Low degree of satisfactory individual pain relief in post-operative pain trials
Research output: Contribution to journal › Article
BACKGROUND: The majority of clinical trials regarding post-operative pain treatment focuses on the average analgesic efficacy, rather than on efficacy in individual patients. It has been argued, that in acute pain trials, the underlying distributions are often skewed, which makes the average unfit as the only way to measure efficacy. Consequently, dichotomised, individual responder analyses using a predefined 'favourable' response, e.g. Visual Analogue Scale (VAS) pain scores ≤ 30, have recently been suggested as a more clinical relevant outcome.
METHODS: We re-analysed data from 16 randomised controlled trials of post-operative pain treatment and from meta-analyses of a systematic review regarding hip arthroplasty. The predefined success criterion was that at least 80% of patients in active treatment groups should obtain VAS < 30 at 6 and 24 h post-operatively.
RESULTS: In the analysis of data from the randomised controlled trials, we found that at 6 h post-operatively, 50% (95% CI: 31-69) of patients allocated to active treatment reached the success criterion for pain at rest and 14% (95% CI: 5-34) for pain during mobilisation. At 24 h post-operatively, 60% (95% CI: 38-78) of patients allocated to active treatment reached the success criterion for pain at rest, and 15% (95% CI: 5-36) for pain during mobilisation. Similar results were found for trials from the meta-analyses.
CONCLUSION: Our results indicate that for conventional, explanatory trials of post-operative pain, individual patient's achievement of a favourable response to analgesic treatment is rather low. Future pragmatic clinical trials should focus on both average pain levels and individual responder analyses in order to promote effective pain treatment at the individually patient level.
|Research areas and keywords||
Subject classification (UKÄ) – MANDATORY
|Number of pages||8|
|Journal||Acta Anaesthesiologica Scandinavica|
|State||Published - 2017 Jan|