“…After deduplication 199 remained, and after screening abstracts and full text, seven were included [ 17 – 19 , 28 – 31 ]. One additional conference citation was found through expert knowledge on the topic [ 32 ], and one paper recently published was included after completion of the first draft [ 33 ]. Fig.…”
“…Smaller citation matrices by outcome can be developed, which will aid in determining if overlap is an issue at the outcome level. More sophisticated methods to present overlap to the readers can be found in Bougioukas and colleagues [ 33 ], such as upset plots, heatmaps and node-link graphs for visualizing overlap.…”
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.
“…After deduplication 199 remained, and after screening abstracts and full text, seven were included [ 17 – 19 , 28 – 31 ]. One additional conference citation was found through expert knowledge on the topic [ 32 ], and one paper recently published was included after completion of the first draft [ 33 ]. Fig.…”
“…Smaller citation matrices by outcome can be developed, which will aid in determining if overlap is an issue at the outcome level. More sophisticated methods to present overlap to the readers can be found in Bougioukas and colleagues [ 33 ], such as upset plots, heatmaps and node-link graphs for visualizing overlap.…”
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.
“…Components that yielded eigenvalues exceeding 1.00 were considered important factors. Moreover, we also drew an Upset plot for overlapping psychotic comorbidities in the same cluster PDs [ 18 ]. All analyses were conducted with SAS 9.4 software (SAS Institute Inc., Cary, NC, USA).…”
Personality disorders (PDs) are grouped into clusters A, B, and C. However, whether the three clusters of PDs have differences in comorbid mental disorders or gender distribution is still lacking sufficient evidence. We aim to investigate the distribution pattern across the three clusters of PDs with a population-based cohort study. This study used the Taiwan national database between 1995 and 2013 to examine the data of patients with cluster A PDs, cluster B PDs, or cluster C PDs. We compared the differences of psychiatric comorbidities classified in the Diagnostic and Statistical Manual of Mental Disorders, fifth edition across the three clusters of PDs. Moreover, we formed gender subgroups of the three PDs to observe the discrepancy between male and female. Among the 9845 patients, those with cluster A PDs had the highest proportion of neurodevelopmental disorders, schizophrenia and neurocognitive disorders, those with cluster B PDs demonstrated the largest percentage of bipolar disorders, trauma and stressor disorders, feeding and eating disorders, and substance and addictive disorders, and those with cluster C PDs had the greatest proportion of depressive disorders, anxiety disorders, obsessive–compulsive disorders, somatic symptom disorders, and sleep–wake disorders. The gender subgroups revealed significant male predominance in neurodevelopmental disorders and female predominance in sleep–wake disorders across all three clusters of PDs. Our findings support that some psychiatric comorbidities are more prevalent in specified cluster PDs and that gender differences exist across the three clusters of PDs. These results are an important reference for clinicians who are developing services that target real-world patients with PDs.
“…A descriptive analysis will be performed and the extent of overlapping among systematic reviews and meta-analyses will be estimated applying the corrected covered area and will be presented using novel graphical approaches. 19 When a systematic review and a meta-analysis addressing the same outcome will be identified, data from the meta-analysis will be reported, provided that the meta-analysis includes more primary studies. Similarly, when a systematic review or a meta-analysis and a network meta-analysis addressing the same outcome will be identified, data from the network meta-analysis will be reported, provided that the network meta-analysis includes more primary studies.…”
IntroductionPhosphodiesterase-type 5 inhibitors (PDE5i) are the recommended first-line treatment for erectile dysfunction. Previous systematic reviews and meta-analyses suggest that they are a safe and effective option in many patient groups. Similarly, PDE5i may be effective as part of combination therapy in non-responders to PDE5i. We will generate an overview of systematic reviews, meta-analyses and network meta-analyses aiming to summarise the available knowledge regarding the efficacy and safety of PDE5i in the general population and in multiple subgroups of patients.Methods and analysisThis overview was designed in accordance with the PRIO-harms and Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols guidelines and its protocol was registered at PROSPERO. We will systematically search PubMed, Web of Science, Cochrane Library and Scopus databases from inception to November 2020 without any language restrictions. We will include systematic reviews or meta-analyses: (1) comparing the efficacy and safety of any dose of PDE5i with each other, with placebo or with other effective treatments for the management of erectile function; (2) exploring the use of any PDE5i alone or in combination with other treatment modalities in the general male population or in specific subgroups and (3) conducted with systematic procedures. Our overview will employ the AMSTAR 2 tool to evaluate the quality of the included studies and the Grading of Recommendations Assessment, Development and Evaluation approach to assess the strength of evidence for all outcomes. We will construct forest plots of risk estimates with the corresponding CI for all outcomes.Ethics and disseminationIn this overview, we will undertake an extensive literature search in an attempt to evaluate the potential benefits and risks of treatment with one PDE5i versus another or versus placebo and provide recommendations for clinicians and policy-makers. No ethical approval is required.PROSPERO registration numberCRD42020216754.
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