DERIVING DICHOTOMOUS OUTCOME MEASURES FROM CONTINUOUS DATA IN RANDOMIZED CONTROLLED TRIALS OF ANALGESICS

Reports of RCTs of analgesics frequently describe results of studies i n the form of mean derived indices, rather than using discontinuous ev ents - such as number or proportion of patients with 50% pain relief. Because mean data inadequately describe information with a non-normal distribution, combining mean data in systematic reviews may compromise the results. Showing that dichotomous data can reliably be derived fr om mean data, at least in acute pain models, indicates that more meani ngful overviews or meta-analysis may be possible. This study investiga ted the relationship between continuous and dichotomous analgesic meas ures in a set of individual patient data, and then used that relations hip to derive dichotomous from continuous information in randomised co ntrolled trials (RCTs) of analgesics. Individual patient information f rom 13 RCTs of parallel-group and crossover design in acute postoperat ive pain was used to calculate the percentage of the maximum possible pain relief score (%maxTOTPAR) and the proportion of patients with gre ater than 50% pain relief (>50%maxTOTPAR) for the different treatments . The relationship between the measures was investigated in 45 actual treatments and 10 000 treatments simulated using the underlying actual distribution; 1283 patients had 45 separate treatments. Mean %maxTOTP AR correlated with the proportion of patients with >50%maxTOTPAR (r(2) = 0.90). The relationship calculated from all the 45 treatments predi cted to within three patients the number of patients with more than 50 % pain relief in 42 of 45 treatments, and 98.8% of 10 000 simulated tr eatments. For seven effective treatments, actual numbers-needed-to-tre at (NNT) to achieve >50%maxTOTPAR compared with placebo were very simi lar to those derived from calculated data.