Systematic review and meta-analysis of cannabinoids, cannabis-based medicines, and endocannabinoid system modulators tested for antinociceptive effects in animal models of injury-related or pathological persistent pain

ABSTRACT

We report a systematic review and meta-analysis of studies that assessed the antinociceptive efficacy of cannabinoids, cannabis-based medicines, and endocannabinoid system modulators on pain-associated behavioural outcomes in animal models of pathological or injury-related persistent pain. In April 2019, we systematically searched 3 online databases and used crowd science and machine learning to identify studies for inclusion. We calculated a standardised mean difference effect size for each comparison and performed a random-effects meta-analysis. We assessed the impact of study design characteristics and reporting of mitigations to reduce the risk of bias. We meta-analysed 374 studies in which 171 interventions were assessed for antinociceptive efficacy in rodent models of pathological or injury-related pain. Most experiments were conducted in male animals (86%). Antinociceptive efficacy was most frequently measured by attenuation of hypersensitivity to evoked limb withdrawal. Selective cannabinoid type 1, cannabinoid type 2, nonselective cannabinoid receptor agonists (including delta-9-tetrahydrocannabinol) and peroxisome proliferator-activated receptor-alpha agonists (predominantly palmitoylethanolamide) significantly attenuated pain-associated behaviours in a broad range of inflammatory and neuropathic pain models. Fatty acid amide hydrolase inhibitors, monoacylglycerol lipase inhibitors, and cannabidiol significantly attenuated pain-associated behaviours in neuropathic pain models but yielded mixed results in inflammatory pain models. The reporting of criteria to reduce the risk of bias was low; therefore, the studies have an unclear risk of bias. The value of future studies could be enhanced by improving the reporting of methodological criteria, the clinical relevance of the models, and behavioural assessments. Notwithstanding, the evidence supports the hypothesis of cannabinoid-induced analgesia.

State of the evidence: a survey of global disparities in clinical trials

Introduction

Ideally, health conditions causing the greatest global disease burden should attract increased research attention. We conducted a comprehensive global study investigating the number of randomised controlled trials (RCTs) published on different health conditions, and how this compares with the global disease burden that they impose.

Methods

We use machine learning to monitor PubMed daily, and find and analyse RCT reports. We assessed RCTs investigating the leading causes of morbidity and mortality from the Global Burden of Disease study. Using regression models, we compared numbers of actual RCTs in different health conditions to numbers predicted from their global disease burden (disability-adjusted life years (DALYs)). We investigated whether RCT numbers differed for conditions disproportionately affecting countries with lower socioeconomic development.

Results

We estimate 463 000 articles describing RCTs (95% prediction interval 439 000 to 485 000) were published from 1990 to July 2020. RCTs recruited a median of 72 participants (IQR 32–195). 82% of RCTs were conducted by researchers in the top fifth of countries by socio-economic development. As DALYs increased for a particular health condition by 10%, the number of RCTs in the same year increased by 5% (3.2%–6.9%), but the association was weak (adjusted R²=0.13). Conditions disproportionately affecting countries with lower socioeconomic development, including respiratory infections and tuberculosis (7000 RCTs below predicted) and enteric infections (9700 RCTs below predicted), appear relatively under-researched for their disease burden. Each 10% shift in DALYs towards countries with low and middle socioeconomic development was associated with a 4% reduction in RCTs (3.7%–4.9%). These disparities have not changed substantially over time.

Conclusion

Research priorities are not well optimised to reduce the global burden of disease. Most RCTs are produced by highly developed countries, and the health needs of these countries have been, on average, favoured.

Management of Laryngeal Trauma

The larynx is a complex anatomic structure and a properly functioning larynx is essential for breathing, voice, and swallowing. Laryngeal trauma is often associated with other injuries, including intracranial injuries, penetrating neck injuries, cervical spine fractures, and facial fractures. Although uncommon, laryngotracheal injuries may lead to life-threatening airway emergencies. Because laryngeal injuries are rare, even surgeons with a great deal of experience in managing maxillofacial trauma have limited exposure to management of laryngeal and tracheal injury. This article reviews a protocol for the evaluation, management, and treatment of these injuries in the trauma patient.

Data extraction methods for systematic review (semi)automation: Update of a living systematic review

Background: The reliable and usable (semi)automation of data extraction can support the field of systematic review by reducing the workload required to gather information about the conduct and results of the included studies. This living systematic review examines published approaches for data extraction from reports of clinical studies. Methods: We systematically and continually search PubMed, ACL Anthology, arXiv, OpenAlex via EPPI-Reviewer, and the  dblp computer science bibliography. Full text screening and data extraction are conducted within an open-source living systematic review application created for the purpose of this review. This living review update includes publications up to December 2022 and OpenAlex content up to March 2023. Results: 76 publications are included in this review. Of these, 64 (84%) of the publications addressed extraction of data from abstracts, while 19 (25%) used full texts. A total of 71 (93%) publications developed classifiers for randomised controlled trials. Over 30 entities were extracted, with PICOs (population, intervention, comparator, outcome) being the most frequently extracted. Data are available from 25 (33%), and code from 30 (39%) publications. Six (8%) implemented publicly available tools Conclusions: This living systematic review presents an overview of (semi)automated data-extraction literature of interest to different types of literature review. We identified a broad evidence base of publications describing data extraction for interventional reviews and a small number of publications extracting epidemiological or diagnostic accuracy data. Between review updates, trends for sharing data and code increased strongly: in the base-review, data and code were available for 13 and 19% respectively, these numbers increased to 78 and 87% within the 23 new publications. Compared with the base-review, we observed another research trend, away from straightforward data extraction and towards additionally extracting relations between entities or automatic text summarisation. With this living review we aim to review the literature continually.

Data extraction methods for systematic review (semi)automation: A living systematic review

Background: The reliable and usable (semi)automation of data extraction can support the field of systematic review by reducing the workload required to gather information about the conduct and results of the included studies. This living systematic review examines published approaches for data extraction from reports of clinical studies. Methods: We systematically and continually search MEDLINE, Institute of Electrical and Electronics Engineers (IEEE), arXiv, and the dblp computer science bibliography databases. Full text screening and data extraction are conducted within an open-source living systematic review application created for the purpose of this review. This iteration of the living review includes publications up to a cut-off date of 22 April 2020. Results: In total, 53 publications are included in this version of our review. Of these, 41 (77%) of the publications addressed extraction of data from abstracts, while 14 (26%) used full texts. A total of 48 (90%) publications developed and evaluated classifiers that used randomised controlled trials as the main target texts. Over 30 entities were extracted, with PICOs (population, intervention, comparator, outcome) being the most frequently extracted. A description of their datasets was provided by 49 publications (94%), but only seven (13%) made the data publicly available. Code was made available by 10 (19%) publications, and five (9%) implemented publicly available tools. Conclusions: This living systematic review presents an overview of (semi)automated data-extraction literature of interest to different types of systematic review. We identified a broad evidence base of publications describing data extraction for interventional reviews and a small number of publications extracting epidemiological or diagnostic accuracy data. The lack of publicly available gold-standard data for evaluation, and lack of application thereof, makes it difficult to draw conclusions on which is the best-performing system for each data extraction target. With this living review we aim to review the literature continually.

The use of Qualitative Comparative Analysis (QCA) to address causality in complex systems: a systematic review of research on public health interventions

Background

Qualitative Comparative Analysis (QCA) is a method for identifying the configurations of conditions that lead to specific outcomes. Given its potential for providing evidence of causality in complex systems, QCA is increasingly used in evaluative research to examine the uptake or impacts of public health interventions. We map this emerging field, assessing the strengths and weaknesses of QCA approaches identified in published studies, and identify implications for future research and reporting.

Methods

PubMed, Scopus and Web of Science were systematically searched for peer-reviewed studies published in English up to December 2019 that had used QCA methods to identify the conditions associated with the uptake and/or effectiveness of interventions for public health. Data relating to the interventions studied (settings/level of intervention/populations), methods (type of QCA, case level, source of data, other methods used) and reported strengths and weaknesses of QCA were extracted and synthesised narratively.

Results

The search identified 1384 papers, of which 27 (describing 26 studies) met the inclusion criteria. Interventions evaluated ranged across: nutrition/obesity (n = 8); physical activity (n = 4); health inequalities (n = 3); mental health (n = 2); community engagement (n = 3); chronic condition management (n = 3); vaccine adoption or implementation (n = 2); programme implementation (n = 3); breastfeeding (n = 2), and general population health (n = 1). The majority of studies (n = 24) were of interventions solely or predominantly in high income countries. Key strengths reported were that QCA provides a method for addressing causal complexity; and that it provides a systematic approach for understanding the mechanisms at work in implementation across contexts. Weaknesses reported related to data availability limitations, especially on ineffective interventions. The majority of papers demonstrated good knowledge of cases, and justification of case selection, but other criteria of methodological quality were less comprehensively met.

Conclusion

QCA is a promising approach for addressing the role of context in complex interventions, and for identifying causal configurations of conditions that predict implementation and/or outcomes when there is sufficiently detailed understanding of a series of comparable cases. As the use of QCA in evaluative health research increases, there may be a need to develop advice for public health researchers and journals on minimum criteria for quality and reporting.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-10926-2.

The impact of living with transfeminine vocal gender dysphoria: Health utility outcomes assessment

Background: The voice signals a tremendous amount of gender cues. Transfeminine individuals report debilitating quality-of-life deficits as a result of their vocal gender dysphoria.Aims: We aimed to quantify the potential impact of this dysphoria experienced with quality-adjusted life years (QALYs), as well as associated treatments, through validated health utility measures. Methods: Peri-operative phonometric audio recordings of a consented transfeminine patient volunteer with a history of vocal gender dysphoria aided in the description of two transfeminine health states, pre- and post-vocal feminization gender dysphoria; monocular and binocular blindness were health state controls. Survey responses from general population adults rate these four health states via visual analogue scale (VAS), standard gamble (SG), and time tradeoff (TTO). Results: Survey respondents totaled 206 with a mean age of 35.8 years. Through VAS measures, these general adult respondents on average perceived a year of life with transfeminine vocal gender dysphoria as approximately three-quarters of a life-year of perfect health. Respondents also on average would have risked a 15%-20% chance of death on SG analysis and would have sacrificed 10 years of their remaining life on TTO measures to cure the condition. The QALY scores for the post-gender affirming treatments for vocal gender dysphoria (+0.09 VAS, p < 0.01) were significantly higher compared to the pretreatment state. There were no differences in the severity of these QALY scores by survey respondent's political affiliation or gender identity. Conclusions: To our knowledge, this study is the first to quantify how the general population perceives the health burden of vocal gender dysphoria experienced by transfeminine patients. Feminization treatments including voice therapy with feminization laryngoplasty appear to significantly increase health utility scores.

Machine learning reduced workload with minimal risk of missing studies: development and evaluation of a randomized controlled trial classifier for Cochrane Reviews

OBJECTIVES

This study developed, calibrated, and evaluated a machine learning classifier designed to reduce study identification workload in Cochrane for producing systematic reviews.

METHODS

A machine learning classifier for retrieving randomized controlled trials (RCTs) was developed (the "Cochrane RCT Classifier"), with the algorithm trained using a data set of title-abstract records from Embase, manually labeled by the Cochrane Crowd. The classifier was then calibrated using a further data set of similar records manually labeled by the Clinical Hedges team, aiming for 99% recall. Finally, the recall of the calibrated classifier was evaluated using records of RCTs included in Cochrane Reviews that had abstracts of sufficient length to allow machine classification.

RESULTS

The Cochrane RCT Classifier was trained using 280,620 records (20,454 of which reported RCTs). A classification threshold was set using 49,025 calibration records (1,587 of which reported RCTs), and our bootstrap validation found the classifier had recall of 0.99 (95% confidence interval 0.98-0.99) and precision of 0.08 (95% confidence interval 0.06-0.12) in this data set. The final, calibrated RCT classifier correctly retrieved 43,783 (99.5%) of 44,007 RCTs included in Cochrane Reviews but missed 224 (0.5%). Older records were more likely to be missed than those more recently published.

CONCLUSIONS

The Cochrane RCT Classifier can reduce manual study identification workload for Cochrane Reviews, with a very low and acceptable risk of missing eligible RCTs. This classifier now forms part of the Evidence Pipeline, an integrated workflow deployed within Cochrane to help improve the efficiency of the study identification processes that support systematic review production.

Metastatic small bowel adenocarcinoma: role of metastasectomy and systemic chemotherapy

Background

Metastatic small bowel adenocarcinoma (SBA) has a poor prognosis. Due to its rarity, high-quality data are lacking to guide treatment. This retrospective analysis was conducted to help characterize the treatment options for patients with metastatic SBA while providing clinically meaningful prognostic information.

Patients and methods

In total, 437 patients who initially presented with or developed metastatic SBA between September 1977 and September 2019 were identified from the MD Anderson Tumor Registry. Clinical data were collected from review of the medical record. Overall response rates (ORR), time to progression (TTP), and overall survival (OS) were assessed across various treatments and treatment lines.

Results

The median OS from diagnosis of metastatic disease was 15.9 months [95% confidence interval (CI): 14.3-17.9]. Seventy-five patients (17.1%) underwent metastasectomy, which was associated with a median OS of 34.5 versus 17.1 months among patients who received chemotherapy alone (P < 0.001). Fluoropyrimidine plus platinum (n = 164) was the most common first-line chemotherapy, associated with an ORR of 59% and TTP of 8.1 months. Irinotecan with 5-FU (n = 101) was the most common second-line therapy associated with an ORR of 31% and TTP of 4.0 months. Twenty-two patients received immunotherapy; 5 of 6 patients with deficient mismatch repair (dMMR) responded, while 0 of 16 with proficient mismatch repair (pMMR) responded. Taxane-based chemotherapy was given to 34 patients with an ORR of 21% and a median TTP of 2.4 months. Among 11 patients who received anti-epidermal-growth-factor-receptor (EGFR) monotherapy, the best response was stable disease (SD) in 1 patient.

Conclusions

In well-selected patients with SBA, metastasectomy appears to be associated with improved OS. This improvement was seen across metastasectomy sites, including liver, lung and peritoneal. Anti-programmed cell death protein 1 (PD-1) based immunotherapy was active for dMMR SBA but not pMMR SBA. While taxane-based chemotherapy demonstrates therapeutic activity, the activity of anti-EGFR therapy was limited.

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Metastasectomy for well-selected metastatic SBA patients was associated with improved OS.

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Anti-PD1-based immunotherapy was active for dMMR SBA but not pMMR SBA.

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Taxane-based chemotherapy demonstrated clinical activity in refractory SBA.

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Anti-EGFR therapy demonstrated minimal activity in SBA.

Rapid systematic review of systematic reviews: what befriending, social support and low intensity psychosocial interventions, delivered remotely, may reduce social isolation and loneliness among older adults and how?

Background: During the COVID-19 pandemic ‘social distancing’ has highlighted the need to minimise loneliness and isolation among older adults (aged 50+). We wanted to know what remotely delivered befriending, social support and low intensity psychosocial interventions may help to alleviate social isolation and loneliness and how they work. Methods: We followed a systematic ‘review of reviews’ approach. Searches of 11 databases from the fields of health, social care, psychology and social science were undertaken during April 2020. Reviews meeting our PICOS criteria were included if they focussed on the evaluation of remote interventions to reduce levels of social isolation or loneliness in adults aged 50+ and were critically appraised using AMSTAR2. Narrative synthesis was used at a review and study level to develop a typology of intervention types and their effectiveness. Intervention Component Analysis (ICA) and Qualitative Comparative Analysis (QCA) were used at a study level to explore the characteristics of successful interventions. Results: We synthesised evidence from five systematic reviews and 18 primary studies. Remote befriending, social support and low intensity psychosocial interventions took the form of: (i) supported video-communication; (ii) online discussion groups and forums; (iii) telephone befriending; (iv) social networking sites; and (v) multi-tool interventions. The majority of studies utilised the first two approaches, and were generally regarded positively by older adults, although with mixed evidence around effectiveness. Focussing on processes and mechanisms, using ICA and QCA, we found that the interventions that were most successful in improving social support: (i) enabled participants to speak freely and to form close relationships; (ii) ensured participants have shared experiences/characteristics; (iii) included some form of pastoral guidance. Conclusions: The findings highlight a set of intervention processes that should be incorporated into interventions, although they do not lead us to recommend specific modes of support, due to the heterogeneity of interventions.

The PRISMA 2020 statement: An updated guideline for reporting systematic reviews

The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.

PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews

The methods and results of systematic reviews should be reported in sufficient detail to allow users to assess the trustworthiness and applicability of the review findings. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement was developed to facilitate transparent and complete reporting of systematic reviews and has been updated (to PRISMA 2020) to reflect recent advances in systematic review methodology and terminology. Here, we present the explanation and elaboration paper for PRISMA 2020, where we explain why reporting of each item is recommended, present bullet points that detail the reporting recommendations, and present examples from published reviews. We hope that changes to the content and structure of PRISMA 2020 will facilitate uptake of the guideline and lead to more transparent, complete, and accurate reporting of systematic reviews.

The PRISMA 2020 statement: an updated guideline for reporting systematic reviews

The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.