Adherence to Consolidated Standards of Reporting Trials (CONSORT) Guidelines for Reporting Safety Outcomes in Trials of Cannabinoids for Chronic Pain: Protocol for a Systematic Review
Bibliographic record
Abstract
BACKGROUND: Chronic pain affects a significant proportion of the population and presents a major challenge to clinicians and pain specialists. Despite the availability of pharmacologic treatment options such as opioids, many patients continue to experience persistent pain. Cannabinoids present an alternative option with some data on efficacy; however, to date, a systematic review of adverse events (AEs) assessment and reporting in randomized clinical trials (RCTs) involving cannabinoids has not been performed. As a result, it is unclear whether a clear profile of cannabinoid-associated AEs has been accurately detailed in the literature. As cannabinoids are likely to become readily available for patients in the near future, it is important to study how well AEs have been reported in trials so that the safety profile of cannabinoids can be better understood. OBJECTIVE: With a potentially enormous shift toward cannabinoid use for managing chronic pain and spasticity, this study aims to reveal the adequacy of AE reporting and cannabinoid-specific AEs in this setting. Spasticity is a major contributor to chronic pain in patients with multiple sclerosis (MS), with a comorbidity of 75%. Many cannabinoid studies have been performed in MS-related painful spasticity with relevant pain outcomes, and these studies will be included in this review for comprehensiveness. The primary outcome will be the quality of AE assessment and reporting by adherence to the Consolidated Standards of Reporting Trials (CONSORT) guidelines. Secondary outcomes will include the type of AE, method of AE reporting, severity of AE, frequency of AEs, patient withdrawals, and reasons for withdrawals. METHODS: We will perform a systematic review by searching for primary reports of double-blind, randomized controlled trials of cannabinoids compared with placebo and any active comparator treatments for chronic pain, with a primary outcome directly related to pain (eg, pain intensity, pain relief, and pain-related interference). We will search the following databases: MEDLINE, Embase, Cochrane Library, and PsycINFO. RevMan software will be used for meta-analysis. RESULTS: The protocol has been registered on the International Prospective Register of Systematic Reviews (CRD42018100401). The project was funded in 2018 and screening has been completed. Data extraction is under way and the first results are expected to be submitted for publication in January or February 2019. CONCLUSIONS: This review will better elucidate the safety of cannabinoids for the treatment of chronic pain and spasticity through identifying gaps in the literature for AE reporting. Like in any new therapy, it is essential that accurate information surrounding the safety and efficacy of cannabinoids be clearly outlined and identified to balance the benefit and harm described for patients. TRIAL REGISTRATION: PROSPERO CRD42018100401; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=100401. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/11637.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.276 | 0.457 |
| Meta-epidemiology (narrow) | 0.010 | 0.010 |
| Meta-epidemiology (broad) | 0.038 | 0.037 |
| Bibliometrics | 0.018 | 0.028 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.008 | 0.008 |
| Research integrity | 0.016 | 0.017 |
| Insufficient payload (model declined to judge) | 0.054 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".