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The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) Statement includes a 22-item checklist, which aims to improve the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. This explanation and elaboration document describes the rationale; clarifies the meaning of each item; and discusses why transparent reporting is important, with a view to assessing risk of bias and clinical usefulness of the prediction model. Each checklist item of the TRIPOD Statement is explained in detail and accompanied by published examples of good reporting. The document also provides a valuable reference of issues to consider when designing, conducting, and analyzing prediction model studies. To aid the editorial process and help peer reviewers and, ultimately, readers and systematic reviewers of prediction model studies, it is recommended that authors include a completed checklist in their submission. The TRIPOD checklist can also be downloaded from www.tripod-statement.org. This article is the translation in to Russian by Dr. Ruslan Saygitov (ORCID: https://orcid.org/0000-0002-8915-6153) from the original published in [Ann Intern Med. 2015;162:W1-W73. doi: https://doi.org/10.7326/M14-0698].

Background. Well-written and transparent case reports (1) reveal early signals of potential benefits, harms, and information on the use of resources; (2) provide information for clinical research and clinical practice guidelines, and (3) inform medical education. High-quality case reports are more likely when authors follow reporting guidelines. During 2011–2012, a group of clinicians, researchers, and journal editors developed recommendations for the accurate reporting of information in case reports that resulted in the CARE (CAse REport) Statement and Checklist. They were presented at the 2013 International Congress on Peer Review and Biomedical Publication, have been endorsed by multiple medical journals, and translated into nine languages.Objectives. This explanation and elaboration document has the objective to increase the use and dissemination of the CARE Checklist in writing and publishing case reports.Article design and setting. Each item from the CARE Checklist is explained and accompanied by published examples. The explanations and examples in this document are designed to support the writing of high-quality case reports by authors and their critical appraisal by editors, peer reviewers, and readers.Results and conclusion. This article and the 2013 CARE Statement and Checklist, available from the CARE website [www.care-statement.org] and the EQUATOR Network [www.equator-network.org], are resources for improving the completeness and transparency of case reports.Source. This article is a translation of the original paper «CARE guidelines for case reports: explanation and elaboration document» in the Journal of Clinical Epidemiology (doi: 10.1016/j.jclinepi.2017.04.026), prepared under the permission of the copyright holder (Elsevier Inc.), with supervision from the Scientific Editor by Professor E.G. Starostina, MD, PhD (translator) (Moscow, Russia). Present translation was first published in Digital Diagnostics. doi: 10.17816/DD105291. It is published with minor changes related to the literary editing of the translation itself. Keywords: case report; case study; EQUATOR network; health research reporting guidelines; CARE guideline; timelines; N-of-1 For citation: Riley David S., Barber Melissa S., Kienle Gunver S., Aronson Jeffrey K., von Schoen-Angerer Tido, Tugwell Peter, Kiene Helmut, Helfand Mark, Altman Douglas G., Sox Harold, Werthmann Paul G., Moher David, Rison Richard A., Shamseer Larissa, Koch Christian A., Sun Gordon H., Hanaway Patrick, Sudak Nancy L., Kaszkin-Bettag Marietta, Carpenter James E., Gagnier Joel J. CARE Guidelines for Case Reports: Explanation and Elaboration Document. Translation into Russian. Voprosy sovremennoi pediatrii — Current Pediatrics. 2023;22(2):88–108. (In Russ). doi: https://doi.org/10.15690/vsp.v22i2.2540

The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) Statement includes a 22-item checklist, which aims to improve the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. This explanation and elaboration document describes the rationale; clarifies the meaning of each item; and discusses why transparent reporting is important, with a view to assessing risk of bias and clinical usefulness of the prediction model. Each checklist item of the TRIPOD Statement is explained in detail and accompanied by published examples of good reporting. The document also provides a valuable reference of issues to consider when designing, conducting, and analyzing prediction model studies. To aid the editorial process and help peer reviewers and, ultimately, readers and systematic reviewers of prediction model studies, it is recommended that authors include a completed checklist in their submission. The TRIPOD checklist can also be downloaded from www.tripod-statement.org. For members of the TRIPOD Group, see the Appendix. This article is the translation in to Russian by Dr. Ruslan Saygitov (ORCID: 0000-0002-8915-6153) from the original published in [Ann Intern Med. 2015; 162:W1-W73. doi: 10.7326/M14-0698 ].

Abstract Background To assess the quality of reporting of RCT protocols approved by UK research ethics committees before and after the publication of the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) guideline. Methods We had access to RCT study protocols that received ethical approval in the UK in 2012 (n=103) and 2016 (n=108). From those, we assessed the adherence to the 33 SPIRIT items (i.e. a total of 64 components of the 33 SPIRIT items). We descriptively analysed the adherence to SPIRIT guidelines as proportion of adequately reported items (median and interquartile range [IQR]) and stratified the results by year of approval and sponsor. Results The proportion of reported SPIRIT items increased from a median of 64.9% (IQR, 57.6–69.2%) in 2012 to a median of 72.5% (IQR, 65.3–78.3%) in 2016. Industry-sponsored RCTs reported more SPIRIT items in 2012 (median 67.4%; IQR, 64.1–69.4%) compared to non-industry-sponsored trials (median 59.8%; IQR, 46.5–67.7%). This gap between industry- and non-industry-sponsored trials increased in 2016 (industry-sponsored: median 75.6%; IQR, 71.2–79.0% vs non-industry-sponsored: median 65.3%; IQR, 51.6–76.3%). Conclusions The adherence to SPIRIT guidelines has improved in the UK from 2012 to 2016 but remains on a modest level, especially for non-industry-sponsored RCTs.

Much medical research is observational. The reporting of observational studies is often of insufficient quality. Poor reporting hampers the assessment of the strengths and weaknesses of a study and the generalisability of its results. Taking into account empirical evidence and theoretical considerations, a group of methodologists, researchers, and editors developed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) recommendations to improve the quality of reporting of observational studies. The STROBE Statement consists of a checklist of 22 items, which relate to the title, abstract, introduction, methods, results and discussion sections of articles. Eighteen items are common to cohort studies, case-control studies and cross-sectional studies and four are specific to each of the three study designs. The STROBE Statement provides guidance to authors about how to improve the reporting of observational studies and facilitates critical appraisal and interpretation of studies by reviewers, journal editors and readers. This explanatory and elaboration document is intended to enhance the use, understanding, and dissemination of the STROBE Statement. The meaning and rationale for each checklist item are presented. For each item, one or several published examples and, where possible, references to relevant empirical studies and methodological literature are provided. Examples of useful flow diagrams are also included. The STROBE Statement, this document, and the associated Web site (http://www. strobe-statement.org/) should be helpful resources to improve reporting of observational research. Present article is Russian-language translation of the original manuscript edited by Doctor of Medicine R.T. Saygitov.Present translation was first published in Digital Diagnostics. doi: 10.17816/DD70821. It is published with minor changes related to the literary editing of the translation itself.

Diagnostic accuracy studies are, like other clinical studies, at risk of bias due to shortcomings in design and conduct, and the results of a diagnostic accuracy study may not apply to other patient groups and settings. Readers of study reports need to be informed about study design and conduct, in sufficient detail to judge the trustworthiness and applicability of the study findings. The STARD statement (Standards for Reporting of Diagnostic Accuracy Studies) was developed to improve the completeness and transparency of reports of diagnostic accuracy studies. STARD contains a list of essential items that can be used as a checklist, by authors, reviewers and other readers, to ensure that a report of a diagnostic accuracy study contains the necessary information. STARD was recently updated. All updated STARD materials, including the checklist, are available at http://www.equator-network.org/reporting-guidelines/stard. Here, we present the STARD 2015 explanation and elaboration document. Through commented examples of appropriate reporting, we clarify the rationale for each of the 30 items on the STARD 2015 checklist, and describe what is expected from authors in developing sufficiently informative study reports. Present article is Russian-language translation of the original manuscript edited by Doctor of Medicine R.T. Saygitov.Present translation was first published in Digital Diagnostics. doi: 10.17816/DD71031. It is published with minor changes related to the literary editing of the translation itself.

BACKGROUND: Well-written and transparent case reports (1) reveal early signals of potential benefits, harms, and information on the use of resources; (2) provide information for clinical research and clinical practice guidelines, and (3) inform medical education. High-quality case reports are more likely when authors follow reporting guidelines. During 20112012, a group of clinicians, researchers, and journal editors developed recommendations for the accurate reporting of information in case reports that resulted in the CARE (CAse REport) Statement and Checklist. They were presented at the 2013 International Congress on Peer Review and Biomedical Publication, have been endorsed by multiple medical journals, and translated into nine languages. OBJECTIVES: This explanation and elaboration document has the objective to increase the use and dissemination of the CARE Checklist in writing and publishing case reports. ARTICLE DESIGN AND SETTING: Each item from the CARE Checklist is explained and accompanied by published examples. The explanations and examples in this document are designed to support the writing of high-quality case reports by authors and their critical appraisal by editors, peer reviewers, and readers. RESULTS AND CONCLUSION: This article and the 2013 CARE Statement and Checklist, available from the CARE website [www.care-statement.org] and the EQUATOR Network [www.equator-network.org], are resources for improving the completeness and transparency of case reports. SOURCE: This article is a translation of the original paper CARE guidelines for case reports: explanation and elaboration document in the Journal of Clinical Epidemiology (doi: 10.1016/j.jclinepi.2017.04.026), prepared under the permission of the copyright holder (Elsevier Inc.), with supervision from the Scientific Editor by Professor E.G. Starostina, MD, PhD (translator) (Moscow, Russia).

Diagnostic accuracy studies are, like other clinical studies, at risk of bias due to shortcomings in design and conduct, and the results of a diagnostic accuracy study may not apply to other patient groups and settings. Readers of study reports need to be informed about study design and conduct, in sufficient detail to judge the trustworthiness and applicability of the study findings. The STARD statement (Standards for Reporting of Diagnostic Accuracy Studies) was developed to improve the completeness and transparency of reports of diagnostic accuracy studies. STARD contains a list of essential items that can be used as a checklist, by authors, reviewers and other readers, to ensure that a report of a diagnostic accuracy study contains the necessary information. STARD was recently updated. All updated STARD materials, including the checklist, are available at http://www.equator-network.org/reporting-guidelines/stard. Here, we present the STARD 2015 explanation and elaboration document. Through commented examples of appropriate reporting, we clarify the rationale for each of the 30 items on the STARD 2015 checklist, and describe what is expected from authors in developing sufficiently informative study reports. This article is the reprint with Russian translation of the original that can be observed here: Cohen JF, Korevaar DA, Altman DG, et al. STARD 2015 guidelines for reporting diagnostic accuracy studies: explanation and elaboration. BMJ Open 2016;6:e012799. doi: 10.1136/bmjopen-2016-012799

Abstract Adaptive designs (ADs) allow pre-planned changes to an ongoing trial without compromising the validity of conclusions and it is essential to distinguish pre-planned from unplanned changes that may also occur. The reporting of ADs in randomised trials is inconsistent and needs improving. Incompletely reported AD randomised trials are difficult to reproduce and are hard to interpret and synthesise. This consequently hampers their ability to inform practice as well as future research and contributes to research waste. Better transparency and adequate reporting will enable the potential benefits of ADs to be realised. This extension to the Consolidated Standards Of Reporting Trials (CONSORT) 2010 statement was developed to enhance the reporting of randomised AD clinical trials. We developed an Adaptive designs CONSORT Extension (ACE) guideline through a two-stage Delphi process with input from multidisciplinary key stakeholders in clinical trials research in the public and private sectors from 21 countries, followed by a consensus meeting. Members of the CONSORT Group were involved during the development process. The paper presents the ACE checklists for AD randomised trial reports and abstracts, as well as an explanation with examples to aid the application of the guideline. The ACE checklist comprises seven new items, nine modified items, six unchanged items for which additional explanatory text clarifies further considerations for ADs, and 20 unchanged items not requiring further explanatory text. The ACE abstract checklist has one new item, one modified item, one unchanged item with additional explanatory text for ADs, and 15 unchanged items not requiring further explanatory text. The intention is to enhance transparency and improve reporting of AD randomised trials to improve the interpretability of their results and reproducibility of their methods, results and inference. We also hope indirectly to facilitate the much-needed knowledge transfer of innovative trial designs to maximise their potential benefits. In order to encourage its wide dissemination this article is freely accessible on the BMJ and Trials journal websites. “To maximise the benefit to society, you need to not just do research but do it well” Douglas G Altman

Introduced in 1983, Bland-Altman methods is now considered the standard approach for assessment of agreement between two methods of measurement. The method is widely used by researchers in various disciplines so that the Bland-Altman 1986 Lancet paper has been named as the 29th mostly highly cited paper ever, over all fields. However, two papers by Hopkins (2004) and Krouwer (2007) questioned the validity of the Bland-Altman analysis. We review the points of critical papers and provide responses to them. The discussions in the critical papers of the Bland-Altman method are scientifically delusive. Hopkins misused the Bland-Altman methodology for research question of model validation and also incorrectly used least-square regression when there is measurement error in the predictor. The problem with Krouwers' paper is making sweeping generalisation of a very narrow and somewhat unrealistic situation. The method proposed by Bland and Altman should be used when the research question is method comparison.

Abstract Background The peer review process has been questioned as it may fail to allow the publication of high-quality articles. This study aimed to evaluate the accuracy in identifying inadequate reporting in RCT reports by early career researchers (ECRs) using an online CONSORT-based peer-review tool (COBPeer) versus the usual peer-review process. Methods We performed a cross-sectional diagnostic study of 119 manuscripts, from BMC series medical journals, BMJ, BMJ Open, and Annals of Emergency Medicine reporting the results of two-arm parallel-group RCTs. One hundred and nineteen ECRs who had never reviewed an RCT manuscript were recruited from December 2017 to January 2018. Each ECR assessed one manuscript. To assess accuracy in identifying inadequate reporting, we used two tests: (1) ECRs assessing a manuscript using the COBPeer tool (after completing an online training module) and (2) the usual peer-review process. The reference standard was the assessment of the manuscript by two systematic reviewers. Inadequate reporting was defined as incomplete reporting or a switch in primary outcome and considered nine domains: the eight most important CONSORT domains and a switch in primary outcome(s). The primary outcome was the mean number of domains accurately classified (scale from 0 to 9). Results The mean (SD) number of domains (0 to 9) accurately classified per manuscript was 6.39 (1.49) for ECRs using COBPeer versus 5.03 (1.84) for the journal’s usual peer-review process, with a mean difference [95% CI] of 1.36 [0.88–1.84] (p

Abstract Background Several hundred core outcome set (COS) projects have been systematically identified to date which, if adopted, ensure that researchers measure and report those outcomes that are most likely to be relevant to users of their research. The uptake of a COS by COS users will depend in part on the transparency and robustness of the methods used in the COS development study, which would be increased by the use of a standardised protocol. This article describes the development of the COS-STAP (Core Outcome Set-STAndardised Protocol Items) Statement for the content of a COS development study protocol. Methods The COS-STAP Statement was developed following the Enhancing the Quality and Transparency Of Health Research (EQUATOR) Network’s methodological framework for guideline development. This included an initial item generation stage, a two-round Delphi survey involving more than 150 participants representing three stakeholder groups (COS developers, journal editors and patient and public involvement researchers interested in COS development), followed by a consensus meeting with eight voting participants. Results The COS-STAP Statement consists of a checklist of 13 items considered essential documentation in a protocol, outlining the scope of the COS, stakeholder involvement, COS development plans and consensus processes. Conclusions Journal editors and peer reviewers can use the guidance to assess the completeness of a COS development study protocol submitted for publication. By providing guidance for key content, the COS-STAP Statement will enhance the drafting of high-quality protocols and determine how the COS development study will be carried out.

Abstract Background Adequate reporting of adaptive designs (ADs) maximises their potential benefits in the conduct of clinical trials. Transparent reporting can help address some obstacles and concerns relating to the use of ADs. Currently, there are deficiencies in the reporting of AD trials. To overcome this, we have developed a consensus-driven extension to the CONSORT statement for randomised trials using an AD. This paper describes the processes and methods used to develop this extension rather than detailed explanation of the guideline. Methods We developed the guideline in seven overlapping stages:1)Building on prior research to inform the need for a guideline;2)A scoping literature review to inform future stages;3)Drafting the first checklist version involving an External Expert Panel;4)A two-round Delphi process involving international, multidisciplinary, and cross-sector key stakeholders;5)A consensus meeting to advise which reporting items to retain through voting, and to discuss the structure of what to include in the supporting explanation and elaboration (E&E) document;6)Refining and finalising the checklist; and7)Writing-up and dissemination of the E&E document. The CONSORT Executive Group oversaw the entire development process. Results Delphi survey response rates were 94/143 (66%), 114/156 (73%), and 79/143 (55%) in rounds 1, 2, and across both rounds, respectively. Twenty-seven delegates from Europe, the USA, and Asia attended the consensus meeting. The main checklist has seven new and nine modified items and six unchanged items with expanded E&E text to clarify further considerations for ADs. The abstract checklist has one new and one modified item together with an unchanged item with expanded E&E text. The E&E document will describe the scope of the guideline, the definition of an AD, and some types of ADs and trial adaptations and explain each reporting item in detail including case studies. Conclusions We hope that making the development processes, methods, and all supporting information that aided decision-making transparent will enhance the acceptability and quick uptake of the guideline. This will also help other groups when developing similar CONSORT extensions. The guideline is applicable to all randomised trials with an AD and contains minimum reporting requirements.

Abstract Background As complete reporting is essential to judge the validity and applicability of multivariable prediction models, a guideline for the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) was introduced. We assessed the completeness of reporting of prediction model studies published just before the introduction of the TRIPOD statement, to refine and tailor its implementation strategy. Methods Within each of 37 clinical domains, 10 journals with the highest journal impact factor were selected. A PubMed search was performed to identify prediction model studies published before the launch of TRIPOD in these journals (May 2014). Eligible publications reported on the development or external validation of a multivariable prediction model (either diagnostic or prognostic) or on the incremental value of adding a predictor to an existing model. Results We included 146 publications (84% prognostic), from which we assessed 170 models: 73 (43%) on model development, 43 (25%) on external validation, 33 (19%) on incremental value, and 21 (12%) on combined development and external validation of the same model. Overall, publications adhered to a median of 44% (25th–75th percentile 35–52%) of TRIPOD items, with 44% (35–53%) for prognostic and 41% (34–48%) for diagnostic models. TRIPOD items that were completely reported for less than 25% of the models concerned abstract (2%), title (5%), blinding of predictor assessment (6%), comparison of development and validation data (11%), model updating (14%), model performance (14%), model specification (17%), characteristics of participants (21%), model performance measures (methods) (21%), and model-building procedures (24%). Most often reported were TRIPOD items regarding overall interpretation (96%), source of data (95%), and risk groups (90%). Conclusions More than half of the items considered essential for transparent reporting were not fully addressed in publications of multivariable prediction model studies. Essential information for using a model in individual risk prediction, i.e. model specifications and model performance, was incomplete for more than 80% of the models. Items that require improved reporting are title, abstract, and model-building procedures, as they are crucial for identification and external validation of prediction models.

Abstract Background Selective reporting of outcomes in clinical trials is a serious problem. We aimed to investigate the influence of the peer review process within biomedical journals on reporting of primary outcome(s) and statistical analyses within reports of randomised trials. Methods Each month, PubMed (May 2014 to April 2015) was searched to identify primary reports of randomised trials published in six high-impact general and 12 high-impact specialty journals. The corresponding author of each trial was invited to complete an online survey asking authors about changes made to their manuscript as part of the peer review process. Our main outcomes were to assess: (1) the nature and extent of changes as part of the peer review process, in relation to reporting of the primary outcome(s) and/or primary statistical analysis; (2) how often authors followed these requests; and (3) whether this was related to specific journal or trial characteristics. Results Of 893 corresponding authors who were invited to take part in the online survey 258 (29%) responded. The majority of trials were multicentre (n = 191; 74%); median sample size 325 (IQR 138 to 1010). The primary outcome was clearly defined in 92% (n = 238), of which the direction of treatment effect was statistically significant in 49%. The majority responded (1–10 Likert scale) they were satisfied with the overall handling (mean 8.6, SD 1.5) and quality of peer review (mean 8.5, SD 1.5) of their manuscript. Only 3% (n = 8) said that the editor or peer reviewers had asked them to change or clarify the trial’s primary outcome. However, 27% (n = 69) reported they were asked to change or clarify the statistical analysis of the primary outcome; most had fulfilled the request, the main motivation being to improve the statistical methods (n = 38; 55%) or avoid rejection (n = 30; 44%). Overall, there was little association between authors being asked to make this change and the type of journal, intervention, significance of the primary outcome, or funding source. Thirty-six percent (n = 94) of authors had been asked to include additional analyses that had not been included in the original manuscript; in 77% (n = 72) these were not pre-specified in the protocol. Twenty-three percent (n = 60) had been asked to modify their overall conclusion, usually (n = 53; 88%) to provide a more cautious conclusion. Conclusion Overall, most changes, as a result of the peer review process, resulted in improvements to the published manuscript; there was little evidence of a negative impact in terms of post hoc changes of the primary outcome. However, some suggested changes might be considered inappropriate, such as unplanned additional analyses, and should be discouraged.

Abstract Background Guidelines for assessing methodological and reporting quality of systematic reviews (SRs) were developed to contribute to implementing evidence-based health care and the reduction of research waste. As SRs assessing a cohort of SRs is becoming more prevalent in the literature and with the increased uptake of SR evidence for decision-making, methodological quality and standard of reporting of SRs is of interest. The objective of this study is to evaluate SR adherence to the Quality of Reporting of Meta-analyses (QUOROM) and PRISMA reporting guidelines and the A Measurement Tool to Assess Systematic Reviews (AMSTAR) and Overview Quality Assessment Questionnaire (OQAQ) quality assessment tools as evaluated in methodological overviews. Methods The Cochrane Library, MEDLINE®, and EMBASE® databases were searched from January 1990 to October 2014. Title and abstract screening and full-text screening were conducted independently by two reviewers. Reports assessing the quality or reporting of a cohort of SRs of interventions using PRISMA, QUOROM, OQAQ, or AMSTAR were included. All results are reported as frequencies and percentages of reports and SRs respectively. Results Of the 20,765 independent records retrieved from electronic searching, 1189 reports were reviewed for eligibility at full text, of which 56 reports (5371 SRs in total) evaluating the PRISMA, QUOROM, AMSTAR, and/or OQAQ tools were included. Notable items include the following: of the SRs using PRISMA, over 85% (1532/1741) provided a rationale for the review and less than 6% (102/1741) provided protocol information. For reports using QUOROM, only 9% (40/449) of SRs provided a trial flow diagram. However, 90% (402/449) described the explicit clinical problem and review rationale in the introduction section. Of reports using AMSTAR, 30% (534/1794) used duplicate study selection and data extraction. Conversely, 80% (1439/1794) of SRs provided study characteristics of included studies. In terms of OQAQ, 37% (499/1367) of the SRs assessed risk of bias (validity) in the included studies, while 80% (1112/1387) reported the criteria for study selection. Conclusions Although reporting guidelines and quality assessment tools exist, reporting and methodological quality of SRs are inconsistent. Mechanisms to improve adherence to established reporting guidelines and methodological assessment tools are needed to improve the quality of SRs.

Abstract The selection of appropriate outcomes is crucial when designing clinical trials in order to compare the effects of different interventions directly. For the findings to influence policy and practice, the outcomes need to be relevant and important to key stakeholders including patients and the public, health care professionals and others making decisions about health care. It is now widely acknowledged that insufficient attention has been paid to the choice of outcomes measured in clinical trials. Researchers are increasingly addressing this issue through the development and use of a core outcome set, an agreed standardised collection of outcomes which should be measured and reported, as a minimum, in all trials for a specific clinical area. Accumulating work in this area has identified the need for guidance on the development, implementation, evaluation and updating of core outcome sets. This Handbook, developed by the COMET Initiative, brings together current thinking and methodological research regarding those issues. We recommend a four-step process to develop a core outcome set. The aim is to update the contents of the Handbook as further research is identified.

Abstract Background The methodological quality and completeness of reporting of the systematic reviews (SRs) is fundamental to optimal implementation of evidence-based health care and the reduction of research waste. Methods exist to appraise SRs yet little is known about how they are used in SRs or where there are potential gaps in research best-practice guidance materials. The aims of this study are to identify reports assessing the methodological quality (MQ) and/or reporting quality (RQ) of a cohort of SRs and to assess their number, general characteristics, and approaches to ‘quality’ assessment over time. Methods The Cochrane Library, MEDLINE®, and EMBASE® were searched from January 1990 to October 16, 2014, for reports assessing MQ and/or RQ of SRs. Title, abstract, and full-text screening of all reports were conducted independently by two reviewers. Reports assessing the MQ and/or RQ of a cohort of ten or more SRs of interventions were included. All results are reported as frequencies and percentages of reports. Results Of 20,765 unique records retrieved, 1189 of them were reviewed for full-text review, of which 76 reports were included. Eight previously published approaches to assessing MQ or reporting guidelines used as proxy to assess RQ were used in 80% (61/76) of identified reports. These included two reporting guidelines (PRISMA and QUOROM) and five quality assessment tools (AMSTAR, R-AMSTAR, OQAQ, Mulrow, Sacks) and GRADE criteria. The remaining 24% (18/76) of reports developed their own criteria. PRISMA, OQAQ, and AMSTAR were the most commonly used published tools to assess MQ or RQ. In conjunction with other approaches, published tools were used in 29% (22/76) of reports, with 36% (8/22) assessing adherence to both PRISMA and AMSTAR criteria and 26% (6/22) using QUOROM and OQAQ. Conclusions The methods used to assess quality of SRs are diverse, and none has become universally accepted. The most commonly used quality assessment tools are AMSTAR, OQAQ, and PRISMA. As new tools and guidelines are developed to improve both the MQ and RQ of SRs, authors of methodological studies are encouraged to put thoughtful consideration into the use of appropriate tools to assess quality and reporting.

Abstract Background Ten events per variable (EPV) is a widely advocated minimal criterion for sample size considerations in logistic regression analysis. Of three previous simulation studies that examined this minimal EPV criterion only one supports the use of a minimum of 10 EPV. In this paper, we examine the reasons for substantial differences between these extensive simulation studies. Methods The current study uses Monte Carlo simulations to evaluate small sample bias, coverage of confidence intervals and mean square error of logit coefficients. Logistic regression models fitted by maximum likelihood and a modified estimation procedure, known as Firth’s correction, are compared. Results The results show that besides EPV, the problems associated with low EPV depend on other factors such as the total sample size. It is also demonstrated that simulation results can be dominated by even a few simulated data sets for which the prediction of the outcome by the covariates is perfect (‘separation’). We reveal that different approaches for identifying and handling separation leads to substantially different simulation results. We further show that Firth’s correction can be used to improve the accuracy of regression coefficients and alleviate the problems associated with separation. Conclusions The current evidence supporting EPV rules for binary logistic regression is weak. Given our findings, there is an urgent need for new research to provide guidance for supporting sample size considerations for binary logistic regression analysis.

Со списком литературы можно ознакомиться на сайте http://www.consort-statement.org

The Revised CONSORT Statement for Reporting Randomized Trials: Explanation and Elaboration (2001) (Part II).

The Revised CONSORT Statement for Reporting Randomized Trials: Explanation and Elaboration (2001) (continuation).

BackgroundThere is still uncertainty about the safety of aprotinin for coronary artery bypass graft surgery. The ART (Arterial Revascularization Trial) was designed to compare survival after bilateral versus single internal thoracic artery grafting. Many of the ART patients (≈30%) received perioperative aprotinin. We investigated the association between perioperative aprotinin administration and short‐term (in‐hospital) and long‐term outcomes by performing a post hoc analysis of the ART. Methods and ResultsAmong patients enrolled in the ART (n=3102) from 2004 to 2007, we excluded those who did not undergo surgery (n=18) and those with no information about use of perioperative aprotinin (n=9). Finally, 836 of 3076 patients (27%) received aprotinin. Propensity matching was used to select 536 pairs for final comparison. Aprotinin was also associated with an increased risk of hospital mortality (9 [1.7%] versus 1 [0.2%]; odds ratio, 9.12; 95% confidence interval [CI], 1.15–72.2; P=0.03), intra‐aortic balloon pump insertion (37 [6.9%] versus 17 [3.2%]; odds ratio, 2.26; 95% CI, 1.26–4.07; P=0.006), and acute kidney injury (102 [19.0%] versus 76 [14.2%]; odds ratio, 1.42; 95% CI, 1.03–1.97; P=0.03). Aprotinin was not associated with a lower incidence of transfusion (37 [6.9%] versus 28 [5.2%]; odds ratio, 1.34; 95% CI, 0.81–2.23; P=0.25) and reexploration (26 [4.9%] versus 19 [3.5%]; hazard ratio, 1.39; 95% CI, 0.76–2.53; P=0.28). At 5 years, all‐cause mortality was significantly increased in the aprotinin group (56 [10.6%] versus 38 [7.3%]; hazard ratio, 1.51; 95% CI, 1.0–2.28; P=0.045). ConclusionsIn the present post hoc ART analysis, aprotinin was associated with a significantly increased risk of early and late mortality. Clinical Trial RegistrationURL: http://www.isrctn.com. Unique identifier: ISRCTN46552265.

In the last decade the number of bioscience journals has increased enormously, with many filling specialised niches reflecting new disciplines and technologies. The emergence of open-access journals has revolutionised the publication process, maximising the availability of research data. Nevertheless, a wealth of evidence shows that across many areas, the reporting of biomedical research is often inadequate, leading to the view that even if the science is sound, in many cases the publications themselves are not “fit for purpose”, meaning that incomplete reporting of relevant information effectively renders many publications of limited value as instruments to inform policy or clinical and scientific practice [1–21]. A recent review of clinical research showed that there is considerable cumulative waste of financial resources at all stages of the research process, including as a result of publications that are unusable due to poor reporting [22]. It is unlikely that this issue is confined to clinical research [2–14,16–20].

Gran parte de la investigación biomédica es de tipo observacional, pero la información difundida sobre esas investigaciones es a menudo insuficiente, lo que dificulta la evaluación de sus puntos fuertes y débiles para la generalización de sus conclusiones. En el marco de la iniciativa STROBE (Strengthening the Reporting of Observational Studies in Epidemiology), se formularon recomendaciones sobre lo que debería contener una notificación precisa de un estudio observacional. Decidimos limitar el alcance de las recomendaciones a tres grandes modalidades de estudio: de cohortes, de casos y controles, y transversales. En septiembre de 2004 organizamos un taller de 2 días con metodólogos, investigadores y editores de revistas para elaborar una lista de verificación de distintos puntos. Esta lista fue revisada posteriormente en varias reuniones del grupo de coordinación y en discusiones mantenidas por correo electrónico con los principales participantes en STROBE, teniendo en cuenta la evidencia empírica y diversas consideraciones metodológicas. El taller y el posterior proceso iterativo de consulta y revisión desembocaron en una lista de verificación de 22 puntos (la declaración STROBE) que guardan relación con el título, el resumen, la introducción y las secciones de métodos, resultados y discusión de los artículos. Dieciocho puntos son comunes a las 3 modalidades de estudio, y 4 se refieren específicamente a los estudios de cohortes, de casos y controles o transversales. Se ha publicado separadamente un documento de explicación y elaboración al que puede accederse libremente en los sitios web de PLoS Medicine, Annals of Internal Medicine y Epidemiology. Esperamos que la declaración STROBE contribuya a mejorar la calidad de la publicación de los estudios observacionales.Much biomedical research is observational. The reporting of such research is often inadequate, which hampers the assessment of its strengths and weaknesses and of a study's generalisability. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) initiative developed recommendations on what should be included in an accurate and complete report of an observational study. We defined the scope of the recommendations to cover three main study designs: cohort, case-control, and cross-sectional studies. We convened a 2-day workshop in September, 2004, with methodologists, researchers, and journal editors to draft a che-cklist of items. This list was subsequently revised during several meetings of the coordinating group and in e-mail discussions with the larger group of STROBE contributors, taking into account empirical evidence and methodological considerations. The workshop and the subsequent iterative process of consultation and revision resulted in a checklist of 22 items (the STROBE statement) that relate to the title, abstract, introduction, methods, results, and discussion sections of articles. 18 items are common to all three study designs and four are specific for cohort, case-control, or cross-sectional studies. A detailed explanation and elaboration document is published separately and is freely available on the websites of PLoS Medicine, Annals of Internal Medicine, and Epidemiology. We hope that the STROBE statement will contribute to improving the quality of reporting of observational studies.

A pesar de que la mayor parte de la investigación biomédica es de tipo observacional, la información difundida sobre estas investigaciones es a menudo insuficiente, lo que dificulta la evaluación de sus puntos fuertes y débiles para la generalización de sus conclusiones. En el marco de la iniciativa STROBE (Strengthening the Reporting of Observational Studies in Epidemiology), se formularon las recomendaciones sobre lo que debería contener una notificación precisa de un estudio observacional. Decidimos limitar el alcance de las recomendaciones a tres grandes modalidades de estudio: de cohortes, de casos y controles, y transversales. En septiembre de 2004 organizamos un taller de 2 días con metodólogos, investigadores y editores de revistas para elaborar una lista de verificación de distintos puntos. Esta lista fue revisada posteriormente en varias reuniones del grupo de coordinación y en discusiones mantenidas por correo electrónico con los principales participantes en STROBE, teniendo en cuenta la evidencia empírica y diversas consideraciones metodológicas. El taller y el posterior proceso iterativo de consulta y revisión desembocaron en una lista de verificación de 22 puntos (la declaración STROBE) que guardan relación con el título, el resumen, la introducción y las secciones de métodos, resultados y discusión de los artículos. Dieciocho puntos son comunes a los tres tipos de estudio, y cuatro son específicas para cada uno de ellos. Se ha publicado separadamente un documento de explicación y elaboración al que puede accederse libremente en los sitios web de PLoS Medicine, Annals of Internal Medicine y Epidemiology. Esperamos que la declaración STROBE contribuya a mejorar la calidad de la publicación de los estudios observacionales.

Gran parte de la investigación biomédica es de tipo observacional. Los informes de los estudios observacionales a menudo poseen una calidad insuficiente, lo que dificulta la evaluación de sus fortalezas y debilidades para generalizar los resultados. Teniendo en cuenta la evidencia empírica y consideraciones teóricas, un grupo de expertos en metodología, investigadores y editores de revistas científicas, desarrollaron una lista de recomendaciones para aumentar la calidad de las publicaciones de los estudios observacionales: Strenghtening the Reporting of Observational Studies in Epidemiology (STROBE). La Declaración STROBE consiste en una lista de verificación de 22 puntos que guardan relación con las diferentes secciones de un artículo: título, resumen, introducción, metodología, resultados y discusión. De ellos, 18 puntos son comunes a los tres diseños de estudio: cohorte, casos y controles, y transversales; los otros cuatro son específicos para cada una de estas tres modalidades. La Declaración STROBE proporciona a los autores información sobre cómo mejorar la calidad de los artículos sobre estudios observacionales y facilita a los revisores, editores de revistas y lectores su apreciación crítica y su interpretación. Este documento explicativo tiene el propósito de impulsar el uso, la comprensión y la difusión de la Declaración STROBE. Se presentan el significado y el análisis razonado para cada punto de la lista de verificación, proporcionando uno o varios ejemplos publicados en la literatura y, en lo posible, referencias de estudios empíricos relevantes y literatura metodológica. También se incluyen ejemplos de diagramas de flujo. La Declaración STROBE, el presente documento y la página Web asociada (http://www.strobe-statement.org/) son recursos útiles para mejorar la divulgación de la investigación observacional.Much medical research is observational. The reporting of observational studies is often of insufficient quality. Poor reporting hampers the assessment of the strengths and weaknesses of a study and the generalisability of its results. Taking into account empirical evidence and theoretical considerations, a group of methodologists, researchers, and editors developed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) recommendations to improve the quality of reporting of observational studies. The STROBE Statement consists of a checklist of 22 items, which relate to the title, abstract, introduction, methods, results and discussion sections of articles. Eighteen items are common to cohort studies, case-control studies and cross-sectional studies and four are specific to each of the three study designs. The STROBE Statement provides guidance to authors about how to improve the reporting of observational studies and facilitates critical appraisal and interpretation of studies by reviewers, journal editors and readers. This explanatory and elaboration document is intended to enhance the use, understanding, and dissemination of the STROBE Statement. The meaning and rationale for each checklist item are presented. For each item, one or several published examples and, where possible, references to relevant empirical studies and methodological literature are provided. Examples of useful flow diagrams are also included. The STROBE Statement, this document, and the associated Web site (http://www.strobe-statement.org/) should be helpful resources to improve reporting of observational research.

The protocol of a clinical trial serves as the foundation for study planning, conduct, reporting, and appraisal. However, trial protocols and existing protocol guidelines vary greatly in content and quality. This article describes the systematic development and scope of SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) 2013, a guideline for the minimum content of a clinical trial protocol. The 33-item SPIRIT checklist applies to protocols for all clinical trials and focuses on content rather than format. The checklist recommends a full description of what is planned; it does not prescribe how to design or conduct a trial. By providing guidance for key content, the SPIRIT recommendations aim to facilitate the drafting of high-quality protocols. Adherence to SPIRIT would also enhance the transparency and completeness of trial protocols for the benefit of investigators, trial participants, patients, sponsors, funders, research ethics committees or institutional review boards, peer reviewers, journals, trial registries, policymakers, regulators, and other key stakeholders.