Search

Public engagement with reproducibility is crucial for fostering trust in science. This Community Page outlines, through the example of baking Christmas tree meringues, how scientists can effectively engage and educate the public about the importance of reproducibility in research.

Abstract Background The dissemination of clinical trial results is an important scientific and ethical endeavour. This survey of completed interventional studies in a French academic center describes their reporting status. Methods We explored all interventional studies sponsored by Rennes University Hospital identified on the French Open Science Monitor which tracks trials registered on EUCTR or clinicaltrials.gov, and provides an automatic assessment of the reporting of results. For each study, we ascertained the actual reporting of results using systematic searches on the hospital internal database, bibliographic databases (Google Scholar, PubMed), and by contacting all principal investigators (PIs). We describe several features (including total budget and numbers of trial participants) of the studies that did not report any results. Results The French Open Science Monitor identified 93 interventional studies, among which 10 (11%) reported results. In contrast, our survey identified 36 studies (39%) reporting primary analysis results and an additional 18 (19%) reporting results for secondary analyses (without results for their primary analysis). The overall budget for studies that did not report any results was estimated to be €5,051,253 for a total of 6,735 trial participants. The most frequent reasons for the absence of results reported by PIs were lack of time for 18 (42%), and logistic difficulties (e.g. delay in obtaining results or another blocking factor) for 12 (28%). An association was found between non-publication and negative results (adjusted Odds Ratio = 4.70, 95% Confidence Interval [1.67;14.11]). Conclusions Even allowing for the fact that automatic searches underestimate the number of studies with published results, the level of reporting was disappointingly low. This amounts to a waste of trial participants' implication and money. Corrective actions are needed. Trial registration https://osf.io/q5hcs

Background Many interventions, especially those linked to open science, have been proposed to improve reproducibility in science. To what extent these propositions are based on scientific evidence from empirical evaluations is not clear. Aims The primary objective is to identify Open Science interventions that have been formally investigated regarding their influence on reproducibility and replicability. A secondary objective is to list any facilitators or barriers reported and to identify gaps in the evidence. Methods We will search broadly by using electronic bibliographic databases, broad internet search, and contacting experts in the field of reproducibility, replicability, and open science. Any study investigating interventions for their influence on the reproducibility and replicability of research will be selected, including those studies additionally investigating drivers and barriers to the implementation and effectiveness of interventions. Studies will first be selected by title and abstract (if available) and then by reading the full text by at least two independent reviewers. We will analyze existing scientific evidence using scoping review and evidence gap mapping methodologies. Results The results will be presented in interactive evidence maps, summarized in a narrative synthesis, and serve as input for subsequent research. Review registration This protocol has been pre-registered on OSF under doi https://doi.org/10.17605/OSF.IO/D65YS

Objective To explore differences between published reviews and their respective protocols in a sample of 97 non-Cochrane Systematic Reviews (non-CSRs) and 97 Cochrane Systematic Reviews (CSRs) in terms of PICOS (Patients/Population, Intervention, Comparison/Control, Outcome, Study type) elements and the extent to which they were reported. Study Design and Setting We searched PubMed and Cochrane databases to identify non-CSRs and CSRs that were published in 2018. We then searched for their corresponding Cochrane or PROSPERO protocols. The published reviews were compared to their protocols. The primary outcome was changes from protocol to review in terms of PICOS elements. Results We identified a total of 227 changes from protocol to review in PICOS elements, 1.11 (Standard Deviation (SD), 1.22) changes per review for CSRs and 1.23 (SD, 1.12) for non-CSRs per review. More than half of each sub-sample (54.6% of CSRs and 67.0% of non-CSRs) (Absolute Risk Reduction (ARR) 12.4% [−1.3%; 26.0%]) had changes in PICOS elements. For both subsamples, approximately a third of all changes corresponded to changes related to primary outcomes. Marked differences were found between the sub-samples for the reporting of changes. 95.8% of the changes in PICOS items were not reported in the non-CSRs compared to 42.6% in the CSRs (ARR 53.2% [43.2%; 63.2%]). Conclusion CSRs showed better results than non-CSRs in terms of the reporting of changes. Reporting of changes from protocol needs to be promoted and requires general improvement. The limitations of this study lie in its observational design. Registration: https://osf.io/6j8gd/.

Objectives This descriptive study of registered trials aimed to identify large clinical trials on antidepressants for mental disorders: (1) to assess what proportion could be labelled as ‘seeding trials’ (trials for marketing purposes) and (2) to describe their methodological characteristics and outcomes.Design A search was conducted across all trials registered on ClinicalTrials.gov by drug name in March 2017.Setting All trials registered in the database of ClinicalTrials.gov were screened. Large registered studies were received and studies focusing prospectively on the effects of antidepressants in mental health disorders. Specific data items were extracted automatically, and subsequently inspected, corrected and completed by hand.Participants Prospective studies were selected focusing on the effects of antidepressants in any mental health disorder with 800 participants or more planned for inclusion.Main outcome measures Three members from the study team independently assessed the following ‘seeding trial’ characteristics in each registered study: a high level of involvement of the product manufacturer in the study design, in the data analysis and reporting of the study, an abnormally low ratio of patient numbers to study site, spin and/or omissions of clinically relevant findings in the abstracts, and conclusions that focused on secondary endpoints and surrogate markers. Secondary outcomes were the exploration of a functional outcome and suicidality.Results 31 trials were identified from clinical trials database. 18/31 were published (58%). 8 of these 18 (44%) studies were identified as possible seeding trials. 13/31 (42%) large trials planned to explore functioning and 5/31 (16%) suicidality.Conclusions Large trials are rare in the field of antidepressant research. Some could be ‘seeding trials’. Few explored suicidality. Identifying seeding trials from incomplete data entries in registries, especially when almost half of the studies were still unpublished, posed considerable challenges. The delay between our research and publication limits the strength of our conclusions.PROSPERO registration number CRD42017065591.

Abstract Background Transparency and reproducibility are expected to be normative practices in clinical trials used for decision-making on marketing authorisations for new medicines. This registered report introduces a cross-sectional study aiming to assess inferential reproducibility for main trials assessed by the European Medicines Agency. Methods Two researchers independently identified all studies on new medicines, biosimilars and orphan medicines given approval by the European Commission between January 2017 and December 2019, categorised as ‘main studies’ in the European Public Assessment Reports (EPARs). Sixty-two of these studies were randomly sampled. One researcher retrieved the individual patient data (IPD) for these studies and prepared a dossier for each study, containing the IPD, the protocol and information on the conduct of the study. A second researcher who had no access to study reports used the dossier to run an independent re-analysis of each trial. All results of these re-analyses were reported in terms of each study’s conclusions, p-values, effect sizes and changes from the initial protocol. A team of two researchers not involved in the re-analysis compared results of the re-analyses with published results of the trial. Results Two hundred ninety-two main studies in 173 EPARs were identified. Among the 62 studies randomly sampled, we received IPD for 10 trials. The median number of days between data request and data receipt was 253 [interquartile range 182–469]. For these ten trials, we identified 23 distinct primary outcomes for which the conclusions were reproduced in all re-analyses. Therefore, 10/62 trials (16% [95% confidence interval 8% to 28%]) were reproduced, as the 52 studies without available data were considered non-reproducible. There was no change from the original study protocol regarding the primary outcome in any of these ten studies. Spin was observed in the report of one study. Conclusions Despite their results supporting decisions that affect millions of people’s health across the European Union, most main studies used in EPARs lack transparency and their results are not reproducible for external researchers. Re-analyses of the few trials with available data showed very good inferential reproducibility. Trial registration https://osf.io/mcw3t/

Abstract Background Tivozanib (Fotivda) is an anti-angiogenic tyrosine kinase inhibitor that was denied access to the US market by the Food and Drug Administration (FDA). In contrast, it was granted approval by the European Medicines Agency (EMA) for the treatment of Renal Cell Carcinoma in adults. Given the conflicting decisions from these regulatory agencies, the objectives of the following study are (i) to critically review the evidence supporting the approval of tivozanib; (ii) to analyse the dissemination of this evidence in the literature by way of a citation analysis. Methods Pivotal trials were searched by two independent reviewers using Medline, Cochrane Library, ClinicalTrials.gov and the European Public Assessment Report. The risk of bias for each trial was then inductively assessed. Articles citing any of these trials were identified using Web of Sciences. Finally, the quality of the citations was evaluated by two independent reviewers according to standard data extraction methods. Results The search for primary evidence identified two pivotal studies: TIVO-1 upon which the FDA and the EMA decisions were based, and TIVO-3 which was conducted after the agencies’ decisions had been issued. The TIVO-1 trial presented several limitations that compromised causal inference, in relation to (i) design (absence of blinding, inappropriate comparator, and one-way crossover), (ii) poor internal consistency in the results for the primary endpoint, (iii) a discrepancy between a benefit observed for progression-free survival (HR: 0.80, 95% CI [0.64–0.99]) and the absence of difference for overall survival (HR: 1.25, 95% CI [0.95 – 1.62]). Our citation search protocol identified 229 articles that cited TIVO-1 in the 7 years following its publication, among which 151 (65.9%) citing articles discussing efficacy. Presence of spin was identified in 64 (42.4%) of these 151 citing articles, and 39 (25.8%) additional articles citing results without providing enough elements to interpret the TIVO-1 results. Conclusion EMA’s approval was based on a single pivotal trial presenting critical limitations, rendering the results from the trial potentially inconclusive. The broad dissemination of TIVO-1 results in the scientific literature may have been affected by spin or results were presented in an inadequate critical manner.

Abstract Background Duloxetine is an antidepressant that benefits from a wide range of approval in the elderly population, while its safety for use compared to non-elderly is not clearly assessed. This protocol outlines a systematic review and individual participant data meta-analysis comparing the tolerability of duloxetine between elderly and non-elderly. Methods Searches will be conducted in PubMed, ClinicalTrials.gov , Clinicaltrialsregister.eu, data sharing platforms, FDA drug approval packages, European public assessment reports and withdrawn applications from the EMA website. The review will be performed on studies available in electronic databases from their date of inception to the 31 March 2022. Only randomized controlled clinical trials, comparing duloxetine to placebo, will be included in this meta-analysis. The studies will be selected if they comprise both elderly and non-elderly adults, in conditions of use of duloxetine approved by the European Medical Agency (EMA) and the Food and Drug Administration (FDA). The primary outcome will be the rate ratio of serious adverse events under duloxetine compared to placebo, between participants at least 65 years old and non-elderly. Second, the number of any adverse events, clinical efficacy and quality of life will be compared between elderly and non-elderly under both interventions. The quality of evidence in the tolerability of duloxetine will be assessed using the GRADE system. A one or two-stage individual participant data random effect meta-analysis will be conducted depending on the availability of the data. Discussion This meta-analysis will investigate the tolerability safety of duloxetine in the elderly population across all conditions approved by European and American regulatory authorities. The results from this meta-analysis are intended to help prescribers to provide better care for the elderly population. Systematic review registration The protocol has been registered at the International Prospective Register of Systematic Reviews (PROSPERO; registration number: CRD42019130488 ).

Clinical trial data-sharing is seen as an imperative for research integrity and is becoming increasingly encouraged or even required by funders, journals, and other stakeholders. However, early experiences with data-sharing have been disappointing because they are not always conducted properly. Health data is indeed sensitive and not always easy to share in a responsible way. We propose 10 rules for researchers wishing to share their data. These rules cover the majority of elements to be considered in order to start the commendable process of clinical trial data-sharing: Rule 1: Abide by local legal and regulatory data protection requirements Rule 2: Anticipate the possibility of clinical trial data-sharing before obtaining funding Rule 3: Declare your intent to share data in the registration step Rule 4: Involve research participants Rule 5: Determine the method of data access Rule 6: Remember there are several other elements to share Rule 7: Do not proceed alone Rule 8: Deploy optimal data management to ensure that the data shared is useful Rule 9: Minimize risks Rule 10: Strive for excellence.

Objective To evaluate the impact of conducting all possible pooled analyses across different combinations of randomised controlled trials and endpoints.Design Multiverse analysis, consisting of numerous pooled analyses of individual participant data.Setting Individual patient data from 12 randomised controlled trials comparing canagliflozin treatment with placebo, shared on the Yale University Open Data Access project (https://yoda.yale.edu/) platform, up to 16 April 2021.Participants 15 094 people with type 2 diabetes mellitus.Main outcome measures Pooled analyses estimated changes in serum glycated haemoglobin (HbA1c), major adverse cardiovascular events, and serious adverse events at weeks 12, 18, 26, and 52. The distribution of effect estimates was calculated for all possible combinations, and the direction and magnitude of the first and 99th centiles of effect estimates were compared.Results Across 16 332 distinct pooled analyses comparing canagliflozin with placebo for changes in HbA1c, standardised effect estimates were in favour of canagliflozin treatment at both the first centile (−0.75%) and 99th centile (−0.48%); 15 994 (97.93%) analyses showed significant results (P

[This corrects the article DOI: 10.1371/journal.pbio.3001133.].

Alongside the growing concerns regarding predatory journal growth, other questionable editorial practices have gained visibility recently. Among them, we explored the usefulness of the Percentage of Papers by the Most Prolific author (PPMP) and the Gini index (level of inequality in the distribution of authorship among authors) as tools to identify journals that may show favoritism in accepting articles by specific authors. We examined whether the PPMP, complemented by the Gini index, could be useful for identifying cases of potential editorial bias, using all articles in a sample of 5,468 biomedical journals indexed in the National Library of Medicine. For articles published between 2015 and 2019, the median PPMP was 2.9%, and 5% of journal exhibited a PPMP of 10.6% or more. Among the journals with the highest PPMP or Gini index values, where a few authors were responsible for a disproportionate number of publications, a random sample was manually examined, revealing that the most prolific author was part of the editorial board in 60 cases (61%). The papers by the most prolific authors were more likely to be accepted for publication within 3 weeks of their submission. Results of analysis on a subset of articles, excluding nonresearch articles, were consistent with those of the principal analysis. In most journals, publications are distributed across a large number of authors. Our results reveal a subset of journals where a few authors, often members of the editorial board, were responsible for a disproportionate number of publications. To enhance trust in their practices, journals need to be transparent about their editorial and peer review practices.

Florian Naudet and co-authors discuss strengthening requirements for sharing clinical trial data.

Florian Naudet and co-authors propose a pathway involving registered criteria for evaluation and approval of new drugs.

Abstract Background Different methodological choices such as inclusion/exclusion criteria and analytical models can yield different results and inferences when meta-analyses are performed. We explored the range of such differences, using several methodological choices for indirect comparison meta-analyses to compare nalmefene and naltrexone in the reduction of alcohol consumption as a case study. Methods All double-blind randomized controlled trials (RCTs) comparing nalmefene to naltrexone or one of these compounds to a placebo in the treatment of alcohol dependence or alcohol use disorders were considered. Two reviewers searched for published and unpublished studies in MEDLINE (August 2017), the Cochrane Library, Embase, and ClinicalTrials.gov and contacted pharmaceutical companies, the European Medicines Agency, and the Food and Drug Administration. The indirect comparison meta-analyses were performed according to different inclusion/exclusion criteria (based on medical condition, abstinence of patients before inclusion, gender, somatic and psychiatric comorbidity, psychological support, treatment administered and dose, treatment duration, outcome reported, publication status, and risk of bias) and different analytical models (fixed and random effects). The primary outcome was the vibration of effects (VoE), i.e. the range of different results of the indirect comparison between nalmefene and naltrexone. The presence of a “Janus effect” was investigated, i.e. whether the 1st and 99th percentiles in the distribution of effect sizes were in opposite directions. Results Nine nalmefene and 51 naltrexone RCTs were included. No study provided a direct comparison between the drugs. We performed 9216 meta-analyses for the indirect comparison with a median of 16 RCTs (interquartile range = 12–21) included in each meta-analysis. The standardized effect size was negative at the 1st percentile (− 0.29, favouring nalmefene) and positive at the 99th percentile (0.29, favouring naltrexone). A total of 7.1% (425/5961) of the meta-analyses with a negative effect size and 18.9% (616/3255) of those with a positive effect size were statistically significant (p

Background: Never before have clinical trials drawn as much public attention as those testing interventions for COVID-19. We aimed to describe the worldwide COVID-19 clinical research response and its evolution over the first 100 days of the pandemic. Methods: Descriptive analysis of planned, ongoing or completed trials by April 9, 2020 testing any intervention to treat or prevent COVID-19, systematically identified in trial registries, preprint servers, and literature databases. A survey was conducted of all trials to assess their recruitment status up to July 6, 2020. Results: Most of the 689 trials (overall target sample size 396,366) were small (median sample size 120; interquartile range [IQR] 60-300) but randomized (75.8%; n=522) and were often conducted in China (51.1%; n=352) or the USA (11%; n=76). 525 trials (76.2%) planned to include 155,571 hospitalized patients, and 25 (3.6%) planned to include 96,821 health-care workers. Treatments were evaluated in 607 trials (88.1%), frequently antivirals (n=144) or antimalarials (n=112); 78 trials (11.3%) focused on prevention, including 14 vaccine trials. No trial investigated social distancing. Interventions tested in 11 trials with >5,000 participants were also tested in 169 smaller trials (median sample size 273; IQR 90-700). Hydroxychloroquine alone was investigated in 110 trials. While 414 trials (60.0%) expected completion in 2020, only 35 trials (4.1%; 3,071 participants) were completed by July 6. Of 112 trials with detailed recruitment information, 55 had recruited

Background: Never before have clinical trials drawn as much public attention as those testing interventions for COVID-19. We aimed to describe the worldwide COVID-19 clinical research response and its evolution over the first 100 days of the pandemic. Methods: Descriptive analysis of planned, ongoing or completed trials by April 9, 2020 testing any intervention to treat or prevent COVID-19, systematically identified in trial registries, preprint servers, and literature databases. A survey was conducted of all trials to assess their recruitment status up to July 6, 2020. Results: Most of the 689 trials (overall target sample size 396,366) were small (median sample size 120; interquartile range [IQR] 60-300) but randomized (75.8%; n=522) and were often conducted in China (51.1%; n=352) or the USA (11%; n=76). 525 trials (76.2%) planned to include 155,571 hospitalized patients, and 25 (3.6%) planned to include 96,821 health-care workers. Treatments were evaluated in 607 trials (88.1%), frequently antivirals (n=144) or antimalarials (n=112); 78 trials (11.3%) focused on prevention, including 14 vaccine trials. No trial investigated social distancing. Interventions tested in 11 trials with >5,000 participants were also tested in 169 smaller trials (median sample size 273; IQR 90-700). Hydroxychloroquine alone was investigated in 110 trials. While 414 trials (60.0%) expected completion in 2020, only 35 trials (4.1%; 3,071 participants) were completed by July 6. Of 112 trials with detailed recruitment information, 55 had recruited

Abstract Background The available evidence on the benefits and harms of novel drugs and therapeutic biologics at the time of approval is reported in publicly available documents provided by the US Food and Drug Administration (FDA). We aimed to create a comprehensive database providing the relevant information required to systematically analyze and assess this early evidence in meta-epidemiological research. Methods We designed a modular and flexible database of systematically collected data. We identified all novel cancer drugs and therapeutic biologics approved by the FDA between 2000 and 2016, recorded regulatory characteristics, acquired the corresponding FDA approval documents, identified all clinical trials reported therein, and extracted trial design characteristics and treatment effects. Herein, we describe the rationale and design of the data collection process, particularly the organization of the data capture, the identification and eligibility assessment of clinical trials, and the data extraction activities. Discussion We established a comprehensive database on the comparative effects of drugs and therapeutic biologics approved by the FDA over a time period of 17 years for the treatment of cancer (solid tumors and hematological malignancies). The database provides information on the clinical trial evidence available at the time of approval of novel cancer treatments. The modular nature and structure of the database and the data collection processes allow updates, expansions, and adaption for a continuous meta-epidemiological analysis of novel drugs. The database allows us to systematically evaluate benefits and harms of novel drugs and therapeutic biologics. It provides a useful basis for meta-epidemiological research on the comparative effects of innovative cancer treatments and continuous evaluations of regulatory developments.

Abstract This paper introduces a “blue pyjama syndrome” (whereby wearing hospital pyjamas results in an exaggerated impression of severity). We performed a 5-day, prospective, randomized, cross-over study in a French mood disorder unit for inpatients. At Day 1 (D1) and Day 5 (D5), two 5-minute video interviews were recorded with patients in pyjamas or in day clothes (the sequence was randomly allocated). Psychiatrists unaware of the study objective assessed the videos and scored their clinical global impressions (CGI, with scores ranging from 1 to 7). Of 30 participants with major depressive episode selected for inclusion, 26 participants (69% women) provided useable data for an evaluation by 10 psychiatrists. Pyjamas significantly increased the psychiatrists’ CGI ratings of disease severity by 0·65 [0·27; 1·02] points. The psychiatrists’ global impressions also rated patients as significantly less severe at D5 in comparison with D1 by −0·66 [−1·03; −0·29] points. The “blue pyjama syndrome” is in the same order of magnitude as the difference observed after a week of hospitalisation. This potentially calls into question the reliability and validity of observer ratings of depression.

BackgroundFunders are key players in supporting randomized controlled trial (RCT) data-sharing. This research aimed to describe commercial and non-commercial funders' data-sharing policies and to assess the compliance of funded RCTs with the existing data-sharing policies.Methods and findingsFunders of clinical research having funded at least one RCT in the years 2016 to 2018 were surveyed. All 78 eligible non-commercial funders retrieved from the Sherpa/Juliet Initiative website and a random sample of 100 commercial funders selected from pharmaceutical association member lists (LEEM, IFPMA, EFPIA) and the top 100 pharmaceutical companies in terms of drug sales were included. Thirty (out of 78; 38%) non-commercial funders had a data-sharing policy with eighteen (out of 30, 60%) making data-sharing mandatory and twelve (40%) encouraging data-sharing. Forty-one (out of 100; 41%) of commercial funders had a data-sharing policy. Among funders with a data-sharing policy, a survey of two random samples of 100 RCTs registered on Clinicaltrial.gov, data-sharing statements were present for seventy-seven (77%, 95% IC [67%-84%]) and eighty-one (81% [72% - 88%]) of RCTs funded by non-commercial and commercial funders respectively. Intention to share data was expressed in 12% [7%-20%] and 59% [49%- 69%] of RCTs funded by non-commercial and commercial funders respectively.ConclusionsThis survey identified suboptimal performances of funders in setting up data-sharing policies. For those with a data-sharing policy, the implementation of the policy in study registration was limited for commercial funders and of concern for non-commercial funders. The limitations of the present study include its cross-sectional nature, since data-sharing policies are continuously changing. We call for a standardization of policies with a strong evaluation component to make sure that, when in place, these policies are effective.

Assessment of researchers is necessary for decisions of hiring, promotion, and tenure. A burgeoning number of scientific leaders believe the current system of faculty incentives and rewards is misaligned with the needs of society and disconnected from the evidence about the causes of the reproducibility crisis and suboptimal quality of the scientific publication record. To address this issue, particularly for the clinical and life sciences, we convened a 22-member expert panel workshop in Washington, DC, in January 2017. Twenty-two academic leaders, funders, and scientists participated in the meeting. As background for the meeting, we completed a selective literature review of 22 key documents critiquing the current incentive system. From each document, we extracted how the authors perceived the problems of assessing science and scientists, the unintended consequences of maintaining the status quo for assessing scientists, and details of their proposed solutions. The resulting table was used as a seed for participant discussion. This resulted in six principles for assessing scientists and associated research and policy implications. We hope the content of this paper will serve as a basis for establishing best practices and redesigning the current approaches to assessing scientists by the many players involved in that process.

Several studies have investigated the age-related impact in cognitive action control. However, to our knowledge, none has focused on the effect of moderate age on the strength of automatic activation according to the activation suppression model. We therefore investigated the effect of moderate age on cognitive action control using an oculomotor version of the Simon task and distributional analyses.A group of middle-aged (n = 39; 57 ± 9 years) healthy adults was compared to a group of young healthy participants (n = 43; 24 ± 3 years). We first analyzed the overall impact of age on the congruence effect and then used conditional accuracy functions and delta plots to assess the strength of automatic activation and selective inhibition respectively.Compared to young participants, middle-aged participants showed a greater congruence effect as well as higher rates of fast errors in conflict situations indicating an enhanced impulsive action selection. Furthermore, the overall downward slope of the congruence effect’s evolution was significantly steeper in older participants and the last slope tended to be significantly steeper. This may indicate that the middle-aged participants exerted a stronger selective inhibition.Our results suggest that middle-aged adults are more prone to impulsive action selection than young adults. Recent theories postulate that older adults might implement compensatory mechanisms to supply cognitive difficulties. This is in line with our results suggesting a potential greater selective inhibition. Overall, this study proposes that moderate aging impacts both processes of impulsive response selection and suppression underlying cognitive action control.

BackgroundNalmefene is a recent option in alcohol dependence treatment. Its approval was controversial. We conducted a systematic review and meta-analysis of the aggregated data (registered as PROSPERO 2014:CRD42014014853) to compare the harm/benefit of nalmefene versus placebo or active comparator in this indication.Methods and findingsThree reviewers searched for published and unpublished studies in Medline, the Cochrane Library, Embase, ClinicalTrials.gov, Current Controlled Trials, and bibliographies and by mailing pharmaceutical companies, the European Medicines Agency (EMA), and the US Food and Drug Administration. Double-blind randomized clinical trials evaluating nalmefene to treat adult alcohol dependence, irrespective of the comparator, were included if they reported (1) health outcomes (mortality, accidents/injuries, quality of life, somatic complications), (2) alcohol consumption outcomes, (3) biological outcomes, or (4) treatment safety outcomes, at 6 mo and/or 1 y. Three authors independently screened the titles and abstracts of the trials identified. Relevant trials were evaluated in full text. The reviewers independently assessed the included trials for methodological quality using the Cochrane Collaboration tool for assessing risk of bias. On the basis of the I2 index or the Cochrane's Q test, fixed or random effect models were used to estimate risk ratios (RRs), mean differences (MDs), or standardized mean differences (SMDs) with 95% CIs. In sensitivity analyses, outcomes for participants who were lost to follow-up were included using baseline observation carried forward (BOCF); for binary measures, patients lost to follow-up were considered equal to failures (i.e., non-assessed patients were recorded as not having responded in both groups). Five randomized controlled trials (RCTs) versus placebo, with a total of 2,567 randomized participants, were included in the main analysis. None of these studies was performed in the specific population defined by the EMA approval of nalmefene, i.e., adults with alcohol dependence who consume more than 60 g of alcohol per day (for men) or more than 40 g per day (for women). No RCT compared nalmefene with another medication. Mortality at 6 mo (RR = 0.39, 95% CI [0.08; 2.01]) and 1 y (RR = 0.98, 95% CI [0.04; 23.95]) and quality of life at 6 mo (SF-36 physical component summary score: MD = 0.85, 95% CI [-0.32; 2.01]; SF-36 mental component summary score: MD = 1.01, 95% CI [-1.33; 3.34]) were not different across groups. Other health outcomes were not reported. Differences were encountered for alcohol consumption outcomes such as monthly number of heavy drinking days at 6 mo (MD = -1.65, 95% CI [-2.41; -0.89]) and at 1 y (MD = -1.60, 95% CI [-2.85; -0.35]) and total alcohol consumption at 6 mo (SMD = -0.20, 95% CI [-0.30; -0.10]). An attrition bias could not be excluded, with more withdrawals for nalmefene than for placebo, including more withdrawals for safety reasons at both 6 mo (RR = 3.65, 95% CI [2.02; 6.63]) and 1 y (RR = 7.01, 95% CI [1.72; 28.63]). Sensitivity analyses showed no differences for alcohol consumption outcomes between nalmefene and placebo, but the weight of these results should not be overestimated, as the BOCF approach to managing withdrawals was used.ConclusionsThe value of nalmefene for treatment of alcohol addiction is not established. At best, nalmefene has limited efficacy in reducing alcohol consumption.

BackgroundDeep brain stimulation has shed new light on the central role of the prefrontal cortex (PFC) in obsessive compulsive disorder (OCD). We explored this structure from a functional perspective, synchronizing neuroimaging and cognitive measures.Methods and findingsThis case-control cross-sectional study compared 15 OCD patients without comorbidities and not currently on serotonin reuptake inhibitors or cognitive behavioural therapy with 15 healthy controls (matched for age, sex and education level) on resting-state (18)FDG-PET scans and a neuropsychological battery assessing executive functions. We looked for correlations between metabolic modifications and impaired neuropsychological scores. Modifications in glucose metabolism were found in frontal regions (orbitofrontal cortex and dorsolateral cortices), the cingulate gyrus, insula and parietal gyrus. Neuropsychological differences between patients and controls, which were subtle, were correlated with the metabolism of the prefrontal, parietal, and temporal cortices.ConclusionAs expected, we confirmed previous reports of a PFC dysfunction in OCD patients, and established a correlation with cognitive deficits. Other regions outside the prefrontal cortex, including the dorsoparietal cortex and the insula, also appeared to be implicated in the pathophysiology of OCD, providing fresh insights on the complexity of OCD syndromes.

BackgroundTo compare response to antidepressants between randomized controlled trials (RCTs) and observational trials.Methods and findingsPublished and unpublished studies (from 1989 to 2009) were searched for by 2 reviewers on Medline, the Cochrane library, Embase, clinicaltrials.gov, Current Controlled Trial, bibliographies and by mailing key organisations and researchers. RCTs and observational studies on fluoxetine or venlafaxine in first-line treatment for major depressive disorder reported in English, French or Spanish language were included in the main analysis. Studies including patients from a wider spectrum of depressive disorders (anxious depression, minor depressive episode, dysthymia) were added in a second analysis. The main outcome was the pre-/post-treatment difference on depression scales standardised to 100 (17-item or 21-item Hamilton Rating Scale for Depression or Montgomery and Åsberg Rating Scale) in each study arm. A meta-regression was conducted to adjust the comparison between observational studies and RCTs on treatment type, study characteristics and average patient characteristics. 12 observational studies and 109 RCTs involving 6757 and 11035 patients in 12 and 149 arms were included in the main analysis. Meta-regression showed that the standardised treatment response in RCTs is greater by a magnitude of 4.59 (2.61 to 6.56). Study characteristics were related to standardised treatment response, positively (study duration, number of follow-up assessments, outpatients versus inpatients, per protocol analysis versus intention to treat analysis) or negatively (blinded design, placebo design). At patient level, response increased with baseline severity and decreased with age. Results of the second analysis were consistent with this.ConclusionsResponse to antidepressants is greater in RCTs than in observational studies. Observational studies should be considered as a necessary complement to RCTs.