BACKGROUND:Meta-analyses are used to summarise the results of several studies on a specific research question. Standard methods for meta-analyses, namely inverse variance random effects models, have unfavourable properties if only very few (2 - 4) studies are available. Therefore, alternative meta-analytic methods are needed. In the case of binary data, the "common-rho" beta-binomial model has shown good results in situations with sparse data or few studies. The major concern of this model is that it ignores the fact that each treatment arm is paired with a respective control arm from the same study. Thus, the randomisation to a study arm of a specific study is disrespected, which may lead to compromised estimates of the treatment effect. Therefore, we extended this model to a version that respects randomisation. The aim of this simulation study was to compare the "common-rho" beta-binomial model and several other beta-binomial models with standard meta-analyses models, including generalised linear mixed models and several inverse variance random effects models. METHODS:We conducted a simulation study comparing beta-binomial models and various standard meta-analysis methods. The design of the simulation aimed to consider meta-analytic situations occurring in practice. RESULTS:No method performed well in scenarios with only 2 studies in the random effects scenario. In this situation, a fixed effect model or a qualitative summary of the study results may be preferable. In scenarios with 3 or 4 studies, most methods satisfied the nominal coverage probability. The "common-rho" beta-binomial model showed the highest power under the alternative hypothesis. The beta-binomial model respecting randomisation did not improve performance. CONCLUSION:The "common-rho" beta-binomial appears to be a good option for meta-analyses of very few studies. As residual concerns about the consequences of disrespecting randomisation may still exist, we recommend a sensitivity analysis with a standard meta-analysis method that respects randomisation.

Hazards constitute key quantities for analyzing, interpreting, and understanding time-to-event data. Hazards and corresponding effect measures, such as the hazard ratio from the Cox proportional hazards model, have a valid causal interpretation if the hazard function is considered as a function in time rather than hazards at specific time points. In this comment, we would like to add two points: (1) The hazard ratio is also a useful population-level estimand with a valid causal interpretation. (2) Empirical evidence shows that problematic situations, which could occur in theory due to strong heterogeneity, are usually avoided in typical randomized controlled trials.

Abstract Background Time-to-event analysis is associated with methodological complexities. Previous research identified flaws in the reporting of time-to-event analyses in randomized trial publications. These hardships impose challenges for meta-analyses of time-to-event outcomes based on aggregate data. We examined the characteristics, reporting and methods of systematic reviews including such analyses. Methods Through a systematic search (02/2017-08/2020), we identified 50 Cochrane Reviews with ≥ 1 meta-analysis based on the hazard ratio (HR) and a corresponding random sample (n = 50) from core clinical journals (Medline; 08/02/2021). Data was extracted in duplicate and included outcome definitions, general and time-to-event specific methods and handling of time-to-event relevant trial characteristics. Results The included reviews analyzed 217 time-to-event outcomes (Median: 2; IQR 1–2), most frequently overall survival (41%). Outcome definitions were provided for less than half of time-to-event outcomes (48%). Few reviews specified general methods, e.g., included analysis types (intention-to-treat, per protocol) (35%) and adjustment of effect estimates (12%). Sources that review authors used for retrieval of time-to-event summary data from publications varied substantially. Most frequently reported were direct inclusion of HRs (64%) and reference to established guidance without further specification (46%). Study characteristics important to time-to-event analysis, such as variable follow-up, informative censoring or proportional hazards, were rarely reported. If presented, complementary absolute effect estimates calculated based on the pooled HR were incorrectly calculated (14%) or correct but falsely labeled (11%) in several reviews. Conclusions Our findings indicate that limitations in reporting of trial time-to-event analyses translate to the review level as well. Inconsistent reporting of meta-analyses of time-to-event outcomes necessitates additional reporting standards.

Im Sortiment des Importhauses Wilms ist Wan Kwai die erste eigene Marke. Entsprechend hoch sind die Erwartungen und der Wille zum Erfolg.

In Europa ist Mutti bereits der führende Markenanbieter von Dosentomaten. Diese Position könnte das Unternehmen bald auch in Deutschland erreichen.

Background: Systematic reviews (SRs) are usually conducted by a highly specialized group of researchers. The routine involvement of methodological experts is a core methodological recommendation. The present commentary describes the qualifications required for information specialists and statisticians involved in SRs, as well as their tasks, the methodological challenges they face, and potential future areas of involvement. Tasks and qualifications: Information specialists select the information sources, develop search strategies, conduct the searches, and report the results. Statisticians select the methods for evidence synthesis, assess the risk of bias, and interpret the results. The minimum requirements for their involvement in SRs are a suitable university degree (e.g., in statistics or librarian/information science or an equivalent degree), methodological and content expertise, and several years of experience. Key arguments: The complexity of conducting SRs has greatly increased due to a massive rise in the amount of available evidence and the number and complexity of SR methods, largely statistical and information retrieval methods. Additional challenges exist in the actual conduct of an SR, such as judging how complex the research question could become and what hurdles could arise during the course of the project. Conclusion: SRs are becoming more and more complex to conduct and information specialists and statisticians should routinely be involved right from the start of the SR. This increases the trustworthiness of SRs as the basis for reliable, unbiased and reproducible health policy, and clinical decision making.

In Bayesian random-effects meta-analysis, the use of weakly informative prior distributions is of particular benefit in cases where only a few studies are included, a situation often encountered in health technology assessment (HTA). Suggestions for empirical prior distributions are available in the literature but it is unknown whether these are adequate in the context of HTA. Therefore, a database of all relevant meta-analyses conducted by the Institute for Quality and Efficiency in Health Care (IQWiG, Germany) was constructed to derive empirical prior distributions for the heterogeneity parameter suitable for HTA. Previously, an extension to the normal-normal hierarchical model had been suggested for this purpose. For different effect measures, this extended model was applied on the database to conservatively derive a prior distribution for the heterogeneity parameter. Comparison of a Bayesian approach using the derived priors with IQWiG's current standard approach for evidence synthesis shows favorable properties. Therefore, these prior distributions are recommended for future meta-analyses in HTA settings and could be embedded into the IQWiG evidence synthesis approach in the case of very few studies.

Bekannt ist Kikkoman vor allem mit Sojasauce. Trotz des schon hohen Marktanteils sieht Vertriebspartner Develey gute Chancen für weiteres Wachstum.

In Bayesian meta-analysis, the specification of prior probabilities for the between-study heterogeneity is commonly required, and is of particular benefit in situations where only few studies are included. Among the considerations in the set-up of such prior distributions, the consultation of available empirical data on a set of relevant past analyses sometimes plays a role. How exactly to summarize historical data sensibly is not immediately obvious; in particular, the investigation of an empirical collection of heterogeneity estimates will not target the actual problem and will usually only be of limited use. The commonly used normal-normal hierarchical model for random-effects meta-analysis is extended to infer a heterogeneity prior. Using an example data set, we demonstrate how to fit a distribution to empirically observed heterogeneity data from a set of meta-analyses. Considerations also include the choice of a parametric distribution family. Here, we focus on simple and readily applicable approaches to then translate these into (prior) probability distributions.

OBJECTIVES:Previous findings indicate limited reporting of systematic reviews with meta-analyses of time-to-event (TTE) outcomes. We assessed corresponding available information in trial publications included in such meta-analyses. STUDY DESIGN AND SETTING:We extracted data from all randomized trials in pairwise, hazard ratio (HR)-based meta-analyses of primary outcomes and overall survival of 50 systematic reviews systematically identified from the Cochrane Database and Core Clinical Journals. Data on methods and characteristics relevant for TTE analysis of reviews, trials, and outcomes were extracted. RESULTS:Meta-analyses included 235 trials with 315 trial analyses. Most prominently assessed was overall survival (91%). Definitions (61%), censoring reasons (41%), and follow-up specifications (56%) for trial outcomes were often missing. Available TTE data per trial were most frequently survival curves (83%), log-rank P values (76%), and HRs (72%). When trial TTE data recalculation was reported, reviews mostly specified HRs or P values (each 5%). Reviews primarily included intention-to-treat analyses (64%) and analyses not adjusted for covariates (25%). Except for missing outcome data, TTE-relevant trial characteristics, for example, informative censoring, treatment switching, and proportional hazards, were sporadically addressed in trial publications. Reporting limitations in trial publications translate to the review level. CONCLUSION:TTE (meta)-analyses, in trial and review publications, need clear reporting standards.

Einen immer größeren Teil seines Geschäfts macht Beretta im Ausland. Besonders aktiv ist das Unternehmen in den USA und China, wo eigene Produktionsstandorte betrieben werden.

Markenlinien wie Viña Albali und Monomarken sollen im Sortiment von Félix Solís wichtiger werden. Durch die steigenden Kosten dürfte der Gewinn aber sinken.

Die Agar- und Lebensmittelwirtschaft in den USA und Kanada sind immer stärker auf den Export ausgerichtet. Jedoch müssen sie daran arbeiten, ihre Angebote zu diversifizieren und die Abhängigkeit von bestehenden Märkten zu verringern.

This chapter contains a methodological framework for choosing a model for the meta-analysis of very few studies and selecting an estimation method for the chosen model by means of study characteristics and by comparing results yielded by different approaches. When the results are inconclusive between different estimation methods, it might be the best solution to refrain from a quantitative meta-analysis but to summarize the study results by means of a qualitative evidence synthesis.

Von einem Nettoimporteur hat sich Spanien in wenigen Jahrzehnten zum größten Exporteur von Fleisch, Obst und Gemüse sowie Wein in der EU entwickelt. Statt Mengenwachstum dürfte in Zukunft die Wertschöpfung wichtiger werden.

Longueuil. Um fast ein Drittel will der Produzentenverband von Ahornsirup in Québec seine Verkäufe bis zum Jahr 2023 steigern. Eine zunehmende Nachfrage wird auch in Deutschland erwartet.

Objectives To provide Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) guidance for the consideration of study limitations (risk of bias) due to missing participant outcome data for time-to-event outcomes in intervention studies. Study Design and Setting We developed this guidance through an iterative process that included membership consultation, feedback, presentation, and iterative discussion at meetings of the GRADE working group. Results The GRADE working group has published guidance on how to account for missing participant outcome data in binary and continuous outcomes. When analyzing time-to-event outcomes (e.g., overall survival and time-to-treatment failure) data of participants for whom the outcome of interest (e.g., death and relapse) has not been observed are dealt with through censoring. To do so, standard methods require that censored individuals are representative for those remaining in the study. Two types of censoring can be distinguished, end of study censoring and censoring because of missing data, commonly named loss to follow-up censoring. However, both types are not distinguishable with the usual information on censoring available to review authors. Dealing with individuals for whom data are missing during follow-up in the same way as individuals for whom full follow-up is available at the end of the study increases the risk of bias. Considerable differences in the treatment arms in the distribution of censoring over time (early versus late censoring), the overall degree of missing follow-up data, and the reasons why individuals were lost to follow-up may reduce the certainty in the study results. With often only very limited data available, review and guideline authors are required to make transparent and well-considered judgments when judging risk of bias of individual studies and then come to an overall grading decision for the entire body of evidence. Conclusion Concern for risk of bias resulting from censoring of participants for whom follow-up data are missing in the underlying studies of a body of evidence can be expressed in the study limitations (risk of bias) domain of the GRADE approach.

Dällikon. Die Corona-Krise hat die Bedürfnisse der Konsumenten nachhaltig verändert. Vor allem das Thema Reinigung spielt eine zunehmende Rolle. Davon profitiert auch die Marke Durgol.