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Abstract:
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Project Data Sphere (PDS) is a research platform that provides the research community with broad access to both de-identified patient-level data from oncology clinical trials and related analytic tools. While these data are rich in terms of measures that characterize the clinical trials under study, data providers are required to de-identify patient-level data by removing key demographic data. To address these analytic constraints, the data profiles in selected PDS patient-level cancer phase III clinical datasets have been augmented by linking the social, economic and health related characteristics of like cancer survivors from nationally representative health and healthcare-related survey data. Using statistical matching and model-based techniques, patient-level records in selected PDS datasets have been linked to comparable cancer survivors, and thereby augmented with survey content on social, economic and health related characteristics. This presentation will provide an overview of the methodologies used to join PDS patient-level data with nationally representative health-related data on cancer survivors from the MEPS and an evaluation of the stability of analytic results.
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