Use of systemic therapy in women with recurrent ovarian cancer—Development of a national clinical practice guideline
Laurie ElitLouise ZitzelsbergerMichael Fung‐Kee‐FungMelissa BrouwersIan D. GrahamGeorge P. BrowmanPaul HoskinsSusie LauPrafull Ghatage
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There is a lack of an instrument to evaluate systematic reviews of non-randomized studies in epidemiological research. The Assessment of Multiple Systematic Reviews (AMSTAR) is widely used to evaluate the scientific quality of systematic reviews, but it has not been validated for SRs of non-randomized studies. The objective of this paper is to report our experience in applying AMSTAR to systematic reviews of non-randomized studies in terms of applicability, reliability and feasibility. Thus, we applied AMSTAR to a recently published review of 32 systematic reviews of non-randomized studies investigating the hospital volume-outcome relationship in surgery. The inter-rater reliability was high (0.76), albeit items 8 (scientific quality used in formulating conclusions), 9 (appropriate method to combine studies), and 11 (conflicts of interest) scored moderate (≤0.58). However, there was a high heterogeneity between the two pairs of reviewers. In terms of feasibility, AMSTAR proved easy to apply to systematic reviews of non-randomized studies, each review taking 5–10 minutes to complete. We faced problems in applying three items, mainly related to scientific quality of the included studies. AMSTAR showed good psychometric properties, comparable to prior findings in systematic reviews of randomized controlled trials. AMSTAR can be applied to systematic reviews of non-randomized studies, although there are some item specific issues users should be aware of. Revisions and extensions of AMSTAR might be helpful.
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Objective: To assess the reporting and methodological quality of systematic reviews and meta-analysis studies on pharmacist interventions in patients with diabetes. Data Sources: A comprehensive literature search was performed in MEDLINE, Scopus, and LILACS databases for systematic reviews and meta-analysis studies published from January 1990 to June 2013. The standardized search strategy included the use of MeSH terms or text words related to pharmacist interventions, diabetes, and systematic reviews. Study Selection and Data Extraction: The overview included systematic reviews and meta-analysis studies published in English, Portuguese, or Spanish that evaluated the effect of pharmacist intervention on outcomes for diabetic patients. Two independent authors performed study selection, data extraction, and quality assessment with a consensus process to address disagreements. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) and Assessment of Multiple Systematic Reviews (AMSTAR) checklists were used to assess reporting characteristics and methodological quality, respectively. Data Synthesis: The literature search yielded 101 records of potential interest, of which 7 satisfied the inclusion criteria. The total average (SD) for PRISMA and AMSTAR scores were 17.4 (5.6) out of 27 and 6.9 (2.0) out of 11, respectively. The most frequent problems included nonregistration of study protocol, absence of a list of excluded studies, and unclear acknowledgment of conflicts of interests. Conclusion: The reporting and methodological quality of systematic reviews and meta-analysis studies were suboptimal, with some areas needing further improvement. It is necessary to ensure better transparency and reproducibility in the literature of clinical pharmacy services for diabetic patients.
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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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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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Background
Well conducted systematic reviews provide transparent and robust evidence syntheses. They are, therefore, important for informing clinical practice and health policy. In systematic reviews where meta-analysis is not possible or appropriate, quantitative data are often synthesised narratively. However, a major concern is that narrative synthesis (NS) can lack transparency, leading to bias in the synthesis and threatening the reliability of these reviews for decision makers. We conducted a systematic assessment of Cochrane reviews to establish prevalence of NS, and to assess current practice and transparency in the conduct and reporting of NS in systematic reviews.Methods
Cochrane systematic reviews published between April 2016 and April 2017 (n=714) were examined to determine the primary method of synthesis. Data were extracted from a sample of reviews (n=60/714) that used NS as the primary method of synthesis. A previously tested data extraction template, based on key guidance on NS, was used. This covered reporting of NS methods; transparency between data and text; management and investigation of heterogeneity; and review authors' reflections on limitations of the synthesis.Results
NS or text only as the primary method of synthesis was used by 16% (n=113/714). In reviews using NS (n=60/113): 53% stated the data were being synthesised narratively; 18% described the NS methods; and 10% referred to NS guidance. Links between the text and the data were clear in 30% (18/60) and, partially in 23% of reviews. The remaining 47% of reviews did not present tabulated summaries of synthesised data. Of the reviews that provided tabulated summaries of data, 16% (n=5/32) did not present the data in the same order and categories as the narrative text. Heterogeneity in the direction of effect of the primary outcome was identified in 14 reviews, of these 46% (n=6/14) attempted to explain the heterogeneity. While 98% of review authors reflected on the limitations of the evidence, 77% reported limitations of the synthesis process.Conclusion
Despite being commonly used, NS is not reported transparently. The limited reporting of methods, and lack of transparency between the data, the narrative and the conclusions, limits assessment of the validity and threatens the reliability of systematic reviews using NS. There is a need for updated guidance on NS. A Delphi survey is underway to develop consensus-based a reporting guideline for NS. The draft items arising from the Delphi survey will be presented.Data extraction
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This study will assess the efficacy and safety of Shenmai injection (SMI) for the treatment of chronic heart failure (CHF).The following electronic bibliographic databases will be searched from inception to the March 25, 2020 without language and publication time limitations: MEDLINE, PUBMED, Cochrane Library, Web of Science, Scopus, WANGFANG, Chinese Biomedical Literature Database, and China National Knowledge Infrastructure. All randomized controlled trials related to the SMI for patients with CHF will be included. All study selection, data extraction, and study quality will be carried out by 2 reviewers. Any disagreements will be solved by a third reviewer through discussion. RevMan 5.3 software will be used for data synthesis and data analysis.This study will summarize the present evidence of SMI for the treatment of patients with CHF.The findings of this study will determine whether SMI is effective and safety for the treatment of CHF or not.INPLASY202050029.
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The percentage of non-overlapping data (PND; Scruggs, Mastropieri, & Casto, 1987) is one of several outcome metrics for aggregating data across studies using single-subject experimental designs. The application of PND requires the systematic reviewer to make various decisions related to the inclusion of studies, extraction of data, and analysis and interpretation of data. The purpose of this systematic review was to determine the reporting characteristics associated with the application of PND in systematic reviews and meta-analyses. The authors engage in a discussion of the reporting characteristics found in the data set and propose several directions for future applications and reporting of PND in systematic reviews.
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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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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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