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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Regional Feedstock Partnership Biomass Quality Assessment Final Report

The United States (U.S.) Department of Energy (DOE) developed the Billion-Ton Vision to enable production of one-billion tons of sustainable, reliable biomass for the bioenergy industry by 2030 (Perlack et al., 2005). The Sun Grant Regional Feedstock Partnership (RFP) was organized to fill information gaps and validate biomass yield assumptions related to the Billion-Ton Study (Owens, 2018; Owens, Karlen, and Lacey, 2016). Along with the more than 130 scientific publications generated from these studies, yield and sustainability data from the RFP field trials not only validated the Billion-Ton estimates, but were critical in developing both the U.S. Billion-Ton Update report in 2011 and the 2016 Billion-Ton Report (DOE, 2011; 2016). The intention of this biomass quality assessment report is to build on these initial successes from the RFP field trials by focusing on variability in biomass quality data necessary to evaluate conversion performance. This report contains a summary of chemical quality results from samples collected as part of the RFP field trials. This report focuses on assessment of the impact of experimental agronomic designs on biomass properties followed by analyses of the impact of environmental and production variables on biomass properties. Datasets include species and other genetic variables, fertilizer treatments, harvest information, and yield, as well as other publicly available data such as precipitation, temperature, soil properties, and drought. The key outcomes from this chemical quality focused assessment have included: • Complete evaluation of the impacts of agronomic designs, genetics, and environmental conditions on chemical properties for Miscanthus, switchgrass, sorghum, energycane, mixed perennial grasses, and shrub willow short-rotation feedstocks • Over 30 peer review publications and technical reports focused on variability in quality data • Development of spatial and temporal environmental quality prediction maps for Miscanthus and switchgrass feedstocks allowing for comprehensive evaluation of variability in feedstock chemical quality across U.S. regions and over multiple harvest years

09 BIOMASS FUELS↗
NASA NTRS1993

Development, refinement, and testing of a short term solar flare prediction algorithm

Progress toward performance of the tasks and accomplishing the goals set forth in the two year Research Grant included primarily analysis of digital data sets and determination of methodology associated with the analysis of the very large, unique, and complex collection of digital solar magnetic field data. The treatment of each magnetogram as a unique set of data requiring special treatment was found to be necessary. It is determined that a person familiar with the data, the analysis system, and logical, coherent outcome of the analysis must conduct each analysis, and interact with the analysis program(s) significantly sometimes many iterations for successful calibration and analysis of the data set. With this interaction, the data sets yield valuable, coherent analyses. During this period, it was also decided that only data sets taken inside heliographic longitudes (Central Meridian Distance) East and West 30 degrees (within 30 degrees of the Central Meridian of the Sun). If the total data set is then found to be numerically inadequate for the final analysis, 30 - 45 degrees Central Meridian Distance data will then be analyzed. The Optical Data storage system (MSFC observatory) was found appropriate for use both in intermediate storage of the data (preliminary to analysis), and for storage of the analyzed data sets for later parametric extraction.

Smith, Jesse B., Jr.↗
DOE OSTI2022

Expanding Medicaid to Reduce Human Immunodeficiency Virus Transmission in Houston, Texas

Context: Medicaid expansion has been nationally shown to improve engagement in the human immunodeficiency virus (HIV) treatment and prevention continua, which are vital steps to stopping the HIV epidemic. New HIV infections in the United States are disproportionately concentrated among young Black men who have sex with men (YBMSM). Houston, TX, is the most populous city in the Southern United States with a racially/ethnically diverse population that is located in 1 of 11 US states that have not yet expanded Medicaid coverage as of 2021. Methods: An agent-based model that incorporated the sexual networks of YBMSM was used to simulate improved antiretroviral treatment and pre-exposure prophylaxis (PrEP) engagement through Medicaid expansion in Houston, TX. Analyses considered the HIV incidence (number of new infections and as a rate metric) among YBMSM over the next 10 years under Medicaid expansion as the primary outcome. Additional scenarios, involving viral suppression and PrEP uptake above the projected levels achieved under Medicaid expansion, were also simulated. Results: The baseline model projected an HIV incidence rate of 4.96 per 100 person years (py) and about 368 new annual HIV infections in the 10th year. Improved HIV treatment and prevention continua engagement under Medicaid expansion resulted in a 14.9% decline in the number of annual new HIV infections in the 10th year. Increasing viral suppression by an additional 15% and PrEP uptake by 30% resulted in a 44.0% decline in new HIV infections in the 10th year, and a 27.1% decline in cumulative infections across the 10 years of the simulated intervention. Findings: Simulation results indicate that Medicaid expansion has the potential to reduce HIV incidence among YBMSM in Houston. Achieving HIV elimination objectives, however, might require additional effective measures to increase antiretroviral treatment and PrEP uptake beyond the projected improvements under expanded Medicaid.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Process Optimization and Real-Time Control of Synergistic Microalgae Cultivation and Wastewater Treatment (Final Technical Report)

The overarching goal of this work was to accelerate the commercialization of high productivity, mixed community microalgal treatment technologies for the synergistic treatment of wastewater and the production of biofuel feedstocks. This project addressed a critical barrier to the financial viability and energy efficiency of algal wastewater treatment: an inability to design and operate high-rate processes that reliably achieve target effluent qualities, areal productivities, and biochemical compositions (lipid, protein, carbohydrate content) despite fluctuations in wastewater composition, weather, and microbial communities. Key outcomes from this work include an optimized and controlled Advanced Biological Nutrient Recovery (ABNR) design as well as a suite of open-source tools that include a calibrated and validated algae process simulator in QSDsan and a novel low-cost, real-time microbial monitoring tool. These tools can be leveraged by other algal cultivation and wastewater treatment technology developers in future work.

09 BIOMASS FUELS↗
NASA NTRSDate not supplied

Improving the Fidelity of Capability & Resource Weighting in A Probalistic Risk Assessment Model for Spaceflight

INTRODUCTION NASA’s Informing Mission Planning via Analysis of Complex Tradespaces (IMPACT) tool uses Probabilistic Risk Assessment (PRA) to provide an evidence-based, data-driven estimate of how medical system capabilities affect mission outcomes. IMPACT maps condition incidence to available resources thereby facilitating the calculation of outcome metrics that allow the estimation of mission medical risk. Conditions can be nominally categorized as either treated or untreated depending on the availability of necessary diagnostic and therapeutic capabilities. This categorization enables IMPACT to estimate the effect of various medical system configurations on mission outcomes such as crew mortality, disability, crew member down-time, return to duty/recovery, and need for evacuation. IMPACT currently employs an equal weighting, “partial credit” approach to define treatment in which each of the capabilities associated with a given condition contributes an equal amount to management of the condition. This feature enables IMPACT to report values in between “fully untreated” and “fully treated” based on the proportion of capabilities available within the model. However, as is normal in medical/clinical practice, not all individual capabilities contribute equally to medical care. For example, the ability to provide intramuscular epinephrine during an anaphylactic episode contributes more likelihood of overall management success than does the administration of oral diphenhydramine. We hypothesize that weighting the relative contribution of each capability to each specific condition will improve outcome prediction and therefore will better provide mission planners with more nuanced and accurate options when designing space medical systems. METHODS Using a five-point Fibonacci scaling sequence (1, 2, 3, 5, 8) subject matter experts from NASA’s Exploration Medical Capabilities (ExMC) element assigned relative contribution weighting values to each identified capability within IMPACT. Since the relative importance of each capability varies depending on the specific condition, the resulting “partial” weighting was completed for more than 1,600 individual weighting assignments for 666 capabilities across 121 conditions. Each assignment required three-physician concurrence based on the overall importance of the capability to the diagnosis and management of the condition being considered and the difficulty with which it could be improvised by the crew. Once complete, 100,000 IMPACT simulations were run for a 6-month Lunar mission with a 30-day surface stay to evaluate the effect of this modification of the model. RESULTS Partial weighting significantly decreased predicted task time loss (TTL), evacuation, and loss of crew life without causing significant changes to the recommended medical system design. CONCLUSIONS The paucity of real-world referent data to support long-duration space missions of this type limits the ability to judge one predictive analytics method as superior to another. However, since the proposed method significantly reduces and optimizes outcome risks—without changing the medical system design—incorporating a partial weighting methodology is likely to provide a more accurate and operationally-relevant representation of medical risk without compromising IMPACTs ability to inform overarching medical system requirements.

Steller JG↗
DOE OSTI2023

VA EDH Data Curation Documentation (FY24-Q1)

The U.S. Department of Veterans Affairs (VA) places the health and well-being of our nation’s veterans as its top priority. VA is dedicated to offering timely access to high-quality, evidence-based mental health care that meets the needs of veterans and supports their reintegration into society. One of our core missions is to prevent suicide among veterans through innovative approaches and resources. Health outcomes, including suicide, are typically influenced by both genetics and environmental factors, such as air quality, transportation access, food availability, homelessness, and more. Mental health outcomes are associated with various stressors across socioeconomic, economic, and physical environments. Analyzing the connections between these stressors, covariates, and health outcomes relies on standardized data, which can be integrated into models like the VA’s Recovery Engagement and Coordination for Health, Veterans Enhanced Treatment (REACH VET). The World Health Organization (WHO) defines Environmental Determinants of Health (EDH) as factors like clean air, stable climate, water and sanitation, chemical safety, radiation protection, safe workplaces, sustainable agriculture, healthy urban environments, and nature preservation, all of which are crucial for good health.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

VA EDH Data Curation Documentation (FY24-Q2)

The U.S. Department of Veterans Affairs (VA) places the health and well-being of our nation’s veterans as its top priority. VA is dedicated to offering timely access to high-quality, evidence-based mental health care that meets the needs of veterans and supports their reintegration into society. One of our core missions is to prevent suicide among veterans through innovative approaches and resources. Health outcomes, including suicide, are typically influenced by both genetics and environmental factors, such as air quality, transportation access, food availability, homelessness, and more. Mental health outcomes are associated with various stressors across socioeconomic, economic, and physical environments. Analyzing the connections between these stressors, covariates, and health outcomes relies on standardized data, which can be integrated into models like the VA’s Recovery Engagement and Coordination for Health, Veterans Enhanced Treatment (REACH VET). The World Health Organization (WHO) defines Environmental Determinants of Health (EDH) as factors like clean air, stable climate, water and sanitation, chemical safety, radiation protection, safe workplaces, sustainable agriculture, healthy urban environments, and nature preservation, all of which are crucial for good health.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

VA EDH Data Curation Documentation (FY24-Q3)

The U.S. Department of Veterans Affairs (VA) places the health and well-being of our nation’s veterans as its top priority. VA is dedicated to offering timely access to high-quality, evidence-based mental health care that meets the needs of veterans and supports their reintegration into society. One of our core missions is to prevent suicide among veterans through innovative approaches and resources. Health outcomes, including suicide, are typically influenced by both genetics and environmental factors, such as air quality, transportation access, food availability, homelessness, and more. Mental health outcomes are associated with various stressors across socioeconomic, economic, and physical environments. Analyzing the connections between these stressors, covariates, and health outcomes relies on standardized data, which can be integrated into models like the VA’s Recovery Engagement and Coordination for Health, Veterans Enhanced Treatment (REACH VET). The World Health Organization (WHO) defines Environmental Determinants of Health (EDH) as factors like clean air, stable climate, water and sanitation, chemical safety, radiation protection, safe workplaces, sustainable agriculture, healthy urban environments, and nature preservation, all of which are crucial for good health.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

VA EDH Data Curation Documentation FY24-Q4

The U.S. Department of Veterans Affairs (VA) places the health and well-being of our nation’s veterans as its top priority. VA is dedicated to offering timely access to high-quality, evidence-based mental health care that meets the needs of veterans and supports their reintegration into society. One of our core missions is to prevent suicide among veterans through innovative approaches and resources. Health outcomes, including suicide, are typically influenced by both genetics and environmental factors, such as air quality, transportation access, food availability, homelessness, and more. Mental health outcomes are associated with various stressors across socioeconomic, economic, and physical environments. Analyzing the connections between these stressors, covariates, and health outcomes relies on standardized data, which can be integrated into models like the VA’s Recovery Engagement and Coordination for Health, Veterans Enhanced Treatment (REACH VET). The World Health Organization (WHO) defines Environmental Determinants of Health (EDH) as factors like clean air, stable climate, water and sanitation, chemical safety, radiation protection, safe workplaces, sustainable agriculture, healthy urban environments, and nature preservation, all of which are crucial for good health.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1998

Prognostic significance of electrical alternans versus signal averaged electrocardiography in predicting the outcome of electrophysiological testing and arrhythmia-free survival

OBJECTIVE: To investigate the accuracy of signal averaged electrocardiography (SAECG) and measurement of microvolt level T wave alternans as predictors of susceptibility to ventricular arrhythmias. DESIGN: Analysis of new data from a previously published prospective investigation. SETTING: Electrophysiology laboratory of a major referral hospital. PATIENTS AND INTERVENTIONS: 43 patients, not on class I or class III antiarrhythmic drug treatment, undergoing invasive electrophysiological testing had SAECG and T wave alternans measurements. The SAECG was considered positive in the presence of one (SAECG-I) or two (SAECG-II) of three standard criteria. T wave alternans was considered positive if the alternans ratio exceeded 3.0. MAIN OUTCOME MEASURES: Inducibility of sustained ventricular tachycardia or fibrillation during electrophysiological testing, and 20 month arrhythmia-free survival. RESULTS: The accuracy of T wave alternans in predicting the outcome of electrophysiological testing was 84% (p < 0.0001). Neither SAECG-I (accuracy 60%; p < 0.29) nor SAECG-II (accuracy 71%; p < 0.10) was a statistically significant predictor of electrophysiological testing. SAECG, T wave alternans, electrophysiological testing, and follow up data were available in 36 patients while not on class I or III antiarrhythmic agents. The accuracy of T wave alternans in predicting the outcome of arrhythmia-free survival was 86% (p < 0.030). Neither SAECG-I (accuracy 65%; p < 0.21) nor SAECG-II (accuracy 71%; p < 0.48) was a statistically significant predictor of arrhythmia-free survival. CONCLUSIONS: T wave alternans was a highly significant predictor of the outcome of electrophysiological testing and arrhythmia-free survival, while SAECG was not a statistically significant predictor. Although these results need to be confirmed in prospective clinical studies, they suggest that T wave alternans may serve as a non-invasive probe for screening high risk populations for malignant ventricular arrhythmias.

Non-NASA Center↗
DOE OSTI2022

Novel Anti-LY6G6D/CD3 T-Cell–Dependent Bispecific Antibody for the Treatment of Colorectal Cancer

Abstract New therapeutics and combination regimens have led to marked clinical improvements for the treatment of a subset of colorectal cancer. Immune checkpoint inhibitors have shown clinical efficacy in patients with mismatch-repair–deficient or microsatellite instability–high (MSI-H) metastatic colorectal cancer (mCRC). However, patients with microsatellite-stable (MSS) or low levels of microsatellite instable (MSI-L) colorectal cancer have not benefited from these immune modulators, and the survival outcome remains poor for the majority of patients diagnosed with mCRC. In this article, we describe the discovery of a novel T-cell–dependent bispecific antibody (TDB) targeting tumor-associated antigen LY6G6D, LY6G6D-TDB, for the treatment of colorectal cancer. RNAseq analysis showed that LY6G6D was differentially expressed in colorectal cancer with high prevalence in MSS and MSI-L subsets, whereas LY6G6D expression in normal tissues was limited. IHC confirmed the elevated expression of LY6G6D in primary and metastatic colorectal tumors, whereas minimal or no expression was observed in most normal tissue samples. The optimized LY6G6D-TDB, which targets a membrane-proximal epitope of LY6G6D and binds to CD3 with high affinity, exhibits potent antitumor activity both in vitro and in vivo. In vitro functional assays show that LY6G6D-TDB–mediated T-cell activation and cytotoxicity are conditional and target dependent. In mouse xenograft tumor models, LY6G6D-TDB demonstrates antitumor efficacy as a single agent against established colorectal tumors, and enhanced efficacy can be achieved when LY6G6D-TDB is combined with PD-1 blockade. Our studies provide evidence for the therapeutic potential of LY6G6D-TDB as an effective treatment option for patients with colorectal cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Neonatal respiratory support strategies—short and long-term respiratory outcomes

Mechanical ventilation (MV), although life-saving, is associated with chronic respiratory morbidity in both preterm and term born infants. New ventilation modes have been developed with the aim of minimising lung injury. These include invasive and non-invasive respiratory support strategies, techniques for less invasive surfactant administration (LISA) and closed-loop automated oxygen control (CLAC) systems. Increasingly, newborn infants with signs of respiratory distress are stabilised on continuous positive airway pressure (CPAP) and receive LISA. Early CPAP when compared to mechanical ventilation reduced the incidence of BPD and respiratory morbidity at 18 to 22 months corrected age. Nasal intermittent positive pressure ventilation reduced treatment failure rates compared to CPAP, but not bronchopulmonary dysplasia (BPD). LISA compared with intubation and surfactant delivery reduced BPD, but there is no evidence from randomised trials regarding long-term respiratory and neurodevelopmental outcomes. Synchronisation of positive pressure inflations with the infant's respiratory efforts used with volume targeting should be applied for infants requiring intubation as this strategy reduces BPD. A large RCT with long term follow up data demonstrated that prophylactic high frequency oscillatory ventilation (HFOV) improved respiratory and functional outcomes at school age, but those effects were not maintained after puberty. CLAC systems appear promising, but their effect on long term clinical outcomes has not yet been explored in randomised trials. Further studies are required to determine the role of newer ventilation modes such as neurally adjusted ventilator assist (NAVA). All such respiratory support strategies should be tested in randomised controlled trials powered to assess long-term outcomes.

Kaltsogianni, Ourania↗
DOE OSTI2024

The TLK-ASF1 histone chaperone pathway plays a critical role in IL-1β–mediated AML progression

Identifying and targeting microenvironment-driven pathways that are active across acute myeloid leukemia (AML) genetic subtypes should allow the development of more broadly effective therapies. The proinflammatory cytokine interleukin-1β (IL-1β) is abundant in the AML microenvironment and promotes leukemic growth. Through RNA-sequencing analysis, we identify that IL-1β–upregulated ASF1B (antisilencing function-1B), a histone chaperone, in AML progenitors compared with healthy progenitors. ASF1B, along with its paralogous protein ASF1A, recruits H3-H4 histones onto the replication fork during S-phase, a process regulated by Tousled-like kinase 1 and 2 (TLKs). Although ASF1s and TLKs are known to be overexpressed in multiple solid tumors and associated with poor prognosis, their functional roles in hematopoiesis and inflammation-driven leukemia remain unexplored. In this study, we identify that ASF1s and TLKs are overexpressed in multiple genetic subtypes of AML. We demonstrate that depletion of ASF1s significantly reduces leukemic cell growth in both in vitro and in vivo models using human cells. Using a murine model, we show that overexpression of ASF1B accelerates leukemia progression. Moreover, Asf1b or Tlk2 deletion delayed leukemia progression, whereas these proteins are dispensable for normal hematopoiesis. Through proteomics and phosphoproteomics analyses, we uncover that the TLK-ASF1 pathway promotes leukemogenesis by affecting the cell cycle and DNA damage pathways. Collectively, our findings identify the TLK1-ASF1 pathway as a novel mediator of inflammatory signaling and a promising therapeutic target for AML treatment across diverse genetic subtypes. Finally, selective inhibition of this pathway offers potential opportunities to intervene effectively, address intratumoral heterogeneity, and ultimately improve clinical outcomes in AML.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Prognostic Importance of MRI-Detected Extramural Venous Invasion in Rectal Cancer: A Literature Review and Systematic Meta-Analysis

Extramural venous invasion (EMVI) is recognized as a poor prognostic factor in rectal cancer. There are well-documented limitations associated with pathology detection of EMVI, including variable reporting and the inability to use it preoperatively to guide neoadjuvant treatment. Magnetic resonance imaging (MRI)-detected EMVI (mrEMVI) has been proposed as an imaging biomarker. This review assesses the prognostic significance of mrEMVI on survival outcomes and whether regression of mrEMVI after neoadjuvant therapy is associated with improvements in survival.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRSDate not supplied

Harnessing Artificial Intelligence for Medical Diagnosis and Treatment During Space Exploration Missions

BACKGROUND The medical capabilities necessary for long-duration exploration missions (LDEMs) will differ tremendously from those currently available to crew medical officers (CMOs) on the International Space Station (ISS). Ground support will be more challenging due to distance-related communication delays and data transmission, and resource utilization must be optimized given limited ability for resupply. Clinical decision support systems (CDSSs) can help mitigate these limitations. The recent launch of generative artificial intelligence (AI) tools based upon large language models (LLM) support the creation of a smart assistant for onboard triage, diagnosis, and guided treatment of medical conditions during these missions. The Informing Mission Planning via Analysis of Complex Tradespaces (IMPACT) tool can help predict which clinical problems and outcomes are likely to occur for a design reference mission (DRM) and assist Medical Operations and systems engineering teams in creating a medical system that may optimally mitigate the predicted risks. The purpose of this study was to identify AI tools currently available or in development for the assistive diagnosis and care of medical conditions predicted for an extended duration Lunar mission. METHODS The 119 medical conditions currently built into the IMPACT suite were categorized into systems, and these diagnoses were used as keywords for our literature search. Using PubMed and Google Scholar, we performed a literature survey of AI tools applicable to these conditions. Article inclusion criteria included publication between the years 2017-2023, as the sentinel paper discussing the “selective attention” driving ChatGPT and other generative transformer models was published in June 2017. Where applicable, we reviewed only the top 1000 research articles (based on relevance) for each of the keywords/phrases. AI tools whose training sets were exclusive to a pediatric patient population were excluded. We also excluded any medical diagnostic tools (such as CT, MRI, mass spectrometry) or procedures (such as endoscopy, surgery) that are unlikely to be available during LDEMs due to mass and volume constraints, CMO knowledge, skills, and abilities, and/or inherent procedural risks. RESULTS Our survey highlighted several AI-driven tools for the triage, diagnosis, and management of those medical conditions highlighted by IMPACT. Selected publications for each medical condition were then screened for inclusion within ten systems-based categories including: general diagnostic tools (25), tools to diagnose and manage respiratory (40), dermatologic (34), neurologic (28), auditory and vestibular (30), ophthalmic (34), musculoskeletal (104), infection-associated (92), and gynecologic (19) conditions, as well as tools that could be deployed in the setting of trauma and emergency (34). CONCLUSIONS Numerous AI-driven tools were highlighted within this literature survey, ranging from chatbot assistants that triage knee pain to vision transformer models for diagnosis of ophthalmic conditions using ocular surface images captured with a mobile phone. Remaining challenges include optimizing connectivity and integration of existing and developing systems into the vehicles or habitats. Notably, findings from this survey could help guide the initial design of an all-encompassing, onboard medical AI assistant for use during future LDEMs.

R A Lacinski↗
DOE OSTI2019

Management of Pulmonary Arterial Hypertension in the Pediatric Patient

Purpose of Review: Pediatric pulmonary arterial hypertension (PAH) is associated with significant morbidity and mortality. Herein we review the diagnosis and classification for pediatric PAH and detail the current therapeutic options available for use in the pediatric PAH population. Recent Findings: Classification and treatment of pediatric PAH is guided by adult criteria and treatment algorithms, yet the distribution of factors contributing to PAH in children differs significantly from that seen in adults. It is necessary to understand these differences in order to appropriately tailor therapy to the needs of the child or adolescent. An expanding array of targeted PAH drugs are now approved for use in adults, and many of these drugs are used “off-label” to treat children and adolescents with PAH. Use of these novel therapies has coincided with marked improvement in outcomes, suggesting significant benefit. However, because most of these drugs have not been studied in rigorous randomized, controlled trials in children, it is critical that physicians understand their mechanisms of action, potential benefits, and safety profiles. Summary: Pediatric PAH outcomes have improved substantially in the modern era, coinciding with the “off-label” use of targeted PAH drugs in children and adolescents. Ideally, care should be provided at centers with specialized expertise in the diagnosis and treatment of pediatric PAH by providers who understand the appropriate diagnostic algorithms, classification schemes, and treatment approaches.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

The Association Between Baseline Hepatic or Renal Function and Clinical Outcomes for Patients With Non–Small Cell Lung Cancer Treated With a PD –1/PD– L1 Blocking Antibody Using Real–World and Trial Data

Clinical trials have demonstrated the benefit of PD-1/PD-L1 blocking antibodies for the treatment of patients with advanced non-small cell lung cancer (NSCLC) in defined patient populations that often exclude patients with moderate or severe hepatic or renal impairment. We assessed the association between overall survival (OS) and baseline organ function in patients with advanced NSCLC treated with PD-1/PD-L1 blocking antibodies in real-world data (RWD; patient-level data from electronic health records) and pooled clinical trial data submitted to the US Food and Drug Administration (FDA). The Kaplan–Meier estimator was used to estimate OS in different subgroups based on organ function. Unadjusted and adjusted Cox proportional hazards models were used to estimate the association between OS and organ function. In this hypothesis-generating study, baseline renal impairment did not appear to be associated with OS, while patients with baseline liver impairment had shorter OS. RWD provided information on a broader range of renal and hepatic function than was evaluated in clinical trials and hold promise to complement trial data in better understanding populations not represented in clinical trials.

60 APPLIED LIFE SCIENCES↗