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      Algorithm for neuropathic pain treatment: an evidence based proposal.

      Brain

      Algorithms, Decision Support Techniques, Evidence-Based Medicine, methods, statistics & numerical data, Humans, Neuralgia, drug therapy, epidemiology, Publications, Randomized Controlled Trials as Topic, Treatment Outcome

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          Abstract

          New studies of the treatment of neuropathic pain have increased the need for an updated review of randomized, double-blind, placebo-controlled trials to support an evidence based algorithm to treat neuropathic pain conditions. Available studies were identified using a MEDLINE and EMBASE search. One hundred and five studies were included. Numbers needed to treat (NNT) and numbers needed to harm (NNH) were used to compare efficacy and safety of the treatments in different neuropathic pain syndromes. The quality of each trial was assessed. Tricyclic antidepressants and the anticonvulsants gabapentin and pregabalin were the most frequently studied drug classes. In peripheral neuropathic pain, the lowest NNT was for tricyclic antidepressants, followed by opioids and the anticonvulsants gabapentin and pregabalin. For central neuropathic pain there is limited data. NNT and NNH are currently the best way to assess relative efficacy and safety, but the need for dichotomous data, which may have to be estimated retrospectively for old trials, and the methodological complexity of pooling data from small cross-over and large parallel group trials, remain as limitations.

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          Journal
          16213659
          10.1016/j.pain.2005.08.013

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