Impact of biobanks on research outcomes in rare diseases: a systematic review
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Alleviating the burden of rare diseases requires research into new diagnostic and therapeutic strategies. We undertook a systematic review to identify and compare the impact of stand-alone registries, registries with biobanks, and rare disease biobanks on research outcomes in rare diseases. A systematic review and meta-aggregation was conducted using the preferred reporting items for systematic reviews and meta-analyses (the PRISMA statement). English language publications were sourced from PubMed, Medline, Scopus, and Web of Science. Original research papers that reported clinical, epidemiological, basic or translational research findings derived from data contained in stand-alone registries, registries with biobanks, and rare disease biobanks were considered. Articles selected for inclusion were assessed using the critical appraisal instruments by JBI-QARI. Each article was read in its entirety and findings were extracted using the online data extraction software from JBI-QARI. Thirty studies including 28 rare disease resources were included in the review. Of those, 14 registries were not associated to biobank infrastructure, 9 registries were associated with biobank infrastructure, and 6 were rare disease biobank resources. Stand-alone registries had the capacity to uncover the natural history of disease and contributed to evidence-based practice. When annexed to biobank infrastructure, registries could also identify and validate biomarkers, uncover novel genes, elucidate pathogenesis at the Omics level, and develop new therapeutic strategies. Rare disease biobanks in this review had similar capacity for biological investigations, but in addition, had far greater sample numbers and higher quality laboratory techniques for quality assurance processes. We examined the research outcomes of three specific populations: stand-alone registries, registries with biobanks, and stand-alone rare disease biobanks and demonstrated that there are key differences among these resources. These differences are a function of the resources' design, aims, and objectives, with each resource having a distinctive and important role in contributing to the body of knowledge for rare disease research. Whilst stand-alone registries had the capacity to uncover the natural history of disease, develop best practice, replace clinical trials, and improve patient outcomes, they were limited in their capacity to conduct basic research. The role of basic research in rare disease research is vital; scientists must first understand the pathways of disease before they can develop appropriate interventions. Rare disease biobanks, on the other hand (particularly larger biobanks), had the key infrastructure required to conduct basic research, making novel Omics discoveries, identify and validate biomarkers, uncover novel genes, and develop new therapeutic strategies. However, these stand-alone rare disease biobanks did not collect comprehensive data or impact on clinical observations like a rare disease registry. Rare disease research is important not only for rare diseases, but also for also common diseases. For example, research of low-density lipoprotein (LDL)-receptors in the rare disease known as familial hypercholesterolemia led to the discovery of statins, a drug therapy that is now used routinely to prevent heart disease. Rare diseases are still under-researched worldwide. This review made the important observation that registries with biobanks had the function of both stand-alone registries (the capacity to collect comprehensive clinical and epidemiological data) and stand-alone rare disease biobanks (the ability to contribute to Omics research). We found registries with biobanks offer a unique, practical, cost-effective, and impactful solution for rare disease research. Linkage of stand-alone registries to rare disease biobanks will provide the appropriate resources required for the effective translation of basic research into clinical practice. Furthermore, facilitators such as collaboration, engagement, blended recruitment, pro-active marketing, broad consent, and "virtual biobank" online catalogues will, if utilised, add to the success of these resources. These important observations can serve to direct future rare diseases research efforts, ultimately improve patient outcomes and alleviate the significant burden associated with rare disease for clinicians, hospitals, society, and most importantly, the patients and their families.Keywords:
Critical appraisal
Researchers and healthcare professionals need to assess the confidence of review results before accepting results of a single systematic review, considering its reputation and influence based on the hierarchy of evidence in an evidence-based practice. A MeaSurement Tool to Assess systematic Reviews 2 (AMSTAR 2), an updated version of AMASTAR, was published in 2017, consists of 16 domains, and is useful as a critical appraisal tool for systematic review of randomized or non-randomized studies of healthcare interventions, or both, in terms of inter-rater agreement and intuitiveness of items. Notably, AMSTAR 2 was not designed to generate an overall score. Moreover, the assessors should evaluate overall confidence in the results of systematic review, by determining critical domains and taking account of the potential impact of critical flaw of each domain on the confidence of the review results.
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Introduction: Making decisions based on evidence has been a challenge for health professionals, given the need to have the tools and skills to carry out a critical appraisal of the evidence and assess the validity of the results. Systematic reviews of the literature (SRL) have been used widely to answer questions in the clinical field. Tools have been developed that support the appraisal of the quality of the studies. AMSTAR is one of these, validated and supported by reproducible evidence, which guides the methodological quality of the SRL.
Objectives: To show a historical, theoretical and practical guide for critical assessment of systematic reviews using AMSTAR to guide the argumental bases for their use according to the components of this methodological structure in health research, and to provide practical examples of how to apply this checklist.
Methods: We conducted a non-exhaustive review of literature in Pubmed and Cochrane Library using “AMSTAR” and “Systematic Reviews” as free terms without language or publication date limit; we also collected information from experts in the evaluation of the quality of the evidence.
Conclusions: AMSTAR is an instrument used, validated and supported by reproducible evidence for the evaluation of the internal validity of systematic reviews of the literature. It consists of 16 items that assess the overall methodological quality of an SRL. It is currently used indiscriminately and favorably, but it is not exempt from limitations and future updates based on new reproducibility and validation studies.
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Given the nature of scientific inquiry, biomedical and genomic researchers have forged innumerable ways to advance our understanding of human disease. In many cases, research requires the involvement of human subjects, and in a subset of these studies, the researcher may collect data and biospecimens from many participants, and even serially collect additional materials over time and across a number of geographically dispersed centers. The organized data and biospecimens are collectively known as research biobanks. Researchers have an obligation to disseminate findings from their research through publications and presentations to other professionals, and when possible, to the public. Sharing genomic data is increasingly being mandated; access to data can be obtained through collaborative or state-funded entities. For example, the database of Genotypes and Phenotypes (dbGAP) and the International Cancer Genome Consortium will grant approved research applicants access to de-identified individual level genomic data with accompanying demographic/clinical information.
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OBJECTIVES: Concise definitive review of how to read and critically appraise a systematic review. DATA SOURCES: None. STUDY SELECTION: Current literature describing the conduct, reporting, and appraisal of systematic reviews and meta-analyses. DATA EXTRACTION: Best practices for conducting, reporting, and appraising systematic review were summarized. DATA SYNTHESIS: A systematic review is a review of a clearly formulated question that uses systematic and explicit methods to identify, select, and critically appraise relevant original research, and to collect and analyze data from the studies that are included in the review. Critical appraisal methods address both the credibility (quality of conduct) and rate the confidence in the quality of summarized evidence from a systematic review. The A Measurement Tool to Assess Systematic Reviews-2 tool is a widely used practical tool to appraise the conduct of a systematic review. Confidence in estimates of effect is determined by assessing for risk of bias, inconsistency of results, imprecision, indirectness of evidence, and publication bias. CONCLUSIONS: Systematic reviews are transparent and reproducible summaries of research and conclusions drawn from them are only as credible and reliable as their development process and the studies which form the systematic review. Applying evidence from a systematic review to patient care considers whether the results can be directly applied, whether all important outcomes have been considered, and if the benefits are worth potential harms and costs.
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Comparison of search strategies in systematic reviews of adverse effects to other systematic reviews
Abstract Background Research indicates that the methods used to identify data for systematic reviews of adverse effects may need to differ from other systematic reviews. Objectives To compare search methods in systematic reviews of adverse effects with other reviews. Methods The search methodologies in 849 systematic reviews of adverse effects were compared with other reviews. Results Poor reporting of search strategies is apparent in both systematic reviews of adverse effects and other types of systematic reviews. Systematic reviews of adverse effects are less likely to restrict their searches to MEDLINE or include only randomised controlled trials ( RCT s). The use of other databases is largely dependent on the topic area and the year the review was conducted, with more databases searched in more recent reviews. Adverse effects search terms are used by 72% of reviews and despite recommendations only two reviews report using floating subheadings. Conclusions The poor reporting of search strategies in systematic reviews is universal, as is the dominance of searching MEDLINE . However, reviews of adverse effects are more likely to include a range of study designs (not just RCT s) and search beyond MEDLINE .
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The number of published systematic reviews of studies of healthcare interventions has increased rapidly and these are used extensively for clinical and policy decisions. Systematic reviews are subject to a range of biases and increasingly include non-randomised studies of interventions. It is important that users can distinguish high quality reviews. Many instruments have been designed to evaluate different aspects of reviews, but there are few comprehensive critical appraisal instruments. AMSTAR was developed to evaluate systematic reviews of randomised trials. In this paper, we report on the updating of AMSTAR and its adaptation to enable more detailed assessment of systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. With moves to base more decisions on real world observational evidence we believe that AMSTAR 2 will assist decision makers in the identification of high quality systematic reviews, including those based on non-randomised studies of healthcare interventions.
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Background: Recently there has been a significant increase in the number of systematic reviews addressing questions of prevalence. Key features of a systematic review include the creation of an a priori protocol, clear inclusion criteria, a structured and systematic search process, critical appraisal of studies, and a formal process of data extraction followed by methods to synthesize, or combine, this data. Currently there exists no standard method for conducting critical appraisal of studies in systematic reviews of prevalence data. Methods: A working group was created to assess current critical appraisal tools for studies reporting prevalence data and develop a new tool for these studies in systematic reviews of prevalence. Following the development of this tool it was piloted amongst an experienced group of sixteen healthcare researchers. Results: The results of the pilot found that this tool was a valid approach to assessing the methodological quality of studies reporting prevalence data to be included in systematic reviews. Participants found the tool acceptable and easy to use. Some comments were provided which helped refine the criteria. Conclusion: The results of this pilot study found that this tool was well-accepted by users and further refinements have been made to the tool based on their feedback. We now put forward this tool for use by authors conducting prevalence systematic reviews.
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Systematic review is a method to combine multiple sources of evidence through an explicit and reproducible way of literature search and critical appraisal of the quality of included studies, with or without mathematical methods to synthesis these information. Since this method was first introduced more than centuries ago, systematic review has been increasingly popular and widely used particularly in the area of medicine. Systematic review is often very useful to physicians to help supporting the clinical decision making and significantly reducing their time to seek for appropriate evidence. However, despite its reproducible and systematic steps to substantially minimize the presence of biases, physicians should still be aware that systematic review is not completely biases resistant. Inclusion of poor quality studies, heterogeneity, and publication or other reporting biases are commonly evident in systematic review that may hinder the quality of the conclusion. This review summarizes the core principals of systematic review and its potential biases, and discusses when the systematic review is useful or needing careful attention. Key words: treatment-scientific evidence- meta-analysis- critical appraisal-outcomes
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Background Recently there has been a significant increase in the number of systematic reviews addressing questions of prevalence. Key features of a systematic review include the creation of an a priori protocol, clear inclusion criteria, a structured and systematic search process, critical appraisal of studies, and a formal process of data extraction followed by methods to synthesize, or combine, this data. Currently there exists no standard method for conducting critical appraisal of studies in systematic reviews of prevalence data. Methods A working group was created to assess current critical appraisal tools for studies reporting prevalence data and develop a new tool for these studies in systematic reviews of prevalence. Following the development of this tool it was piloted amongst an experienced group of sixteen healthcare researchers. Results The results of the pilot found that this tool was a valid approach to assessing the methodological quality of studies reporting prevalence data to be included in systematic reviews. Participants found the tool acceptable and easy to use. Some comments were provided which helped refine the criteria. Conclusion The results of this pilot study found that this tool was well-accepted by users and further refinements have been made to the tool based on their feedback. We now put forward this tool for use by authors conducting prevalence systematic reviews.
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