Dataset Information

Stroke Treatment Academic Industry Roundtable Recommendations for Individual Data Pooling Analyses in Stroke.

ABSTRACT: Pooled analysis of individual patient data from stroke trials can deliver more precise estimates of treatment effect, enhance power to examine prespecified subgroups, and facilitate exploration of treatment-modifying influences. Analysis plans should be declared, and preferably published, before trial results are known. For pooling trials that used diverse analytic approaches, an ordinal analysis is favored, with justification for considering deaths and severe disability jointly. Because trial pooling is an incremental process, analyses should follow a sequential approach, with statistical adjustment for iterations. Updated analyses should be published when revised conclusions have a clinical implication. However, caution is recommended in declaring pooled findings that may prejudice ongoing trials, unless clinical implications are compelling. All contributing trial teams should contribute to leadership, data verification, and authorship of pooled analyses. Development work is needed to enable reliable inferences to be drawn about individual drug or device effects that contribute to a pooled analysis, versus a class effect, if the treatment strategy combines ?2 such drugs or devices. Despite the practical challenges, pooled analyses are powerful and essential tools in interpreting clinical trial findings and advancing clinical care.

SUBMITTER: Lees KR

PROVIDER: S-EPMC4961517 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Stroke Treatment Academic Industry Roundtable Recommendations for Individual Data Pooling Analyses in Stroke.

Lees Kennedy R KR Khatri Pooja P

Stroke 20160712 8

Pooled analysis of individual patient data from stroke trials can deliver more precise estimates of treatment effect, enhance power to examine prespecified subgroups, and facilitate exploration of treatment-modifying influences. Analysis plans should be declared, and preferably published, before trial results are known. For pooling trials that used diverse analytic approaches, an ordinal analysis is favored, with justification for considering deaths and severe disability jointly. Because trial p ...[more]

PMID: 27406108

Similar Datasets

Project description:BackgroundIndividual participant data (IPD) meta-analyses that obtain "raw" data from studies rather than summary data typically adopt a "two-stage" approach to analysis whereby IPD within trials generate summary measures, which are combined using standard meta-analytical methods. Recently, a range of "one-stage" approaches which combine all individual participant data in a single meta-analysis have been suggested as providing a more powerful and flexible approach. However, they are more complex to implement and require statistical support. This study uses a dataset to compare "two-stage" and "one-stage" models of varying complexity, to ascertain whether results obtained from the approaches differ in a clinically meaningful way.Methods and findingsWe included data from 24 randomised controlled trials, evaluating antiplatelet agents, for the prevention of pre-eclampsia in pregnancy. We performed two-stage and one-stage IPD meta-analyses to estimate overall treatment effect and to explore potential treatment interactions whereby particular types of women and their babies might benefit differentially from receiving antiplatelets. Two-stage and one-stage approaches gave similar results, showing a benefit of using anti-platelets (Relative risk 0.90, 95% CI 0.84 to 0.97). Neither approach suggested that any particular type of women benefited more or less from antiplatelets. There were no material differences in results between different types of one-stage model.ConclusionsFor these data, two-stage and one-stage approaches to analysis produce similar results. Although one-stage models offer a flexible environment for exploring model structure and are useful where across study patterns relating to types of participant, intervention and outcome mask similar relationships within trials, the additional insights provided by their usage may not outweigh the costs of statistical support for routine application in syntheses of randomised controlled trials. Researchers considering undertaking an IPD meta-analysis should not necessarily be deterred by a perceived need for sophisticated statistical methods when combining information from large randomised trials.

Project description:Introduction: Individual participant data meta-analyses (IPD-MAs) include the raw data from relevant randomised clinical trials (RCTs) and involve secondary analyses of the data. Performed since the late 1990s, ~50 such meta-analyses have been carried out in psychiatry, mostly in the field of treatment. IPD-MAs are particularly relevant for three objectives: (1) evaluation of the average effect of an intervention by combining effects from all included trials, (2) evaluation of the heterogeneity of an intervention effect and sub-group analyses to approach personalised psychiatry, (3) mediation analysis or surrogacy evaluation to replace a clinical (final) endpoint for the evaluation of new treatments with intermediate or surrogate endpoints. The objective is to describe the interest and the steps of an IPD-MA method applied to the field of psychiatric therapeutic research. Method: The method is described in three steps. First, the identification of the relevant trials with an explicit description of the inclusion/exclusion criteria for the RCT to be incorporated in the IPD-MA and a definition of the intervention, the population, the context and the relevant points (outcomes or moderators). Second, the data management with the standardisation of collected variables and the evaluation and the assessment of the risk-of-bias for each included trial and of the global risk. Third, the statistical analyses and their interpretations, depending on the objective of the meta-analysis. All steps are illustrated with examples in psychiatry for treatment issues, excluding study protocols. Conclusion: The meta-analysis of individual patient data is challenging. Only strong collaborations between all stakeholders can make such a process efficient. An "ecosystem" that includes all stakeholders (questions of interest prioritised by the community, funders, trialists, journal editors, institutions, …) is required. International medical societies can play a central role in favouring the emergence of such communities.

Project description:PurposeThe microbiological aetiology of pneumonia complicating stroke is poorly characterised. In this second Pneumonia in Stroke ConsEnsuS statement, we propose a standardised approach to empirical antibiotic therapy in pneumonia complicating stroke, based on likely microbiological aetiology, to improve antibiotic stewardship.MethodsSystematic literature searches of multiple databases were undertaken. An evidence review and a round of consensus consultation were completed prior to a final multi-disciplinary consensus meeting in September 2017, held in Barcelona, Spain. Consensus was approached using a modified Delphi technique and defined a priori as 75% agreement between the consensus group members.Findings: No randomised trials to guide antibiotic treatment of pneumonia complicating stroke were identified. Consensus was reached for the following: (1) Stroke-associated pneumonia may be caused by organisms associated with either community-acquired or hospital-acquired pneumonia; (2) Treatment for early stroke-associated pneumonia (<72 h of stroke onset) should cover community-acquired pneumonia organisms; (3) Treatment for late stroke-associated pneumonia (≥72 h and within seven days of stroke onset) should cover community-acquired pneumonia organisms plus coliforms +/- Pseudomonas spp. if risk factors; (4) No additional antimicrobial cover is required for patients with dysphagia or aspiration; (5) Pneumonia occurring after seven days from stroke onset should be treated as for hospital-acquired pneumonia; (6) Treatment should continue for at least seven days for each of these scenarios.DiscussionConsensus recommendations for antibiotic treatment of the spectrum of pneumonia complicating stroke are proposed. However, there was limited evidence available to formulate consensus on choice of specific antibiotic class for pneumonia complicating stroke.ConclusionFurther studies are required to inform evidence-based treatment of stroke-associated pneumonia including randomised trials of antibiotics and validation of candidate biomarkers.

Dataset Information

Stroke Treatment Academic Industry Roundtable Recommendations for Individual Data Pooling Analyses in Stroke.

Publications

Stroke Treatment Academic Industry Roundtable Recommendations for Individual Data Pooling Analyses in Stroke.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets