Dataset Information

Systematic reviews of animal studies; missing link in translational research?

ABSTRACT:

Background

The methodological quality of animal studies is an important factor hampering the translation of results from animal studies to a clinical setting. Systematic reviews of animal studies may provide a suitable method to assess and thereby improve their methodological quality.

Objectives

The aims of this study were: 1) to evaluate the risk of bias assessment in animal-based systematic reviews, and 2) to study the internal validity of the primary animal studies included in these systematic reviews.

Data sources

We systematically searched Pubmed and Embase for SRs of preclinical animal studies published between 2005 and 2012.

Results

A total of 91 systematic reviews met our inclusion criteria. The risk of bias was assessed in 48 (52.7%) of these 91 systematic reviews. Thirty-three (36.3%) SRs provided sufficient information to evaluate the internal validity of the included studies. Of the evaluated primary studies, 24.6% was randomized, 14.6% reported blinding of the investigator/caretaker, 23.9% blinded the outcome assessment, and 23.1% reported drop-outs.

Conclusions

To improve the translation of animal data to clinical practice, systematic reviews of animal studies are worthwhile, but the internal validity of primary animal studies needs to be improved. Furthermore, risk of bias should be assessed by systematic reviews of animal studies to provide insight into the reliability of the available evidence.

SUBMITTER: van Luijk J

PROVIDER: S-EPMC3966727 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Publications

Systematic reviews of animal studies; missing link in translational research?

van Luijk Judith J Bakker Brenda B Rovers Maroeska M MM Ritskes-Hoitinga Merel M de Vries Rob B M RB Leenaars Marlies M

PloS one 20140326 3

<h4>Background</h4>The methodological quality of animal studies is an important factor hampering the translation of results from animal studies to a clinical setting. Systematic reviews of animal studies may provide a suitable method to assess and thereby improve their methodological quality.<h4>Objectives</h4>The aims of this study were: 1) to evaluate the risk of bias assessment in animal-based systematic reviews, and 2) to study the internal validity of the primary animal studies included in ...[more]

PMID: 24670965

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Project description:BackgroundSeveral studies have documented the production of wasteful research, defined as research of no scientific importance and/or not meeting societal needs. We argue that this redundancy in research may to a large degree be due to the lack of a systematic evaluation of the best available evidence and/or of studies assessing societal needs.ObjectivesThe aim of this scoping review is to (A) identify meta-research studies evaluating if redundancy is present within biomedical research, and if so, assessing the prevalence of such redundancy, and (B) to identify meta-research studies evaluating if researchers had been trying to minimise or avoid redundancy.Eligibility criteriaMeta-research studies (empirical studies) were eligible if they evaluated whether redundancy was present and to what degree; whether health researchers referred to all earlier similar studies when justifying and designing a new study and/or when placing new results in the context of earlier similar trials; and whether health researchers systematically and transparently considered end users' perspectives when justifying and designing a new study.Sources of evidenceThe initial overall search was conducted in MEDLINE, Embase via Ovid, CINAHL, Web of Science, Social Sciences Citation Index, Arts & Humanities Citation Index, and the Cochrane Methodology Register from inception to June 2015. A 2nd search included MEDLINE and Embase via Ovid and covered January 2015 to 26 May 2021. No publication date or language restrictions were applied.Charting methodsCharting methods included description of the included studies, bibliometric mapping, and presentation of possible research gaps in the identified meta-research.ResultsWe identified 69 meta-research studies. Thirty-four (49%) of these evaluated the prevalence of redundancy and 42 (61%) studies evaluated the prevalence of a systematic and transparent use of earlier similar studies when justifying and designing new studies, and/or when placing new results in context, with seven (10%) studies addressing both aspects. Only one (1%) study assessed if the perspectives of end users had been used to inform the justification and design of a new study. Among the included meta-research studies evaluating whether redundancy was present, only two of nine health domains (medical areas) and only two of 10 research topics (different methodological types) were represented. Similarly, among the included meta-research studies evaluating whether researchers had been trying to minimise or avoid redundancy, only one of nine health domains and only one of 10 research topics were represented.Conclusions that relate to the review questions and objectivesEven with 69 included meta-research studies, there was a lack of information for most health domains and research topics. However, as most included studies were evaluating across different domains, there is a clear indication of a high prevalence of redundancy and a low prevalence of trying to minimise or avoid redundancy. In addition, only one meta-research study evaluated whether the perspectives of end users were used to inform the justification and design of a new study.Systematic review registrationProtocol registered at Open Science Framework: https://osf.io/3rdua/ (15 June 2021).

Project description:There is a great deal of interest in personalized, individualized, or precision interventions for disease and health-risk mitigation. This is as true of nutrition-based intervention and prevention strategies as it is for pharmacotherapies and pharmaceutical-oriented prevention strategies. Essentially, technological breakthroughs have enabled researchers to probe an individual's unique genetic, biochemical, physiological, behavioral, and exposure profile, allowing them to identify very specific and often nuanced factors that an individual might possess, which may make it more or less likely that he or she responds favorably to a particular intervention (e.g., nutrient supplementation) or disease prevention strategy (e.g., specific diet). However, as compelling and intuitive as personalized nutrition might be in the current era in which data-intensive biomedical characterization of individuals is possible, appropriately and objectively vetting personalized nutrition strategies is not trivial and requires novel study designs and data analytical methods. These designs and methods must consider a very integrated use of the multiple contemporary biomedical assays and technologies that motivate them, which adds to their complexity. Single-subject or N-of-1 trials can be used to assess the utility of personalized interventions and, in addition, can be crafted in such a way as to accommodate the necessarily integrated use of many emerging biomedical technologies and assays. In this review, we consider the motivation, design, and implementation of N-of-1 trials in translational nutrition research that are meant to assess the utility of personalized nutritional strategies. We provide a number of example studies, discuss appropriate analytical methods given the complex data they generate and require, and consider how such studies could leverage integration of various biomarker assays and clinical end points. Importantly, we also consider the development of strategies and algorithms for matching nutritional needs to individual biomedical profiles and the issues surrounding them. Finally, we discuss the limitations of personalized nutrition studies, possible extensions of N-of-1 nutritional intervention studies, and areas of future research.

Project description:BackgroundResults of new studies should be interpreted in the context of what is already known to compare results and build the state of the science. This systematic review and meta-analysis aimed to identify and synthesise results from meta-research studies examining if original studies within health use systematic reviews to place their results in the context of earlier, similar studies.MethodsWe searched MEDLINE (OVID), EMBASE (OVID), and the Cochrane Methodology Register for meta-research studies reporting the use of systematic reviews to place results of original clinical studies in the context of existing studies. The primary outcome was the percentage of original studies included in the meta-research studies using systematic reviews or meta-analyses placing new results in the context of existing studies. Two reviewers independently performed screening and data extraction. Data were synthesised using narrative synthesis and a random-effects meta-analysis was performed to estimate the mean proportion of original studies placing their results in the context of earlier studies. The protocol was registered in Open Science Framework.ResultsWe included 15 meta-research studies, representing 1724 original studies. The mean percentage of original studies within these meta-research studies placing their results in the context of existing studies was 30.7% (95% CI [23.8%, 37.6%], I2=87.4%). Only one of the meta-research studies integrated results in a meta-analysis, while four integrated their results within a systematic review; the remaining cited or referred to a systematic review. The results of this systematic review are characterised by a high degree of heterogeneity and should be interpreted cautiously.ConclusionOur systematic review demonstrates a low rate of and great variability in using systematic reviews to place new results in the context of existing studies. On average, one third of the original studies contextualised their results. Improvement is still needed in researchers' use of prior research systematically and transparently-also known as the use of an evidence-based research approach, to contribute to the accumulation of new evidence on which future studies should be based.Systematic review registrationOpen Science registration number https://osf.io/8gkzu/.

Dataset Information

Systematic reviews of animal studies; missing link in translational research?

Background

Objectives

Data sources

Results

Conclusions

Publications

Systematic reviews of animal studies; missing link in translational research?

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