Kyle Webb

Project Personnel, NIH

5 active projects

Diabetes Comparison Workspace

What are the differences in A1c levels between diabetic and control populations and how do these comparisons vary when controlling for other covariates (age, gender, race, demographic information).

Scientific Questions Being Studied

What are the differences in A1c levels between diabetic and control populations and how do these comparisons vary when controlling for other covariates (age, gender, race, demographic information).

Project Purpose(s)

  • Other Purpose (This workspace's main purpose will be to provide a place to learn first hand how to create and analyze data from All of Us. The "research aim" of this project will be to compare diabetes patients and control patients, however this is only meant as a directive for the ultimate purpose of better understanding workspace creation and analysis in AoU. )

Scientific Approaches

We plan to use simple comparative statistical analyses such as t-tests and Bayesian analyses to explore group differences. Linear regression and more advanced modeling techniques (regularized regression, tree based methods) may be used to further define differences between the groups. Most of the analysis will be conducted in R.

Anticipated Findings

Anticipated findings are that A1c levels are higher among diabetes and prediabetes patients than controls.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

Collaborators:

  • Josh Denny - Other, All of Us Program Operational Use

Rheumatoid Arthritis Analysis 2

Prevalence of Rheumatoid Arthritis in AoU and the phenotypes associated after conditioning for different co-morbidities, medications, gender, race, etc.

Scientific Questions Being Studied

Prevalence of Rheumatoid Arthritis in AoU and the phenotypes associated after conditioning for different co-morbidities, medications, gender, race, etc.

Project Purpose(s)

  • Disease Focused Research (rheumatoid arthritis)

Scientific Approaches

Mainly statistical and machine learning modeling and PheWAS software for determining RA diagnosis and associated diagnoses as well as outcomes. The goal of this research is to compare findings across other datasets and especially the differences in phenotypes across different sites, as explained by the models.

Anticipated Findings

We expect that on average our models will find consistent markers for RA diagnoses across sites, however there will likely be large outliers. RA phenotypes will not likely be a surprise, since this is a commonly researched disease area.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

COPE survey analysis

We are interested in using the COPE survey questions and answers from respondents to see how differences may occur by geographic location and demographic information. Specifically, we are interested in social distancing and mental health questions.

Scientific Questions Being Studied

We are interested in using the COPE survey questions and answers from respondents to see how differences may occur by geographic location and demographic information. Specifically, we are interested in social distancing and mental health questions.

Project Purpose(s)

  • Disease Focused Research (COVID-19)

Scientific Approaches

We plan to use the COPE survey data, linked patient information, geographic information for each site, (possibly) medication data, and condition occurrence data. We plan to use phenome wide association studies (PheWAS) in order to determine likely phenotypes associated with outcomes of interest, such as social distancing measures.

Anticipated Findings

We anticipate to find those with debilitating diseases to be more concerned with social distancing, however we are unsure which diseases will have greater association. We also suspect that measures of depression and loss due to covid to be highly associated with more social distancing. We propose that these PheWAS analyses and investigations into differences of social distancing and mental health will heavily contribute to the field of study on COVID-19 and sociological and behavioral health effects.

Demographic Categories of Interest

  • Race / Ethnicity

Research Team

Owner:

N3C Comparison

We plan to provide phecode counts and percentages across COVID-19 diagnosis, both of enrolled participants and EHR observations for AoU and N3C. We plan to stratify by demographics of interest and age and compare measures of relative risk and odds…

Scientific Questions Being Studied

We plan to provide phecode counts and percentages across COVID-19 diagnosis, both of enrolled participants and EHR observations for AoU and N3C. We plan to stratify by demographics of interest and age and compare measures of relative risk and odds ratios between AoU and N3C COVID-19 positive and negative participants. This analysis is at a high level, but provides some valuable measures to compare common diagnoses and comorbidities associated with COVID-19. It also provides a good measure for differences in conditions between AoU and N3C participants.

Project Purpose(s)

  • Disease Focused Research (COVID-19)

Scientific Approaches

We plan to use N3C OMOP compliant datasets in order to compare diagnostic level counts with AoU. Mainly will be working with SQL, R, and Python programming languages to merge this information and conduct the broad analysis.

Anticipated Findings

We anticipate that some common respiratory, disease, and heart complications will be more common in the COVID-19 positive patients from N3C when compared to phenotypes from our AoU cohort. We do not have great expectations when comparing the patients not exhibiting COVID-19 in N3C with the AoU population.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

Rheumatoid Arthritis Analysis

Prevalence of Rheumatoid Arthritis in AoU and the phenotypes associated after conditioning for different co-morbidities, medications, gender, race, etc.

Scientific Questions Being Studied

Prevalence of Rheumatoid Arthritis in AoU and the phenotypes associated after conditioning for different co-morbidities, medications, gender, race, etc.

Project Purpose(s)

  • Disease Focused Research (rheumatoid arthritis)

Scientific Approaches

Mainly statistical and machine learning modeling and PheWAS software for determining RA diagnosis and associated diagnoses as well as outcomes. The goal of this research is to compare findings across other datasets and especially the differences in phenotypes across different sites, as explained by the models.

Anticipated Findings

We expect that on average our models will find consistent markers for RA diagnoses across sites, however there will likely be large outliers. RA phenotypes will not likely be a surprise, since this is a commonly researched disease area.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

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