Sean David
NorthShore University HealthSystem
2 active projects
Pharmacogenomics and Medical Outcomes 2
Scientific Questions Being Studied
We propose a retrospective cohort study within the All of US Study of ~96,000 participants who have pharmacogenomic data to evaluate gene-x-drug interactions on hospital admissions, readmissions, adverse drug reactions (ADRs), and death over a two-year follow-up period from the time of genotyping. Aim 1: To identify hospital readmissions associated with inadequate drug response or toxicity and the clinical and demographic predictors of those admissions. Aim 2: To identify hospital readmissions associated with drug response or toxicity among patients discharged on medications for which there is evidence of genetic variability for outcomes. We will identify all patients taking PGx actionable medications within 30 days prior to hospital admissions. Aim 3: To use longitudinal data from over 96,000 patients to determine the contribution of specific genotypes to medication-related hospital readmissions.
Project Purpose(s)
- Population Health
- Ancestry
Scientific Approaches
The scientific approaches will include patients who have undergone genotyping pharmacogenomic (PGx) tests. We will evaluate gene-x-drug interactions with Clinical Pharmacogenomics Implementation Consortium (CPIC) guideline medications and risk for hospitalization and major medical outcomes. The analytic methodology will be multivariate logistic regression with primary outcome of hospital admission from the time of All of Us study entry, with independent variables (medications (CPIC or non CPIC medications), genotype for PGx polymorphisms, sociodemographic covariates (age, gender, ethnic/racial group, SES/income, zip code, other social vulnerability metrics), major medical conditions (cardiovascular disease, type 1 or type 2 diabetes, hypertension, cancer), other risk factors (including BMI, smoking/tobacco use, alcohol use). We will use similar analytic strategies as described in our recent publication in the Journal of Personalized Medicine (https://pubmed.ncbi.nlm.nih.gov/34945714/).
Anticipated Findings
Based on research we have conducted to date in two Chicago-based health systems (NorthShore University HealthSystem and the University of Chicago), we have formulated the hypotheses that are stated below: Hypothesis 1: We hypothesize that adverse drug reactions will be more likely to result in 90-day hospital readmissions for patients with more severe comorbidity who are taking certain culprit medications for certain conditions. Hypothesis 2: We hypothesize that drugs with actionable genotypes affecting optimal dosing or drug selection contribute to hospital readmissions. Hypothesis 3A: We hypothesize that gene-x-drug interactions will modify risk of hospital admission. Hypothesis 3B: We will explore, in preliminary fashion, the contribution of gene-x-drug interactions and high-risk medical events resulting in hospital readmission.
Demographic Categories of Interest
- Race / Ethnicity
- Age
- Sex at Birth
- Gender Identity
- Sexual Orientation
- Geography
- Disability Status
- Access to Care
- Education Level
- Income Level
Data Set Used
Controlled TierResearch Team
Owner:
- Sean David - Other, NorthShore University HealthSystem
Collaborators:
- Mohammad Shahriar - Research Fellow, University of Chicago
- Jennifer Zhang - Project Personnel, All of Us Program Operational Use
- Henry Condon - Project Personnel, All of Us Program Operational Use
Pharmacogenomics and Medical Outcomes
Scientific Questions Being Studied
We propose a retrospective cohort study within the All of US Study of ~96,000 participants who have pharmacogenomic data to evaluate gene-x-drug interactions on hospital admissions, readmissions, adverse drug reactions (ADRs), and death over a two-year follow-up period from the time of genotyping. Aim 1: To identify hospital readmissions associated with inadequate drug response or toxicity and the clinical and demographic predictors of those admissions. Aim 2: To identify hospital readmissions associated with drug response or toxicity among patients discharged on medications for which there is evidence of genetic variability for outcomes. We will identify all patients taking PGx actionable medications within 30 days prior to hospital admissions. Aim 3: To use longitudinal data from over 96,000 patients to determine the contribution of specific genotypes to medication-related hospital readmissions.
Project Purpose(s)
- Ancestry
Scientific Approaches
The scientific approaches will include patients who have undergone genotyping pharmacogenomic (PGx) tests. We will evaluate gene-x-drug interactions with Clinical Pharmacogenomics Implementation Consortium (CPIC) guideline medications and risk for hospitalization and major medical outcomes. The analytic methodology will be multivariate logistic regression with primary outcome of hospital admission from the time of All of Us study entry, with independent variables (medications (CPIC or non CPIC medications), genotype for PGx polymorphisms, sociodemographic covariates (age, gender, ethnic/racial group, SES/income, zip code, other social vulnerability metrics), major medical conditions (cardiovascular disease, type 1 or type 2 diabetes, hypertension, cancer), other risk factors (including BMI, smoking/tobacco use, alcohol use). We will use similar analytic strategies as described in our recent publication in the Journal of Personalized Medicine (https://pubmed.ncbi.nlm.nih.gov/34945714/).
Anticipated Findings
Based on research we have conducted to date in two Chicago-based health systems (NorthShore University HealthSystem and the University of Chicago), we have formulated the hypotheses that are stated below:
Hypothesis 1: We hypothesize that adverse drug reactions will be more likely to result in 90-day hospital readmissions for patients with more severe comorbidity who are taking certain culprit medications for certain conditions.
Hypothesis 2: We hypothesize that drugs with actionable genotypes affecting optimal dosing or drug selection contribute to hospital readmissions.
Hypothesis 3A: We hypothesize that gene-x-drug interactions will modify risk of hospital admission.
Hypothesis 3B: We will explore, in preliminary fashion, the contribution of gene-x-drug interactions and high-risk medical events resulting in hospital readmission.
Demographic Categories of Interest
- Race / Ethnicity
- Age
- Sex at Birth
- Gender Identity
- Geography
- Access to Care
- Education Level
- Income Level
Data Set Used
Registered TierResearch Team
Owner:
- Sameep Shah - Project Personnel, University of Chicago
- Sean David - Other, NorthShore University HealthSystem
Collaborators:
- Mohammad Shahriar - Research Fellow, University of Chicago
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