Deriving dichotomous outcome measures from continuous data in randomised controlled trials of analgesics: use of pain intensity and visual analogue scales

Abstract

The aim of this study was to examine whether mean data from categorical pain intensity and visual analogue scales for both pain intensity and relief could be used reliably to derive dichotomous outcome measures for meta-analysis. Individual patient data from randomised controlled trials of single-dose analgesics in acute postoperative pain were used. The methods used were as follows: data from 132 treatments with over 4700 patients were used to calculate mean %maxSPID (categorical pain intensity), %maxVAS-SPID (visual analogue pain intensity) and %maxVAS-TOTPAR (visual analogue pain relief); these were used to derive relationships with the number of patients who achieved at least 50% pain relief (%maxTOTPAR). Good agreement was obtained between the actual number of patients with > 50%maxTOTPAR and the number calculated for all three measures. For SPID, verification included independent data sets. For calculations involving each measure, summing the positive and negative differences between actual and calculated numbers of patients with > 50%maxTOTPAR gave an average difference of less than 0.25 patients per treatment arm. Reports of randomised trials of analgesics frequently describe results of studies in the form of mean derived indices, rather than using discontinuous events, such as number of proportion of patients obtaining at least 50% pain relief. Because mean data inadequately describe information with a non-normal distribution, combining such mean data in systematic reviews may compromise the results. Showing that dichotomous data can reliably be derived from mean SPID, VAS-SPID and VAS-TOTPAR as well as TOTPAR data in previously published acute pain studies makes much more information accessible for meta-analysis.