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ABSTRACT The CONSORT 2010 statement provides minimum guidelines for reporting randomized trials. Its widespread use has been instrumental in ensuring transparency in the evaluation of new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate impact on health outcomes. The CONSORT-AI (Consolidated Standards of Reporting Trials-Artificial Intelligence) extension is a new reporting guideline for clinical trials evaluating interventions with an AI component. It was developed in parallel with its companion statement for clinical trial protocols: SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials-Artificial Intelligence). Both guidelines were developed through a staged consensus process involving literature review and expert consultation to generate 29 candidate items, which were assessed by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed upon in a two-day consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants). The CONSORT-AI extension includes 14 new items that were considered sufficiently important for AI interventions that they should be routinely reported in addition to the core CONSORT 2010 items. CONSORT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention is integrated, the handling of inputs and outputs of the AI intervention, the human-AI interaction and provision of an analysis of error cases. CONSORT-AI will help promote transparency and completeness in reporting clinical trials for AI interventions. It will assist editors and peer reviewers, as well as the general readership, to understand, interpret and critically appraise the quality of clinical trial design and risk of bias in the reported outcomes.
RESUMO A declaração CONSORT 2010 apresenta diretrizes mínimas para relatórios de ensaios clínicos randomizados. Seu uso generalizado tem sido fundamental para garantir a transparência na avaliação de novas intervenções. Recentemente, tem-se reconhecido cada vez mais que intervenções que incluem inteligência artificial (IA) precisam ser submetidas a uma avaliação rigorosa e prospectiva para demonstrar seus impactos sobre os resultados de saúde. A extensão CONSORT-AI (Consolidated Standards of Reporting Trials - Artificial Intelligence) é uma nova diretriz para relatórios de ensaios clínicos que avaliam intervenções com um componente de IA. Ela foi desenvolvida em paralelo à sua declaração complementar para protocolos de ensaios clínicos, a SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials - Artificial Intelligence). Ambas as diretrizes foram desenvolvidas por meio de um processo de consenso em etapas que incluiu revisão da literatura e consultas a especialistas para gerar 29 itens candidatos. Foram feitas consultas sobre esses itens a um grupo internacional composto por 103 interessados diretos, que participaram de uma pesquisa Delphi em duas etapas. Chegou-se a um acordo sobre os itens em uma reunião de consenso que incluiu 31 interessados diretos, e os itens foram refinados por meio de uma lista de verificação piloto que envolveu 34 participantes. A extensão CONSORT-AI inclui 14 itens novos que, devido à sua importância para as intervenções de IA, devem ser informados rotineiramente juntamente com os itens básicos da CONSORT 2010. A CONSORT-AI preconiza que os pesquisadores descrevam claramente a intervenção de IA, incluindo instruções e as habilidades necessárias para seu uso, o contexto no qual a intervenção de IA está inserida, considerações sobre o manuseio dos dados de entrada e saída da intervenção de IA, a interação humano-IA e uma análise dos casos de erro. A CONSORT-AI ajudará a promover a transparência e a integralidade nos relatórios de ensaios clínicos com intervenções que utilizam IA. Seu uso ajudará editores e revisores, bem como leitores em geral, a entender, interpretar e avaliar criticamente a qualidade do desenho do ensaio clínico e o risco de viés nos resultados relatados.
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ABSTRACT The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol reporting by providing evidence-based recommendations for the minimum set of items to be addressed. This guidance has been instrumental in promoting transparent evaluation of new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate their impact on health outcomes. The SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials-Artificial Intelligence) extension is a new reporting guideline for clinical trial protocols evaluating interventions with an AI component. It was developed in parallel with its companion statement for trial reports: CONSORT-AI (Consolidated Standards of Reporting Trials-Artificial Intelligence). Both guidelines were developed through a staged consensus process involving literature review and expert consultation to generate 26 candidate items, which were consulted upon by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed upon in a consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants). The SPIRIT-AI extension includes 15 new items that were considered sufficiently important for clinical trial protocols of AI interventions. These new items should be routinely reported in addition to the core SPIRIT 2013 items. SPIRIT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention will be integrated, considerations for the handling of input and output data, the human-AI interaction and analysis of error cases. SPIRIT-AI will help promote transparency and completeness for clinical trial protocols for AI interventions. Its use will assist editors and peer reviewers, as well as the general readership, to understand, interpret and critically appraise the design and risk of bias for a planned clinical trial.
RESUMO A declaração SPIRIT 2013 tem como objetivo melhorar a integralidade dos relatórios dos protocolos de ensaios clínicos, fornecendo recomendações baseadas em evidências para o conjunto mínimo de itens que devem ser abordados. Essas orientações têm sido fundamentais para promover uma avaliação transparente de novas intervenções. Recentemente, tem-se reconhecido cada vez mais que intervenções que incluem inteligência artificial (IA) precisam ser submetidas a uma avaliação rigorosa e prospectiva para demonstrar seus impactos sobre os resultados de saúde. A extensão SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials - Artificial Intelligence) é uma nova diretriz de relatório para protocolos de ensaios clínicos que avaliam intervenções com um componente de IA. Essa diretriz foi desenvolvida em paralelo à sua declaração complementar para relatórios de ensaios clínicos, CONSORT-AI (Consolidated Standards of Reporting Trials - Artificial Intelligence). Ambas as diretrizes foram desenvolvidas por meio de um processo de consenso em etapas que incluiu revisão da literatura e consultas a especialistas para gerar 26 itens candidatos. Foram feitas consultas sobre esses itens a um grupo internacional composto por 103 interessados diretos, que participaram de uma pesquisa Delphi em duas etapas. Chegou-se a um acordo sobre os itens em uma reunião de consenso que incluiu 31 interessados diretos, e os itens foram refinados por meio de uma lista de verificação piloto que envolveu 34 participantes. A extensão SPIRIT-AI inclui 15 itens novos que foram considerados suficientemente importantes para os protocolos de ensaios clínicos com intervenções que utilizam IA. Esses itens novos devem constar dos relatórios de rotina, juntamente com os itens básicos da SPIRIT 2013. A SPIRIT-AI preconiza que os pesquisadores descrevam claramente a intervenção de IA, incluindo instruções e as habilidades necessárias para seu uso, o contexto no qual a intervenção de IA será integrada, considerações sobre o manuseio dos dados de entrada e saída, a interação humano-IA e a análise de casos de erro. A SPIRIT-AI ajudará a promover a transparência e a integralidade nos protocolos de ensaios clínicos com intervenções que utilizam IA. Seu uso ajudará editores e revisores, bem como leitores em geral, a entender, interpretar e avaliar criticamente o delineamento e o risco de viés de um futuro estudo clínico.
RESUMO
resumen está disponible en el texto completo
ABSTRACT The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol reporting by providing evidence-based recommendations for the minimum set of items to be addressed. This guidance has been instrumental in promoting transparent evaluation of new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate their impact on health outcomes. The SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials-Artificial Intelligence) extension is a new reporting guideline for clinical trial protocols evaluating interventions with an AI component. It was developed in parallel with its companion statement for trial reports: CONSORT-AI (Consolidated Standards of Reporting Trials-Artificial Intelligence). Both guidelines were developed through a staged consensus process involving literature review and expert consultation to generate 26 candidate items, which were consulted upon by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed upon in a consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants). The SPIRIT-AI extension includes 15 new items that were considered sufficiently important for clinical trial protocols of AI interventions. These new items should be routinely reported in addition to the core SPIRIT 2013 items. SPIRIT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention will be integrated, considerations for the handling of input and output data, the human-AI interaction and analysis of error cases. SPIRIT-AI will help promote transparency and completeness for clinical trial protocols for AI interventions. Its use will assist editors and peer reviewers, as well as the general readership, to understand, interpret and critically appraise the design and risk of bias for a planned clinical trial.
RESUMO A declaração SPIRIT 2013 tem como objetivo melhorar a integralidade dos relatórios dos protocolos de ensaios clínicos, fornecendo recomendações baseadas em evidências para o conjunto mínimo de itens que devem ser abordados. Essas orientações têm sido fundamentais para promover uma avaliação transparente de novas intervenções. Recentemente, tem-se reconhecido cada vez mais que intervenções que incluem inteligência artificial (IA) precisam ser submetidas a uma avaliação rigorosa e prospectiva para demonstrar seus impactos sobre os resultados de saúde. A extensão SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials - Artificial Intelligence) é uma nova diretriz de relatório para protocolos de ensaios clínicos que avaliam intervenções com um componente de IA. Essa diretriz foi desenvolvida em paralelo à sua declaração complementar para relatórios de ensaios clínicos, CONSORT-AI (Consolidated Standards of Reporting Trials - Artificial Intelligence). Ambas as diretrizes foram desenvolvidas por meio de um processo de consenso em etapas que incluiu revisão da literatura e consultas a especialistas para gerar 26 itens candidatos. Foram feitas consultas sobre esses itens a um grupo internacional composto por 103 interessados diretos, que participaram de uma pesquisa Delphi em duas etapas. Chegou-se a um acordo sobre os itens em uma reunião de consenso que incluiu 31 interessados diretos, e os itens foram refinados por meio de uma lista de verificação piloto que envolveu 34 participantes. A extensão SPIRIT-AI inclui 15 itens novos que foram considerados suficientemente importantes para os protocolos de ensaios clínicos com intervenções que utilizam IA. Esses itens novos devem constar dos relatórios de rotina, juntamente com os itens básicos da SPIRIT 2013. A SPIRIT-AI preconiza que os pesquisadores descrevam claramente a intervenção de IA, incluindo instruções e as habilidades necessárias para seu uso, o contexto no qual a intervenção de IA será integrada, considerações sobre o manuseio dos dados de entrada e saída, a interação humano-IA e a análise de casos de erro. A SPIRIT-AI ajudará a promover a transparência e a integralidade nos protocolos de ensaios clínicos com intervenções que utilizam IA. Seu uso ajudará editores e revisores, bem como leitores em geral, a entender, interpretar e avaliar criticamente o delineamento e o risco de viés de um futuro estudo clínico.
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The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.
La declaración PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses), publicada en 2009, se diseñó para ayudar a los autores de revisiones sistemáticas a documentar de manera transparente el porqué de la revisión, qué hicieron los autores y qué encontraron. Durante la última década, ha habido muchos avances en la metodología y terminología de las revisiones sistemáticas, lo que ha requerido una actualización de esta guía. La declaración PRISMA 2020 sustituye a la declaración de 2009 e incluye una nueva guía de presentación de las publicaciones que refleja los avances en los métodos para identificar, seleccionar, evaluar y sintetizar estudios. La estructura y la presentación de los ítems ha sido modificada para facilitar su implementación. En este artículo, presentamos la lista de verificación PRISMA 2020 con 27 ítems, y una lista de verificación ampliada que detalla las recomendaciones en la publicación de cada ítem, la lista de verificación del resumen estructurado PRISMA 2020 y el diagrama de flujo revisado para revisiones sistemáticas.
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RESUMO A declaração dos Principais Itens para Relatar Revisões Sistemáticas e Meta-análises (PRISMA), publicada em 2009, foi desenvolvida para ajudar revisores sistemáticos a relatar de forma transparente por que a revisão foi feita, os métodos empregados e o que os autores encontraram. Na última década, os avanços na metodologia e terminologia de revisões sistemáticas exigiram a atualização da diretriz. A declaração PRISMA 2020 substitui a declaração de 2009 e inclui novas orientações para relato que refletem os avanços nos métodos para identificar, selecionar, avaliar e sintetizar estudos. A estrutura e apresentação dos itens foram modificadas para facilitar a implementação. Neste artigo, apresentamos a lista de checagem PRISMA 2020 de 27 itens, uma lista de checagem expandida que detalha as recomendações para relato para cada item, a lista de checagem PRISMA 2020 para resumos e os fluxogramas revisados para novas revisões e para atualização de revisões.
ABSTRACT The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.
RESUMEN La declaración PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses), publicada en 2009, se diseñó para ayudar a los autores de revisiones sistemáticas a documentar de manera transparente el porqué de la revisión, qué hicieron los autores y qué encontraron. Durante la última década, ha habido muchos avances en la metodología y terminología de las revisiones sistemáticas, lo que ha requerido una actualización de esta guía. La declaración PRISMA 2020 sustituye a la declaración de 2009 e incluye una nueva guía de presentación de las publicaciones que refleja los avances en los métodos para identificar, seleccionar, evaluar y sintetizar estudios. La estructura y la presentación de los ítems ha sido modificada para facilitar su implementación. En este artículo, presentamos la lista de verificación PRISMA 2020 con 27 ítems, y una lista de verificación ampliada que detalla las recomendaciones en la publicación de cada ítem, la lista de verificación del resumen estructurado PRISMA 2020 y el diagrama de flujo revisado para revisiones sistemáticas.
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The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews. Full English text available from:www.revespcardiol.org/en.
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Lista de Checagem , Editoração , HumanosRESUMO
The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.
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Projetos de Pesquisa/normas , Revisões Sistemáticas como Assunto/métodos , Medicina Baseada em Evidências , Guias como Assunto , Humanos , Revisões Sistemáticas como Assunto/normasRESUMO
The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.
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Guias como Assunto , Relatório de Pesquisa/normas , Revisões Sistemáticas como Assunto , Lista de Checagem , Humanos , EditoraçãoAssuntos
Projetos de Pesquisa/normas , Revisões Sistemáticas como Assunto , Confiabilidade dos Dados , Medicina Baseada em Evidências , Humanos , Escrita Médica/normas , Metanálise como Assunto , Guias de Prática Clínica como Assunto , Controle de Qualidade , Estatística como Assunto , Revisões Sistemáticas como Assunto/métodos , Revisões Sistemáticas como Assunto/normas , Terminologia como AssuntoAssuntos
Projetos de Pesquisa/normas , Revisões Sistemáticas como Assunto , Humanos , Escrita Médica/normas , Metanálise como Assunto , Guias de Prática Clínica como Assunto , Controle de Qualidade , Estatística como Assunto , Revisões Sistemáticas como Assunto/métodos , Revisões Sistemáticas como Assunto/normas , Terminologia como AssuntoRESUMO
Matthew Page and co-authors describe PRISMA 2020, an updated reporting guideline for systematic reviews and meta-analyses.
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Medicina Baseada em Evidências/normas , Editoração/normas , Revisões Sistemáticas como Assunto , Humanos , Revisões Sistemáticas como Assunto/métodos , Revisões Sistemáticas como Assunto/normasRESUMO
OBJECTIVES: To describe the processes used to update the PRISMA 2009 statement for reporting systematic reviews, present results of a survey conducted to inform the update, summarize decisions made at the PRISMA update meeting, and describe and justify changes made to the guideline. METHODS: We reviewed 60 documents with reporting guidance for systematic reviews to generate suggested modifications to the PRISMA 2009 statement. We invited 220 systematic review methodologists and journal editors to complete a survey about the suggested modifications. The results of these projects were discussed at a 21-member in-person meeting. Following the meeting, we drafted the PRISMA 2020 statement and refined it based on feedback from co-authors and a convenience sample of 15 systematic reviewers. RESULTS: The review of 60 documents revealed that all topics addressed by the PRISMA 2009 statement could be modified. Of the 110 survey respondents, more than 66% recommended keeping six of the original checklist items as they were and modifying 15 of them using wording suggested by us. Attendees at the in-person meeting supported the revised wording for several items but suggested rewording for most to enhance clarity, and further refinements were made over six drafts of the guideline. CONCLUSIONS: The PRISMA 2020 statement consists of updated reporting guidance for systematic reviews. We hope that providing this detailed description of the development process will enhance the acceptance and uptake of the guideline and assist those developing and updating future reporting guidelines.
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Guias como Assunto/normas , Relatório de Pesquisa/normas , Consenso , Medicina Baseada em Evidências , Fidelidade a Diretrizes , Humanos , Inquéritos e Questionários , Revisões Sistemáticas como AssuntoRESUMO
Editor's Note: This article is a reprint of a previously published article. For citation purposes, please use the original publication details: Harris RP, Helfand M, Woolf SH, et al. Current methods of the U.S. Preventive Services Task Force: a review of the process. Am J Prev Med. 2001;20(3S):21-35. The U.S. Preventive Services Task Force (USPSTF/Task Force) represents one of several efforts to take a more evidence-based approach to the development of clinical practice guidelines. As methods have matured for assembling and reviewing evidence and for translating evidence into guidelines, so too have the methods of the USPSTF. This paper summarizes the current methods of the third USPSTF, supported by the Agency for Healthcare Research and Quality (AHRQ) and two of the AHRQ Evidence-based Practice Centers (EPCs). The Task Force limits the topics it reviews to those conditions that cause a large burden of suffering to society and that also have available a potentially effective preventive service. It focuses its reviews on the questions and evidence most critical to making a recommendation. It uses analytic frameworks to specify the linkages and key questions connecting the preventive service with health outcomes. These linkages, together with explicit inclusion criteria, guide the literature searches for admissible evidence. Once assembled, admissible evidence is reviewed at three strata: (1) the individual study, (2) the body of evidence concerning a single linkage in the analytic framework, and (3) the body of evidence concerning the entire preventive service. For each stratum, the Task Force uses explicit criteria as general guidelines to assign one of three grades of evidence: good, fair, or poor. Good or fair quality evidence for the entire preventive service must include studies of sufficient design and quality to provide an unbroken chain of evidence-supported linkages, generalizable to the general primary care population, that connect the preventive service with health outcomes. Poor evidence contains a formidable break in the evidence chain such that the connection between the preventive service and health outcomes is uncertain. For services supported by overall good or fair evidence, the Task Force uses outcomes tables to help categorize the magnitude of benefits, harms, and net benefit from implementation of the preventive service into one of four categories: substantial, moderate, small, or zero/negative. The Task Force uses its assessment of the evidence and magnitude of net benefit to make a recommendation, coded as a letter: from A (strongly recommended) to D (recommend against). It gives an I recommendation in situations in which the evidence is insufficient to determine net benefit. The third Task Force and the EPCs will continue to examine a variety of methodologic issues and document work group progress in future communications.
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OBJECTIVES: The aim of the study was to generate a comprehensive bank of systematic review (SR) reporting items to inform an update of the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 2009 statement. METHODS: We searched the Enhancing the QUAlity and Transparency Of health Research Network library in May 2019 to identify all reporting guidelines for SRs that were published after 2009, regardless of the scope of the guideline. We also conducted a selective review of four guidance manuals for SRs, three tools for assessing the risk of bias in SRs, six meta-research studies evaluating the reporting quality of SRs using a tailored checklist, and five reporting guidelines for other study designs. One author screened and selected sources for inclusion, extracted reporting guidance from sources, and mapped guidance against the PRISMA 2009 checklist items. RESULTS: We included 60 sources providing guidance on reporting of SRs and meta-analyses. From these, we collated a list of 221 unique reporting items. Items were categorized into title (four items), abstract (10 items), introduction (12 items), methods (111 items), results (61 items), discussion (12 items), funding and conflicts of interest (four items), administrative information (three items), and data availability (four items). This exercise generated 175 reporting items that could be added to the guidance in the PRISMA 2009 statement. CONCLUSION: Generation of a comprehensive item bank through review and mapping of the literature facilitates identification of missing items and those needing modification, which may not otherwise be identified by the guideline development team or from other activities commonly used to develop reporting guidelines.