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On weighted composite scores for early Alzheimer's trials
Author(s) -
Jin Kun,
Cameron Briana,
Dunn Billy
Publication year - 2018
Publication title -
pharmaceutical statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 38
eISSN - 1539-1612
pISSN - 1539-1604
DOI - 10.1002/pst.1920
Subject(s) - set (abstract data type) , clinical trial , statistics , test (biology) , computer science , statistical power , data set , statistical hypothesis testing , psychology , artificial intelligence , medicine , econometrics , mathematics , biology , paleontology , programming language
Recent research on finding appropriate composite endpoints for preclinical Alzheimer's disease has focused considerable effort on finding “optimized” weights in the construction of a weighted composite score. In this paper, several proposed methods are reviewed. Our results indicate no evidence that these methods will increase the power of the test statistics, and some of these weights will introduce biases to the study. Our recommendation is to focus on identifying more sensitive items from clinical practice and appropriate statistical analyses of a large Alzheimer's data set. Once a set of items has been selected, there is no evidence that adding weights will generate more sensitive composite endpoints.