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Inhaled Cannabis for Chronic Neuropathic Pain: A Meta-analysis of Individual Patient Data

机译:吸入大麻可治疗慢性神经性疼痛:个别患者数据的荟萃分析

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Chronic neuropathic pain, the most frequent condition affecting the peripheral nervous system, remains underdiagnosed and difficult to treat. Inhaled cannabis may alleviate chronic neuropathic pain. Our objective was to synthesize the evidence on the use of inhaled cannabis for chronic neuropathic pain. We performed a systematic review and a meta-analysis of individual patient data. We registered our protocol with PROSPERO CRD42011001182. We searched in Cochrane Central, PubMed, EMBASE, and AMED. We considered all randomized controlled trials investigating chronic painful neuropathy and comparing inhaled cannabis with placebo. We pooled treatment effects following a hierarchical random-effects Bayesian responder model for the population-averaged subject-specific effect. Our evidence synthesis of individual patient data from 178 participants with 405 observed responses in 5 randomized controlled trials following patients for days to weeks provides evidence that inhaled cannabis results in short-term reductions in chronic neuropathic pain for 1 in every 5 to 6 patients treated (number needed to treat = 5.6 with a Bayesian 95% credible interval ranging between 3.4 and 14). Our inferences were insensitive to model assumptions, priors, and parameter choices. We caution that the small number of studies and participants, the short follow-up, shortcomings in allocation concealment, and considerable attrition limit the conclusions that can be drawn from the review. The Bayes factor is 332, corresponding to a posterior probability of effect of 99.7%.
机译:慢性神经性疼痛是影响周围神经系统的最常见疾病,目前仍未得到充分诊断,并且难以治疗。吸入大麻可以减轻慢性神经性疼痛。我们的目标是综合使用吸入性大麻治疗慢性神经性疼痛的证据。我们对每个患者的数据进行了系统的审查和荟萃分析。我们已在PROSPERO CRD42011001182中注册了我们的协议。我们在Cochrane Central,PubMed,EMBASE和AMED中进行了搜索。我们考虑了所有调查慢性疼痛神经病变并将吸入大麻与安慰剂进行比较的随机对照试验。我们按照分层的随机效应贝叶斯响应者模型汇总了总体平均受试者特异性效应的治疗效应。我们的证据综合了来自178名参与者的独立患者数据,在患者进行数天至数周的5项随机对照试验后,共观察到405例反应,这提供了证据表明,吸入大麻可短期缓解每5至6例接受治疗的慢性神经病性疼痛(1)需要治疗的次数= 5.6,贝叶斯95%可信区间在3.4和14之间)。我们的推论对模型假设,先验和参数选择不敏感。我们告诫,研究和参与者的数量少,随访时间短,分配隐瞒的缺点以及大量的减员,限制了可以从审查中得出的结论。贝叶斯因子是332,对应于99.7%的后验概率。

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