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Background Building a dataset of individual participant data (IPD) for meta-analysis represents considerable research investment as well as collaboration across multiple institutions and researchers. Making arrangements to curate and share the dataset beyond the IPD meta-analysis project for which it was established, for reuse in future research projects, would maximise the value of this investment. Methods Our aim was to establish the Cochrane repository for individual patient data from clinical trials in pregnancy and childbirth (CRIB) as an example of how an IPD repository could become part of Cochrane infrastructure. We believed that establishing CRIB under Cochrane auspices would engender trust and encourage trial investigators to share data, and at the same time position Cochrane to take steps towards expanding the number of reviews with IPD synthesis. Results CRIB was designed as a web-based platform to receive, host and facilitate onward sharing of de-identified data. Development was not straightforward and we did not fully achieve our aim as intended. We describe the challenges encountered and suggest ways that future repositories might overcome these. In particular, securing the legal agreements required to facilitate data sharing proved to be the main barrier, being time-consuming and more complex than anticipated. Conclusions We would recommend that researchers conducting IPD meta-analysis should consider discussing the option to transfer the curated IPD datasets to a repository at the end of the initial meta-analysis and this should be recognised within the data sharing agreements made with the original data contributors.

Medical interventions may be more effective in some types of individuals than others and identifying characteristics that modify the effectiveness of an intervention is a cornerstone of precision or stratified medicine. The opportunity for detailed examination of treatment-covariate interactions can be an important driver for undertaking an individual participant data (IPD) meta-analysis, rather than a meta-analysis using aggregate data. A number of recent modelling approaches are available. We apply these methods to the Perinatal Antiplatelet Review of International Studies (PARIS) Collaboration IPD dataset and compare estimates between them. We discuss the practical implications of applying these methods, which may be of interest to aid meta-analysists in the use of these, often complex models.Models compared included the two-stage meta-analysis of interaction terms and one-stage models which fit multiple random effects and separate within and between trial information. Models were fitted for nine covariates and five binary outcomes and results compared.Interaction terms produced by the methods were generally consistent. We show that where data are sparse and there is low heterogeneity in the covariate distributions across trials, the meta-analysis of interactions may produce unstable estimates and have issues with convergence. In this IPD dataset, varying assumptions by using multiple random effects in one-stage models or using only within trial information made little difference to the estimates of treatment-covariate interaction. Method choice will depend on datasets characteristics and individual preference.

Background Several aggregate published reviews have compared the effectiveness of one- and two-stage surgical revision to prevent re-infection following prosthetic hip infection and have reported inconsistent results. In addition, there were several features of these previous reviews which limited the validity of the findings. In the absence of a well-designed clinical trial, we propose the Global Infection Orthopaedic Management (INFORM) collaboration, a worldwide collaborative systematic review and meta-analysis of individual participant data (IPD) to address the existing uncertainties. Methods Cohort studies (prospective or retrospective) and randomised controlled trials conducted in unselected patients with infection treated exclusively by one- or two-stage revision and reporting re-infection outcomes within 2 years of revision will be retrieved by searching the following databases: MEDLINE, EMBASE, Web of Science, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials and the WHO International Clinical Trials Registry Platform. Reference lists of relevant studies will be manually scanned and there will be email contact with investigators of grey literature and conference abstracts. Investigators will be invited to join the Global INFORM collaboration and share their individual level data. The primary outcome of the analyses will be incidence of re-infection within 2 years of commencement of revision surgery. Primary analyses will be conducted comparing the one-stage to the two-stage surgical revision. IPD analyses will be based on Cox proportional hazard (PH) models estimated for each study separately. Study-specific log hazard ratios will be combined using random-effects meta-analysis with fixed-effects meta-analysis in subsidiary analyses. Hazard ratios for re-infection according to different individual level characteristics such as sex, age groups, body mass index and comorbidities will also be assessed. Discussion The analyses will enable a consistent approach to the definition of re-infection outcomes, more detailed analyses under a broader range of circumstances and exploration of potential sources of heterogeneity and produce much more valid and precise estimates of re-infection outcomes. Systematic review registration PROSPERO 2015: CRD42015016664 Electronic supplementary material The online version of this article (doi:10.1186/s13643-015-0044-0) contains supplementary material, which is available to authorized users.

BackgroundThe primary aim of this study is to assess, using individual participant data (IPD) meta-analysis, the effects of administration of antenatal magnesium sulphate given to women at risk of preterm birth on important clinical outcomes for their child such as death and neurosensory disability. The secondary aim is to determine whether treatment effects differ depending on important pre-specified participant and treatment characteristics, such as reasons at risk of preterm birth, gestational age, or type, dose and mode of administration of magnesium sulphate.MethodsDesignThe Antenatal Magnesium Individual Participant Data (IPD) International Collaboration: assessing the benefits for babies using the best level of evidence (AMICABLE) Group will perform an IPD meta-analysis to answer these important clinical questions.Setting/TimelineThe AMICABLE Group was formed in 2009 with data collection commencing late 2010.Inclusion CriteriaFive trials involving a total 6,145 babies are eligible for inclusion in the IPD meta-analysis.Primary study outcomesFor the infants/children: Death or cerebral palsy. For the women: Any severe maternal outcome potentially related to treatment (death, respiratory arrest or cardiac arrest).DiscussionResults are expected to be publicly available in 2012.

The Statistical Methods Group has played a pivotal role in The Cochrane Collaboration over the past 20 years. The Statistical Methods Group has determined the direction of statistical methods used within Cochrane reviews, developed guidance for these methods, provided training, and continued to discuss and consider new and controversial issues in meta-analysis. The contribution of Statistical Methods Group members to the meta-analysis literature has been extensive and has helped to shape the wider meta-analysis landscape. In this paper, marking the 20th anniversary of The Cochrane Collaboration, we reflect on the history of the Statistical Methods Group, beginning in 1993 with the identification of aspects of statistical synthesis for which consensus was lacking about the best approach. We highlight some landmark methodological developments that Statistical Methods Group members have contributed to in the field of meta-analysis. We discuss how the Group implements and disseminates statistical methods within The Cochrane Collaboration. Finally, we consider the importance of robust statistical methodology for Cochrane systematic reviews, note research gaps, and reflect on the challenges that the Statistical Methods Group faces in its future direction.