Impact of the treatment assignment model on propensity score-based methods

Standard statistical methods assess the association between treatments or exposures and the outcome. To better estimate the causal effect, defined as the expected difference in potential outcomes, several methods have been proposed, including propensity-score (PS) based methods. PS-based methods use the predicted probability of being assigned to a given treatment to produce a pseudo population which better resembles that of a randomized trial. Standard statistical methods can then be applied to that pseudo population to better estimate the causal effect. The goal of this thesis is to describe how choice of treatment assignment model can impact the results of PS-based methods, using an empirical example of a binary outcome with a binary treatment variable and both continuous and categorical confounders. We hypothesize that using different treatment assignment mechanisms will produce differing degrees of overlap (between treatment groups), which will then lead to different pseudo populations and different estimates of treatment effect. The treatment assignment mechanism was modeled using three approaches: logistic regression, classification trees, and a random forest model. Next, three pseudo populations were created from each of the resulting PS distributions: one using 1:1 propensity score matching, one using stratification into quintiles, and one using inverse probability of treatment weighting (IPTW). Covariate balance was assessed by calculating the standardized mean differences of covariates in the entire sample and in each pseudo population. A Cox proportional hazard model was then fit for each pseudo population to estimate the treatment effect. Results varied for different outcomes models. The forest model gave a significant estimate in matched pseudo populations, no model was significant in stratified pseudo populations, and both the unpruned tree and forest models gave significant estimates in IPTW pseudo populations. In conclusion, these mixed results indicated that the assignment mechanism model, the approach for forming the pseudo population, and the choice of outcomes model, can all significantly influence results. This thesis is significant to public health because it illustrates a comparative effectiveness research analysis of the causal effect of two treatments using only observational data. The methods used are a frequent approach in public health studies involving nonrandomized data

Severe Acute Respiratory Infection-Preparedness: Protocol for a Multicenter Prospective Cohort Study of Viral Respiratory Infections

OBJECTIVES: Respiratory virus infections cause significant morbidity and mortality ranging from mild uncomplicated acute respiratory illness to severe complications, such as acute respiratory distress syndrome, multiple organ failure, and death during epidemics and pandemics. We present a protocol to systematically study patients with severe acute respiratory infection (SARI), including severe acute respiratory syndrome coronavirus 2, due to respiratory viral pathogens to evaluate the natural history, prognostic biomarkers, and characteristics, including hospital stress, associated with clinical outcomes and severity. DESIGN: Prospective cohort study. SETTING: Multicenter cohort of patients admitted to an acute care ward or ICU from at least 15 hospitals representing diverse geographic regions across the United States. PATIENTS: Patients with SARI caused by infection with respiratory viruses that can cause outbreaks, epidemics, and pandemics. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Measurements include patient demographics, signs, symptoms, and medications; microbiology, imaging, and associated tests; mechanical ventilation, hospital procedures, and other interventions; and clinical outcomes and hospital stress, with specimens collected on days 0, 3, and 7-14 after enrollment and at discharge. The primary outcome measure is the number of consecutive days alive and free of mechanical ventilation (VFD) in the first 30 days after hospital admission. Important secondary outcomes include organ failure-free days before acute kidney injury, shock, hepatic failure, disseminated intravascular coagulation, 28-day mortality, adaptive immunity, as well as immunologic and microbiologic outcomes. CONCLUSIONS: SARI-Preparedness is a multicenter study under the collaboration of the Society of Critical Care Medicine Discovery, Resilience Intelligence Network, and National Emerging Special Pathogen Training and Education Center, which seeks to improve understanding of prognostic factors associated with worse outcomes and increased resource utilization. This can lead to interventions to mitigate the clinical impact of respiratory virus infections associated with SARI

Angiopoietin-Like4 Is a Novel Marker of COVID-19 Severity

IMPORTANCE: Vascular dysfunction and capillary leak are common in critically ill COVID-19 patients, but identification of endothelial pathways involved in COVID-19 pathogenesis has been limited. Angiopoietin-like 4 (ANGPTL4) is a protein secreted in response to hypoxic and nutrient-poor conditions that has a variety of biological effects including vascular injury and capillary leak. OBJECTIVES: To assess the role of ANGPTL4 in COVID-19-related outcomes. DESIGN SETTING AND PARTICIPANTS: Two hundred twenty-five COVID-19 ICU patients were enrolled from April 2020 to May 2021 in a prospective, multicenter cohort study from three different medical centers, University of Washington, University of Southern California and New York University. MAIN OUTCOMES AND MEASURES: Plasma ANGPTL4 was measured on days 1, 7, and 14 after ICU admission. We used previously published tissue proteomic data and lung single nucleus RNA (snRNA) sequencing data from specimens collected from COVID-19 patients to determine the tissues and cells that produce ANGPTL4. RESULTS: Higher plasma ANGPTL4 concentrations were significantly associated with worse hospital mortality (adjusted odds ratio per log CONCLUSIONS AND RELEVANCE: ANGPTL4 is expressed in pulmonary epithelial cells and fibroblasts and is associated with clinical prognosis in critically ill COVID-19 patients

Multi-Gene Phylogenetic Approach for Identification and Diversity Analysis of <i>Bipolaris maydis</i> and <i>Curvularia lunata</i> Isolates Causing Foliar Blight of <i>Zea mays</i>

Bipolaris species are known to be important plant pathogens that commonly cause leaf spot, root rot, and seedling blight in a wide range of hosts worldwide. In 2017, complex symptomatic cases of maydis leaf blight (caused by Bipolaris maydis) and maize leaf spot (caused by Curvularia lunata) have become increasingly significant in the main maize-growing regions of India. A total of 186 samples of maydis leaf blight and 129 maize leaf spot samples were collected, in 2017, from 20 sampling sites in the main maize-growing regions of India to explore the diversity and identity of this pathogenic causal agent. A total of 77 Bipolaris maydis isolates and 74 Curvularia lunata isolates were screened based on morphological and molecular characterization and phylogenetic analysis based on ribosomal markers—nuclear ribosomal DNA (rDNA) internal transcribed spacer (ITS) region, 28S nuclear ribosomal large subunit rRNA gene (LSU), D1/D2 domain of large-subunit (LSU) ribosomal DNA (rDNA), and protein-coding gene-glyceraldehyde-3-phosphate dehydrogenase (GAPDH). Due to a dearth of molecular data from ex-type cultures, the use of few gene regions for species resolution, and overlapping morphological features, species recognition in Bipolaris has proven difficult. The present study used the multi-gene phylogenetic approach for proper identification and diversity of geographically distributed B. maydis and C. lunata isolates in Indian settings and provides useful insight into and explanation of its quantitative findings

Fabrication of Poly (D,L-Lactic-Co-Glycolic Acid) Microparticles for Improved Human Papillomavirus Vaccine Delivery

Human papillomavirus (HPV) is the leading cause of cervical cancer and the most prevalent sexually transmitted disease worldwide. HPV vaccines require a multi-dose regimen to provide immunity, contributing to low patient compliance. We addressed this problem by formulating biodegradable poly(D,L-lactic-co-glycolic acid) (PLGA) microparticles and assessing their viability for use in controlled-release vaccines. We hypothesized that we could alter fabrication parameters to produce 1-10 μm microparticles in order to encapsulate ovalbumin (OVA) and HPV virus-like particles (VLPs). Microparticles were fabricated using a double emulsion method and used to elicit an immune response in JAWSII cells. Our results contribute to knowledge of vaccine delivery mechanisms and controlled-release technology, and could contribute to the creation of a viable controlled-release HPV vaccine

Angiopoietin-Like4 Is a Novel Marker of COVID-19 Severity

IMPORTANCE:. Vascular dysfunction and capillary leak are common in critically ill COVID-19 patients, but identification of endothelial pathways involved in COVID-19 pathogenesis has been limited. Angiopoietin-like 4 (ANGPTL4) is a protein secreted in response to hypoxic and nutrient-poor conditions that has a variety of biological effects including vascular injury and capillary leak. OBJECTIVES:. To assess the role of ANGPTL4 in COVID-19–related outcomes. DESIGN, SETTING, AND PARTICIPANTS:. Two hundred twenty-five COVID-19 ICU patients were enrolled from April 2020 to May 2021 in a prospective, multicenter cohort study from three different medical centers, University of Washington, University of Southern California and New York University. MAIN OUTCOMES AND MEASURES:. Plasma ANGPTL4 was measured on days 1, 7, and 14 after ICU admission. We used previously published tissue proteomic data and lung single nucleus RNA (snRNA) sequencing data from specimens collected from COVID-19 patients to determine the tissues and cells that produce ANGPTL4. RESULTS:. Higher plasma ANGPTL4 concentrations were significantly associated with worse hospital mortality (adjusted odds ratio per log2 increase, 1.53; 95% CI, 1.17–2.00; p = 0.002). Higher ANGPTL4 concentrations were also associated with higher proportions of venous thromboembolism and acute respiratory distress syndrome. Longitudinal ANGPTL4 concentrations were significantly different during the first 2 weeks of hospitalization in patients who subsequently died compared with survivors (p for interaction = 8.1 × 10–5). Proteomics analysis demonstrated abundance of ANGPTL4 in lung tissue compared with other organs in COVID-19. ANGPTL4 single-nuclear RNA gene expression was significantly increased in pulmonary alveolar type 2 epithelial cells and fibroblasts in COVID-19 lung tissue compared with controls. CONCLUSIONS AND RELEVANCE:. ANGPTL4 is expressed in pulmonary epithelial cells and fibroblasts and is associated with clinical prognosis in critically ill COVID-19 patients