Cannabis for the treatment of Crohn's disease
Abstract
This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:
The primary objective is to assess the efficacy and safety of cannabis for induction and maintenance of remission in patients with Crohn’s disease.
Background
Cannabis sativa (Cannabis or marijuana) is a widely used recreational drug which alters sensory perception and causes euphoria (Tibirica 2010). It has been promoted as a treatment for a variety of diseases such as cancer, glaucoma and autoimmune diseases (Hill 2015). Cannabis has also been hypothesized to improve disease activity in Crohn’s disease via modulation of the endocannabinoid system (Tibirica 2010). The endocannabinoid system has been shown to help regulate brain function and the immune system (Klein 2006).
Studies have found a higher prevalence of cannabis use in patients with IBD who claim it relieves symptoms such as abdominal pain, diarrhea, and reduced appetite (Lal 2011; Weiss 2015). It is unclear if this is due to the known psychotropic effects of cannabis such as analgesia and euphoria or if it is related to anti‐inflammatory effects demonstrated in recent studies and experimental animal models (Hasenoehrl 2016; Klein 2006; Singh 2012). There is also evidence that cannabis use in patients with Crohn's disease has potential for harm. Cannabis has been associated with higher risk of surgery in people with Crohn's disease (Storr 2014). Cannabinoids have been associated with an increased risk of transient adverse events including weakness, dizziness, and diarrhea (Whiting 2015). Despite these conflicting data, physicians are often asked to prescribe cannabis in the context of a rapidly growing medical marijuana industry (Fletcher 2013).
There were no placebo‐controlled trials evaluating the use of cannabis in IBD patients until the first prospective, placebo‐controlled trial was published in 2013 (Naftali 2013). This study raised important questions regarding the exact role of cannabis in treating patients with Crohn’s disease: Does cannabis lead to symptomatic improvement only or does it also objectively reduce inflammation? Is cannabis safe?
Description of the condition
Crohn’s disease (CD) is a chronic immune‐mediated condition of transmural inflammation in the gastrointestinal tract. CD is associated with significant morbidity and decreased quality of life (Lahat 2012; Rubin 2004). In North America, the prevalence of CD is estimated to range from 26 to 199 cases per 100,000 person‐years (Friedman 2012).
CD can affect anywhere from the mouth to the perianal area. The pathophysiology of this condition is multifactorial and patients may have a genetic predisposition (Friedman 2012). CD is thought to arise from a dysregulated immune response towards commensal microbiota and dietary contents in the gastrointestinal tract (Friedman 2012). This leads to an inappropriate inflammatory cascade of activated T cells secreting excessive pro‐inflammatory cytokines such as interleukin‐1 (IL‐1), IL‐6, and tumor necrosis factor‐alpha (TNF‐α) (Friedman 2012). This results in damage to previously healthy tissues.
CD is characterized by periods of relapse and remission (Friedman 2012). Symptoms may include low grade fevers, malaise, diarrhea, crampy abdominal pain, or hematochezia (Friedman 2012). The site of inflammation influences the symptoms. Complications of CD include fistula and abscess formation, perforations and fibrotic strictures (Friedman 2012; Lahat 2012).
Usual treatment options for CD include anti‐inflammatory and immunosuppressant agents (Friedman 2012). Commonly used drugs are 5‐ASA, sulfasalazine, corticosteroids, thiopurine drugs, methotrexate and biologic therapies such as anti‐TNF‐α agents (Friedman 2012). Management includes control of acute exacerbations, induction of remission, and maintenance of remission.
Description of the intervention
Cannabis sativa consists of numerous compounds called cannabinoids, of which delta 9‐tetrahydrocannabinol (THC) is the main psychotropic component (Klein 2006). Many natural and synthetic cannabinoids have been found and studied including cannabidiol, cannabinol, cannabigerol, and dronabinol (Klein 2006). Some of these cannabinoids are psychoactive, whereas other are not (Klein 2006). Multiple experimental animal models have shown anti‐inflammatory properties of various cannabinoids (Klein 2006).
How the intervention might work
The endocannabinoid system helps regulate the central nervous sytem, peripheral tissues, and multiple immune cells (Tibirica 2010). This system consists of cannabinoid (CB) receptors 1 and 2, several endogenous ligands called 'endocannabinoids', and associated enzymes (Hasenoehrl 2016; Klein 2006). Multiple studies have shown that the endocannabinoid system helps control physiologic functions of the gut including motility, secretion and epithelial barrier integrity (Coutts 1998; Hasenoehrl 2016; Pinto 2002; Vianna 2012). This makes the endocannabinoid system a potential therapeutic target for gastrointestinal diseases. Cannabis and cannabinoids appear to influence this system via CB1 and CB2 receptors and other mechanisms (Hasenoehrl 2016; Klein 2006).
CB1 receptors are widely expressed in the gastrointestinal tract, central nervous system and peripheral tissues such as blood vessels (Hasenoehrl 2016; Klein 2006). In the GI tract, the CB1 receptors are found in the enteric nervous system, the epithelial lining, plasma cells, and smooth muscle cells of blood vessels (Hasenoehrl 2016). CB1 receptor activation may reduce gastric emptying, intestinal transit time, as well as reduce colonic propulsion (Pinto 2002). The brain‐gut axis also influences motility and CB1 receptors in the vagus nerve are part of normal motility (Vianna 2012). CB1 receptors modulate the release of multiple neurotransmitters in the central nervous system causing central effects such as a reduction in pain and nausea (Klein 2006; Tibirica 2010). Activation of the CB1 receptor may enhance epithelial wound closure in the colon (Wright 2005). There is also evidence that upregulation of CB1 receptors and activation of CB1 receptors physiologically protects the colon during excessive inflammation in the colon (Massa 2004).
CB2 receptors are mainly expressed in immune cells, myenteric plexus neurons, and in epithelial cells during ulcerative colitis (Hasenoehrl 2016; Klein 2006; Marquez 2009). CB2 receptors are expressed on immune cells such B‐cells, NK cells and macrophages (Klein 2006). CB2 activation leads to T‐cell apoptosis and decreased proliferation in colitis (Singh 2012). CB2 activation also decreases the recruitment of neutrophils, T cells and macrophages to the inflamed colon (Singh 2012).
Other receptors in the GI tract have been found to be endocannabinoid‐responsive through mechanisms separate from CB1 and CB2 receptors (Hasenoehrl 2016). These include the peroxisome proliferator‐activated receptor alpha, the G‐protein coupled receptor 55, and transient receptor potential cation channel subfamily V member 1 (Hasenoehrl 2016). Cannabinoids also help modulate chemokine and cytokine release (Klein 2006).
Why it is important to do this review
It is important to do this review to evaluate the strength of evidence for the use of cannabis and cannabinoids as treatment for CD. It will help clarify if this therapy leads to objective physiological improvement beyond subjective and psychotropic scores. Further, we hope to evaluate various modes of consumption and assess for adverse effects.
Objectives
The primary objective is to assess the efficacy and safety of cannabis for induction and maintenance of remission in patients with Crohn’s disease.
Methods
Criteria for considering studies for this review
Types of studies
Randomized controlled intervention trials will be considered for inclusion. Studies published as abstracts will only be included if the authors can be reached for further information to allow for evaluation of quality and main outcomes.
Types of participants
Adult patients (> 18 years of age) with Crohn’s disease (as defined by the included studies) will be considered for inclusion. Clinical remission or quiescent disease is often defined by the Crohn's Disease Activity Index (CDAI). Patients with active (e.g. CDAI > 150) or quiescent disease (defined as mild or absent symptoms prior to entering the study or by a CDAI < 150) will be included. Patients with surgically‐induced remission will be excluded.
Types of interventions
Studies comparing any form of cannabis or its cannabinoid derivatives (natural or synthetic) to placebo or an active therapy for Crohn’s disease will be included. We will also include studies that assess different cannabis or cannabinoid doses, and analyze dose response.
Types of outcome measures
Primary outcomes
The primary outcome will be remission at study endpoint for induction of remission studies (as defined by a CDAI < 150) and relapse (e.g. CDAI > 150) at study endpoint for maintenance studies. Any validated scoring system such as the CDAI or Disease Activity Score (DAS) will be included.
Secondary outcomes
Secondary outcomes will include:
1. Endoscopic remission;
2. Endoscopic improvement;
3. Histological response;
4. Quality of life;
5. CRP and fecal calprotectin measurements;
6. Adverse events;
7. Serious adverse events;
8. Withdrawal due to adverse events; and
9. Cannabis dependence and withdrawal effects.
Search methods for identification of studies
Electronic searches
We will search the following databases from inception to date:
1. MEDLINE (Ovid);
2. EMBASE (Ovid);
3. The Cochrane IBD Group Specialized Register; and
4. CENTRAL.
Searching other resources
Conference proceedings will be searched to identify studies published in abstract form. We will also search the references of applicable studies and systematic reviews to identify additional studies. We will search ClinicalTrials.gov and the EU Clinical Trials Register to identify ongoing studies.
Data collection and analysis
Selection of studies
Study papers and abstracts will be identified by the literature search and reviewed. Two authors (TK and NC) will independently screen the search results to identify potentially relevant studies for full text evaluation. The studies selected for full text review will be independently assessed by two authors (TK and NC) and consensus for study inclusion and exclusion will be reached through discussion. Any conflicts regarding inclusion or exclusion will be resolved by consultation with a third author (JKM). Studies published in abstract form will only be included if the authors can be reached for further information.
Data extraction and management
Two authors (TK and NC) will independently extract the outcome data of interest from each study. Any conflicts will be resolved by discussion and consensus or by consultation with a third author (JKM) as necessary. If data are missing or unclear, the study authors will be contacted for clarification.
Other information extracted from the studies will include:
a. Study characteristics and design;
b. Characteristics of patients;
c. Inclusion and exclusion criteria;
d. Interventions; and
e. Outcomes scoring methods.
Assessment of risk of bias in included studies
Two authors (TK and NC) will independently assess the methodological quality of included studies using the Cochrane risk of bias tool (Higgins 2011a). Any conflicts will be resolved by discussion and consensus or by consultation with a third author (JKM) as required. Items to be assessed will include:
1. Random sequence generation;
2. Allocation sequence concealment;
3. Blinding of participants, personnel and assessment of outcome;
4. Incomplete outcome data;
5. Selective outcome reporting; and
6. Other potential sources of bias.
Each category will be evaluated as low, high or unclear risk and judgment justification provided in the Characteristics of included studies section of the review.
GRADE Analysis
The overall quality of the evidence supporting the primary outcome and selected secondary outcomes will be evaluated using the GRADE criteria (Guyatt 2008; Schünemann 2011). Using this approach outcome data will be rated high, moderate, low or very low quality. Outcome data from randomized controlled trials begins as high quality, but can be downgraded based on several criteria. These criteria include:
1. Risk of bias from the studies;
2. Indirect evidence (by comparison, population, setting);
3. Inconsistency (i.e. unexplained heterogeneity);
4. Imprecision in data (i.e. few events and wide confidence intervals); and
5. Likelihood of publication bias.
Measures of treatment effect
For dichotomous outcomes, we will calculate the risk ratio (RR) and corresponding 95% confidence interval (CI). For continuous outcomes, we will calculate the mean difference (MD) and corresponding 95% CI .
Unit of analysis issues
For multi‐arm trials with a single placebo group and two treatment dose groups, we will split the placebo group in half to avoid a unit of analysis error (Higgins 2011b). To avoid potential carry‐over effects, we will only include the first part of the study (i.e. before the cross‐over) for any cross‐over studies (Higgins 2011b).
For studies where events may reoccur we will include the proportion of patients who experience at least one event (i.e. the first event). When there are repeated observations on participants, we will use the primary endpoint defined by the study. It is unlikely that we will find study designs applicable to cannabis in Crohn’s disease where multiple treatment attempts are used. We do not anticipate any available cluster‐randomized studies.
Dealing with missing data
Data will be analyzed on an intention‐to‐treat basis. Studies will be evaluated for missing data and where explanations were not provided, the patient outcome will be considered to be a treatment failure. For dichotomous outcomes, we can deal with missing data by treating missing participants as treatment failures. We will count failures as a relapse for maintenance studies and as failure to enter remission for induction studies.
We will conduct an available case analysis for missing continuous outcomes. For missing standard deviations of continuous outcomes, we will impute standard deviations where reasonably possible. Sensitivity analysis will be used to assess the impact of any imputation.
Assessment of heterogeneity
Statistical heterogeneity will be assessed using the Chi2 test and I2 statistic. For the Chi2 test a P value of less than 0.1 will be considered statistically significant. The degree of statistical heterogeneity will be quantified using the I2 statistic. We will investigate heterogeneity by visually inspecting the forest plots to identify outliers. If outliers are identified, we will conduct sensitivity analysis to explore potential explanations for the heterogeneity. If significant heterogeneity is identified, a random‐effects model will be used. We will not pool data for meta‐analysis when a high degree of heterogeneity is detected (e.g. I2 > 75%).
Assessment of reporting biases
We will assess selective reporting by comparing outcomes pre‐specified in study protocols to those reported in study manuscripts. If protocols were not available for the included studies, we will assess reporting bias by comparing the outcomes specified in the methods section of the manuscript to those reported in the results section. If there are more than 10 included studies in a pooled analysis, we plan to investigate publication bias by constructing funnel plots (Egger 1997).
Data synthesis
Data from individual trials will be combined for meta‐analysis when the interventions, patient groups and outcomes are sufficiently similar (to be determined by consensus). We will calculate the pooled RR and 95% CI for dichotomous outcomes using a fixed‐effect model. For continuous outcomes we will calculate the pooled MD and corresponding 95% CI . For continuous outcomes that utilize different scales to measure the same underlying construct we will calculate the standardized mean difference (SMD) and corresponding 95% CI.
Subgroup analysis and investigation of heterogeneity
We will attempt to perform subgroup analyses by dose (based on percentage of THC) if the data allow for such comparisons. Other subgroup analysis of interest will be effect based on disease location, cigarette smoking status, history of biologic therapy and failure of biologic therapy.
Sensitivity analysis
We will undertake a sensitivity analysis of study quality by excluding low quality studies to see if there is an impact on the point estimate.
