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An Analytic Approach To Quantifying Pain Scores
Author(s) -
Laska Eugene M.,
Meisner Morris,
Takeuchi Kei,
Wanderling Joseph A.,
Siegel Carole,
Sunshine Abraham
Publication year - 1986
Publication title -
pharmacotherapy: the journal of human pharmacology and drug therapy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.227
H-Index - 109
eISSN - 1875-9114
pISSN - 0277-0008
DOI - 10.1002/j.1875-9114.1986.tb03488.x
Subject(s) - psychology , physical medicine and rehabilitation , computer science , medicine
Statistical problems in clinical trials frequently involve fitting regression lines when the underlying data are categorical or ordinal response variables. Usually an ad hoc a priori quantification is used to assign values to these ordinal responses. For pain intensity data collected in analgesic trials, the usual approach is to set none equal to 0, mild equal to 1, moderate equal to 2, and severe equal to 3. While this scheme has been generally accepted, on the basis that for similar clinical trials reasonably similar results are obtained by different investigators, concern exists that the distances between pain scores are probably not equal. A method is presented for quantifying categorical responses so that the resulting scores maximize the simultaneous fit of the dose‐response regression lines. The optimal scores derived by this technique may then be used in a bioassay analysis to estimate the relative potency of 2 compounds. As illustrative examples, this method was applied to data from 2 clinical trials and the results were compared to the usual method.