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      Prevalence of cognitive impairment following chemotherapy treatment for breast cancer: a systematic review and meta-analysis

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          Abstract

          Breast cancer survival rates have markedly improved. Consequently, survivorship issues have received increased attention. One common sequel of treatment is chemotherapy-induced cognitive impairment (CICI). CICI causes a range of impairments that can have a significant negative impact on quality of life. Knowledge of the prevalence of this condition is required to inform survivorship plans, and ensure adequate resource allocation and support is available for sufferers, hence a systematic review of prevalence data was performed. Medline, Scopus, CINAHL and PSYCHInfo were searched for eligible studies which included prevalence data on CICI, as ascertained though the use of self-report, or neuropsychological tests. Methodological quality of included studies was assessed. Findings were synthesised narratively, with meta-analyses being used to calculate pooled prevalence when impairment was assessed by neuropsychological tests. The review included 52 studies. Time-points considered ranged from the chemotherapy treatment period to greater than 10 years after treatment cessation. Summary prevalence figures (across time-points) using self-report, short cognitive screening tools and neuropsychological test batteries were 44%, 16% and 21–34% respectively (very low GRADE evidence). Synthesised findings demonstrate that 1 in 3 breast cancer survivors may have clinically significant cognitive impairment. Prevalence is higher when self-report based on patient experience is considered. This review highlights a number of study design issues that may have contributed to the low certainty rating of the evidence. Future studies should take a more consistent approach to the criteria used to assess impairment. Larger studies are urgently needed.

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          The PRISMA 2020 statement: an updated guideline for reporting systematic reviews

          The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.
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            Methodological guidance for systematic reviews of observational epidemiological studies reporting prevalence and cumulative incidence data.

            There currently does not exist guidance for authors aiming to undertake systematic reviews of observational epidemiological studies, such as those reporting prevalence and incidence information. These reviews are particularly useful to measure global disease burden and changes in disease over time. The aim of this article is to provide guidance for conducting these types of reviews.
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              Meta-analysis of prevalence.

              Meta-analysis is a method to obtain a weighted average of results from various studies. In addition to pooling effect sizes, meta-analysis can also be used to estimate disease frequencies, such as incidence and prevalence. In this article we present methods for the meta-analysis of prevalence. We discuss the logit and double arcsine transformations to stabilise the variance. We note the special situation of multiple category prevalence, and propose solutions to the problems that arise. We describe the implementation of these methods in the MetaXL software, and present a simulation study and the example of multiple sclerosis from the Global Burden of Disease 2010 project. We conclude that the double arcsine transformation is preferred over the logit, and that the MetaXL implementation of multiple category prevalence is an improvement in the methodology of the meta-analysis of prevalence.
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                Author and article information

                Contributors
                alexandra.whittaker@adelaide.edu.au
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                8 February 2022
                8 February 2022
                2022
                : 12
                : 2135
                Affiliations
                [1 ]GRID grid.1010.0, ISNI 0000 0004 1936 7304, School of Animal and Veterinary Sciences, , The University of Adelaide, ; Roseworthy Campus, Roseworthy, SA 5371 Australia
                [2 ]GRID grid.5379.8, ISNI 0000000121662407, Faculty of Biology, Medicine and Health, , University of Manchester, ; Manchester, UK
                [3 ]GRID grid.5379.8, ISNI 0000000121662407, Division of Dentistry, School of Medical Sciences, Manchester Academic Health Sciences Centre, , University of Manchester, ; Manchester, UK
                Article
                5682
                10.1038/s41598-022-05682-1
                8826852
                35136066
                f040afc2-7bc7-48f4-96fe-bbf3e4e52903
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 18 August 2021
                : 17 January 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000925, National Health and Medical Research Council;
                Award ID: (APP1140072).
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2022

                Uncategorized
                cancer,cognitive neuroscience
                Uncategorized
                cancer, cognitive neuroscience

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