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

Abstract

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%.

Perspective: This novel Bayesian meta-analysis of individual patient data from 5 randomized trials suggests that inhaled cannabis may provide short-term relief for 1 in 5 to 6 patients with neuropathic pain. Pragmatic trials are needed to evaluate the long-term benefits and risks of this treatment.

Keywords: Bayesian analysis; Cannabis; chronic pain; human immunodeficiency virus; meta-analysis; meta-analysis of individual patient data; neuropathy; painful; polyneuropathy.

Copyright © 2015 American Pain Society. Published by Elsevier Inc. All rights reserved.

Figures

Figure 1

The Quorum flow chart details our search in a diagram. We selected 165 articles for full review from 1738 hits in multiple electronic databases; five randomized trials (RCT) met the inclusion criteria. Excluded studies are double counted if they met more than one exclusion criterion, e.g. disease andmode of administration.

Figure 2

This summary of bias graph shows that the included studies were mostly of good quality in the domains of sequence generation, concealed allocation, incomplete outcome data and selective reporting and with regards to conflict of interest. However, the nature of the intervention likely interfered with effective blinding resulting possibly in high risk of performance bias in all studies and possibly detection bias due to a lack of blinding of outcome observers.

Figure 3

The forest plot displays odds ratio (with the 95% credible interval indicated by horizontal bars on the log scale) to indicate their contribution to the Bayesian pooled effect estimate shown below as a diamond with the Bayesian 95% credible interval. The table on the left lists the raw responder data at the study level. For Ware 2010, Wilsey 2008 and Wilsey 2013, the responder data are broken down by dose, listing the number of observed responses for each crossover periods and the corresponding cannabis dose. The increased effect with increased cannabis content (evident in the period level data of Ware 2010, Wilsey 2008 and Wilsey 2013) is additional evidence in support of cannabis’s effect for chronic painful neuropathy.