.3% were female and 62.9% had DR. Median (interquartile range) of sleep variability was 69 (56,84) minutes. Median A1C was 7.5 (6.6, 8.7)% and hs-CRP was 2.4 (1.4, 4.6) mg/L. Higher hs-CRP was significantly associated with higher sleep variability (r=0.342, p=0.04), HbA1c (r=0.431, p=0.01) and LDL (r=0.379, p=0.03), but not with sleep duration, sleep efficiency, sleep apnea severity, DR status or other variables. Multiple regression analysis showed that higher sleep variability (B = 0.91, p=0.034) and higher HbA1c (B = 1.51, p=0.035), but not LDL, contributed to higher hs-CRP. Conclusion Higher sleep variability in non-shift working T2D patients was shown to be independently associated with higher systemic inflammation, conferring higher cardiovascular risk. This data supports the role of even a mild degree of circadian misalignment on systemic inflammation. Further investigations are needed to determine whether sleep intervention to increase sleep regularity can reduce systemic inflammation and improve cardiometabolic health. Support (if any) NEI R01EY029782 The University of Illinois Chicago Center for Clinical and Translational Science, which is supported by the National Center for Advancing Translational Sciences (NCATS), National Institutes of Health, through Grant Award Number UL1TR002003.”

439 Research Dynamics within a New Multi-Institutional Cross-Disciplinary Translational Team (MCTT): A Formative Study

OBJECTIVES/GOALS: This report evaluates participants’experiences from three universities who assembled a complex grant proposal related to research on post-acute sequala of COVID-19 (PASC), also called long COVID. Activities reviewed ranged from the assembly of the team to responses to reviews by the National Center for Advancing Translational Sciences (NCATS). METHODS/STUDY POPULATION: Data were collected by means of semi-structured interviews, conducted and recorded on Zoom, with a sample of 15 scientists and staff both during proposal assembly and following proposal review. The sample comprised 40% of the total team equally selected from the 3 universities, The interview protocol was reviewed by the IRB at UTMB and the interviews were recorded on Zoom, and analyzed by means of the constant comparative strategy in the grounded theory method of qualitative research. Given the relatively small number of interviews in this project, we paid special attention to preserving the confidentiality of respondents. Only the verbal tracks of the interviews were professionally transcribed. Respondents were asked to suggest changes for future inter-organizational proposals. RESULTS/ANTICIPATED RESULTS: FIRST INTERVIEWS *LEADERSHIP: The scope of leadership opportunities was expanded as sub-teams in specific areas such as community engagement were formed. *TEAM: Each university’s community engagement team specializes in a different ethnic clientele, precluding a singular statement for the proposal. SECOND INTERVIEWS *LEADERSHIP: Staff members noted that the team concept too easily evolved into a bureaucratic format, resulting in less negotiation and more direction. *ASSEMBLY TASKS: The Writing Team turned out to be one of the most critical staff teams. *COMMUNICATION: The behavioral scientists in community engagement do not necessarily share paradigms (e.g., public health, psychology, and social work). They had difficulty generating productive communication and a unified statement for the proposal. DISCUSSION/SIGNIFICANCE: The scientists, as a group, suggested that future proposals should focus on one general topic, such as the microbiome, as opposed to attempting to integrate widely divergent interests. The scientists as a group should decide a priori whether to treat innovative ideas such as machine learning science as a science or a service.

MP41-02 TUMOR SIZE IS ASSOCIATED WITH GROWTH KINETICS IN SMALL RENAL MASSES ON ACTIVE SURVEILLANCE

You have accessJournal of UrologyCME1 Apr 2023MP41-02 TUMOR SIZE IS ASSOCIATED WITH GROWTH KINETICS IN SMALL RENAL MASSES ON ACTIVE SURVEILLANCE Maximilian Pallauf, Michael Rezaee, Roy Elias, Tina Wlajnitz, Sean A. Fletcher, Khalid Alkhatib, Peter Chang, Andrew A. Wagner, James M. McKiernan, Mohammad E. Allaf, Phillip M. Pierorazio, and Nirmish Singla Maximilian PallaufMaximilian Pallauf More articles by this author , Michael RezaeeMichael Rezaee More articles by this author , Roy EliasRoy Elias More articles by this author , Tina WlajnitzTina Wlajnitz More articles by this author , Sean A. FletcherSean A. Fletcher More articles by this author , Khalid AlkhatibKhalid Alkhatib More articles by this author , Peter ChangPeter Chang More articles by this author , Andrew A. WagnerAndrew A. Wagner More articles by this author , James M. McKiernanJames M. McKiernan More articles by this author , Mohammad E. AllafMohammad E. Allaf More articles by this author , Phillip M. PierorazioPhillip M. Pierorazio More articles by this author , and Nirmish SinglaNirmish Singla More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003279.02AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Active surveillance (AS) is an accepted treatment strategy for small renal masses (SRM) <4 cm. Intervention is recommended for SRMs exceeding growth rates (GR) of 0.5 cm/year. We sought to identify clinical factors predictive of GR >0.5 cm/year for SRM on AS. METHODS: We queried the prospective, multi-institutional Delayed Intervention and Surveillance for SRM (DISSRM) registry for patients enrolled in AS. We tabulated clinical factors, including age, sex, and tumor size, and quantified GRs of SRMs between study enrollment and delayed intervention, metastasis, death, or last follow-up, whichever occurred first. GR was defined by the change in tumor size over time between the first and latest imaging. We defined growth progression as a GR in excess of 0.5 cm/year. We used recurrent-event multivariable Cox-regression modeling to test the associations between clinical factors and growth progression; age and tumor size were handled as time-varying covariates. Tumor size was tested as a continuous and dichotomized variable based on a cutoff of 2 cm, endorsed by the AUA guidelines. To account for GR variability within the first few months of AS, we excluded follow-up visits earlier than six months. RESULTS: Between 2009 and 2022, 591 patients were initially enrolled onto AS within the DISSRM registry, of whom 332 were on AS for at least six months. The median follow-up time of patients who continued AS was 4.0 years (IQR 2.6-6.1). Sixty-six patients (20%) exhibited growth progression, but no patient developed metastatic disease. Fifty patients (15%) underwent delayed intervention. While age and sex were not associated with growth progression, tumor size was an independent predictor of growth progression on multivariable analysis (HR 2.61 (95% CI 2.16-3.15), p<0.001). On dichotomization of tumor size, we found that tumors ≥ 2 cm were significantly associated with growth progression compared to those <2 cm (HR 4.29 (95% CI 2.43-7.61), p<0.001) (Figure). The mean GR for tumors ≥ 2 cm was 0.21 cm/year (±0.31) vs. 0.06 cm/year (±0.26) for those <2 cm. CONCLUSIONS: Larger tumor size is independently associated with clinically meaningful growth progression (GR >0.5 cm/year) for SRMs on AS. Identifying clinical factors predictive of growth kinetics for SRMs is important to guide patient counseling by informing personalized strategies of AS versus intervention. Source of Funding: This publication was made possible by the Johns Hopkins Institute for Clinical and Translational Research (ICTR) which is funded in part by Grant Number UL1 TR003098 from the National Center for Advancing Translational Sciences (NCATS) a component of the National Institutes of Health (NIH), and NIH Roadmap for Medical Research. Its contents are solely the responsibility of the authors and do not necessarily represent the official view of the Johns Hopkins ICTR, NCATS or NIH.Pallauf M gratefully acknowledges the support of the Paracelsus Medical University Research and Innovation Fund (2022-FIRE-004-Pallauf). © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e554 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Maximilian Pallauf More articles by this author Michael Rezaee More articles by this author Roy Elias More articles by this author Tina Wlajnitz More articles by this author Sean A. Fletcher More articles by this author Khalid Alkhatib More articles by this author Peter Chang More articles by this author Andrew A. Wagner More articles by this author James M. McKiernan More articles by this author Mohammad E. Allaf More articles by this author Phillip M. Pierorazio More articles by this author Nirmish Singla More articles by this author Expand All Advertisement PDF downloadLoading ...

First person – Patricia Dranchak

ABSTRACT First Person is a series of interviews with the first authors of a selection of papers published in Disease Models &amp; Mechanisms, helping researchers promote themselves alongside their papers. Patricia Dranchak is first author on ‘ In vivo quantitative high-throughput screening for drug discovery and comparative toxicology’, published in DMM. She is a staff scientist in the lab of James Inglese at the National Center for Advancing Translational Sciences (NCATS), Rockville, MD, USA. Patricia is interested in developing and integrating novel strategies and model systems to identify chemical modulators targeting the molecular basis of rare and neglected disease pathophysiologies.

Addressing institutional and community barriers to development and implementation of community-engaged research through competency-based academic and community training.

The National Center for Advancing Translational Sciences (NCATS) focuses on reducing barriers to effective translational research that rapidly translates science to clinical and community interventions to improve individual and community health. Community-Engaged Research (CEnR) plays a crucial role in this process by bridging gaps between research and practice. It effectively generates bi-directional knowledge and communication by engaging patients and communities throughout the translation research process. Skills development, however, is critical to enable investigators and communities to establish successful partnerships in research. While there are many independent CEnR education programs nationally, few curricula are mapped to identified domains and competencies. We located three comprehensive efforts to identify CEnR domains and competencies that we aligned to inform development of our curriculum, which we then mapped to these competencies. The first, undertaken by the NCATS Joint Workgroup on Researcher Training and Education and Community Capacity Building (JWG) was developed to assess training opportunities for academic researchers and community partners to increase their capacity to meaningfully engage collaborators in translational research. The JWG identified curricula, resources, tools, strategies, and models for innovative training programs and community engagement in all stages of research. It also conducted a gap analysis of deficiencies in available resources. Using Competency Mapping, they developed a framework for curriculum mapping that included eight domains, each with two to five competencies of knowledge, attitudes, and skills. The second aligned community-engaged research competencies with online training resources across the CTSA consortium, while the third was focused on Dissemination and Implementation training. Further informed by a conceptual model to advance health equity, we have adapted and integrated these components into a set of modules designed to educate and empower investigators, trainees, students, and community partners to engage in effective CEnR. This curriculum fills an important gap in our workforce development and helps to meet needs of our community partners. Following program evaluation and validation, we will offer the curriculum for use and further evaluation by other groups interested in using or adapting it for their own programming.

Approaches for enhancing the informativeness and quality of clinical trials: Innovations and principles for implementing multicenter trials from the Trial Innovation Network.

One challenge for multisite clinical trials is ensuring that the conditions of an informative trial are incorporated into all aspects of trial planning and execution. The multicenter model can provide the potential for a more informative environment, but it can also place a trial at risk of becoming uninformative due to lack of rigor, quality control, or effective recruitment, resulting in premature discontinuation and/or non-publication. Key factors that support informativeness are having the right team and resources during study planning and implementation and adequate funding to support performance activities. This communication draws on the experience of the National Center for Advancing Translational Science (NCATS) Trial Innovation Network (TIN) to develop approaches for enhancing the informativeness of clinical trials. We distilled this information into three principles: (1) assemble a diverse team, (2) leverage existing processes and systems, and (3) carefully consider budgets and contracts. The TIN, comprised of NCATS, three Trial Innovation Centers, a Recruitment Innovation Center, and 60+ CTSA Program hubs, provides resources to investigators who are proposing multicenter collaborations. In addition to sharing principles that support the informativeness of clinical trials, we highlight TIN-developed resources relevant for multicenter trial initiation and conduct.

Challenges in catalyzing and sustaining research in translational science.

Advancing the new field of translational science and developing innovative solutions to overcome translational roadblocks are key priorities of the Clinical and Translational Science Awards (CTSA) Program of the National Center for Advancing Translational Science (NCATS). However, interpreting this emerging concept of "translational science" (TS) as a field of inquiry distinct from "translational research" (TR) and developing real-world investigations in TS can be challenging. The goal of this paper is to share the obstacles the Einstein-Montefiore CTSA hub has faced in generating institutional interest and research in TS and to present potential strategies for addressing them. The aim is to stimulate dialog within the wider CTSA community and beyond about the need to systematically examine how TS should be efficiently and effectively pursued, that is, the science of translational science. The collective sharing of experiences and innovative approaches to overcoming TS challenges that arise at CTSA hubs is critical if the field is to grow and gain wider recognition and acceptance by the scientific and broader communities.

Abstract IA010: NCATS Collaborative Translational Research/Drug Development Resources

Abstract The mission of the National Center for Advancing Translational Sciences (NCATS) is to catalyze the generation of innovative methods and technologies that will enhance the development, testing, and implementation of interventions across a wide range of human diseases and conditions. NCATS is directly addressing this problem by discovering new technologies and other approaches that could greatly accelerate the process of developing and deploying therapeutic solutions. An introduction of the Center’s internal research operations will be presented, focusing on the use of advanced assay and chemistry technologies to address the wide range of needs associated with early discovery space. Further, an overview of collaborative opportunities for joint projects will be provided. Citation Format: Anton Simeonov. NCATS Collaborative Translational Research/Drug Development Resources [abstract]. In: Proceedings of the Second Biennial NCI Meeting: Translational Advances in Cancer Prevention Agent Development (TACPAD); 2022 Sep 7-9. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_2): Abstract nr IA010.

DEIA is essential to advance the goals of translational science: Perspectives from NCATS.

The National Center for Advancing Translational Science (NCATS) seeks to improve upon the translational process to advance research and treatment across all diseases and conditions and bring these interventions to all who need them. Addressing the racial/ethnic health disparities and health inequities that persist in screening, diagnosis, treatment, and health outcomes (e.g., morbidity, mortality) is central to NCATS' mission to deliver more interventions to all people more quickly. Working toward this goal will require enhancing diversity, equity, inclusion, and accessibility (DEIA) in the translational workforce and in research conducted across the translational continuum, to support health equity. This paper discusses how aspects of DEIA are integral to the mission of translational science (TS). It describes recent NIH and NCATS efforts to advance DEIA in the TS workforce and in the research we support. Additionally, NCATS is developing approaches to apply a lens of DEIA in its activities and research - with relevance to the activities of the TS community - and will elucidate these approaches through related examples of NCATS-led, partnered, and supported activities, working toward the Center's goal of bringing more treatments to all people more quickly.

Advancing translational science education.

In this communication, the authors offer considerations for how the scientific community can capitalize on decades of translational science advances and experiential knowledge to develop new education opportunities for a diverse and highly skilled translational science workforce. Continued advancement of the field of translational science will require new education approaches that distill key concepts in translational science from past and ongoing research initiatives and teach this foundational knowledge to current and future translational scientists. These key concepts include generalizable scientific and operational principles to guide translational science, as well as evidence-informed practices. Inspired by this approach, the National Center for Advancing Translational Sciences (NCATS) has developed an initial set of guiding principles for translational science generated via case studies of multiple highly successful translational science initiatives, and is now teaching them via new education activities that aim to reach a broad scientific audience interested in translational science. Our goal with this review is to prompt continued conversation with the translational science community regarding capitalizing on our collective translational science knowledge to advance core content for translational science education and disseminating this content to a broad range of scientific audiences.

Development of a Digital Game Intervention Targeting Suicide Prevention in Adolescents Who Misuse Opioids

Background Suicide is the second leading cause of death in adolescents aged 14-18 years. Adolescents who misused prescription opioids are more likely to experience suicidal thoughts and behaviors than adolescents who did not. Compelling evidence shows “serious games” (ie, games for a purpose other than solely entertainment) can promote healthy behaviors, reduce risk factors, enhance protective factors through skill-building, and target prevention. Objective Our primary objective was to design and develop a digital game intervention that models the process of a safety planning intervention. We explored peer and student perceptions around potential warning signs, coping strategies, and seeking help among youth who may be at greater risk of suicide due to misuse of opioids. Methods We conducted 8 focus groups with a total of 30 participants, including 9 high school–aged adolescents (aged 16-18 years), 8 college-aged youth (aged 18-21 years), and 13 providers, as well as 5 interviews with adults who had experience with opioids in their youth (aged 40-47 years) to inform the content of the digital game intervention. Focus groups and interviews were conducted via Zoom between February 2022 and April 2022. A semistructured focus group/interview guide was developed, pilot tested, and used in focus groups and interviews. The guides align constructs from the intersectional ecological model to better identify how to help students cope with social and cultural stressors and how to strengthen individual and community assets. Using this lens, questions were related to potential warning signs of emotional distress, coping strategies, and seeking help to prevent suicidal thoughts and behaviors among youth who misuse opioids. Focus groups and interviews were approximately 60-90 minutes. Debrief summaries were completed after each one. Participants received a $25 gift card and additional mental health and opioid misuse resources following the session. Focus groups and interviews were audiotaped and then transcribed. Results Findings will inform the development of a digital game intervention to prevent suicide among adolescents who misuse opioids. Salient themes were extracted from the focus groups and interviews. They include themes related to previous substance misuse, later diagnosis of a mental health disorder, grief, bullying, stigma, family dynamics, and the role of identity. Potential story lines will focus on improving one’s self-esteem, managing conflict at home, navigating peer influence, addressing concerns about seeking help, and increasing access to resources for seeking help based on identity. Gameplay will incorporate techniques that enhance mindfulness, emotion regulation, interpersonal effectiveness, and distress tolerance from dialectical behavioral therapy for adolescents. Conclusions Digital game interventions may play a critical role in preventing suicide among youth who misuse opioids. Next steps include a pilot randomized controlled trial to evaluate the user experience, acceptability, and feasibility of the intervention in fall 2022. Conflicts of Interest None declared. Acknowledgments This study was funded by CTSA grant number KL2 TR001862 from the National Center for Advancing Translational Science (NCATS)/National Institutes of Health (NIH).

142-LB: Cognitive Screening among Older Adults with Diabetes

Background: Diabetes affects approximately 24.4% of older adults in the United States and increases the risk of cognitive dysfunction and future dementia. Patients with cognitive dysfunction may find it harder to manage their diabetes and have more complications such as hypoglycemia. Yearly cognitive screening is recommended for all older adults with diabetes but may not be widely conducted. Methods: We performed cognitive screening with the Mini-Cog test for a subset of patients with diabetes seen in Endocrine Clinics in one large healthcare system in 2020-21. We used a retrospective chart review to compare patient screening results between Endocrine (Endo) , Geriatric (Geri) and multidisciplinary Endo-Geriatric practices (Geri-Endo) . We used Chi-square tests to examine differences between clinic cohorts and a multivariate logistic regression to predict risk of cognitive dysfunction. We adjusted for age, ethnicity, sex, type of diabetes, Sulfonylurea (SU) use, ACE inhibitors (ACEI) / Angiotensin Receptor Blocker (ARB) use, smoking history, statin use, and BMI. Findings: Among 198 patients screened (Endo=80, Geri=32, Geri-Endo=86) , those seen in Geri-endo (40.7%) and Geri (31.3%) were more likely to have lower Mini-COG scores (lower scores suggest worse cognition) as compared to those in Endo (6.3%) (p&amp;lt;.0001) . Patients in Endo and Geri-Endo had longer duration of diabetes, were more likely to use insulin and had higher incidence of documented hypoglycemia. Higher age &amp;gt; 75 years (p=0.0105) , previous CV events (p=0.0006) and BMI &amp;lt;30 (p=0.0115) were significantly associated with lower Mini-COG scores. Conclusion: Our study shows that cognitive screening can help identify older adults at risk for dementia in diabetes clinic. Patients with older age, previous CV events and lower BMI may be at higher risk for cognitive dysfunction. Older adults should be screened yearly for cognition as part of routine diabetes care. Disclosure D. Gupta: None. H. Wilhalme: None. G. Sauder: None. T. Moin: None. Funding NIH National Center for Advancing Translational Science (NCATS) , UCLA CTSI (UL1TR001881)