Publications by authors named "Sarah C Stallings"

Objective: Blood pressure is a complex, polygenic trait, and the need to identify prehypertensive risks and new gene targets for blood pressure control therapies or prevention continues. We hypothesize a developmental origins model of blood pressure traits through the life course where the placenta is a conduit mediating genomic and nongenomic transmission of disease risk. Genetic control of placental gene expression has recently been described through expression quantitative trait loci (eQTL) studies which have identified associations with childhood phenotypes.

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As precision medicine approaches are implemented, cancer treatment decisions have come to require comprehension of genetic tests and their role in risk stratification and treatment options. Acceptance and implementation of precision medicine requires patient understanding of numeracy, genetic literacy, health literacy, and medical trust. Implementing precision medicine in a US federally qualified community health center (FQCHC) setting has received little attention.

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Importance: Historically, trust in biomedical research has been lower among minoritized racial and ethnic groups who are underrepresented in and excluded from research, with the same groups experiencing worse health outcomes. Unfortunately, instruments that measure trust may not capture components of trust relevant to minoritized racial and ethnic groups.

Objective: To develop and validate a scale to measure trust in biomedical research among minoritized racial and ethnic groups.

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Background: Previous studies support cultural tailoring of recruitment materials as a strategy to promote the enrollment of minoritized groups in clinical trials. However, there is a lack of guidance for research teams to create culturally tailored materials, potentially contributing to low recruitment rates of minoritized groups. We describe the development and pilot testing of recruitment material guidelines used to culturally tailor clinical trial recruitment materials targeting African Americans and Latinos.

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Background: Racial and ethnic minorities are often underrepresented in clinical trials, threatening the generalizability of trial results. Several factors may contribute to underrepresentation of minorities in clinical trials, including lack of training for researchers and staff on the importance of diversity in clinical trials and effective strategies for recruiting and retaining minority populations.

Methods: Applying community engaged research principles, we developed a massive open online course (MOOC) to help research team members develop knowledge and skills to enhance the recruitment of minorities in clinical trials.

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Background: Collecting social determinants of health in electronic health records is time-consuming. Meanwhile, an Area Deprivation Index (ADI) aggregates sociodemographic information from census data. The objective of this study was to ascertain whether ADI is associated with stage of human papillomavirus (HPV)-related cancer at diagnosis.

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Precision medicine holds great promise for improving health and reducing health disparities that can be most fully realized by advancing diversity and inclusion in research participants. Without engaging underrepresented groups, precision medicine could not only fail to achieve its promise but also further exacerbate the health disparities already burdening the most vulnerable. Yet underrepresentation by people of non-European ancestry continues in precision medicine research and there are disparities across racial groups in the uptake of precision medicine applications and services.

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Background: Community engagement is increasingly recognized as a valuable tool in clinical and translational research; however, the impact of engagement is not fully understood. No standard nomenclature yet exists to clearly define how research changes when community stakeholders are engaged across the research spectrum. This severely limits our ability to assess the value of community engagement in research.

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Objective: We describe a stratified sampling design that combines electronic health records (EHRs) and United States Census (USC) data to construct the sampling frame and an algorithm to enrich the sample with individuals belonging to rarer strata.

Materials And Methods: This design was developed for a multi-site survey that sought to examine patient concerns about and barriers to participating in research studies, especially among under-studied populations (eg, minorities, low educational attainment). We defined sampling strata by cross-tabulating several socio-demographic variables obtained from EHR and augmented with census-block-level USC data.

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Aim: Person-centeredness shifts the focus of healthcare and research to the needs and priorities of patients and communities, and may improve health outcomes. There are no instruments available, however, with which we can assess the degree to which research is indeed person-centered. Our aim was to develop and validate a quantitative instrument to rate person-centeredness of research.

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Article Synopsis
  • The study highlights the challenge of interpreting and implementing electronic health record (EHR) algorithms that are usually shared as free-text descriptions.
  • The Phenotype Execution and Modeling Architecture (PhEMA) was developed to standardize and automate the execution of computable phenotype algorithms, specifically for benign prostatic hyperplasia.
  • Results showed that six out of eight sites successfully executed the algorithm, yielding over 90% positive predictive value (PPV) and substantial overlap with previous implementations, indicating the promise of PhEMA in automating phenotyping across varied EHR systems despite some challenges.
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There has been extensive debate about both the necessity of orthogonal confirmation of next-generation sequencing (NGS) results in Clinical Laboratory Improvement Amendments-approved laboratories and return of research NGS results to participants enrolled in research studies. In eMERGE-PGx, subjects underwent research NGS using PGRNseq and orthogonal targeted genotyping in clinical laboratories, which prompted a comparison of genotyping results between platforms. Concordance (percentage agreement) was reported for 4077 samples tested across nine combinations of research and clinical laboratories.

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Knowledge of the genetic basis of the type 2 diabetes (T2D)-related quantitative traits fasting glucose (FG) and insulin (FI) in African ancestry (AA) individuals has been limited. In non-diabetic subjects of AA (n = 20,209) and European ancestry (EA; n = 57,292), we performed trans-ethnic (AA+EA) fine-mapping of 54 established EA FG or FI loci with detailed functional annotation, assessed their relevance in AA individuals, and sought previously undescribed loci through trans-ethnic (AA+EA) meta-analysis. We narrowed credible sets of variants driving association signals for 22/54 EA-associated loci; 18/22 credible sets overlapped with active islet-specific enhancers or transcription factor (TF) binding sites, and 21/22 contained at least one TF motif.

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Hereditary hemochromatosis (HH) is a common autosomal-recessive disorder associated with pathogenic HFE variants, most commonly those resulting in p.Cys282Tyr and p.His63Asp.

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Introduction: Pharmacogenomics and personalized medicine promise to improve healthcare by increasing drug efficacy and minimizing side effects. There may also be substantial savings realized by eliminating costs associated with failed treatment. This paper describes a framework using health claims data for analyzing the potential value of pharmacogenomic testing in clinical practice.

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Context: In the past, cancer patients entering phase 1 studies confronted the prospects of high risk and unlikely benefit. Over the last decade, cancer drugs under development have become more targeted, and the clinical research environment has become more scrutinized. The impact of these changes on the risks and benefits to patients who participate in phase 1 cancer trials is unknown.

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Objectives: The aims of this study were to estimate the effects of demographics, location, severity of multiple sclerosis (MS), comorbidities, plan type, coinsurance levels, and time of entry into the sample on the use of disease-modifying agents.

Methods: A retrospective analysis of medical claims data from 1996 through 2000 was conducted with a sample of MS patients covered by self-insured, employer-sponsored health plans. Proportional hazard analysis with the SAS procedure for proportional hazards regression was used to estimate the impact of the factors of interest on the use of disease-modifying agents.

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