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Statistical issues in interpreting clinical trials
Author(s) -
DeMets D. L.
Publication year - 2004
Publication title -
journal of internal medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.625
H-Index - 160
eISSN - 1365-2796
pISSN - 0954-6820
DOI - 10.1111/j.1365-2796.2004.01320.x
Subject(s) - medicine , missing data , clinical trial , research design , medical physics , outcome (game theory) , interpretation (philosophy) , randomized controlled trial , subgroup analysis , intensive care medicine , risk analysis (engineering) , data mining , statistics , computer science , surgery , machine learning , pathology , meta analysis , mathematics , mathematical economics , programming language
Abstract. Randomized clinical trial is an important research tool in evaluating new therapeutic agents, devices and procedures. In order to obtain reliable and unbiased results, careful consideration must be given in the design and conduct of the trial. However, bias can be introduced in the analysis of the final data if certain principles are not followed. Several issues are described that make interpretation of analyses challenging. These include the intent‐to‐treat principle, the use of surrogate outcome measures, subgroup analyses, missing data and noninferiority trials.