21 research outputs found

    The Future of Precision Medicine : Potential Impacts for Health Technology Assessment

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    Objective Precision medicine allows health care interventions to be tailored to groups of patients based on their disease susceptibility, diagnostic or prognostic information or treatment response. We analyse what developments are expected in precision medicine over the next decade and consider the implications for health technology assessment (HTA) agencies. Methods We perform a pragmatic review of the literature on the health economic challenges of precision medicine, and conduct interviews with representatives from HTA agencies, research councils and researchers from a variety of fields, including digital health, health informatics, health economics and primary care research. Results Three types of precision medicine are highlighted as likely to emerge in clinical practice and impact upon HTA agencies: complex algorithms, digital health applications and ‘omics’-based tests. Defining the scope of an evaluation, identifying and synthesizing the evidence and developing decision analytic models will more difficult when assessing more complex and uncertain treatment pathways. Stratification of patients will result in smaller subgroups, higher standard errors and greater decision uncertainty. Equity concerns may present in instances where biomarkers correlate with characteristics such as ethnicity, whilst fast-paced innovation may reduce the shelf-life of guidance and necessitate more frequent reviewing. Discussion Innovation in precision medicine promises substantial benefits to patients, but will also change the way in which some health services are delivered and evaluated. As biomarker discovery accelerates and AI-based technologies emerge, the technical expertise and processes of HTA agencies will need to adapt if the objective of value for money is to be maintained

    Specifying the True- and False-Positive Rates in Basket Trials

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    Basket Designs: Statistical Considerations for Oncology Trials

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    Review of Statistical Methods for Biomarker-Driven Clinical Trials

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    Personalized Cancer Genomics

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