Cochrane Back Review Group Risk of Bias Tool
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Evaluation of the Cochrane tool for assessing take a chance of bias in randomized clinical trials: overview of published comments and analysis of user exercise in Cochrane and not-Cochrane reviews
Systematic Reviews volume 5, Commodity number:80 (2016) Cite this article
Abstract
Background
The Cochrane risk of bias tool for randomized clinical trials was introduced in 2008 and has frequently been commented on and used in systematic reviews. We wanted to evaluate the tool past reviewing published comments on its strengths and challenges and by describing and analysing how the tool is applied to both Cochrane and non-Cochrane systematic reviews.
Methods
A review of published comments (searches in PubMed, The Cochrane Methodology Register and Google Scholar) and an observational study (100 Cochrane and 100 non-Cochrane reviews from 2014).
Results
Our review included 68 comments, 15 of which were categorised equally major. The main strengths of the tool were considered to exist its aim (to assess trial conduct and not reporting), its developmental basis (wide consultation, empirical and theoretical evidence) and its transparent procedures. The challenges of the tool were mainly considered to be its pick of core bias domains (e.yard. not involving funding/conflicts of involvement) and bug to do with implementation (i.e. modest inter-rater understanding) and terminology. Our observational written report found that the tool was used in all Cochrane reviews (100/100) and was the preferred tool in non-Cochrane reviews (31/100). Both types of reviews frequently implemented the tool in not-recommended means. Nearly Cochrane reviews planned to use risk of bias assessments as ground for sensitivity analyses (70 %), simply only a minority conducted such analyses (xix %) because, in many cases, few trials were assessed as having "depression" risk of bias for all standard domains (6 %). The sentence of at to the lowest degree i gamble of bias domain as "unclear" was found in 89 % of included randomized clinical trials (1103/1242).
Conclusions
The Cochrane tool has get the standard approach to assess risk of bias in randomized clinical trials simply is frequently implemented in a not-recommended way. Based on published comments and how it is applied in practice in systematic reviews, the tool may exist further improved by a revised structure and more focused guidance.
Peer Review reports
Background
Since the early 1990s, the number of published systematic reviews of randomized trials, both Cochrane and not-Cochrane reviews, has steadily increased. The ideal of taking a systematic approach to identify, summarise and analyse comparable clinical trials as a basis for therapeutic decisions has become more widespread, and systematic reviews have had a huge affect on clinical enquiry and practise.
However, i obstacle to the usefulness of a systematic review is the possibility that some of the included trials are biased due to flaws in their design, conduct, analysis or reporting. A meta-analysis of biased effect estimates will probable produce a biased pooled analysis with increased precision and greater credibility. Thus, for authors of a systematic review, information technology is paramount to fairly address the risk of bias in the included trials [1].
For this purpose, the Cochrane tool for assessing hazard of bias in randomized clinical trials (i.due east. the tool) was released in 2008 and updated in 2011. The tool is based on 7 bias domains: sequence generation and allocation darkening (both within the domain of choice bias or allocation bias), blinding of participants and personnel (performance bias), blinding of outcome assessors (detection bias), incomplete outcome information (attrition bias), selective reporting (reporting bias) and an auxiliary domain: "other bias." For each bias domain, the tool urges users to assign a judgement of "loftier," "low" or "unclear" risk of bias and to document the basis for their judgements (e.chiliad. with verbatim quotes). The bias domains of the tool were selected with the intention to encompass all key bias mechanisms in randomized trials [two].
Several years have passed since the release of the offset version of the tool. Over this period, the tool has been used in numerous systematic reviews, the scientific debate on chance of bias has proceeded (for example, reflecting on the function of source of funding [3–6] or other "meta-biases" [7]) and research publications have analysed user feel [8] and inter-agreement rates [nine–11]. Additionally, a complementary tool for assessing non-randomized trials has been developed [12].
Researchers from the original evolution team and members of the Cochrane Bias Methods Grouping are planning a revision of the tool. To evaluate the tool and to provide a better footing for the revision, nosotros intended (ane) to identify, summarise and analyse published comments on the strengths and challenges of the tool and (2) to depict and analyse how the tool is used in both Cochrane and non-Cochrane reviews.
Methods
This written report involved a review of published comments on the Cochrane tool for assessing take a chance of bias in randomized clinical trials and an observational study of how the tool is used in systematic reviews (please refer to Additional file 1 for the report's PRISMA checklist).
Review of published comments
We sought publications that explicitly commented on the tool. We divers "major comments" as longer comments with a substantial reflection (typically ≥100 words of text) on the strengths or weaknesses of the tool, for example, in the form of an editorial. We likewise included "pocket-size comments," which we defined every bit shorter comments without a substantial reflection (typically <100 words of text) on the strengths or weaknesses of the tool, for case, in the form of modest elements of a discussion in a publication. We excluded "peripheral remarks" on the tool, which we defined every bit remarks that were implicit or curt and tangential. If an author had several publications included with similar comment contents, only the publication with the most detailed annotate was considered major.
Nosotros searched PubMed, The Cochrane Methodology Register and Google Scholar for publications from the start of 2008 to the stop of 2014. No language restriction was applied, and Google Interpret was used for not-familiar languages. The search strategy was adult iteratively (see Additional file ii).
Ane author (LJ) decided on inclusion of publications and categorised them as "major comments" and "small-scale comments" (and "peripheral remarks"). A second writer (Equally) checked the categorisation. 2 authors (LJ and Equally) extracted data independently. Whatever disagreements were solved by give-and-take and by consulting a tertiary author (DL or AH).
The following information was extracted: publication year, publication blazon, tool version considered (i.eastward. 2008 or 2011) and the exact wording of the annotate.
Comments from the included publications were categorised according to whether they expressed "strengths," "challenges" or "suggestions" and summarised into broader themes (each addressing a similar type of topic). Nosotros noted the numerical distribution of comparable comments, only our main intention was a qualitative mapping of the themes addressed and a categorisation according to whether they addressed a core design feature of the tool or an issue related to implementation.
Observational study of how the tool is used in systematic reviews
One author (DL) identified 100 Cochrane reviews (or Cochrane review updates) from PubMed in reverse chronological club from 31.12.2014 until 20.11.2014 (encounter Additional file ii). The same author manually identified 100 non-Cochrane reviews from PubMed in reverse chronological club from 31.12.2014 until 22.12.2014. A 2d author (AS) checked the inclusion. Nosotros defined a non-Cochrane review as a self-alleged systematic review with at to the lowest degree one included randomized clinical trial. Nosotros excluded any non-Cochrane review that was as well published as a Cochrane review.
Iii authors (AS, DL and LJ) extracted data independently: intervention blazon (pharmacological or non-pharmacological); inclusion of meta-analyses; number of trials and how many trials were categorised as "high," "unclear" and "low" risk of bias; the method used for judging hazard of bias (or quality) and how it was implemented; the type and frequency of both standard and non-standard domain use; the use of merging or splitting of standard domains (e.g. merging blinding domains or splitting for dissimilar outcomes); the use of the "other bias" domain; how risk of bias assessments were incorporated into statistical assay using sensitivity analyses; whether risk of bias judgements were explicitly mentioned in the abstract, discussion or decision; and whether The Grading of Recommendations Assessment, Evolution and Evaluation (brusk GRADE) had been incorporated. We compared differences in proportions between Cochrane and non-Cochrane reviews using Fisher's verbal test. In cases where Cochrane or non-Cochrane reviews included both randomized clinical trials and non-randomized clinical trials, we disregarded the not-randomized trials.
Results
Review of published comments
Nosotros read 976 full text publications of which we excluded 908 (Fig. 1). Thus, nosotros included 68 publications, of which we categorised xv as "major comments" and 53 as "small-scale comments" (Tables one and 2).
Flowchart of the inclusion of comments on the Cochrane risk of bias tool for randomized clinical trials—evaluation of the Cochrane tool for assessing risk of bias in randomized clinical trials. 1N= the number of records/comments screened for inclusion. 2Of the 976 full-texts assessed, 793 full-texts did not comment on the Cochrane gamble of bias tool for randomized clinical trials (i.e. the tool). iii7 records (ordered through The Regal Danish Library) were not retrievable and therefore non assessed. 4183 publications were independently assessed past 2 authors to check type, categorisation and commentary. 5Major comments were defined every bit longer comments with a substantial reflection (typically ≥100 words of text) on the strengths or challenges of the tool. 6Minor comments were defined as shorter comments without a substantial reflection (typically <100 words of text) on the strengths or challenges of the tool. sevenPeripheral remarks (defined as implicit or short and tangential) were excluded
The strengths of the tool were addressed in 5 "major comments" relating to 3 themes: aims, developmental basis and transparency. The comments praised the tool for aiming to appraise deport (and not reporting), existence based on theoretical and empirical evidence and on broad consultation and facilitating transparent assessment of bias.
The challenges of the tool were addressed in 15 "major comments" relating to 4 themes: choice of the cadre bias domains, implementation, overall risk of bias and special situations. The comments on choice of cadre bias domains expressed concern whether the chosen domains comprehensively address all threats to validity (for instance, five comments reflected on including funding as an independent bias domain). Comments on implementation pointed to difficulties in the subjective interpretation of the tool and expressed concerns about small inter-observer agreement, difficulty in assessing selective reporting of outcomes, terminological ambiguity (i.e. of the terms subjective/objective) and the low proportion of reviews using take a chance of bias assessments every bit a basis for sensitivity analyses. The comments on overall risk of bias expressed concern nigh the challenges in assigning an overall hazard of bias to a trial based on adventure of bias of single domains to the trial as such. A unmarried comment regarded the special situation where the tool was used to appraise risk of bias based on clinical study reports (and non clinical trial publications).
Specific suggestions to improve the tool were included in nine "major comments" relating to three themes: improved guidelines, further research and the inclusion of funding as a bias domain. The comments on guidelines suggested that updated and improved guidance and more training options for users were needed. The comments on enquiry suggested further methodological inquiry (for example, blind versus not-bullheaded take a chance of bias assessments). The comments on funding suggested that funding/conflicts of interest should be incorporated into the tool as a specific bias domain.
All themes addressed in the "major comments" were represented in the "minor comments" (see Additional file 2). Additional themes addressed only in the "pocket-sized comments" included graphical representation, external validity and non-randomized designs. Specifically, (i) one comment praised the tool for its graphical representation of adventure of bias assessments, (ii) one annotate criticised that the tool does not accost external validity (and only focuses on internal validity) and (iii) 1 comment noted that non-randomized trials should be included in Cochrane reviews and should be addressed in hazard of bias assessments. The latter two suggestions are inconsistent with the aim of the tool, which is to appraise merely bias (i.e. internal validity) in randomized clinical trials. Such comments help to unveil the assumptions and basic construction of the tool only would be difficult to implement without significantly changing the tool.
Other comments reflected concerns about the implementation of the tool. An example is the suggestion for improved guidelines for how to assess selective outcome reporting. Also, improved grooming options and more detailed guidelines aimed to better agreement rates address the implementation of the tool. Such suggestions are easier to implement while keeping the fundamental structure of the tool intact.
Analysis of user patterns in systematic reviews
All Cochrane reviews assessed risk of bias using the Cochrane risk of bias tool (100/100, 100 %) (Tables three and 4). Virtually of the non-Cochrane reviews assessed risk of bias (eighty/100, 80 %), with the Cochrane tool being the most frequently used (31/eighty, 39 %). Other tools and scales used to assess gamble of bias included the Jadad Quality Assessment Scale (19/80, 24 %) [13] and the Physiotherapy Evidence Database (brusk PEDro) scale (5/80, 6 %) [xiv] (Table four).
The majority of Cochrane reviews included i or more than meta-analyses (85/100, 85 %). According to the information reported in their methods section, most of the Cochrane reviews had planned to perform sensitivity analyses based on risk of bias (seventy/100, 70 %). One fifth of the Cochrane reviews reported to take performed sensitivity analyses (19/100, 19 %). Few reviews based sensitivity analyses on an overall risk of bias (2/19, 11 %). Most reviews based sensitivity analyses on private bias domains (9/19, 47 %) or did non country what sensitivity analyses were based on (8/xix, 42 %). The bulk of the Cochrane reviews who did not conduct the planned analyses reported that the lack thereof was due to insufficient information (41/50, 82 %), either because there were few trials included in the review or few trials with "low" take chances of bias. The remaining reviews did non explain why they did not perform the planned analyses (9/50, 18 %) (Tables 3 and iv).
I tenth of the not-Cochrane reviews that had any risk of bias assessment reported plans for sensitivity analyses based on gamble of bias assessments (8/80, 10 %). One in 7 of all the not-Cochrane reviews reported to have performed sensitivity analyses based on run a risk of bias or quality assessments (11/eighty, fourteen %). In nine reviews, the sensitivity analyses were based on an overall adventure of bias (9/eleven, 82 %) (Tabular array 4).
2 Cochrane reviews performed subgroup analyses (both with "low" versus "high" risk of bias) (2/100, two %). None of the non-Cochrane reviews performed subgroup analyses based on risk of bias.
Almost Cochrane reviews explicitly commented on risk of bias assessments in the discussion and/or conclusion (89/100, 89 %), although fewer incorporated this information into the abstract (eighty/100, 80 %). Most of the non-Cochrane reviews that applied the Cochrane tool and some of the not-Cochrane reviews that applied not-Cochrane tools explicitly commented on risk of bias assessments in the discussion and/or conclusion (Cochrane tool: 25/31, 81 %; not-Cochrane tools: 12/49, 24 %) and more than half incorporated this information into the abstract (Cochrane tool: eighteen/31, 58 %; not-Cochrane tools: thirty/49, 61 %). No significant differences were establish between the non-Cochrane reviews that used the Cochrane tool versus the non-Cochrane reviews that used other risk of bias tools when comparing the use of risk of bias results in the abstract and discussion/conclusion.
The majority of Cochrane reviews (64/100, 64 %) and few not-Cochrane reviews (iv/eighty, 5 %) incorporated GRADE in their overall assessment of conviction in the results (Table four).
The majority of Cochrane reviews applied all standard domains (59/100, 59 %). Simply few Cochrane reviews explicitly assessed risk of bias on an outcome level (i.eastward. differentiating between subjective versus objective outcomes) (12/100, 12 %). Most Cochrane reviews (88/100, 88 %) performed one risk of bias assessment without making it clear whether this assessment concerned a single outcome, a group of outcomes or the trial equally a whole. A similar design was seen for not-Cochrane reviews (Table 5).
One third of the Cochrane reviews merged standard bias domains (37/100, 37 %), most often merging "performance bias" and "detection bias" into a single blinding bias domain (31/37, 84 %) (predominantly done in updates of reviews that had originally used the 2008 version of the tool in which the domains were merged (21/31, 68 %)). Approximately one fifth of the Cochrane reviews split a standard bias domain into separate sub-entities (18/100, xviii %), for case, blinding (within the performance bias domain) was divide into blinding of personnel and blinding of patients or incomplete outcome data (i.e. attrition bias) was split into assessment of intention-to-care for and assessment of dropouts. Over again, a similar design was seen for non-Cochrane reviews (Table 5).
A minority of Cochrane reviews added non-standard bias domains to the tool (11/100, 11 %). "Baseline imbalance" (half-dozen/11, 55 %) and "funding/conflicts of interest" (5/xi, 45 %) were the most used. A similar design was plant for non-Cochrane reviews (Table 6). The bulk of Cochrane reviews used the "other bias" domain option for the same purpose (73/100, 73 %). "Baseline imbalance" (33/73, 45 %) and "funding/conflicts of interest" (23/73, 32 %) were also the most used "other biases." Most non-Cochrane reviews that used the Cochrane tool included the "other bias" domain (17/31, 55 %), only none of the non-Cochrane reviews reported what specific items were considered as "other biases" (Table 6).
Very few of the randomized clinical trials included in the Cochrane reviews had all standard domains judged as "low" risk of bias (74 of 1242 trials, 6 %). Near had at least 1 standard domain judged as "unclear" take a chance of bias (407 of 1242 trials, 33 %) or every bit "high" risk of bias (761 of 1242 trials, 61 %). A similar pattern was constitute for the non-Cochrane reviews (Tabular array 3).
Thus, only a few reviews could conduct sensitivity analyses based on overall risk of bias, e.thou. the Cochrane reviews with at least i trial with all standard domains judged as "low" risk of bias and at least i trial with 1 bias domain judged as "high" risk of bias (26/100, 26 %) (or equally "loftier"/"unclear" risk of bias (32/100, 32 %)). A like blueprint was found for the non-Cochrane reviews (Table 3).
Word
Published comments about the Cochrane risk of bias tool considered it to be an of import step forrad just highlighted some challenges including its omission of funding/conflicts of interest and its small inter-agreement rates. Suggestions for improvement included more explicit guidelines and grooming options. The tool was used in 100 % of Cochrane reviews and in 31 % of non-Cochrane reviews in a sample published towards the end of 2014. Often the tool was implemented in a non-recommended mode. Also, seventy % of Cochrane reviews planned to use the take chances of bias assessment as basis for sensitivity analyses, but only 19 % of Cochrane reviews conducted such analyses, in many cases, because there were few trials with "low" gamble of bias.
Strengths and weaknesses
We are non enlightened of other reviews of published comments on the Cochrane run a risk of bias tool. Our study complements previous studies of user experience [viii] and inter-observer variance [9–11].
It is challenging to search for published comments as not all are indexed in standard databases. Notwithstanding, we focused on "major comments," which are more reliably identified. It is reasonable to assume that the threshold for publishing a comment pointing out a problem with the tool (and maybe suggesting an comeback) is lower than for publishing a comment praising the tool. Thus, we consider the qualitative summary of the expressed themes as more than interesting than the quantitative distribution of the themes. The analyses of how the tool was used were based on samples of representative and contemporary Cochrane and non-Cochrane reviews, enabling both a description and comparison between the two types of reviews.
Other similar studies
Based on feedback from focus groups and an online survey, Savović and colleagues ended that users of the Cochrane tool identified positive experiences and perceptions of the tool and that revisions and associated guidance as well equally improved provision of grooming may amend implementation [viii]. Several studies have analysed the assessment of gamble of bias in systematic reviews [ten–xv]. Hartling and colleagues and Armijo-Olivo and colleagues concluded unsatisfactory agreement rates by users of the tool and suggested the need for more detailed guidance in assessing the chance of bias [nine, xv]. Comments fabricated past the authors of all three studies are included in our study.
Hopewell and colleagues [16] studied assessment of risk of bias in Cochrane and non-Cochrane reviews indexed in The Database of Abstracts of Reviews of Effects (Dare) [17] and published in 2012. They reported that all reviews incorporated some kind of cess of hazard of bias, even though Cochrane reviews more oftentimes specified which tool was used. Also, the Cochrane tool was used more than often in Cochrane reviews (and the Jadad calibration was used less often). A depression proportion of reviews incorporated sensitivity analyses based on risk of bias in their conclusion.
Our study confirms and expands on the findings of Hopewell and colleagues. We establish that all 100 Cochrane reviews in our sample used the Cochrane risk of bias tool, simply that only i in 5 Cochrane reviews conducted sensitivity analyses based on take a chance of bias assessments, despite the fact that seven in ten had planned to exercise so.
Mechanisms and implications
Based on the degree of implementation, the tool has proven successful. All Cochrane reviews and a off-white proportion of non-Cochrane reviews used the tool in 2014. All the same, the tool is often used in ways not recommended.
Firstly, both Cochrane and non-Cochrane reviews implemented non-standard domains, either as fully new domains or incorporated into the "other bias" function. Approximately i in six Cochrane reviews added "intervention differed between groups" under "other bias," though this trouble is intended to exist addressed under "performance bias." Furthermore, a like proportion of Cochrane reviews added "unclear reporting" under "other bias," although the tool specifically addresses deport and non reporting (unclear reporting would commonly effect in contacting trial authors for clarification). Thus, there seems to be a widespread dubiety as to the scope of what the tool seeks to evaluate. Calculation bias domains and using the "other bias" pick are primarily intended for special situations, for instance, when assessing crossover trials. Thus, better guidance as to what is meant by "bias," "bias domain" and the basic purpose of the tool is warranted.
Secondly, only a minority of reviews used the risk of bias assessments equally a ground for sensitivity analyses. This trouble seems to exist a result of few trials having a "low" risk of bias, although sensitivity analyses may be based on "unclear" versus "loftier" risk of bias. Only 6 % of the trials included in our review sample had been classified as "low" risk of bias for all domains. Information technology is unclear whether such a low proportion (besides found by east.1000. Hartling and colleagues [9] and Hopewell and colleagues [16]) is a fair reflection of the "true" risk of bias in trials or whether the tool as currently applied is too sensitive (or authors simply do non utilize all sources of information equally recommended and mayhap opt for "unclear" based on the published report). A better guideline on how to move from the level of private bias domains to an overall take a chance of bias is warranted.
Thirdly, nigh reviews based their run a risk of bias assessment on a singular risk of bias assessment despite including more i outcome and several reviews (more often than not updates) merged "blinding of participants and personnel" and "blinding of outcome assessor" into a single blinding bias domain. The latter was recommended in the 2008 version of the tool, but non in the updated 2011 version [18]. Hopefully, the merging of blinding associated bias domains will be addressed when the reviews in question are updated (again).
Fourthly, risk of bias is very ofttimes assessed based on incomplete or missing information. The judgement of at to the lowest degree 1 risk of bias domain as "unclear" was establish in 1103 of 1242 included randomized clinical trials (89 %). Though "unclear" may be a reasonable pick in some trials, this large proportion is a considerable trouble. In many cases, the uncertainty can be resolved by contacting trial authors (who are ofttimes able to provide the information) or by searching publicly available trial registers. Occasionally, 1 may access trial protocols, internal company study reports or reports by drug regulation agencies (such as the The states' Food & Drug Administration) to facilitate better hazard of bias judgements [19]. Improved guidelines on how to admission and acquire the relevant information for assessing hazard of bias are warranted.
Furthermore, depression inter-rater agreement rates for take a chance of bias assessors are a potential trouble for users of systematic reviews. Readers may consider whether a review'due south conclusion would have been dissimilar if other reviewers had assessed the risk of bias in the included trials. It is prudent to check the hazard of bias assessments in a review. Fortunately, the tool has a configuration that facilitates such checking. Studies assessing between-rater agreement for complex assessment procedures often have modest understanding rates [20], which in some cases may be improved with training [21]. The Cochrane tool is no exception. Disagreement seems to occur when terminology is used inconsistently (e.chiliad. for blinding [22]), when judgements are based on insufficient information or when the intervention is more than complex (eastward.m. in non-pharmacological trials [9]). In addition, reviewers often encounter problems when assessing the domains "incomplete upshot data" and "selective outcome reporting" [8]. Clarified terminology, revised structure, better training options and guidance will hopefully improve agreement rates. It volition be interesting to read the result of a forthcoming report on the impact of training [23].
Funding/conflicts of interest is also a challenge for the tool. Information technology is widely believed that industry funding and other conflicts of interest are associated with higher estimates of treatment effects in randomized trials [24]. It is more controversial whether this association is appropriately deemed for by adding "funding/conflicts of interest" as an contained bias domain. Calculation a domain would go confronting the logic structure of the tool, which is based on core bias domains that reflect primal, independent bias mechanisms. An alternative choice would be to accost the issue within the existing bias domains (for example, under take a chance of selective outcome reporting), while paying careful attention to any clinical or methodological differences between industry funded and non-funded trials, such as choice of control groups. The problem with the latter pick is that detailed information on trial behave is ofttimes missing. Information technology is notable that 5 % of Cochrane reviews added funding every bit a split domain and that 32 % incorporated funding into the "other bias" function. Conspicuously, more work is needed on this issue.
A full general tension exists betwixt bias in randomized trials as divers mechanistically in the tool, and as defined empirically based on results from meta-epidemiological studies. Several design features of randomized clinical trials take been reported in meta-epidemiological studies to be associated with exaggerated treatment effects, such every bit sample size [25], evolution country condition [26], single eye status [27] and stopping a trial early [28]. The list of potential bias domains selected purely on empirical grounds will speedily become quite large and involve a run a risk of spurious inclusion of bias domains that are secondary in nature (and thus, in principle, explainable past the core bias domains). However, an open question is whether a pragmatic and conscientious selection of a few empirically defined bias domains that are simple to appraise (such every bit sample size or single middle status) may deed as proxy measures and supplement a gamble of bias tool based on mechanistically defined core bias domains.
Conclusions
Based on published comments, the Cochrane tool for assessing hazard of bias in randomized clinical trials is regarded equally an of import step forwards simply challenged past how to deal with the hazard of bias associated with funding/conflicts of interest and modest inter-rater agreement. The tool is used in a very high proportion of Cochrane reviews and in many non-Cochrane reviews, but often in a non-recommended way, for instance, by incorporating boosted bias domains. The tool has go the standard approach to assess risk of bias in randomized clinical trials. Its implementation may exist further improved by a revised construction, further enquiry and more focused guidance.
Abbreviations
- DARE:
-
The Database of Abstracts of Reviews of Furnishings
- Class:
-
The Grading of Recommendations Assessment, Development and Evaluation
- PEDro:
-
Physiotherapy Evidence Database
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Acknowledgements
LJ would similar to thank Allison E. Creepo for her assistance in editing the manuscript.
The study received no funding or grant other than standard bacon to the data collectors (LJ, AS and DL) provided by The Nordic Cochrane Centre (Rigshospitalet, Copenhagen). The National Plant supports JS for Health Research Collaboration for Leadership in Applied Health Research and Care West (NIHR CLAHRC Westward). The views expressed are those of the authors and non necessarily those of the NHS, the NIHR or the Department of Wellness.
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All authors are affiliated with the Cochrane Collaboration. JH, JS, IB, JACS and AH accept comments included in our review of published comments. We have no farther conflicts of interest to declare.
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LJ contributed to the pattern of the report, the collection and assembly of data, the analysis and interpretation of the data, the drafting of the article, the critical revision of the article for important intellectual content and the final approval of the commodity. AS contributed to the blueprint of the written report, the drove and assembly of data, the analysis and interpretation of the data, the disquisitional revision of the article for of import intellectual content and the terminal approval of the commodity. DL contributed to the pattern of the study, the drove and associates of data, the disquisitional revision of the article for of import intellectual content and the concluding blessing of the commodity. JS contributed to the conception of the study, the critical revision of the article for important intellectual content and the final approval of the commodity. IB contributed to the conception of the report, the critical revision of the commodity for of import intellectual content and the concluding approval of the article. JACS contributed to the conception of the written report, the critical revision of the article for important intellectual content and the final blessing of the article. JH contributed to the conception of the study, the pattern of the report, the critical revision of the article for important intellectual content and the final blessing of the article. AH contributed to the formulation of the study, the design of the study, the analysis and interpretation of the data, the drafting of the article, the disquisitional revision of the article for important intellectual content and the terminal blessing of the article.
Additional file
Additional file 1:
PRISMA 2009 Checklist. (DOCX 179 kb)
Additional file 2:
Appendices - Evaluation of the Cochrane tool for assessing risk of bias in randomized clinical trials. (DOCX 229 kb)
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Jørgensen, L., Paludan-Müller, A.S., Laursen, D.R.T. et al. Evaluation of the Cochrane tool for assessing gamble of bias in randomized clinical trials: overview of published comments and analysis of user do in Cochrane and non-Cochrane reviews. Syst Rev 5, fourscore (2016). https://doi.org/10.1186/s13643-016-0259-8
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DOI : https://doi.org/ten.1186/s13643-016-0259-8
Keywords
- Cochrane
- Systematic review
- Bias
- Tool
- Comment
- User do
- Randomized clinical trial
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Source: https://systematicreviewsjournal.biomedcentral.com/articles/10.1186/s13643-016-0259-8
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