Overlap of primary studies among systematic reviews (SRs) is one of the main methodological challenges when conducting overviews. If not assessed properly, overlapped primary studies may mislead findings, since they may have a major influence either in qualitative analyses or in statistical weight. Moreover, overlapping SRs may represent the existence of duplicated efforts. Matrices of evidence and the calculation of the overall corrected covered area (CCA) are appropriate methods to address this issue, but they seem to be not comprehensive enough. In this article we present Graphical Representation of Overlap for OVErviews (GROOVE), an easy‐to‐use tool for overview authors. Starting from a matrix of evidence, GROOVE provides the number of included primary studies and SRs included in the matrix; the absolute number of overlapped and non‐overlapped primary studies; and an overall CCA assessment. The tool also provides a detailed CCA assessment for each possible pair of SRs (or “nodes”), with a graphical and easy‐to‐read representation of these results. Additionally, it includes an advanced optional usage, incorporating structural missingness in the matrix. In this article, we show the details about how to use GROOVE, what results it achieves and how the tool obtains these results. GROOVE is intended to improve the overlap assessment by making it easier, faster, and more friendly for both authors and readers. The tool is freely available at http://doi.org/10.17605/OSF.IO/U2MS4 and https://es.cochrane.org/es/groovetool

Introduction: Evidence about coronavirus disease 2019 (COVID‐19) and pregnancy has rapidly increased since December 2019, making it difficult to make rigorous evidence‐based decisions. The objective of this overview of systematic reviews is to conduct a comprehensive analysis of the current evidence on prognosis of COVID‐19 in pregnant women.Material and methods: We used the Living OVerview of Evidence (L·OVE) platform for COVID‐19, which continually retrieves studies from 46 data sources (including PubMed/MEDLINE, Embase, other electronic databases, clinical trials registries, and preprint repositories, among other sources relevant to COVID‐19), mapping them into PICO (population, intervention, control, and outcomes) questions. The search covered the period from the inception date of each database to 13 September 2020. We included systematic reviews assessing outcomes of pregnant women with COVID‐19 and/or their newborns. Two authors independently screened the titles and abstracts, assessed full texts to select the studies that met the inclusion criteria, extracted data, and appraised the risk of bias of each included systematic review. We measured the overlap of primary studies included among the selected systematic reviews by building a matrix of evidence, calculating the corrected covered area, and assessing the level of overlap for every pair of systematic reviews.Results: Our search yielded 1132 references. 52 systematic reviews met inclusion criteria and were included in this overview. Only one review had a low risk of bias, three had an unclear risk of bias, and 48 had a high risk of bias. Most of the included reviews were highly overlapped among each other. In the included reviews, rates of maternal death varied from 0% to 11.1%, admission to intensive care from 2.1% to 28.5%, preterm deliveries before 37 weeks from 14.3% to 61.2%, and cesarean delivery from 48.3% to 100%. Regarding neonatal outcomes, neonatal death varied from 0% to 11.7% and the estimated infection status of the newborn varied between 0% and 11.5%.Conclusions: Only one of 52 systematic reviews had a low risk of bias. Results were heterogeneous and the overlap of primary studies was frequently very high between pairs of systematic reviews. High‐quality evidence syntheses of comparative studies are needed to guide future clinical decisions.

To study the impact of lack of blinding of outcome assessors on estimated treatment effects of randomized clinical trials. Meta-epidemiological study. We included randomized trials with binary or measurement scale outcomes that (1) allocated patients to subtrials with and without blinded outcome assessment, or (2) had both blinded and non-blinded assessments of the same outcome. We identified trials from previous meta-epidemiological studies and searched six databases from 2013 to 2024. We calculated a ratio of odds ratios (ROR) for each trial. A ROR < 1 indicated a more favorable effect estimate by the non-blinded assessor. We pooled RORs using random effects meta-analysis and conducted meta-regression, subgroup, and sensitivity analyses. We included 66 trials (9451 patients) across 18 clinical specialties. The pooled RORs in 43 trials (7055 patients) was 0.71 (0.55-0.92). Thirty of the 43 trials assessed highly subjective outcomes. Meta-regression showed no statistically significant association between ROR and scores for outcome subjectivity (P = .53), vulnerability (P = .91), and involvement (P = .99). Heterogeneity was partly explained by a larger impact in non-drug trials, ROR 0.62 (0.46-0.84), and industry-funded trials, ROR 0.57 (0.37-0.88). Sensitivity analyses, including imputed data for 23 trials (2396 patients randomized), did not modify the observed impact importantly. We provide empirical evidence of considerable bias in effect estimates of randomized trials with non-blinded assessors of subjective binary and measurement scale outcomes. Non-blinded assessors exaggerated effect estimates, expressed as odds ratios, by 29% (8%-45%) on average. This strongly supports blinding outcome assessors of subjective outcomes. In a randomized clinical trial, the person evaluating the results (assessor) may be either unaware of the intervention received by participants (blinded assessor) or aware of it (non-blinded assessor). Knowing which treatment a patient received can influence the assessor's evaluation of the effect; for example, if an assessor has high expectations for a new experimental intervention, they may rate a patient's improvement more favorably in the group that received the intervention compared to the group that did not. We call this observer bias. In this study, we compared the results obtained from blinded assessors to those from non-blinded assessors within the same trials to estimate the impact of observer bias in randomized trials. We found that non-blinded assessors exaggerated the experimental intervention effect by approximately 29%, on average, compared to blinded assessors. Our results indicate that when an evaluation of a patient in a randomized trial requires judgment, there is potential for substantial bias if assessors are not blinded. To ensure more reliable results, randomized clinical trials should blind assessors whenever possible.

Purpose: Clinical guidelines’ (CGs) adherence supports high-quality care. However, healthcare providers do not always comply with CGs recommendations. This systematic literature review aims to assess the extent of healthcare providers’ adherence to breast cancer CGs in Europe and to identify the factors that impact on healthcare providers’ adherence. Methods: We searched for systematic reviews and quantitative or qualitative primary studies in MEDLINE and Embase up to May 2019. The eligibility assessment, data extraction, and risk of bias assessment were conducted by one author and cross-checked by a second author. We conducted a narrative synthesis attending to the modality of the healthcare process, methods to measure adherence, the scope of the CGs, and population characteristics. Results: Out of 8137 references, we included 41 primary studies conducted in eight European countries. Most followed a retrospective cohort design (19/41; 46%) and were at low or moderate risk of bias. Adherence for overall breast cancer care process (from diagnosis to follow-up) ranged from 54 to 69%; for overall treatment process [including surgery, chemotherapy (CT), endocrine therapy (ET), and radiotherapy (RT)] the median adherence was 57.5% (interquartile range (IQR) 38.8–67.3%), while for systemic therapy (CT and ET) it was 76% (IQR 68–77%). The median adherence for the processes assessed individually was higher, ranging from 74% (IQR 10–80%), for the follow-up, to 90% (IQR 87–92.5%) for ET. Internal factors that potentially impact on healthcare providers’ adherence were their perceptions, preferences, lack of knowledge, or intentional decisions. Conclusions: A substantial proportion of breast cancer patients are not receiving CGs-recommended care. Healthcare providers’ adherence to breast cancer CGs in Europe has room for improvement in almost all care processes. CGs development and implementation processes should address the main factors that influence healthcare providers' adherence, especially patient-related ones. Registration: PROSPERO (CRD42018092884).

The exponential growth of currently available evidence has made it necessary to collect, filter, critically appraise, and synthesize biomedical information to keep up to date. In this sense, sys-tematic reviews are a helpful tool and can be reliable sources to assist in evidence- based decision-making. Systematic reviews are secondary research or syntheses of evidence focused on a specific question that --based on a structured methodology --make it possible to identify, select, critically appraise, and summarize findings from relevant studies. Systematic reviews have sev-eral potential advantages, such as minimizing biases or obtaining more accurate results. The reliability of the evidence presented in systematic reviews is determined, amongst other factors, by the quality of their methodology and the included studies. To conduct a systematic review, a series of steps must be followed: the formulation of a research question using the participants, interventions, comparisons, outcomes (PICO) format; an exhaustive literature search; the selec-tion of relevant studies; the critical appraisal of the data obtained from the included studies; the synthesis of results, often using statistical methods (meta-analysis); and finally, estimating the certainty of the evidence for each outcome. In this methodological note, we will define the basic concepts of systematic reviews, their methods, and their limitations.