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Statistical methods for clinical studies in the presence of surrogate end points

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The use of surrogate end points has become increasingly common in medical and biological research. This is primarily because, in many studies, the primary end point of interest is too expensive or too difficult to obtain. There is now a large volume of statistical methods for analysing studies with surrogate end point data. However, to our knowledge, there has not been a comprehensive review of these methods to date. This paper reviews some existing methods and summarizes the strengths and weaknesses of each method. It also discusses the assumptions that are made by each method and critiques how likely these assumptions are met in practice.

Keywords: Auxiliary information; Censoring; Coarsening; Markov process; Missing values

Document Type: Original Article


Affiliations: Memorial Sloan–Kettering Cancer Center, New York, USA, and Singapore Management University, Singapore

Publication date: January 1, 2001


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