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Hendershot, T.

Publications and source records attributed to Hendershot, T..

2 recordsLinked to original sources

CureSCi Metadata Catalog - finding and harmonizing studies for secondary analysis of hydroxyurea use for sickle cell disease

ObjectivesSickle cell disease (SCD) is a rare group of inherited red blood cell disorders that affect hemoglobin, resulting in serious multi-system complications. The limited number of patients available to participate in research studies can inhibit investigating sophisticated relationships. Secondary analysis is a research method that involves using existing data to answer new research questions. Data harmonization enables secondary analysis by combining data across studies, especially helpful for rare disease research where individual studies may be small. The National Heart, Lung, and Blood Institute Cure Sickle Cell Initiative (CureSCi) Metadata Catalog is a web-based tool to identify SCD study datasets for conducting data harmonization and secondary analysis. We present a proof-of-concept secondary analysis to explore factors associated with discontinuation of hydroxyurea, a safe and effective first line SCD therapy, to illustrate the utility of the CureSCi Metadata Catalog to expedite and enable more robust SCD research. MethodsWe performed secondary analysis of SCD studies using a multi-step workflow: develop research questions, identify study datasets, identify variables of interest, harmonize variables, and establish an analysis method. A harmonized dataset consisting of eight predictor variables across five studies was created. Secondary analysis involved a generalized linear model was employed to identify factors that significantly impact hydroxyurea discontinuation. ResultsThe CureSCi Metadata Catalog provided a platform to efficiently find relevant studies and design a harmonization strategy to prepare data for secondary analysis. Multivariate analysis of the harmonized identified that patients who are older, are female, had a history of blood transfusion therapy, had episodes of acute chest syndrome, and had the SC sickle cell genotype are more likely to stop hydroxyurea treatment. ConclusionThis secondary analysis provides a template for how the CureSCi Metadata Catalog expedites dataset discovery of sickle cell studies for identifying relationships between variables or validating existing findings.

bioinformatics↗

CureSCi Metadata Catalog - Making sickle cell studies findable

ObjectivesTo adopt the FAIR principles (Findable, Accessible, Interoperable, Reusable) to enhance data sharing, the Cure Sickle Cell Initiative (CureSCi) MetaData Catalog (MDC) was developed to make Sickle Cell Disease (SCD) study datasets more Findable by curating study metadata and making them available through an open-access web portal. MethodsStudy metadata, including study protocol, data collection forms, and data dictionaries, describe information about study patient-level data. We curated key metadata of 16 SCD studies in a three-tiered conceptual framework of category, subcategory, and data element using ontologies and controlled vocabularies to organize the study variables. We developed the CureSCi MDC by indexing study metadata to enable effective browse and search capabilities at three levels: study, Patient-Reported Outcome (PRO) Measures, and data element levels. ResultsThe CureSCi MDC offers several browse and search tools to discover studies by study level, PRO Measures, and data elements. The "Browse Studies," "Browse Studies by PRO Measures," and "Browse Studies by Data Elements" tools allow users to identify studies through pre-defined conceptual categories. "Search by Keyword" and "Search Data Element by Concept Category" can be used separately or in combination to provide more granularity to refine the search results. This resource helps investigators find information about specific data elements across studies using public browsing/search tools, before going through data request procedures to access controlled datasets. The MDC makes SCD studies more Findable through browsing/searching study information, PRO Measures, and data elements, aiding in the reuse of existing SCD data.

bioinformatics↗