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Burrowing behaviour is used to assess pain-associated behaviour in laboratory rodents. To gain insight into how models of disease-associated persistent pain and analgesics affect burrowing behaviour, we performed a systematic review and meta-analysis of studies that assessed burrowing behaviour. A systematic search in March 2020 and update in September 2020 was conducted in 4 databases. Study design characteristics and experimental data were extracted, followed by a random-effects meta-analysis. We explored the association between burrowing and monofilament-induced limb withdrawal. Dose response relationship was investigated for some analgesics. Forty-five studies were included in the meta-analysis, in which 16 model types and 14 drug classes were used. Most experiments used rat (79%) and male (72%) animals. Somatic inflammation and trauma-induced neuropathy models were associated with reduced burrowing behaviour. Analgesics (nonsteroidal anti-inflammatory drug and gabapentinoids) attenuated burrowing deficits in these models. Reporting of measures to reduce risk of bias was unclear except for randomisation which was high. There was not a correlation ( R2 = 0.1421) between burrowing and monofilament-induced limb withdrawal. Opioids, gabapentin, and naproxen showed reduced burrowing behaviour at high doses, whereas ibuprofen and celecoxib showed opposite trend. The findings indicate that burrowing could be used to assess pain-associated behaviour. We support the use of a portfolio of composite measures including spontaneous and stimulus-evoked tests. The information collected here could help in designing experiments involving burrowing assessment in models of disease-associated pain.

BackgroundMandates and recommendations related to embedding open science practices within the research lifecycle are increasingly common. Few stakeholders, however, are monitoring compliance to their mandates or recommendations. It is necessary to monitor the current state of open science to track changes over time and to identify areas to create interventions to drive improvements.Monitoring open science practices requires that they are defined and operationalized. Involving the biomedical community, we sought to reach consensus on a core set of open science practices to monitor at biomedical research institutions.Methods and FindingsTo establish consensus in a structured and systematic fashion, we conducted a modified 3-round Delphi study. Participants in Round 1 were 80 individuals from 20 biomedical research institutions that exhibit interest in or actively support open science. Participants were research administrators, researchers, specialists in dedicated open science roles, and librarians. In Rounds 1 and 2, participants completed an online survey evaluating a set of potential open science practices that could be important and meaningful to monitor in an automated institutional open science dashboard. Participants voted on the inclusion of each item and provided a rationale for their choice. We defined consensus as 80% agreement. Between rounds, participants received aggregated voting scores for each item and anonymized comments from all participants, and were asked to re-vote on items that did not reach consensus. For Round 3, we hosted two half- day virtual meetings with 21 and 17 participants respectively to discuss and vote on all items that had not reached consensus after Round 2. Ultimately, participants reached consensus to include a 19 open science practices.ConclusionsA group of international stakeholders used a modified Delphi process to agree upon open science practices to monitor in a proposed open science dashboard for biomedical institutions. The core set of 19 open science practices identified by participants will form the foundation for institutional dashboards that display compliance with open science practices. They will now be assessed and tested for automatic inclusion in terms of technical feasibility. Using user-centered design, participating institutions will be involved in creating a dashboard prototype, which can then be implemented to monitor rates of open science practices at biomedical institutions. Our methods and approach may also transfer to other research settings–other disciplines could consider using our consensus list as a starting point for agreement upon a discipline-specific set of open science practices to monitor. The findings may also be of broader value to the development of policy, education, and interventions.

Contains fulltext : 225443.pdf (Publisher’s version ) (Open Access) This paper is the initial Position Statement of Evidence Synthesis International, a new partnership of organizations that produce, support and use evidence synthesis around the world. The paper (i) argues for the importance of synthesis as a research exercise to clarify what is known from research evidence to inform policy, practice and personal decision making; (ii) discusses core issues for research synthesis such as the role of research evidence in decision making, the role of perspectives, participation and democracy in research and synthesis as a core component of evidence ecosystems; (iii) argues for 9 core principles for ESI on the nature and role of research synthesis; and (iv) lists the 5 main goals of ESI as a coordinating partnership for promoting and enabling the production and use of research synthesis.

Background Time-to-event data is frequently reported in both clinical and preclinical research spheres. Systematic review and meta-analysis is a tool that can help to identify pitfalls in preclinical research conduct and reporting that can help to improve translational efficacy. However, pooling of studies using hazard ratios (HRs) is cumbersome especially in preclinical meta-analyses including large numbers of small studies. Median survival is a much simpler metric although because of some limitations, which may not apply to preclinical data, it is generally not used in survival meta-analysis. We aimed to appraise its performance when compared with hazard ratio-based meta-analysis when pooling large numbers of small, imprecise studies. Methods We simulated a survival dataset with features representative of a typical preclinical survival meta-analysis, including with influence of a treatment and a number of covariates. We calculated individual patient data-based hazard ratios and median survival ratios (MSRs), comparing the summary statistics directly and their performance at random-effects meta-analysis. Finally, we compared their sensitivity to detect associations between treatment and influential covariates at meta-regression. Results There was an imperfect correlation between MSR and HR, although the opposing direction of treatment effects between summary statistics appeared not to be a major issue. Precision was more conservative for HR than MSR, meaning that estimates of heterogeneity were lower. There was a slight sensitivity advantage for MSR at meta-analysis and meta-regression, although power was low in all circumstances. Conclusions We believe we have validated MSR as a summary statistic for use in a meta-analysis of small, imprecise experimental survival studies—helping to increase confidence and efficiency in future reviews in this area. While assessment of study precision and therefore weighting is less reliable, MSR appears to perform favourably during meta-analysis. Sensitivity of meta-regression was low for this set of parameters, so pooling of treatments to increase sample size may be required to ensure confidence in preclinical survival meta-regressions.

Background The ARRIVE (Animal Research: Reporting of In Vivo Experiments) guidelines are widely endorsed but compliance is limited. We sought to determine whether journal-requested completion of an ARRIVE checklist improves full compliance with the guidelines. Methods In a randomised controlled trial, manuscripts reporting in vivo animal research submitted to PLOS ONE (March–June 2015) were randomly allocated to either requested completion of an ARRIVE checklist or current standard practice. Authors, academic editors, and peer reviewers were blinded to group allocation. Trained reviewers performed outcome adjudication in duplicate by assessing manuscripts against an operationalised version of the ARRIVE guidelines that consists 108 items. Our primary outcome was the between-group differences in the proportion of manuscripts meeting all ARRIVE guideline checklist subitems. Results We randomised 1689 manuscripts (control: n = 844, intervention: n = 845), of which 1269 were sent for peer review and 762 (control: n = 340; intervention: n = 332) accepted for publication. No manuscript in either group achieved full compliance with the ARRIVE checklist. Details of animal husbandry (ARRIVE subitem 9b) was the only subitem to show improvements in reporting, with the proportion of compliant manuscripts rising from 52.1 to 74.1% (X 2 = 34.0, df = 1, p = 2.1 × 10−7) in the control and intervention groups, respectively. Conclusions These results suggest that altering the editorial process to include requests for a completed ARRIVE checklist is not enough to improve compliance with the ARRIVE guidelines. Other approaches, such as more stringent editorial policies or a targeted approach on key quality items, may promote improvements in reporting.

Throughout the global coronavirus pandemic, we have seen an unprecedented volume of COVID-19 researchpublications. This vast body of evidence continues to grow, making it difficult for research users to keep up with the pace of evolving research findings. To enable the synthesis of this evidence for timely use by researchers, policymakers, and other stakeholders, we developed an automated workflow to collect, categorise, and visualise the evidence from primary COVID-19 research studies. We trained a crowd of volunteer reviewers to annotate studies by relevance to COVID-19, study objectives, and methodological approaches. Using these human decisions, we are training machine learning classifiers and applying text-mining tools to continually categorise the findings and evaluate the quality of COVID-19 evidence.

BackgroundResearchers who perform systematic searches across multiple databases often identify duplicate publications. Identifying such duplicates (“deduplication”) can be extremely time-consuming, but failure to remove these citations can, in the worst instance, lead to the wrongful inclusion of duplicate data. Many existing tools are not sensitive enough, lack interoperability with other tools, are not freely accessible, or are difficult to use without programming knowledge. Here, we report the performance of our Automated Systematic Search Deduplicator (ASySD), a novel tool to perform automated deduplication of systematic searches for biomedical reviews.MethodsWe evaluated ASySD’s performance on 5 unseen biomedical systematic search datasets of various sizes (1,845 – 79,880 citations), which had been deduplicated by human reviewers. We compared the performance of ASySD with Endnote’s automated deduplication option and with the Systematic Review Accelerator Deduplication Module (SRA-DM).ResultsASySD identified more duplicates than either SRA-DM or Endnote, with a sensitivity in different datasets of 0.95 to 0.99. The false-positive rate was comparable to human performance, with a specificity of 0.94-0.99. The tool took less than 1 hour to deduplicate all datasets.ConclusionsFor duplicate removal in biomedical systematic reviews, ASySD is a highly sensitive, reliable, and time-saving tool. It is open source and freely available online as both an R package and a user-friendly web application.

Preclinical research is a vital step in the drug discovery pipeline and more generally in helping to better understand human disease aetiology and its management. Systematic reviews (SRs) can be powerful in summarising and appraising this evidence concerning a specific research question, to highlight areas of improvements, areas for further research and areas where evidence may be sufficient to take forward to other research domains, for instance clinical trial. Guidance and tools for preclinical research synthesis remain limited despite their clear utility. We aimed to create an online end-to-end platform primarily for conducting SRs of preclinical studies, that was flexible enough to support a wide variety of experimental designs, was adaptable to different research questions, would allow users to adopt emerging automated tools and support them during their review process using best practice. In this article, we introduce the Systematic Review Facility (https://syrf.org.uk), which was launched in 2016 and designed to support primarily preclinical SRs from small independent projects to large, crowdsourced projects. We discuss the architecture of the app and its features, including the opportunity to collaborate easily, to efficiently manage projects, to screen and annotate studies for important features (metadata), to extract outcome data into a secure database, and tailor these steps to each project. We introduce how we are working to leverage the use of automation tools and allow the integration of these services to accelerate and automate steps in the systematic review workflow.

ObjectiveThigmotaxis is an innate predator avoidance behaviour of rodents and is enhanced when animals are under stress. It is characterised by the preference of a rodent to seek shelter, rather than expose itself to the aversive open area. The behaviour has been proposed to be a measurable construct that can address the impact of pain on rodent behaviour. This systematic review will assess whether thigmotaxis can be influenced by experimental persistent pain and attenuated by pharmacological interventions in rodents.Search strategyWe will conduct search on three electronic databases to identify studies in which thigmotaxis was used as an outcome measure contextualised to a rodent model associated with persistent pain. All studies published until the date of the search will be considered.Screening and annotationTwo independent reviewers will screen studies based on the order of (1) titles and abstracts, and (2) full texts.Data management and reportingFor meta-analysis, we will extract thigmotactic behavioural data and calculate effect sizes. Effect sizes will be combined using a random-effects model. We will assess heterogeneity and identify sources of heterogeneity. A risk-of-bias assessment will be conducted to evaluate study quality. Publication bias will be assessed using funnel plots, Egger’s regression and trim-and-fill analysis. We will also extract stimulus-evoked limb withdrawal data to assess its correlation with thigmotaxis in the same animals. The evidence obtained will provide a comprehensive understanding of the strengths and limitations of using thigmotactic outcome measure in animal pain research so that future experimental designs can be optimised. We will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines and disseminate the review findings through publication and conference presentation.

Great expectations have been set around the clinical potential of regenerative and reparative medicine in the treatment of cardiovascular diseases [i.e. in particular, heart failure (HF)]. Initial excitement, spurred by encouraging preclinical data, resulted in a rapid translation into clinical research. The sobering outcome of the resulting clinical trials suggests that preclinical testing may have been insufficient to predict clinical outcome. A number of barriers for clinical translation include the inherent variability of the biological products and difficulties to develop potency and quality assays, insufficient rigour of the preclinical research and reproducibility of the results, manufacturing challenges, and scientific irregularities reported in the last years. The failure to achieve clinical success led to an increased scrutiny and scepticism as to the clinical readiness of stem cells and gene therapy products among clinicians, industry stakeholders, and funding bodies. The present impasse has attracted the attention of some of the most active research groups in the field, which were then summoned to analyse the position of the field and tasked to develop a strategy, to re-visit the undoubtedly promising future of cardiovascular regenerative and reparative medicine, based on lessons learned over the past two decades. During the scientific retreat of the ESC Working Group on Cardiovascular Regenerative and Reparative Medicine (CARE) in November 2018, the most relevant and timely research aspects in regenerative and/or reparative medicine were presented and critically discussed, with the aim to lay out a strategy for the future development of the field. We report herein the main ideas and conclusions of that meeting.

Assessment of outcome in preclinical studies of vascular cognitive impairment (VCI) is heterogenous. Through an ARUK Scottish Network supported questionnaire and workshop (mostly UK-based researchers), we aimed to determine underlying variability and what could be implemented to overcome identified challenges. Twelve UK VCI research centres were identified and invited to complete a questionnaire and attend a one-day workshop. Questionnaire responses demonstrated agreement that outcome assessments in VCI preclinical research vary by group and even those common across groups, may be performed differently. From the workshop, six themes were discussed: issues with preclinical models, reasons for choosing functional assessments, issues in interpretation of functional assessments, describing and reporting functional outcome assessments, sharing resources and expertise, and standardization of outcomes. Eight consensus points emerged demonstrating broadly that the chosen assessment should reflect the deficit being measured, and therefore that one assessment does not suit all models; guidance/standardisation on recording VCI outcome reporting is needed and that uniformity would be aided by a platform to share expertise, material, protocols and procedures thus reducing heterogeneity and so increasing potential for collaboration, comparison and replication. As a result of the workshop, UK wide consensus statements were agreed and future priorities for preclinical research identified.

An important factor for successful translational stroke research is study quality. Low-quality studies are at risk of biased results and effect overestimation, as has been intensely discussed for small animal stroke research. However, little is known about the methodological rigor and quality in large animal stroke models, which are becoming more frequently used in the field. Based on research in two databases, this systematic review surveys and analyses the methodological quality in large animal stroke research. Quality analysis was based on the Stroke Therapy Academic Industry Roundtable and the Animals in Research: Reporting In Vivo Experiments guidelines. Our analysis revealed that large animal models are utilized with similar shortcomings as small animal models. Moreover, translational benefits of large animal models may be limited due to lacking implementation of important quality criteria such as randomization, allocation concealment, and blinded assessment of outcome. On the other hand, an increase of study quality over time and a positive correlation between study quality and journal impact factor were identified. Based on the obtained findings, we derive recommendations for optimal study planning, conducting, and data analysis/reporting when using large animal stroke models to fully benefit from the translational advantages offered by these models.

Reproducible science requires transparent reporting. The ARRIVE guidelines were originally developed in 2010 to improve the reporting of animal research. They consist of a checklist of information to include in publications describing in vivo experiments to enable others to scrutinise the work adequately, evaluate its methodological rigour, and reproduce the methods and results. Despite considerable levels of endorsement by funders and journals over the years, adherence to the guidelines has been inconsistent, and the anticipated improvements in the quality of reporting in animal research publications have not been achieved.Here we introduce ARRIVE 2019. The guidelines have been updated and information reorganised to facilitate their use in practice. We used a Delphi exercise to prioritise the items and split the guidelines into two sets, the ARRIVE Essential 10, which constitute the minimum requirement, and the Recommended Set, which describes the research context. This division facilitates improved reporting of animal research by supporting a stepwise approach to implementation. This helps journal editors and reviewers to verify that the most important items are being reported in manuscripts. We have also developed the accompanying Explanation and Elaboration document that serves 1) to explain the rationale behind each item in the guidelines, 2) to clarify key concepts and 3) to provide illustrative examples. We aim through these changes to help ensure that researchers, reviewers and journal editors are better equipped to improve the rigour and transparency of the scientific process and thus reproducibility.

Improving the reproducibility of biomedical research is a major challenge. Transparent and accurate reporting are vital to this process; it allows readers to assess the reliability of the findings, and repeat or build upon the work of other researchers. The NC3Rs developed the ARRIVE guidelines in 2010 to help authors and journals identify the minimum information necessary to report in publications describing in vivo experiments.Despite widespread endorsement by the scientific community, the impact of the ARRIVE guidelines on the transparency of reporting in animal research publications has been limited. We have revised the ARRIVE guidelines to update them and facilitate their use in practice. The revised guidelines are published alongside this paper. This Explanation and Elaboration document was developed as part of the revision. It provides further information about each of the 21 items in ARRIVE 2019, including the rationale and supporting evidence for their inclusion in the guidelines, elaboration of details to report, and examples of good reporting from the published literature.

ObjectiveTo determine whether and to what degree bias and underestimated variability undermine the predictive value of preclinical research for clinical translation.MethodsWe investigated experimental spinal cord injury (SCI) studies for outcome heterogeneity and the impact of bias. Data from 549 preclinical SCI studies including 9,535 animals were analyzed with meta-regression to assess the effect of various study characteristics and the quality of neurologic recovery.ResultsOverall, the included interventions reported a neurobehavioral outcome improvement of 26.3% (95% confidence interval 24.3–28.4). Response to treatment was dependent on experimental modeling paradigms (neurobehavioral score, site of injury, and animal species). Applying multiple outcome measures was consistently associated with smaller effect sizes compared with studies applying only 1 outcome measure. More than half of the studies (51.2%) did not report blinded assessment, constituting a likely source of evaluation bias, with an overstated effect size of 7.2%. Assessment of publication bias, which extrapolates to identify likely missing data, suggested that between 2% and 41% of experiments remain unpublished. Inclusion of these theoretical missing studies suggested an overestimation of efficacy, reducing the effect sizes by between 0.9% and 14.3%.ConclusionsWe provide empirical evidence of prevalent bias in the design and reporting of experimental SCI studies, resulting in overestimation of the effectiveness. Bias compromises the internal validity and jeopardizes the successful translation of SCI therapies from the bench to bedside.

We report a systematic review and meta-analysis of research using animal models of chemotherapy-induced peripheral neuropathy (CIPN). We systematically searched 5 online databases in September 2012 and updated the search in November 2015 using machine learning and text mining to reduce the screening for inclusion workload and improve accuracy. For each comparison, we calculated a standardised mean difference (SMD) effect size, and then combined effects in a random-effects meta-analysis. We assessed the impact of study design factors and reporting of measures to reduce risks of bias. We present power analyses for the most frequently reported behavioural tests; 337 publications were included. Most studies (84%) used male animals only. The most frequently reported outcome measure was evoked limb withdrawal in response to mechanical monofilaments. There was modest reporting of measures to reduce risks of bias. The number of animals required to obtain 80% power with a significance level of 0.05 varied substantially across behavioural tests. In this comprehensive summary of the use of animal models of CIPN, we have identified areas in which the value of preclinical CIPN studies might be increased. Using both sexes of animals in the modelling of CIPN, ensuring that outcome measures align with those most relevant in the clinic, and the animal’s pain contextualised ethology will likely improve external validity. Measures to reduce risk of bias should be employed to increase the internal validity of studies. Different outcome measures have different statistical power, and this can refine our approaches in the modelling of CIPN., This systematic review assesses limitations in the experimental design of studies modelling peripheral neuropathy induced by chemotherapy. The data allow the authors to provide guidance on experimental design to improve the robustness and validity of future studies., Author summary Many frequently used and effective cancer chemotherapies can cause a disabling side effect that features pain, numbness, tingling, and sensitivity to cold and heat in the extremities known as chemotherapy-induced peripheral neuropathy (CIPN). There are currently no effective therapies to treat or prevent this condition, and animal models have been developed to address this. It is important that experiments using animal models of CIPN are robust and valid if they are to effectively help patients. We used a systematic approach to identify all 337 studies that have been published describing the use of animal models of CIPN. We were able to identify that many studies are imperfect in their experimental design, use only male animals, and assess outcomes with limited relevance to the human condition. Based on a meta-analysis, we provide guidance to the CIPN animal modelling community to guide future experiments that may improve their utility and validity.

Objective To determine whether a change in editorial policy, including the implementation of a checklist, has been associated with improved reporting of measures which might reduce the risk of bias.Methods The study protocol has been published at doi: 10.1007/s11192-016-1964-8.Design Observational cohort study.Population Articles describing research in the life sciences published in Nature journals, submitted after 1 May 2013.Intervention Mandatory completion of a checklist during manuscript revision.Comparators (1) Articles describing research in the life sciences published in Nature journals, submitted before May 2013; and (2) similar articles in other journals matched for date and topic.Primary outcome The primary outcome is change in the proportion of Nature articles describing in vivo research published before and after May 2013 reporting the ‘Landis 4’ items (randomisation, blinding, sample size calculation and exclusions). We included 448 Nature Publishing Group (NPG) articles (223 published before May 2013, and 225 after) identified by an individual hired by NPG for this specific task, working to a standard procedure; and an independent investigator used PubMed ‘Related Citations’ to identify 448 non-NPG articles with a similar topic and date of publication from other journals; and then redacted all articles for time-sensitive information and journal name. Redacted articles were assessed by two trained reviewers against a 74-item checklist, with discrepancies resolved by a third.Results 394 NPG and 353 matching non-NPG articles described in vivo research. The number of NPG articles meeting all relevant Landis 4 criteria increased from 0/203 prior to May 2013 to 31/181 (16.4%) after (two-sample test for equality of proportions without continuity correction, Χ²=36.2, df=1, p=1.8×10−9). There was no change in the proportion of non-NPG articles meeting all relevant Landis 4 criteria (1/164 before, 1/189 after). There were more substantial improvements in the individual prevalences of reporting of randomisation, blinding, exclusions and sample size calculations for in vivo experiments, and less substantial improvements for in vitro experiments.Conclusion There was an improvement in the reporting of risks of bias in in vivo research in NPG journals following a change in editorial policy, to a level that to our knowledge has not been previously observed. However, there remain opportunities for further improvement.This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

Any given research claim can be made with a degree of confidence that a phenomenon is present, with an estimate of the precision of the observed effects and a prediction of the extent to which the findings might hold true under different experimental or real-world conditions. In some situations, the certainty and precision obtained from a single study are sufficient reliably to inform future research decisions. However, in other situations greater certainty is required. This might be the case where a substantial research investment is planned, a pivotal claim is to be made or the launch of a clinical trial programme is being considered. Under these circumstances, some form of summary of findings across studies may be helpful.Summary estimates can describe findings from exploratory (observational) or hypothesis testing experiments, but importantly, the creation of such summaries is, in itself, observational rather than experimental research. The process is therefore particularly at risk from selective identification of literature to be included, and this can be addressed using systematic search strategies and pre-specified criteria for inclusion and exclusion against which possible contributing data will be assessed. This characterises a systematic review (in contrast to nonsystematic or narrative reviews). In meta-analysis, there is an attempt to provide a quantitative summary of such research findings.

Introduction: Globally, stroke is the second leading cause of death. Despite the burden of illness and death, few acute interventions are available to patients with ischemic stroke. Over 1,000 potential neuroprotective therapeutics have been evaluated in preclinical models. It is important to use robust evidence synthesis methods to appropriately assess which therapies should be translated to the clinical setting for evaluation in human studies. This protocol details planned methods to conduct a systematic review to identify and appraise eligible studies and to use a network meta-analysis to synthesize available evidence to answer the following questions: in preclinical in vivo models of focal ischemic stroke, what are the relative benefits of competing therapies tested in combination with the gold standard treatment alteplase in (i) reducing cerebral infarction size, and (ii) improving neurobehavioural outcomes? Methods: We will search Ovid Medline and Embase for articles on the effects of combination therapies with alteplase. Controlled comparison studies of preclinical in vivo models of experimentally induced focal ischemia testing the efficacy of therapies with alteplase versus alteplase alone will be identified. Outcomes to be extracted include infarct size (primary outcome) and neurobehavioural measures. Risk of bias and construct validity will be assessed using tools appropriate for preclinical studies. Here we describe steps undertaken to perform preclinical network meta-analysis to synthesise all evidence for each outcome and obtain a comprehensive ranking of all treatments. This will be a novel use of this evidence synthesis approach in stroke medicine to assess pre-clinical therapeutics. Combining all evidence to simultaneously compare mutliple therapuetics tested preclinically may provide a rationale for the clinical translation of therapeutics for patients with ischemic stroke. Dissemination: Review findings will be submitted to a peer-reviewed journal and presented at relevant scientific meetings to promote knowledge transfer. Registration: PROSPERO number to be submitted following peer review.

In recent years there has been increasing concern about the rigor of laboratory research. Here we present the protocol for a study comparing the completeness of reporting of in vivo and in vitro research carried in Nature Publication Group journals before and after the introduction of a change in editorial policy (the introduction of a set of guidelines for reporting); and in similar research published in other journals in the same periods. Electronic supplementary material The online version of this article (doi:10.1007/s11192-016-1964-8) contains supplementary material, which is available to authorized users.

Multiple recent pharmacological clinical trials in neuropathic pain have failed to show beneficial effect of drugs with previously demonstrated efficacy, and estimates of drug efficacy seems to have decreased with accumulation of newer trials. However, this has not been systematically assessed. Here, we analyze time-dependent changes in estimated treatment effect size in pharmacological trials together with factors that may contribute to decreases in estimated effect size. This study is a secondary analysis of data from a previous published NeuPSIG systematic review and meta-analysis, updated to include studies published up till March 2017. We included double-blind, randomized, placebo-controlled trials examining the effect of drugs for which we had made strong or weak recommendations for use in neuropathic pain in the previously published review. As the primary outcome, we used an aggregated number needed to treat for 50% pain reduction (alternatively 30% pain reduction or moderate pain relief). Analyses involved 128 trials. Number needed to treat values increased from around 2 to 4 in trials published between 1982 and 1999 to much higher (less effective) values in studies published from 2010 onwards. Several factors that changed over time, such as larger study size, longer study duration, and more studies reporting 50% or 30% pain reduction, correlated with the decrease in estimated drug effect sizes. This suggests that issues related to the design, outcomes, and reporting have contributed to changes in the estimation of treatment effects. These factors are important to consider in design and interpretation of individual study data and in systematic reviews and meta-analyses.

© 2018 Yarborough et al. http://creativecommons.org/licenses/by/4.0/ Millions of people worldwide currently suffer from serious neurological diseases and injuries for which there are few, and often no, effective treatments. The paucity of effective interventions is, no doubt, due in large part to the complexity of the disorders, as well as our currently limited understanding of their pathophysiology. The bleak picture for patients, however, is also attributable to avoidable impediments stemming from quality concerns in preclinical research that often escape detection by research regulation efforts. In our essay, we connect the dots between these concerns about the quality of preclinical research and their potential ethical impact on the patients who volunteer for early trials of interventions informed by it. We do so in hopes that a greater appreciation among preclinical researchers of these serious ethical consequences can lead to a greater commitment within the research community to adopt widely available tools and measures that can help to improve the quality of research.

Background and aimsChemotherapy-induced peripheral neuropathy (CIPN) can be a severely disabling side-effect of commonly used cancer chemotherapeutics, requiring cessation or dose reduction, impacting on survival and quality of life. Our aim was to conduct a systematic review and meta-analysis of research using animal models of CIPN to inform robust experimental design.MethodsWe systematically searched 5 online databases (PubMed, Web of Science, Citation Index, Biosis Previews and Embase (September 2012) to identify publications reporting in vivo CIPN modelling. Due to the number of publications and high accrual rate of new studies, we ran an updated search November 2015, using machine-learning and text mining to identify relevant studies.All data were abstracted by two independent reviewers. For each comparison we calculated a standardised mean difference effect size then combined effects in a random effects meta- analysis. The impact of study design factors and reporting of measures to reduce the risk of bias was assessed. We ran power analysis for the most commonly reported behavioural tests.Results341 publications were included. The majority (84%) of studies reported using male animals to model CIPN; the most commonly reported strain was Sprague Dawley rat. In modelling experiments, Vincristine was associated with the greatest increase in pain-related behaviour (−3.22 SD [−3.88; −2.56], n=152, p=0). The most commonly reported outcome measure was evoked limb withdrawal to mechanical monofilaments. Pain-related complex behaviours were rarely reported. The number of animals required to obtain 80% power with a significance level of 0.05 varied substantially across behavioural tests. Overall, studies were at moderate risk of bias, with modest reporting of measures to reduce the risk of bias.ConclusionsHere we provide a comprehensive summary of the field of animal models of CIPN and inform robust experimental design by highlighting measures to increase the internal and external validity of studies using animal models of CIPN. Power calculations and other factors, such as clinical relevance, should inform the choice of outcome measure in study design.

In 2010, the NC3Rs published the Animal Research:Reporting of In Vivo Experiments (ARRIVE) guidelinesto improve the reporting of animal research. Despiteconsiderable levels of support from the scientific community,the impact on the quality of reporting in animal researchpublications has been limited. This position paper highlightsthe strategy of an expert working group established torevise the guidelines and facilitate their uptake. The group’sinitial work will focus on three main areas: prioritisationof the ARRIVE items into a tiered system, development ofan explanation and elaboration document, and revision ofspecific items.