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Background: Network meta-analysis (NMA) allows estimating and ranking the effects of several interventions for a clinical condition. Component network meta-analysis (CNMA) is an extension of NMA which considers the individual components of multicomponent interventions. CNMA allows to "reconnect" a disconnected network with common components in subnetworks. An additive CNMA assumes that component effects are additive. This assumption can be relaxed by including interaction terms in the CNMA. Methods: We evaluate a forward model selection strategy for component network meta-analysis to relax the additivity assumption that can be used in connected or disconnected networks. In addition, we describe a procedure to create disconnected networks in order to evaluate the properties of the model selection in connected and disconnected networks. We apply the methods to simulated data and a Cochrane review on interventions for postoperative nausea and vomiting in adults after general anaesthesia. Model performance is compared using average mean squared errors and coverage probabilities. Results: CNMA models provide good performance for connected networks and can be an alternative to standard NMA if additivity holds. For disconnected networks, we recommend to use additive CNMA only if strong clinical arguments for additivity exist. Conclusions: CNMA methods are feasible for connected networks but questionable for disconnected networks. [ABSTRACT FROM AUTHOR]

Background: Specialist palliative care (SPC) interventions aim to relieve and prevent suffering in the physical, psychological, social, and spiritual domain. Therefore, SPC is carried out by a multi-professional team with different occupations (e.g., physician, nurse, psychologist, and social worker). Remaining skepticism concerning the need for SPC may be based on the scarcity of high-quality evaluations about the external evidence for SPC. Therefore, we will conduct a systematic review according to Cochrane standards to examine the effects of SPC for adults with advanced illness. Methods/design: The comprehensive systematic literature search will include randomized controlled trials (RCTs) and cluster RCTs. We will search the databases MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL), and PsycINFO. Patients must be adults suffering from life-limiting diseases. Proxy and caregiver outcomes will not be assessed in order to ensure a clear and well-defined research question for this review. Interventions may be in an in- or outpatient setting, e.g., consulting service, palliative care ward, and palliative outpatient clinic. In line with the multi-dimensional scope of palliative care, the primary outcome is quality of life (QoL). Key secondary outcomes are patients' symptom burden, place of death and survival, and health economic aspects. Subgroup analysis will assess results according to cancer type, age, early vs not early SPC, site of care, and setting. Analysis will be performed with the current RevMan software. We will use the Cochrane Collaboration risk of bias assessment tool. The quality of evidence will be judged according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. Discussion: The available evidence will be summarized and discussed to provide a basis for decision-making among health care professionals and policy makers. For SPC, we believe that multi-professional care is of utmost importance. Therefore, single-profession interventions such as physician consultations will not be included. Based on the multidimensional scope of palliative care, we chose QoL as the primary outcome, despite an expected heterogeneity among the QoL outcomes. We consider unidimensional endpoints such as "pain" for the physical domain to be inadequate for capturing the true scope of (S)PC (i.e., QoL) as defined by the World Health Organization. [ABSTRACT FROM AUTHOR]

Background Statisticians investigate new methods in simulations to evaluate their properties for future real data applications. Results are often presented in a number of figures, e.g., Trellis plots. We had conducted a simulation study on six statistical methods for estimating the treatment effect in binary outcome meta-analyses, where selection bias (e.g., publication bias) was suspected because of apparent funnel plot asymmetry. We varied five simulation parameters: true treatment effect, extent of selection, event proportion in control group, heterogeneity parameter, and number of studies in meta-analysis. In combination, this yielded a total number of 768 scenarios. To present all results using Trellis plots, 12 figures were needed. Methods Choosing bias as criterion of interest, we present a 'nested loop plot', a diagram type that aims to have all simulation results in one plot. The idea was to bring all scenarios into a lexicographical order and arrange them consecutively on the horizontal axis of a plot, whereas the treatment effect estimate is presented on the vertical axis. Results The plot illustrates how parameters simultaneously influenced the estimate. It can be combined with a Trellis plot in a so-called hybrid plot. Nested loop plots may also be applied to other criteria such as the variance of estimation. Conclusion The nested loop plot, similar to a time series graph, summarizes all information about the results of a simulation study with respect to a chosen criterion in one picture and provides a suitable alternative or an addition to Trellis plots. [ABSTRACT FROM AUTHOR]

Background: In order to reduce systematic errors (such as language bias) and increase the precision of the summary treatment effect estimate, a comprehensive identification of randomised controlled trials (RCT), irrespective of publication language, is crucial in systematic reviews and meta-analyses. We identified trials in the German general health care literature. Methods: Eight German language general health care journals were searched for randomised controlled trials and analysed with respect to the number of published RCTs each year and the size of trials. Results: A total of 1618 trials were identified with a median total number of 43 patients per trial. Between 1970 and 2004 a small but constant rise in sample size from a median number of 30 to 60 patients per trial can be observed. The number of published trials was very low between 1948 and 1970, but increased between 1970 and 1986 to a maximum of 11.2 RCTs per journal and year. In the following time period a striking decline of the number of RCTs was observed. Between 1999 and 2001 only 0.8 RCTs per journal and year were published, in the next three years, the number of published trials increased to 1.7 RCTs per journal and year. Conclusion: German language general health care journals no longer have a role in the dissemination of trial results. The slight rise in the number of published RCTs in the last three years can be explained by a change of publication language from German to English of three of the analysed journals. [ABSTRACT FROM AUTHOR]

Background: The heterogeneity statistic I(2), interpreted as the percentage of variability due to heterogeneity between studies rather than sampling error, depends on precision, that is, the size of the studies included.Methods: Based on a real meta-analysis, we simulate artificially 'inflating' the sample size under the random effects model. For a given inflation factor M = 1, 2, 3,... and for each trial i, we create a M-inflated trial by drawing a treatment effect estimate from the random effects model, using s(i)(2)/M as within-trial sampling variance.Results: As precision increases, while estimates of the heterogeneity variance tau(2) remain unchanged on average, estimates of I(2) increase rapidly to nearly 100%. A similar phenomenon is apparent in a sample of 157 meta-analyses.Conclusion: When deciding whether or not to pool treatment estimates in a meta-analysis, the yard-stick should be the clinical relevance of any heterogeneity present. tau(2), rather than I(2), is the appropriate measure for this purpose. [ABSTRACT FROM AUTHOR]

Background: Health professionals and policymakers aspire to make healthcare decisions based on the entire relevant research evidence. This, however, can rarely be achieved because a considerable amount of research findings are not published, especially in case of 'negative' results - a phenomenon widely recognized as publication bias. Different methods of detecting, quantifying and adjusting for publication bias in meta-analyses have been described in the literature, such as graphical approaches and formal statistical tests to detect publication bias, and statistical approaches to modify effect sizes to adjust a pooled estimate when the presence of publication bias is suspected. An up-to-date systematic review of the existing methods is lacking., Methods/design: The objectives of this systematic review are as follows:• To systematically review methodological articles which focus on non-publication of studies and to describe methods of detecting and/or quantifying and/or adjusting for publication bias in meta-analyses.• To appraise strengths and weaknesses of methods, the resources they require, and the conditions under which the method could be used, based on findings of included studies.We will systematically search Web of Science, Medline, and the Cochrane Library for methodological articles that describe at least one method of detecting and/or quantifying and/or adjusting for publication bias in meta-analyses. A dedicated data extraction form is developed and pilot-tested. Working in teams of two, we will independently extract relevant information from each eligible article. As this will be a qualitative systematic review, data reporting will involve a descriptive summary., Discussion: Results are expected to be publicly available in mid 2013. This systematic review together with the results of other systematic reviews of the OPEN project (To Overcome Failure to Publish Negative Findings) will serve as a basis for the development of future policies and guidelines regarding the assessment and handling of publication bias in meta-analyses.

Background: Selective publication of studies, which is commonly called publication bias, is widely recognized. Over the years a new nomenclature for other types of bias related to non-publication or distortion related to the dissemination of research findings has been developed. However, several of these different biases are often still summarized by the term 'publication bias'., Methods/design: As part of the OPEN Project (To Overcome failure to Publish nEgative fiNdings) we will conduct a systematic review with the following objectives:- To systematically review highly cited articles that focus on non-publication of studies and to present the various definitions of biases related to the dissemination of research findings contained in the articles identified.- To develop and discuss a new framework on nomenclature of various aspects of distortion in the dissemination process that leads to public availability of research findings in an international group of experts in the context of the OPEN Project.We will systematically search Web of Knowledge for highly cited articles that provide a definition of biases related to the dissemination of research findings. A specifically designed data extraction form will be developed and pilot-tested. Working in teams of two, we will independently extract relevant information from each eligible article.For the development of a new framework we will construct an initial table listing different levels and different hazards en route to making research findings public. An international group of experts will iteratively review the table and reflect on its content until no new insights emerge and consensus has been reached., Discussion: Results are expected to be publicly available in mid-2013. This systematic review together with the results of other systematic reviews of the OPEN project will serve as a basis for the development of future policies and guidelines regarding the assessment and prevention of publication bias.

Background: Meta-analyses are particularly vulnerable to the effects of publication bias. Despite methodologists' best efforts to locate all evidence for a given topic the most comprehensive searches are likely to miss unpublished studies and studies that are published in the gray literature only. If the results of the missing studies differ systematically from the published ones, a meta-analysis will be biased with an inaccurate assessment of the intervention's effects.As part of the OPEN project (http://www.open-project.eu) we will conduct a systematic review with the following objectives:▪ To assess the impact of studies that are not published or published in the gray literature on pooled effect estimates in meta-analyses (quantitative measure).▪ To assess whether the inclusion of unpublished studies or studies published in the gray literature leads to different conclusions in meta-analyses (qualitative measure)., Inclusion Criteria: Methodological research projects of a cohort of meta-analyses which compare the effect of the inclusion or exclusion of unpublished studies or studies published in the gray literature., Literature Search: To identify relevant research projects we will conduct electronic searches in Medline, Embase and The Cochrane Library; check reference lists; and contact experts., Outcomes: 1) The extent to which the effect estimate in a meta-analyses changes with the inclusion or exclusion of studies that were not published or published in the gray literature; and 2) the extent to which the inclusion of unpublished studies impacts the meta-analyses' conclusions., Data Collection: Information will be collected on the area of health care; the number of meta-analyses included in the methodological research project; the number of studies included in the meta-analyses; the number of study participants; the number and type of unpublished studies; studies published in the gray literature and published studies; the sources used to retrieve studies that are unpublished, published in the gray literature, or commercially published; and the validity of the methodological research project., Data Synthesis: DATA SYNTHESIS will involve descriptive and statistical summaries of the findings of the included methodological research projects., Discussion: Results are expected to be publicly available in the middle of 2013.

Background: Systematic reviews and meta-analyses of pre-clinical studies, in vivo animal experiments in particular, can influence clinical care. Publication bias is one of the major threats of validity in systematic reviews and meta-analyses. Previous empirical studies suggested that systematic reviews and meta-analyses have become more prevalent until 2010 and found evidence for compromised methodological rigor with a trend towards improvement. We aim to comprehensively summarize and update the evidence base on systematic reviews and meta-analyses of animal studies, their methodological quality and assessment of publication bias in particular., Methods/design: The objectives of this systematic review are as follows: •To investigate the epidemiology of published systematic reviews of animal studies until present. •To examine methodological features of systematic reviews and meta-analyses of animal studies with special attention to the assessment of publication bias. •To investigate the influence of systematic reviews of animal studies on clinical research by examining citations of the systematic reviews by clinical studies. Eligible studies for this systematic review constitute systematic reviews and meta-analyses that summarize in vivo animal experiments with the purpose of reviewing animal evidence to inform human health. We will exclude genome-wide association studies and animal experiments with the main purpose to learn more about fundamental biology, physical functioning or behavior. In addition to the inclusion of systematic reviews and meta-analyses identified by other empirical studies, we will systematically search Ovid Medline, Embase, ToxNet, and ScienceDirect from 2009 to January 2013 for further eligible studies without language restrictions. Two reviewers working independently will assess titles, abstracts, and full texts for eligibility and extract relevant data from included studies. Data reporting will involve a descriptive summary of meta-analyses and systematic reviews., Discussion: Results are expected to be publicly available later in 2013 and may form the basis for recommendations to improve the quality of systematic reviews and meta-analyses of animal studies and their use with respect to clinical care.

Background: Methodological research has found that non-published studies often have different results than those that are published, a phenomenon known as publication bias. When results are not published, or are published selectively based on the direction or the strength of the findings, healthcare professionals and consumers of healthcare cannot base their decision-making on the full body of current evidence., Methods: As part of the OPEN project (http://www.open-project.eu) we will conduct a systematic review with the following objectives:1. To determine the proportion and/or rate of non-publication of studies by systematically reviewing methodological research projects that followed up a cohort of studies that a. received research ethics committee (REC) approval,b. were registered in trial registries, orc. were presented as abstracts at conferences.2. To assess the association of study characteristics (for example, direction and/or strength of findings) with likelihood of full publication.To identify reports of relevant methodological research projects we will conduct electronic database searches, check reference lists, and contact experts. Published and unpublished projects will be included. The inclusion criteria are as follows:a. RECs: methodological research projects that examined the subsequent proportion and/or rate of publication of studies that received approval from RECs;b. Trial registries: methodological research projects that examine the subsequent proportion and/or rate of publication of studies registered in trial registries;c. Conference abstracts: methodological research projects that examine the subsequent proportion and/or rate of full publication of studies which were initially presented at conferences as abstracts., Primary Outcomes: Proportion/rate of published studies; time to full publication (mean/median; cumulative publication rate by time)., Secondary Outcomes: Association of study characteristics with full publication.The different questions (a, b, and c) will be investigated separately. Data synthesis will involve a combination of descriptive and statistical summaries of the included methodological research projects., Discussion: Results are expected to be publicly available in mid 2013.