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Background Prospective registration aims to reduce bias in the conduct and reporting of research and to increase transparency. In addition, prospective registration of systematic reviews is argued to help preventing unintended duplication, thereby reducing research waste. PROSPERO was launched in 2011 as the first prospective register for systematic reviews. While it has long been the only option to prospectively register systematic reviews, recently there have been new developments. Our aim was to identify and characterize current options to prospectively register a systematic review to assist review authors in choosing a suitable register. Methods To identify systematic review registers, we independently performed internet searches in January 2021 using keywords related to systematic reviews and prospective registration. “Registration” was defined as the process of entering information about a planned systematic review into a database before starting the systematic review process. We collected data on the characteristics of the identified registries and contacted the responsible party of each register for verification of the data related to their registry. Results Overall, we identified five options to prospectively register a systematic review: PROSPERO, the Registry of Systematic Reviews/Meta-Analyses in Research Registry, and INPLASY, which are specific to systematic reviews, and the Open Science Framework Registries and protocols.io, which represent generic registers open to any study type. Detailed information on each register is presented in tables in the main text. Regarding the systematic-review-specific registries, authors have to trade-off between the costs of registration and the processing time of their registration record. All registers provide an option to search for systematic reviews already registered in the register. However, it is unclear how useful these search functions are. Conclusion Authors can prospectively register their systematic review in five registries, which come with different characteristics and features. The research community should discuss fair and sustainable financing models for registers that are not operated by for-profit organizations.

Distinguishing cohort studies from case series is difficult. We propose a conceptualization of cohort studies in systematic reviews of comparative studies. The main aim of this conceptualization is to clarify the distinction between cohort studies and case series. We discuss the potential impact of the proposed conceptualization on the body of evidence and workload. All studies with exposure-based sampling gather multiple exposures (with at least two different exposures or levels of exposure) and enable calculation of relative risks that should be considered cohort studies in systematic reviews, including non-randomized studies. The term “enables/can” means that a predefined analytic comparison is not a prerequisite (i.e., the absolute risks per group and/or a risk ratio are provided). Instead, all studies for which sufficient data are available for reanalysis to compare different exposures (e.g., sufficient data in the publication) are classified as cohort studies. There are possibly large numbers of studies without a comparison for the exposure of interest but that do provide the necessary data to calculate effect measures for a comparison. Consequently, more studies could be included in a systematic review. Therefore, on the one hand, the outlined approach can increase the confidence in effect estimates and the strengths of conclusions. On the other hand, the workload would increase (e.g., additional data extraction and risk of bias assessment, as well as reanalyses).

Background Overviews often identify and synthesise a large number of systematic reviews on the same topic, which is likely to lead to overlap (i.e. duplication) in primary studies across the reviews. Using a primary study result multiple times in the same analysis overstates its sample size and number of events, falsely leading to greater precision in the analysis. This paper aims to: (a) describe types of overlapping data that arise from the same primary studies reported across multiple reviews, (b) describe methods to identify and explain overlap of primary study data, and (c) present six case studies illustrating different approaches to manage overlap. Methods We first updated the search in PubMed for methods from the MOoR framework relating to overlap of primary studies. One author screened the studies titles and abstracts, and any full-text articles retrieved, extracted methods data relating to overlap of primary studies and mapped it to the overlap methods from the MOoR framework. We also describe six case studies as examples of overviews that use specific overlap methods across the steps in the conduct of an overview. For each case study, we discuss potential methodological implications in terms of limitations, efficiency, usability, and resource use. Results Nine methods studies were found and mapped to the methods identified by the MOoR framework to address overlap. Overlap methods were mapped across four steps in the conduct of an overview – the eligibility criteria step, the data extraction step, the assessment of risk of bias step, and the synthesis step. Our overview case studies used multiple methods to reduce overlap at different steps in the conduct of an overview. Conclusions Our study underlines that there is currently no standard methodological approach to deal with overlap in primary studies across reviews. The level of complexity when dealing with overlap can vary depending on the yield, trends and patterns of the included literature and the scope of the overview question. Choosing a method might be dependent on the number of included reviews and their primary studies. Gaps in evaluation of methods to address overlap were found and further investigation in this area is needed.

Background Stringent requirements exist regarding the transparency of the study selection process and the reliability of results. A 2-step selection process is generally recommended; this is conducted by 2 reviewers independently of each other (conventional double-screening). However, the approach is resource intensive, which can be a problem, as systematic reviews generally need to be completed within a defined period with a limited budget. The aim of the following methodological systematic review was to analyse the evidence available on whether single screening is equivalent to double screening in the screening process conducted in systematic reviews. Methods We searched Medline, PubMed and the Cochrane Methodology Register (last search 10/2018). We also used supplementary search techniques and sources (“similar articles” function in PubMed, conference abstracts and reference lists). We included all evaluations comparing single with double screening. Data were summarized in a structured, narrative way. Results The 4 evaluations included investigated a total of 23 single screenings (12 sets for screening involving 9 reviewers). The median proportion of missed studies was 5% (range 0 to 58%). The median proportion of missed studies was 3% for the 6 experienced reviewers (range: 0 to 21%) and 13% for the 3 reviewers with less experience (range: 0 to 58%). The impact of missing studies on the findings of meta-analyses had been reported in 2 evaluations for 7 single screenings including a total of 18,148 references. In 3 of these 7 single screenings – all conducted by the same reviewer (with less experience) – the findings would have changed substantially. The remaining 4 of these 7 screenings were conducted by experienced reviewers and the missing studies had no impact or a negligible on the findings of the meta-analyses. Conclusions Single screening of the titles and abstracts of studies retrieved in bibliographic searches is not equivalent to double screening, as substantially more studies are missed. However, in our opinion such an approach could still represent an appropriate methodological shortcut in rapid reviews, as long as it is conducted by an experienced reviewer. Further research on single screening is required, for instance, regarding factors influencing the number of studies missed.

Background A standard or consensus definition of a systematic review does not exist. Therefore, if there is no definition about a systematic review in secondary studies that analyse them or the definition is too broad, inappropriate studies might be included in such evidence synthesis. The aim of this study was to analyse the definition of a systematic review (SR) in health care literature, elements of the definitions that are used and to propose a starting point for an explicit and non-ambiguous SR definition. Methods We included overviews of systematic reviews (OSRs), meta-epidemiological studies and epidemiology textbooks. We extracted the definitions of SRs, as well as the inclusion and exclusion criteria that could indicate which definition of a SR the authors used. We extracted individual elements of SR definitions, categorised and quantified them. Results Among the 535 analysed sources of information, 188 (35%) provided a definition of a SR. The most commonly used reference points for the definitions of SRs were Cochrane and the PRISMA statement. We found 188 different elements of SR definitions and divided them into 14 categories. The highest number of SR definition elements was found in categories related to searching ( N  = 51), analysis/synthesis ( N  = 23), overall methods ( N  = 22), quality/bias/appraisal/validity ( N  = 22) and aim/question ( N  = 13). The same five categories were also the most commonly used combination of categories in the SR definitions. Conclusion Currently used definitions of SRs are vague and ambiguous, often using terms such as clear, explicit and systematic, without further elaboration. In this manuscript we propose a more specific definition of a systematic review, with the ultimate aim of motivating the research community to establish a clear and unambiguous definition of this type of research.

Background Sedentary lifestyle is a major risk factor for noncommunicable diseases such as cardiovascular diseases, cancer and diabetes. It has been estimated that approximately 3.2 million deaths each year are attributable to insufficient levels of physical activity. We evaluated the available evidence from Cochrane systematic reviews (CSRs) on the effectiveness of exercise/physical activity for various health outcomes. Methods Overview and meta-analysis. The Cochrane Library was searched from 01.01.2000 to issue 1, 2019. No language restrictions were imposed. Only CSRs of randomised controlled trials (RCTs) were included. Both healthy individuals, those at risk of a disease, and medically compromised patients of any age and gender were eligible. We evaluated any type of exercise or physical activity interventions; against any types of controls; and measuring any type of health-related outcome measures. The AMSTAR-2 tool for assessing the methodological quality of the included studies was utilised. Results Hundred and fifty CSRs met the inclusion criteria. There were 54 different conditions. Majority of CSRs were of high methodological quality. Hundred and thirty CSRs employed meta-analytic techniques and 20 did not. Limitations for studies were the most common reasons for downgrading the quality of the evidence. Based on 10 CSRs and 187 RCTs with 27,671 participants, there was a 13% reduction in mortality rates risk ratio (RR) 0.87 [95% confidence intervals (CI) 0.78 to 0.96]; I 2  = 26.6%, [prediction interval (PI) 0.70, 1.07], median effect size (MES) = 0.93 [interquartile range (IQR) 0.81, 1.00]. Data from 15 CSRs and 408 RCTs with 32,984 participants showed a small improvement in quality of life (QOL) standardised mean difference (SMD) 0.18 [95% CI 0.08, 0.28]; I 2  = 74.3%; PI -0.18, 0.53], MES = 0.20 [IQR 0.07, 0.39]. Subgroup analyses by the type of condition showed that the magnitude of effect size was the largest among patients with mental health conditions. Conclusion There is a plethora of CSRs evaluating the effectiveness of physical activity/exercise. The evidence suggests that physical activity/exercise reduces mortality rates and improves QOL with minimal or no safety concerns. Trial registration Registered in PROSPERO ( CRD42019120295 ) on 10th January 2019.

Background Our objective was to assess the frequency of data extraction errors and its potential impact on results in systematic reviews. Furthermore, we evaluated the effect of different extraction methods, reviewer characteristics and reviewer training on error rates and results. Methods We performed a systematic review of methodological literature in PubMed, Cochrane methodological registry, and by manual searches (12/2016). Studies were selected by two reviewers independently. Data were extracted in standardized tables by one reviewer and verified by a second. Results The analysis included six studies; four studies on extraction error frequency, one study comparing different reviewer extraction methods and two studies comparing different reviewer characteristics. We did not find a study on reviewer training. There was a high rate of extraction errors (up to 50%). Errors often had an influence on effect estimates. Different data extraction methods and reviewer characteristics had moderate effect on extraction error rates and effect estimates. Conclusion The evidence base for established standards of data extraction seems weak despite the high prevalence of extraction errors. More comparative studies are needed to get deeper insights into the influence of different extraction methods.

Background The surgeon volume-outcome relationship has been discussed for many years and its existence or nonexistence is of importance for various reasons. A lot of empirical work has been published on it. We aimed to summarize systematic reviews in order to present current evidence. Methods Medline, Embase, Cochrane database of systematic reviews (CDSR), and health technology assessment websites were searched up to October 2015 for systematic reviews on the surgeon volume-outcome relationship. Reviews were critically appraised, and results were extracted and synthesized by type of surgical procedure/condition. Results Thirty-two reviews reporting on 15 surgical procedures/conditions were included. Methodological quality of included systematic reviews assessed with the assessment of multiple systematic reviews (AMSTAR) was generally moderate to high albeit included literature partly neglected considering methodological issues specific to volume-outcome relationship. Most reviews tend to support the presence of a surgeon volume-outcome relationship. This is most clear-cut in colorectal cancer, bariatric surgery, and breast cancer where reviews of high quality show large effects. Conclusions When taking into account its limitations, this overview can serve as an informational basis for decision makers. Our results seem to support a positive volume-outcome relationship for most procedures/conditions. However, forthcoming reviews should pay more attention to methodology specific to volume-outcome relationship. Due to the lack of information, any numerical recommendations for minimum volume thresholds are not possible. Further research is needed for this issue.

Background Data extraction forms link systematic reviews with primary research and provide the foundation for appraising, analysing, summarising and interpreting a body of evidence. This makes their development, pilot testing and use a crucial part of the systematic reviews process. Several studies have shown that data extraction errors are frequent in systematic reviews, especially regarding outcome data. Methods We reviewed guidance on the development and pilot testing of data extraction forms and the data extraction process. We reviewed four types of sources: 1) methodological handbooks of systematic review organisations (SRO); 2) textbooks on conducting systematic reviews; 3) method documents from health technology assessment (HTA) agencies and 4) journal articles. HTA documents were retrieved in February 2019 and database searches conducted in December 2019. One author extracted the recommendations and a second author checked them for accuracy. Results are presented descriptively. Results Our analysis includes recommendations from 25 documents: 4 SRO handbooks, 11 textbooks, 5 HTA method documents and 5 journal articles. Across these sources the most common recommendations on form development are to use customized or adapted standardised extraction forms (14/25); provide detailed instructions on their use (10/25); ensure clear and consistent coding and response options (9/25); plan in advance which data are needed (9/25); obtain additional data if required (8/25); and link multiple reports of the same study (8/25). The most frequent recommendations on piloting extractions forms are that forms should be piloted on a sample of studies (18/25); and that data extractors should be trained in the use of the forms (7/25). The most frequent recommendations on data extraction are that extraction should be conducted by at least two people (17/25); that independent parallel extraction should be used (11/25); and that procedures to resolve disagreements between data extractors should be in place (14/25). Conclusions Overall, our results suggest a lack of comprehensiveness of recommendations. This may be particularly problematic for less experienced reviewers. Limitations of our method are the scoping nature of the review and that we did not analyse internal documents of health technology agencies.

Background When conducting an Overviews of Reviews on health-related topics, it is unclear which combination of bibliographic databases authors should use for searching for SRs. Our goal was to determine which databases included the most systematic reviews and identify an optimal database combination for searching systematic reviews. Methods A set of 86 Overviews of Reviews with 1219 included systematic reviews was extracted from a previous study. Inclusion of the systematic reviews was assessed in MEDLINE, CINAHL, Embase, Epistemonikos, PsycINFO, and TRIP. The mean inclusion rate (% of included systematic reviews) and corresponding 95% confidence interval were calculated for each database individually, as well as for combinations of MEDLINE with each other database and reference checking. Results Inclusion of systematic reviews was higher in MEDLINE than in any other single database (mean inclusion rate 89.7%; 95% confidence interval [89.0–90.3%]). Combined with reference checking, this value increased to 93.7% [93.2–94.2%]. The best combination of two databases plus reference checking consisted of MEDLINE and Epistemonikos (99.2% [99.0–99.3%]). Stratification by Health Technology Assessment reports (97.7% [96.5–98.9%]) vs. Cochrane Overviews (100.0%) vs. non-Cochrane Overviews (99.3% [99.1–99.4%]) showed that inclusion was only slightly lower for Health Technology Assessment reports. However, MEDLINE, Epistemonikos, and reference checking remained the best combination. Among the 10/1219 systematic reviews not identified by this combination, five were published as websites rather than journals, two were included in CINAHL and Embase, and one was included in the database ERIC. Conclusions MEDLINE and Epistemonikos, complemented by reference checking of included studies, is the best database combination to identify systematic reviews on health-related topics.