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Objectives: To describe, and explain the rationale for, the methods used and decisions made during development of the updated SPIRIT 2024 and CONSORT 2024 reporting guidelines., Methods: We developed SPIRIT 2024 and CONSORT 2024 together to facilitate harmonization of the two guidelines, and incorporated content from key extensions. We conducted a scoping review of comments suggesting changes to SPIRIT 2013 and CONSORT 2010, and compiled a list of other possible revisions based on existing SPIRIT and CONSORT extensions, other reporting guidelines, and personal communications. From this, we generated a list of potential modifications or additions to SPIRIT and CONSORT, which we presented to stakeholders for feedback in an international online Delphi survey. The Delphi survey results were discussed at an online expert consensus meeting attended by 30 invited international participants. We then drafted the updated SPIRIT and CONSORT checklists and revised them based on further feedback from meeting attendees., Results: We compiled 83 suggestions for revisions or additions to SPIRIT and/or CONSORT from the scoping review and 85 from other sources, from which we generated 33 potential changes to SPIRIT (n = 5) or CONSORT (n = 28). Of 463 participants invited to take part in the Delphi survey, 317 (68%) responded to Round 1, 303 (65%) to Round 2 and 290 (63%) to Round 3. Two additional potential checklist changes were added to the Delphi survey based on Round 1 comments. Overall, 14/35 (SPIRIT n = 0; CONSORT n = 14) proposed changes reached the predefined consensus threshold (≥80% agreement), and participants provided 3580 free-text comments. The consensus meeting participants agreed with implementing 11/14 of the proposed changes that reached consensus in the Delphi and supported implementing a further 4/21 changes (SPIRIT n = 2; CONSORT n = 2) that had not reached the Delphi threshold. They also recommended further changes to refine key concepts and for clarity., Conclusion: The forthcoming SPIRIT 2024 and CONSORT 2024 Statements will provide updated, harmonized guidance for reporting randomized controlled trial protocols and results, respectively. The simultaneous development of the SPIRIT and CONSORT checklists has been informed by current empirical evidence and extensive input from stakeholders. We hope that this report of the methods used will be helpful for developers of future reporting guidelines., Competing Interests: Declaration of competing interest R. T. received support from the Medical Research Council–National Institute of Health and Care Research (MRC-NIHR). S. H. received support from MRC-NIHR. G. S. C. received support from MRC-NIHR. J. A. d. B. received support from MRC-NIHR. S. H., I. B., A.-W. C., A. H., K. F. S., and D. M. are members of the SPIRIT–CONSORT Executive Group. G. S. C. is director of the UK EQUATOR Centre. D. M. is director of the Canadian EQUATOR Centre. I. B. is deputy director of the French EQUATOR Centre. J. A. d. B. is a member of the UK EQUATOR Centre. D. M., A. H., and I. B. are members of the editorial board of the Journal of Clinical Epidemiology. Other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this article., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Objective: To describe the frequency of open science practices in a contemporary sample of studies developing prognostic models using machine learning methods in the field of oncology., Study Design and Setting: We conducted a systematic review, searching the MEDLINE database between December 1, 2022, and December 31, 2022, for studies developing a multivariable prognostic model using machine learning methods (as defined by the authors) in oncology. Two authors independently screened records and extracted open science practices., Results: We identified 46 publications describing the development of a multivariable prognostic model. The adoption of open science principles was poor. Only one study reported availability of a study protocol, and only one study was registered. Funding statements and conflicts of interest statements were common. Thirty-five studies (76%) provided data sharing statements, with 21 (46%) indicating data were available on request to the authors and seven declaring data sharing was not applicable. Two studies (4%) shared data. Only 12 studies (26%) provided code sharing statements, including 2 (4%) that indicated the code was available on request to the authors. Only 11 studies (24%) provided sufficient information to allow their model to be used in practice. The use of reporting guidelines was rare: eight studies (18%) mentioning using a reporting guideline, with 4 (10%) using the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis Or Diagnosis statement, 1 (2%) using Minimum Information About Clinical Artificial Intelligence Modeling and Consolidated Standards Of Reporting Trials-Artificial Intelligence, 1 (2%) using Strengthening The Reporting Of Observational Studies In Epidemiology, 1 (2%) using Standards for Reporting Diagnostic Accuracy Studies, and 1 (2%) using Transparent Reporting of Evaluations with Nonrandomized Designs., Conclusion: The adoption of open science principles in oncology studies developing prognostic models using machine learning methods is poor. Guidance and an increased awareness of benefits and best practices of open science are needed for prediction research in oncology., Competing Interests: Declaration of competing interest All authors declare no conflicts of interest., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background and Objectives: We investigated the developing methods of reporting guidelines in the EQUATOR (Enhancing the QUAlity and Transparency Of health Research) Network's database., Methods: In October 2018, we screened all records and excluded those not describing reporting guidelines from further investigation. Twelve researchers performed duplicate data extraction on bibliometrics, scope, development methods, presentation, and dissemination of all publications. Descriptive statistics were used to summarize the findings., Results: Of the 405 screened records, 262 described a reporting guidelines development. The number of reporting guidelines increased over the past 3 decades, from 5 in the 1990s and 63 in the 2000s to 157 in the 2010s. Development groups included 2-151 people. Literature appraisal was performed during the development of 56% of the reporting guidelines; 33% used surveys to gather external opinion on items to report; and 42% piloted or sought external feedback on their recommendations. Examples of good reporting for all reporting items were presented in 30% of the reporting guidelines. Eighteen percent of the reviewed publications included some level of spin., Conclusion: Reporting guidelines have been developed with varying methodology. Reporting guideline developers should use existing guidance and take an evidence-based approach, rather than base their recommendations on expert opinion of limited groups of individuals., Competing Interests: Declaration of Competing Interest No author has any financial interests to declare. All authors are members of, or have collaborations with, The EQUATOR Network., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Journal articles describing randomized controlled trials (RCTs) and systematic reviews with meta-analysis of RCTs are not optimally reported and often miss crucial details. This poor reporting makes assessing these studies' risk of bias or reproducing their results difficult. However, the reporting quality of diet- and nutrition-related RCTs and meta-analyses has not been explored., Objective: We aimed to assess the reporting completeness and identify the main reporting limitations of diet- and nutrition-related RCTs and meta-analyses of RCTs, estimate the frequency of reproducible research practices among these RCTs, and estimate the frequency of distorted presentation or spin among these meta-analyses., Methods: Two independent meta-research studies will be conducted using articles published in PubMed-indexed journals. The first will include a sample of diet- and nutrition-related RCTs; the second will include a sample of systematic reviews with meta-analysis of diet- and nutrition-related RCTs. A validated search strategy will be used to identify RCTs of nutritional interventions and an adapted strategy to identify meta-analyses in PubMed. We will search for RCTs and meta-analyses indexed in 1 calendar year and randomly select 100 RCTs (June 2021 to June 2022) and 100 meta-analyses (July 2021 to July 2022). Two reviewers will independently screen the titles and abstracts of records yielded by the searches, then read the full texts to confirm their eligibility. The general features of these published RCTs and meta-analyses will be extracted into a research electronic data capture database (REDCap; Vanderbilt University). The completeness of reporting of each RCT will be assessed using the items in the CONSORT (Consolidated Standards of Reporting Trials), its extensions, and the TIDieR (Template for Intervention Description and Replication) statements. Information about practices that promote research transparency and reproducibility, such as the publication of protocols and statistical analysis plans will be collected. There will be an assessment of the completeness of reporting of each meta-analysis using the items in the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) statement and collection of information about spin in the abstracts and full-texts. The results will be presented as descriptive statistics in diagrams or tables. These 2 meta-research studies are registered in the Open Science Framework., Results: The literature search for the first meta-research retrieved 20,030 records and 2182 were potentially eligible. The literature search for the second meta-research retrieved 10,918 records and 850 were potentially eligible. Among them, random samples of 100 RCTs and 100 meta-analyses were selected for data extraction. Data extraction is currently in progress, and completion is expected by the beginning of 2023., Conclusions: Our meta-research studies will summarize the main limitation on reporting completeness of nutrition- or diet-related RCTs and meta-analyses and provide comprehensive information regarding the particularities in the reporting of intervention studies in the nutrition field., International Registered Report Identifier (irrid): DERR1-10.2196/43537., (©Flávia Silva, Amanda Rodrigues Amorim Adegboye, Carl Lachat, Cintia Curioni, Fabio Gomes, Gary S Collins, Gilberto Kac, Jennifer Anne de Beyer, Jonathan Cook, Leila Cheikh Ismail, Matthew Page, Neha Khandpur, Sarah Lamb, Sally Hopewell, Shona Kirtley, Solange Durão, Colby J Vorland, Michael M Schlussel. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 23.03.2023.)

Background: Th EQUATOR Network improves the quality and transparency in health research, primarily by promoting awareness and use of reporting guidelines. In 2018, the UK EQUATOR Centre launched GoodReports.org , a website that helps authors find and use reporting guidelines. This paper describes the tool's development so far. We describe user experience and behaviour of using GoodReports.org both inside and outside a journal manuscript submission process. We intend to use our findings to inform future development and testing of the tool., Methods: We conducted a survey to collect data on user experience of the GoodReports website. We cross-checked a random sample of 100 manuscripts submitted to a partner journal to describe the level of agreement between the tool's checklist recommendation and what we would have recommended. We compared the proportion of authors submitting a completed reporting checklist alongside their manuscripts between groups exposed or not exposed to the GoodReports tool. We also conducted a study comparing completeness of reporting of manuscript text before an author received a reporting guideline recommendation from GoodReports.org with the completeness of the text subsequently submitted to a partner journal., Results: Seventy percent (423/599) of survey respondents rated GoodReports 8 or more out of 10 for usefulness, and 74% (198/267) said they had made changes to their manuscript after using the website. We agreed with the GoodReports reporting guideline recommendation in 84% (72/86) of cases. Of authors who completed the guideline finder questionnaire, 14% (10/69) failed to submit a completed checklist compared to 30% (41/136) who did not use the tool. Of the 69 authors who received a GoodReports reporting guideline recommendation, 20 manuscript pairs could be reviewed before and after use of GoodReports. Five included more information in their methods section after exposure to GoodReports. On average, authors reported 57% of necessary reporting items before completing a checklist on GoodReports.org and 60% after., Conclusion: The data suggest that reporting guidance is needed early in the writing process, not at submission stage. We are developing GoodReports by adding more reporting guidelines and by creating editable article templates. We will test whether GoodReports users write more complete study reports in a randomised trial targeting researchers starting to write health research articles., (© 2021. The Author(s).)

Competing Interests: Competing interest: All authors completed an ICMJE conflicts of interest form, available upon request from the corresponding author. All authors are involved, as part of the EQUATOR Network, in the development, update, implementation and dissemination of reporting guidelines.

Background: Cancer prognostic biomarkers have shown disappointing clinical applicability. The objective of this study was to classify and estimate how study results are overinterpreted and misreported in prognostic factor studies in oncology., Methods: This systematic review focused on 17 oncology journals with an impact factor above 7. PubMed was searched for primary clinical studies published in 2015, evaluating prognostic factors. We developed a classification system, focusing on three domains: misleading reporting (selective, incomplete reporting, misreporting), misleading interpretation (unreliable statistical analysis, spin) and misleading extrapolation of the results (claiming irrelevant clinical applicability, ignoring uncertainty)., Results: Our search identified 10,844 articles. The 98 studies included investigated a median of two prognostic factors (Q1-Q3, 1-7). The prognostic factors' effects were selectively and incompletely reported in 35/98 and 24/98 full texts, respectively. Twenty-nine articles used linguistic spin in the form of strong statements. Linguistic spin rejecting non-significant results was found in 34 full-text results and 15 abstract results sections. One in five articles had discussion and/or abstract conclusions that were inconsistent with the study findings. Sixteen reports had discrepancies between their full-text and abstract conclusions., Conclusions: Our study provides evidence of frequent overinterpretation of findings of prognostic factor assessment in high-impact medical oncology journals.

Many reports of health research omit important information needed to assess their methodological robustness and clinical relevance. Without clear and complete reporting, it is not possible to identify flaws or biases, reproduce successful interventions, or use the findings in systematic reviews or meta-analyses. The EQUATOR Network (http://www.equator-network.org/) promotes responsible reporting and the use of reporting guidelines to improve the accuracy, completeness, and transparency of health research. EQUATOR supports researchers by providing online resources and training. EQUATOR Oncology, a project funded by Cancer Research UK, aims to support cancer researchers reporting their research through the provision of online resources. In this article, our objective is to highlight reporting issues related to oncology research publications and to introduce reporting guidelines that are designed to aid high-quality reporting. We describe generic reporting guidelines for the main study types, and explain how these guidelines should and should not be used. We also describe 37 oncology-specific reporting guidelines, covering different clinical areas (e.g., haematology or urology) and sections of the report (e.g., methods or study characteristics); most of these are little-used. We also provide some background information on EQUATOR Oncology, which focuses on addressing the reporting needs of the oncology research community.

Tracking bacteria using video microscopy is a powerful experimental approach to probe their motile behaviour. The trajectories obtained contain much information relating to the complex patterns of bacterial motility. However, methods for the quantitative analysis of such data are limited. Most swimming bacteria move in approximately straight lines, interspersed with random reorientation phases. It is therefore necessary to segment observed tracks into swimming and reorientation phases to extract useful statistics. We present novel robust analysis tools to discern these two phases in tracks. Our methods comprise a simple and effective protocol for removing spurious tracks from tracking datasets, followed by analysis based on a two-state hidden Markov model, taking advantage of the availability of mutant strains that exhibit swimming-only or reorientating-only motion to generate an empirical prior distribution. Using simulated tracks with varying levels of added noise, we validate our methods and compare them with an existing heuristic method. To our knowledge this is the first example of a systematic assessment of analysis methods in this field. The new methods are substantially more robust to noise and introduce less systematic bias than the heuristic method. We apply our methods to tracks obtained from the bacterial species Rhodobacter sphaeroides and Escherichia coli. Our results demonstrate that R. sphaeroides exhibits persistence over the course of a tumbling event, which is a novel result with important implications in the study of this and similar species.

We have developed a stable isopropyl-beta-d-thiogalactopyranoside (IPTG)-inducible-expression plasmid, pIND4, which allows graduated levels of protein expression in the alphaproteobacteria Rhodobacter sphaeroides and Paracoccus denitrificans. pIND4 confers kanamycin resistance and combines the stable replicon of pMG160 with the lacI(q) gene from pYanni3 and the lac promoter, P(A1/04/03), from pJBA24.

During the course of the past ten years, the World Bank has become the single largest external financier of health activities in low and middle income countries and an important voice in national and international debates on health policy. This article highlights the Bank's new strategic direction in the health sector aimed at: improving health, nutrition, and population outcomes of the poor; enhancing the performance of health care systems; and securing sustainable health care financing. Millions of preventable deaths and treatable illnesses, together with health systems that are inefficient, inequitable and ineffective, have motivated expanded Bank support for the health sector in many of its client countries. The new policy directions and system-wide reforms observed in these countries are the result of both demand and supply factors. It is part of a general shift in the Bank's approach to development assistance, which sees systemic reform as a way to improve the impact and sustainability of investments in health. On the demand side, the Bank is trying to adapt to ongoing political, technological, economic, demographic, epidemiological and social pressures. On the supply side, the Bank's growing international experience and substantial financial resources are used to complement the development assistance provided by other organizations and the global effort to improve health and health systems in low and middle income countries.