Cochrane Evidence Synthesis and Methods最新文献

{"title":"Multiple Long-Term Conditions, Co-Long-Term Conditions and Polyvascular Disease: Considerations for Evidence Synthesis and Meta-Analyses","authors":"Gillian Mead,&nbsp;Alex Todhunter-Brown,&nbsp;Ukachukwu Abaraogu,&nbsp;Amanda Barugh,&nbsp;Arohi Chauhan,&nbsp;Juan Erviti Lopez,&nbsp;Valery Feigin,&nbsp;Jaya Singh Kshatri,&nbsp;Atsushi Mizuno,&nbsp;Sanghamitra Pati,&nbsp;Jackie Price,&nbsp;Rui Providência,&nbsp;Gerry Stansby,&nbsp;Rod Taylor,&nbsp;David J. Williams,&nbsp;James M. Wright,&nbsp;Simiao Wu,&nbsp;Leon Flicker","doi":"10.1002/cesm.70027","DOIUrl":"https://doi.org/10.1002/cesm.70027","url":null,"abstract":"<p>Cochrane's scientific strategy for 2025 to 2030 has four research priorities, including improving the lives of people living with multiple chronic conditions. The purpose of this article written by the Cochrane Thematic Group in Heart, Stroke and Circulation is to explore considerations around multiple chronic conditions (also referred to as ‘multiple long-term conditions’ i.e. two or more long-term conditions) in systematic reviews. Rather than using the term ‘comorbidity’, we introduce a new term ‘co-long-term conditions’. We also explore how to define ‘polyvascular disease’. We suggest that review authors consider co-long-term conditions and multiple long-term conditions in their reviews e.g. extract data about how primary studies address co-long-term conditions, perform subgroup analyses according to presence or not of co-long-term conditions, and include a section in the discussion about how well participants with co-long-term conditions were represented in the primary studies. This is especially pertinent for reviews addressing heart, circulatory or stroke disease, and polyvascular disease.</p>","PeriodicalId":100286,"journal":{"name":"Cochrane Evidence Synthesis and Methods","volume":"3 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cesm.70027","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143769980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cochrane's COVID-19 Living Systematic Reviews: A Mixed-Methods Study of Their Conduct, Reporting and Currency","authors":"Kevindu De Silva,&nbsp;Tari Turner,&nbsp;Steve McDonald","doi":"10.1002/cesm.70024","DOIUrl":"https://doi.org/10.1002/cesm.70024","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Living systematic reviews (LSRs) should provide up-to-date evidence for priority questions where the evidence may be uncertain and fast-moving. LSRs featured prominently during COVID-19 and formed part of Cochrane's response to the pandemic. We conducted a mixed-methods study to describe the characteristics of Cochrane's COVID-19 living reviews, determine the currency of the included evidence, and evaluate authors' experiences in conducting and publishing these reviews.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We identified living reviews of COVID-19 from the <i>Cochrane Database of Systematic Reviews</i> and extracted data on the number of versions published and publication timelines. We assessed the currency of evidence by comparing studies included in the reviews against a comprehensive list of studies maintained for the Australian living guidelines for COVID-19. The qualitative component involved semi-structured interviews with review authors to identify the barriers and enablers to conducting, reporting and publishing living reviews.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Cochrane published 25 COVID-19 living systematic reviews. Half of these reviews had not been updated when assessed in June 2023 and only four had been updated more than once. A total of 118 studies were included in the living reviews. We estimated that an additional 119 studies were available and potentially relevant for inclusion. Interviews with six authors indicated that publication timelines were reduced by editorial delays, loss of funding, waning commitment, and the burden of screening search results. An inability to communicate the living status of reviews in the Cochrane Library was a common frustration for many authors. Although authors felt the conclusions of their reviews were still current, only one living review communicated its updated status and made new evidence accessible after the review was published.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Maintaining and communicating the currency of Cochrane's COVID-19 living systematic reviews was not feasible for many author teams because of author-side, editorial and platform barriers.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100286,"journal":{"name":"Cochrane Evidence Synthesis and Methods","volume":"3 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cesm.70024","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143717433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Certainty of evidence assessment in high-impact medical journals: A meta-epidemiological survey","authors":"Madelin R. Siedler,&nbsp;Neha Tangri,&nbsp;Leena AlShenaiber,&nbsp;Tejanth Pasumarthi,&nbsp;Faisal Shaukat Ali,&nbsp;Volf Gaby,&nbsp;Katie N. Harris,&nbsp;Yngve Falck-Ytter,&nbsp;Reem A. Mustafa,&nbsp;Shahnaz Sultan,&nbsp;Philipp Dahm,&nbsp;M. Hassan Murad,&nbsp;Rebecca L. Morgan","doi":"10.1002/cesm.70014","DOIUrl":"https://doi.org/10.1002/cesm.70014","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>While certainty of evidence assessment is key to a rigorous and transparent systematic review, it is unknown how – and how frequently – it is assessed in systematic reviews. The objective of this study was to examine the prevalence and approaches used for certainty of evidence assessment in systematic reviews published in high-impact medicine journals over the past 11 years.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A PubMed search and hand-searching of relevant journal websites identified systematic reviews published between 24 January 2013 and 23 January 2024 in any of the ten highest-impact journals in the General and Internal Medicine category of the Journal Citation Report. Two reviewers independently selected any systematic review related to health outcomes assessing certainty of evidence using any method. We extracted data related to review characteristics, certainty of evidence and risk of bias/methodological quality assessment frameworks, and reported consideration of certainty of evidence domains. Logistic regression examined year of publication to determine whether the prevalence of certainty of evidence assessment changed over time.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Of 1,023 included reviews, 346 (33.8%) assessed certainty of evidence. Prevalence of certainty of evidence assessment increased over time (0.16 ± 0.2; <i>p</i> &lt; .001). Most (89.3%) of reviews used the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework to assess certainty of evidence.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Only one in three systematic reviews published in the highest-impact medical journals over the past 11 years assessed certainty of evidence, though prevalence increased over time. The use of specific domains within each certainty of evidence framework was not clearly described in all reviews.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100286,"journal":{"name":"Cochrane Evidence Synthesis and Methods","volume":"3 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cesm.70014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143688888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coproducing a Cochrane Qualitative Evidence Synthesis: Process, Outcomes, and Reflections on Power","authors":"Bronwen Merner,&nbsp;Rebecca Ryan","doi":"10.1002/cesm.70025","DOIUrl":"https://doi.org/10.1002/cesm.70025","url":null,"abstract":"<p>Reflecting a broader movement toward knowledge democratization, coproducing Cochrane evidence with interest holders outside universities is increasingly encouraged. However, only limited research exists on the approaches used to coproduce Cochrane reviews. Furthermore, the outcomes of coproduction are rarely described. In this commentary, we aim to address these gaps by describing the process and outcomes of coproduction used in a recently published Cochrane qualitative evidence synthesis (QES). We also reflect on power imbalances in our coproduction approach and how these could be minimized in future review coproduction activities.</p>","PeriodicalId":100286,"journal":{"name":"Cochrane Evidence Synthesis and Methods","volume":"3 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cesm.70025","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143645809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Count data, rates, rate differences, and rate ratios in meta-analysis: A tutorial","authors":"Christopher James Rose,&nbsp;Milena Geist,&nbsp;Matteo Bruschettini","doi":"10.1002/cesm.70022","DOIUrl":"https://doi.org/10.1002/cesm.70022","url":null,"abstract":"<p>This tutorial focuses on trials that assess outcomes by counting events that can occur zero, one, or more than one time in each participant. Trials and meta-analyses can estimate treatment effects for count outcomes using rate differences or rate ratios. We explain why it may be appropriate to meta-analyze count data to estimate rate ratios rather than odds ratios, risk ratios, or risk differences. We explain what count data are, how trials may estimate treatment effects, how to interpret such estimates, and how to extract data from trials that use count outcomes for meta-analysis. Finally, we discuss some common misunderstandings and subtleties. Supplementary materials include an Excel file for performing calculations, mathematical background, and additional advice.</p>","PeriodicalId":100286,"journal":{"name":"Cochrane Evidence Synthesis and Methods","volume":"3 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cesm.70022","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143513860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Common statistical errors in systematic reviews: A tutorial","authors":"Afroditi Kanellopoulou,&nbsp;Kerry Dwan,&nbsp;Rachel Richardson","doi":"10.1002/cesm.70013","DOIUrl":"https://doi.org/10.1002/cesm.70013","url":null,"abstract":"<p>The aim of this article is to present the most common statistical errors in meta-analyses included in systematic reviews; these are confusing standard deviation and standard error, using heterogeneity estimators for choosing between a common-effect and random-effects model, improper handling of multiarm trials, and unnecessary and misinterpreted subgroup analyses. We introduce some useful terminology and explain what authors can do to avoid these errors and how peer reviewers can spot them. We have also developed a micro-learning module to provide practical hands-on tutorial.</p>","PeriodicalId":100286,"journal":{"name":"Cochrane Evidence Synthesis and Methods","volume":"3 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cesm.70013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143120601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Incorporating uncertainty in the baseline risk: An R Shiny tool and an empirical study","authors":"M. Hassan Murad,&nbsp;Lifeng Lin","doi":"10.1002/cesm.70018","DOIUrl":"https://doi.org/10.1002/cesm.70018","url":null,"abstract":"<p>The common practice in meta-analysis and clinical practice guidelines is to derive the absolute treatment effect (also called risk difference, RD) from a combination of a pooled relative risk (RR) that resulted from a meta-analysis, and a user-provided baseline risk (BR). However, this method does not address the uncertainty in BR. We developed a web-based R Shiny tool to perform simple microsimulation and incorporate uncertainty in BR into the precision of RD. We empirically evaluated this approach by estimating the impact of incorporating this uncertainty when BR is derived from the control group rates in 3,128 meta-analyses curated from the Cochrane Library (26,964 individual studies). When BR was derived from the largest study in each meta-analysis, the median width of the CI of BR was 11.6% (interquartile range (IQR), 6.30%–18.5%). Incorporating this uncertainty in BR led to expansion of the RD CI by a median of 8 per 1,000 persons (IQR 2–24). This expansion increased in a linear fashion with BR imprecision and was more prominent in meta-analyses with low BR. This study provides a web-based tool to perform simple microsimulation and incorporate uncertainty in BR into the CI of RD.</p>","PeriodicalId":100286,"journal":{"name":"Cochrane Evidence Synthesis and Methods","volume":"3 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cesm.70018","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143120134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single-arm interventional versus observational studies for assessing efficacy: A meta-epidemiological study","authors":"Mary Chappell,&nbsp;Deborah Watkins,&nbsp;Alice Sanderson,&nbsp;Lavinia Ferrante di Ruffano,&nbsp;Paul Miller,&nbsp;Hariet Fewster,&nbsp;Anita Fitzgerald,&nbsp;Mary Edwards,&nbsp;Rachael McCool","doi":"10.1002/cesm.70016","DOIUrl":"https://doi.org/10.1002/cesm.70016","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Interventional single-arm trials (SATs) are increasingly being used as evidence, despite a lack of agreement on their validity and where they should sit in the hierarchy of evidence. We conducted a meta-epidemiological study to investigate whether there are systematic differences in outcomes and levels of between-study heterogeneity for SATs compared with their observational counterpart, single-arm cohort studies.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We identified systematic reviews (SRs) of pharmacological interventions, published in 2023, that included both interventional and observational single-arm studies. For each SR, subgroup meta-analysis of dichotomous outcomes was conducted for included SATs and single-arm cohort studies to assess effect sizes, levels of heterogeneity and between group differences. In a sensitivity analysis, clinically heterogeneous primary studies were removed and analyses re-run.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>66 SRs contained single-arm studies, of which 13 reported meta-analyses of dichotomous efficacy outcomes. There was no overall risk difference for SATs compared with single-arm cohort studies (risk difference: −0.020, 95% CI: −0.092 to 0.052, <i>p</i> = 0.59). In the sensitivity analysis, there was a tendency to higher effect for single-arm cohort studies, but no significant difference (risk difference: −0.071, 95% CI: −0.161, 0.019, <i>p</i> = 0.12). There were high levels of between-study heterogeneity within both SATs (median; range <i>I</i>²: 54.8; 11.3–91.0) and single-arm cohorts (median; range <i>I</i>²: 77.2; 0–94.7) and heterogeneity remained high in the sensitivity analysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>There do not appear to be systematic differences in outcome between SATs and single-arm cohort studies, but further research is recommended to confirm this finding. Levels of heterogeneity are high within both designs, even after attempts to reduce clinical heterogeneity. Because clinical heterogeneity had potentially been removed, remaining statistical heterogeneity may have been due to bias related to study conduct. Future work should utilize larger samples and additional methods to further clarify the relative validity of single-arm designs.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100286,"journal":{"name":"Cochrane Evidence Synthesis and Methods","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cesm.70016","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143115215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Can using the Cochrane RCT classifier in EPPI-Reviewer help speed up study selection in qualitative evidence syntheses? A retrospective evaluation","authors":"Heather Melanie R. Ames,&nbsp;Christine Hillestad Hestevik,&nbsp;Patricia Sofia Jacobsen Jardim,&nbsp;Martin Smådal Larsen,&nbsp;Lars Jørun Langøien,&nbsp;Hans Bugge Bergsund,&nbsp;Tiril Cecilie Borge","doi":"10.1002/cesm.70012","DOIUrl":"https://doi.org/10.1002/cesm.70012","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Using machine learning functions, such as study design classifiers, to automatically identify studies that do not meet the inclusion criteria, is one way to speed up the systematic review screening process. As a qualitative study design classifier is yet to be developed, using the Cochrane randomized controlled trial (RCT) classifier in reverse is one possible way to speed up the identification of primary qualitative studies during screening. The objective of this study was to evaluate whether the Cochrane RCT classifier can be used to speed up the study selection process for qualitative evidence synthesis (QES).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We performed a retrospective evaluation where we first identified QES. We then extracted the bibliographic information of the included primary qualitative studies in each QES, and uploaded the references into our data management tool, EPPI-Reviewer. We then ran the Cochrane RCT classifier on each group of included studies for each QES.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Eighty-two QES with 2828 unique primary studies were included in the analysis. 56% of the primary studies were classified as unlikely to be an RCT and 40% as being 0–9% likely to be an RCT. 4% were classified as being 10% or more likely to be an RCT. Of these, only 1.7% were classified as being 50% or more likely to be an RCT.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The Cochrane RCT classifier could be a useful tool to identify primary studies with qualitative study designs to speed up study selection in a QES. However, it is possible that mixed methods studies or qualitative studies conducted as part of a clinical trial may be missed. Further evaluations using the Cochrane RCT classifier on all the references retrieved from the complete literature search is needed to investigate time- and resource savings.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100286,"journal":{"name":"Cochrane Evidence Synthesis and Methods","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cesm.70012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143114777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Inclusion, characteristics and methodological limitations of systematic reviews in doctoral theses: A cross-sectional study of all universities in Sweden","authors":"M. Ringsten,&nbsp;K. Färnqvist,&nbsp;M. Bruschettini,&nbsp;M. Johansson","doi":"10.1002/cesm.70015","DOIUrl":"https://doi.org/10.1002/cesm.70015","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Intro</h3>\u0000 \u0000 <p>A systematic review (SR) attempts to find, assess and summarize all the empirical evidence to answer a specific research question. We aim to explore to what extent reviews are included in doctoral theses from all universities with a medical faculty in Sweden, and to describe the type, topic and assess the methodological quality of the reviews.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Duplicate assessors independently searched local and national repositories for doctoral theses published in 2021 within all seven medical faculties in Sweden, and categorized identified reviews based on review type, topic, and methodological quality using AMSTAR-2.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>5.4% (45/852) of all doctoral theses included a review, and 1.3% (45/3461) of all included studies were reviews. Of these, two thirds (31) were SRs and the rest (14) were broader ‘big picture’ reviews. The most common topics were interventions (42%) and exposure/etiology (32%), with no reviews of diagnostic tests. The majority of the SRs had very low (71%) or low (19%) quality, and few reached a high (7%) or moderate (3%) quality. The most common issues were limitations with protocols, limited search strategies, and failure to account for risk of bias in drawn conclusions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Few doctoral students included SRs in their theses, and the few SRs included in doctoral theses generally had a low quality. There is no consensus on the appropriate proportion of doctoral thesis including a SR. We argue that conducting a SR within a doctoral thesis can reduce redundant, harmful and unethical research, identify knowledge gaps, and help the doctoral student obtain important skills to conduct and use research.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100286,"journal":{"name":"Cochrane Evidence Synthesis and Methods","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cesm.70015","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143113480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}