图书简介

Preface.- Part I. Real-World Data and Evidence to Accelerate Medical Product Development.- The need for real world data/evidence in clinical development and life cycle management, and future directions.- Overview of current RWE/RWD landscape.- Key considerations in forming research questions.- Part II. Fit-for-use RWD Assessment and Data Standards.- Assessment of fit-for-use real-world data sources and applications.- Key variables ascertainment and validation in real-world setting.- Data standards and platform interoperability.- Privacy-preserving data linkage for real-world datasets.- Part III. Causal Inference Framework and Methodologies in RWE Research.- Causal Inference with Targeted Learning for Producing and Evaluating Real-World Evidence.- Framework and Examples of Estimands in Real-World Studies.- Clinical Studies Leveraging Real-World Data Using Propensity Score-Based Methods.- Recent statistical development for comparative effectiveness research beyond propensity-score methods.- Innovative Hybrid Designs and Analytical Approaches leveraging Real-Word Data and Clinical Trial data.- Statistical challenges for causal inference using time-to-event real-world data.- Sensitivity Analyses for Unmeasured Confounding: This is the way.- Sensitivity analysis in the analysis of real-world data.- Personalized medicine with advanced analytics.- Use of Real-World Evidence in Health Technology Assessment Submissions.- Part IV. Application and Case studies.- Examples of applying causal-inference roadmap to real-world studies.- Applications using real-world evidence to accelerate medical product development.- The use of real-world data to support the assessment of the benefit and risk of a medicine to treat spinal muscular atrophy.- Index.

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