Anticoagulation with Edoxaban in Patients with Atrial High-Rate Episodes.

BACKGROUND: Device-detected atrial high-rate episodes (AHREs) are atrial arrhythmias detected by implanted cardiac devices. AHREs resemble atrial fibrillation but are rare and brief. Whether the occurrence of AHREs in patients without atrial fibrillation (as documented on a conventional electrocardiogram [ECG]) justifies the initiation of anticoagulants is not known. METHODS: We conducted an event-driven, double-blind, double-dummy, randomized trial involving patients 65 years of age or older who had AHREs lasting for at least 6 minutes and who had at least one additional risk factor for stroke. Patients were randomly assigned in a 1:1 ratio to receive edoxaban or placebo. The primary efficacy outcome was a composite of cardiovascular death, stroke, or systemic embolism, evaluated in a time-to-event analysis. The safety outcome was a composite of death from any cause or major bleeding. RESULTS: The analysis population consisted of 2536 patients (1270 in the edoxaban group and 1266 in the placebo group). The mean age was 78 years, 37.4% were women, and the median duration of AHREs was 2.8 hours. The trial was terminated early, at a median follow-up of 21 months, on the basis of safety concerns and the results of an independent, informal assessment of futility for the efficacy of edoxaban; at termination, the planned enrollment had been completed. A primary efficacy outcome event occurred in 83 patients (3.2% per patient-year) in the edoxaban group and in 101 patients (4.0% per patient-year) in the placebo group (hazard ratio, 0.81; 95% confidence interval [CI], 0.60 to 1.08; P = 0.15). The incidence of stroke was approximately 1% per patient-year in both groups. A safety outcome event occurred in 149 patients (5.9% per patient-year) in the edoxaban group and in 114 patients (4.5% per patient-year) in the placebo group (hazard ratio, 1.31; 95% CI, 1.02 to 1.67; P = 0.03). ECG-diagnosed atrial fibrillation developed in 462 of 2536 patients (18.2% total, 8.7% per patient-year). CONCLUSIONS: Among patients with AHREs detected by implantable devices, anticoagulation with edoxaban did not significantly reduce the incidence of a composite of cardiovascular death, stroke, or systemic embolism as compared with placebo, but it led to a higher incidence of a composite of death or major bleeding. The incidence of stroke was low in both groups. (Funded by the German Center for Cardiovascular Research and others; NOAH-AFNET 6 ClinicalTrials.gov number, NCT02618577; ISRCTN number, ISRCTN17309850.).

Anticoagulation with edoxaban in patients with long atrial high-rate episodes ≥24†h.

BACKGROUND AND AIMS: Patients with long atrial high-rate episodes (AHREs) ≥24 h and stroke risk factors are often treated with anticoagulation for stroke prevention. Anticoagulation has never been compared with no anticoagulation in these patients. METHODS: This secondary pre-specified analysis of the Non-vitamin K antagonist Oral anticoagulants in patients with Atrial High-rate episodes (NOAH-AFNET 6) trial examined interactions between AHRE duration at baseline and anticoagulation with edoxaban compared with placebo in patients with AHRE and stroke risk factors. The primary efficacy outcome was a composite of stroke, systemic embolism, or cardiovascular death. The safety outcome was a composite of major bleeding and death. Key secondary outcomes were components of these outcomes and electrocardiogram (ECG)-diagnosed atrial fibrillation. RESULTS: Median follow-up of 2389 patients with core lab-verified AHRE was 1.8 years. AHRE ≥24 h were present at baseline in 259/2389 patients (11%, 78 ± 7 years old, 28% women, CHA2DS2-VASc 4). Clinical characteristics were not different from patients with shorter AHRE. The primary outcome occurred in 9/132 patients with AHRE ≥24 h (4.3%/patient-year, 2 strokes) treated with anticoagulation and in 14/127 patients treated with placebo (6.9%/patient-year, 2 strokes). Atrial high-rate episode duration did not interact with the efficacy (P-interaction = .65) or safety (P-interaction = .98) of anticoagulation. Analyses including AHRE as a continuous parameter confirmed this. Patients with AHRE ≥24 h developed more ECG-diagnosed atrial fibrillation (17.0%/patient-year) than patients with shorter AHRE (8.2%/patient-year; P < .001). CONCLUSIONS: This hypothesis-generating analysis does not find an interaction between AHRE duration and anticoagulation therapy in patients with device-detected AHRE and stroke risk factors. Further research is needed to identify patients with long AHRE at high stroke risk.

[Special issue PRO] Considering endpoints for comparative tolerability of cancer treatments using patient report given the estimand framework.

Regulatory agencies are advancing the use of systematic approaches to collect patient experience data, including patient-reported outcomes (PROs), in cancer clinical trials to inform regulatory decision-making. Due in part to clinician under-reporting of symptomatic adverse events, there is a growing recognition that evaluation of cancer treatment tolerability should include the patient experience, both in terms of the overall side effect impact and symptomatic adverse events. Methodologies around implementation, analysis, and interpretation of "patient" reported tolerability are under development, and current approaches are largely descriptive. There is robust guidance for use of PROs as efficacy endpoints to compare cancer treatments, but it is unclear to what extent this can be relied-upon to develop tolerability endpoints. An important consideration when developing endpoints to compare tolerability between treatments is the linkage of trial design, objectives, and statistical analysis. Despite interest in and frequent collection of PRO data in oncology trials, heterogeneity in analyses and unclear PRO objectives mean that design, objectives, and analysis may not be aligned, posing substantial challenges for the interpretation of results. The recent ICH E9 (R1) estimand framework represents an opportunity to help address these challenges. Efforts to apply the estimand framework in the context of PROs have primarily focused on efficacy outcomes. In this paper, we discuss considerations for comparing the patient-reported tolerability of different treatments in an oncology trial context.

Predictors of quality of life, functional status, depression and fatigue in early arthritis: comparison between clinically suspect arthralgia, unclassified arthritis and rheumatoid arthritis.

BACKGROUND: Rheumatoid arthritis (RA) is often preceded by symptomatic phases during which classification criteria are not fulfilled. The health burden of these "at-risk" stages is not well described. This study assessed health-related quality of life (HRQoL), function, fatigue and depression in newly presenting patients with clinically suspect arthralgia (CSA), unclassified arthritis (UA) or RA. METHODS: Cross-sectional analysis of baseline Patient-Reported Outcome Measures (PROMs) was conducted in patients from the Birmingham Early Arthritis Cohort. HRQoL, function, depression and fatigue at presentation were assessed using EQ-5D, HAQ-DI, PHQ-9 and FACIT-F. PROMs were compared across CSA, UA and RA and with population averages from the HSE with descriptive statistics. Multivariate linear regression assessed associations between PROMs and clinical and sociodemographic variables. RESULTS: Of 838 patients included in the analysis, 484 had RA, 200 had CSA and 154 had UA. Patients with RA reported worse outcomes for all PROMs than those with CSA or UA. However, "mean EQ-5D utilities were 0.65 (95%CI: 0.61 to 0.69) in CSA, 0.61 (0.56 to 0.66) in UA and 0.47 (0.44 to 0.50) in RA, which was lower than in general and older (≥ 65 years) background populations." In patients with CSA or UA, HRQoL was comparable to chronic conditions such as heart failure, severe COPD or mild angina. Higher BMI and older age (≥ 60 years) predicted worse depression (PHQ-9: -2.47 (-3.85 to -1.09), P < 0.001) and fatigue (FACIT-F: 5.05 (2.37 to 7.73), P < 0.001). Women were more likely to report worse function (HAQ-DI: 0.13 (0.03 to 0.21), P = 0.01) and fatigue (FACIT-F: -3.64 (-5.59 to -1.70), P < 0.001), and residents of more deprived areas experienced decreased function (HAQ-DI: 0.23 (0.10 to 0.36), P = 0.001), greater depression (PHQ-9: 1.89 (0.59 to 3.18), P = 0.004) and fatigue (FACIT-F: -2.60 (-5.11 to 0.09), P = 0.04). After adjustments for confounding factors, diagnostic category was not associated with PROMs, but disease activity and polypharmacy were associated with poorer performance across all PROMs. CONCLUSIONS: Patient-reported outcomes were associated with disease activity and sociodemographic characteristics. Patients presenting with RA reported a higher health burden than those with CSA or UA, however HRQoL in the pre-RA groups was significantly lower than population averages.

[Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extensionDiretrizes para protocolos de ensaios clínicos com intervenções que utilizam inteligência artificial: a extensão SPIRIT-AI]. / Directrices para los protocolos de ensayos clínicos de intervenciones con inteligencia artificial: la extensión SPIRIT-AI.

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.

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.

[Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extensionDiretrizes para relatórios de ensaios clínicos com intervenções que utilizam inteligência artificial: a extensão CONSORT-AI]. / Directrices para presentación de informes de ensayos clínicos sobre intervenciones con inteligencia artificial: extensión CONSORT-AI.

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.

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.

Recommendations on the use of item libraries for patient-reported outcome measurement in oncology trials: findings from an international, multidisciplinary working group.

The use of item libraries for patient-reported outcome (PRO) measurement in oncology allows for the customisation of PRO assessment to measure key health-related quality of life concepts of relevance to the target population and intervention. However, no high-level recommendations exist to guide users on the design and implementation of these customised PRO measures (item lists) across different PRO measurement systems. To address this issue, a working group was set up, including international stakeholders (academic, independent, industry, health technology assessment, regulatory, and patient advocacy), with the goal of creating recommendations for the use of item libraries in oncology trials. A scoping review was carried out to identify relevant publications and highlight any gaps. Stakeholders commented on the available guidance for each research question, proposed recommendations on how to address gaps in the literature, and came to an agreement using discussion-based methods. Nine primary research questions were identified that formed the scope and structure of the recommendations on how to select items and implement item lists created from item libraries. These recommendations address methods to drive item selection, plan the structure and analysis of item lists, and facilitate their use in conjunction with other measures. The findings resulted in high-level, instrument-agnostic recommendations on the use of item-library-derived item lists in oncology trials.

Perspectives on Patient-Reported Outcome Data After Treatment Discontinuation in Cancer Clinical Trials.

OBJECTIVES: Patient-reported outcome (PRO) data are critical in understanding treatments from the patient perspective in cancer clinical trials. The potential benefits and methodological approaches to the collection of PRO data after treatment discontinuation (eg, because of progressive disease or unacceptable drug toxicity) are less clear. The purpose of this article is to describe the Food and Drug Administration's Oncology Center of Excellence and the Critical Path Institute cosponsored 2-hour virtual roundtable, held in 2020, to discuss this specific issue. METHODS: We summarize key points from this discussion with 16 stakeholders representing academia, clinical practice, patients, international regulatory agencies, health technology assessment bodies/payers, industry, and PRO instrument development. RESULTS: Stakeholders recognized that any PRO data collection after treatment discontinuation should have clearly defined objectives to ensure that data can be analyzed and reported. CONCLUSIONS: Data collection after discontinuation without a justification for its use wastes patients' time and effort and is unethical.

[Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extensionDiretrizes para protocolos de ensaios clínicos com intervenções que utilizam inteligência artificial: a extensão SPIRIT-AI]. / Directrices para los protocolos de ensayos clínicos de intervenciones con inteligencia artificial: la extensión SPIRIT-AI.

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.

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.

[Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extensionDiretrizes para protocolos de ensaios clínicos com intervenções que utilizam inteligência artificial: a extensão SPIRIT-AI]. / Directrices para los protocolos de ensayos clínicos de intervenciones con inteligencia artificial: la extensión SPIRIT-AI.

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.

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.

Symptom burden and health-related quality of life in chronic kidney disease: A global systematic review and meta-analysis.

BACKGROUND: The importance of patient-reported outcome measurement in chronic kidney disease (CKD) populations has been established. However, there remains a lack of research that has synthesised data around CKD-specific symptom and health-related quality of life (HRQOL) burden globally, to inform focused measurement of the most relevant patient-important information in a way that minimises patient burden. The aim of this review was to synthesise symptom prevalence/severity and HRQOL data across the following CKD clinical groups globally: (1) stage 1-5 and not on renal replacement therapy (RRT), (2) receiving dialysis, or (3) in receipt of a kidney transplant. METHODS AND FINDINGS: MEDLINE, PsycINFO, and CINAHL were searched for English-language cross-sectional/longitudinal studies reporting prevalence and/or severity of symptoms and/or HRQOL in CKD, published between January 2000 and September 2021, including adult patients with CKD, and measuring symptom prevalence/severity and/or HRQOL using a patient-reported outcome measure (PROM). Random effects meta-analyses were used to pool data, stratified by CKD group: not on RRT, receiving dialysis, or in receipt of a kidney transplant. Methodological quality of included studies was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Studies Reporting Prevalence Data, and an exploration of publication bias performed. The search identified 1,529 studies, of which 449, with 199,147 participants from 62 countries, were included in the analysis. Studies used 67 different symptom and HRQOL outcome measures, which provided data on 68 reported symptoms. Random effects meta-analyses highlighted the considerable symptom and HRQOL burden associated with CKD, with fatigue particularly prevalent, both in patients not on RRT (14 studies, 4,139 participants: 70%, 95% CI 60%-79%) and those receiving dialysis (21 studies, 2,943 participants: 70%, 95% CI 64%-76%). A number of symptoms were significantly (p < 0.05 after adjustment for multiple testing) less prevalent and/or less severe within the post-transplantation population, which may suggest attribution to CKD (fatigue, depression, itching, poor mobility, poor sleep, and dry mouth). Quality of life was commonly lower in patients on dialysis (36-Item Short Form Health Survey [SF-36] Mental Component Summary [MCS] 45.7 [95% CI 45.5-45.8]; SF-36 Physical Component Summary [PCS] 35.5 [95% CI 35.3-35.6]; 91 studies, 32,105 participants for MCS and PCS) than in other CKD populations (patients not on RRT: SF-36 MCS 66.6 [95% CI 66.5-66.6], p = 0.002; PCS 66.3 [95% CI 66.2-66.4], p = 0.002; 39 studies, 24,600 participants; transplant: MCS 50.0 [95% CI 49.9-50.1], p = 0.002; PCS 48.0 [95% CI 47.9-48.1], p = 0.002; 39 studies, 9,664 participants). Limitations of the analysis are the relatively few studies contributing to symptom severity estimates and inconsistent use of PROMs (different measures and time points) across the included literature, which hindered interpretation. CONCLUSIONS: The main findings highlight the considerable symptom and HRQOL burden associated with CKD. The synthesis provides a detailed overview of the symptom/HRQOL profile across clinical groups, which may support healthcare professionals when discussing, measuring, and managing the potential treatment burden associated with CKD. PROTOCOL REGISTRATION: PROSPERO CRD42020164737.

Using Patient-Reported Outcomes in Dose-Finding Oncology Trials: Surveys of Key Stakeholders and the National Cancer Research Institute Consumer Forum.

BACKGROUND: Patient-reported adverse events may be a useful adjunct for assessing a drug's tolerability in dose-finding oncology trials (DFOT). We conducted surveys of international stakeholders and the National Cancer Research Institute (NCRI) Consumer Forum to understand attitudes about patient-reported outcome (PRO) use in DFOT. METHODS: A 35-question survey of clinicians, trial managers, statisticians, funders, and regulators of DFOT was distributed via professional bodies examining experience using PROs, benefits/barriers, and their potential role in defining tolerable doses. An 8-question survey of the NCRI Consumer Forum explored similar themes. RESULTS: International survey: 112 responses from 15 September-30 November 2020; 103 trialists [48 clinicians (42.9%), 38 statisticians (34.0%), 17 trial managers (15.2%)], 7 regulators (6.3%), 2 funders (1.8%)]. Most trialists had no experience designing (73, 70.9%), conducting (52, 50.5%), or reporting (88, 85.4%) PROs in DFOT. Most agreed that PROs could identify new toxicities (75, 67.0%) and provide data on the frequency (86, 76.8%) and duration (81, 72.3%) of toxicities. The top 3 barriers were lack of guidance regarding PRO selection (73/103, 70.9%), missing PRO data (71/103, 68.9%), and overburdening staff (68/103, 66.0%). NCRI survey: 57 responses on 21 March 2021. A total of 28 (49.1%) were willing to spend <15 min/day completing PROs. Most (55, 96.5%) preferred to complete PROs online. 61 (54.5%) trialists and 57 (100%) consumers agreed that patient-reported adverse events should be used to inform dose-escalation decisions. CONCLUSION: Stakeholders reported minimal experience using PROs in DFOT but broadly supported their use. Guidelines are needed to standardize PRO selection, analysis, and reporting in DFOT.

Knowledge translation concerns for the CONSORT-PRO extension reporting guidance: a review of reviews.

This review of reviews aimed to appraise the use of the CONSORT-PRO Extension as an evaluation tool for assessing the reporting of patient-reported outcome (PROs) in publications, and to describe the reporting of PRO research across reviews. We also outlined how variation in such evaluations impacts knowledge translation and may lead to potential misuse of the CONSORT-PRO Extension. We systematically searched Medline, Pubmed and CINAHL from 2013 to 2025 March 2021 for reviews of the completeness of reporting of PRO endpoints according to CONSORT-PRO criteria. Two reviewers extracted details of each review, the percentage of included studies that addressed each CONSORT-PRO item, and key recommendations from each review. Fourteen reviews met inclusion criteria, and only six of these used the full CONSORT-PRO checklist with minimal justified modifications. The remaining eight studies made significant or unjustified adjustments to the CONSORT-PRO Extension. Review studies also varied in how they scored multi-component CONSORT-PRO items. CONSORT-PRO items were often unreported in trial reports, and certain CONSORT-PRO items were reported less often than others. The reporting of statistical approaches to dealing with missing PRO data were poor in RCTs included in all 14 review articles. Studies reviewing PRO publications often omitted recommended CONSORT-PRO items from their evaluations, which may cause confusion among readers regarding how best to report their PRO research according to the CONSORT-PRO extension. Many trials published since CONSORT-PRO's release did not report recommended CONSORT-PRO items, which may lead to misinterpretation and consequently to research waste.

The PROTEUS-Trials Consortium: Optimizing the use of patient-reported outcomes in clinical trials.

BACKGROUND: The assessment of patient-reported outcomes in clinical trials has enormous potential to promote patient-centred care, but for this potential to be realized, the patient-reported outcomes must be captured effectively and communicated clearly. Over the past decade, methodologic tools have been developed to inform the design, analysis, reporting, and interpretation of patient-reported outcome data from clinical trials. We formed the PROTEUS-Trials Consortium (Patient-Reported Outcomes Tools: Engaging Users and Stakeholders) to disseminate and implement these methodologic tools. METHODS: PROTEUS-Trials are engaging with patient, clinician, research, and regulatory stakeholders from 27 organizations in the United States, Canada, Australia, the United Kingdom, and Europe to develop both organization-specific and cross-cutting strategies for implementing and disseminating the methodologic tools. Guided by the Knowledge-to-Action framework, we conducted consortium-wide webinars and meetings, as well as individual calls with participating organizations, to develop a workplan, which we are currently executing. RESULTS: Six methodologic tools serve as the foundation for PROTEUS-Trials dissemination and implementation efforts: the Standard Protocol Items: Recommendations for Interventional Trials-patient-reported outcome extension for writing protocols with patient-reported outcomes, the International Society for Quality of Life Research Minimum Standards for selecting a patient-reported outcome measure, Setting International Standards in Analysing Patient-Reported Outcomes and Quality of Life Endpoints Data Consortium recommendations for patient-reported outcome data analysis, the Consolidated Standards for Reporting of Trials-patient-reported outcome extension for reporting clinical trials with patient-reported outcomes, recommendations for the graphic display of patient-reported outcome data, and a Clinician's Checklist for reading and using an article about patient-reported outcomes. The PROTEUS-Trials website (www.TheProteusConsortium.org) serves as a central repository for the methodologic tools and associated resources. To date, we have developed (1) a roadmap to visually display where each of the six methodologic tools applies along the clinical trial trajectory, (2) web tutorials that provide guidance on the methodologic tools at different levels of detail, (3) checklists to provide brief summaries of each tool's recommendations, (4) a handbook to provide a self-guided approach to learning about the tools and recommendations, and (5) publications that address key topics related to patient-reported outcomes in clinical trials. We are also conducting organization-specific activities, including meetings, presentations, workshops, and webinars to publicize the existence of the methodologic tools and the PROTEUS-Trials resources. Work to develop communications strategies to ensure that PROTEUS-Trials reach key audiences with relevant information about patient-reported outcomes in clinical trials and PROTEUS-Trials is ongoing. DISCUSSION: The PROTEUS-Trials Consortium aims to help researchers generate patient-reported outcome data from clinical trials to (1) enable investigators, regulators, and policy-makers to take the patient perspective into account when conducting research and making decisions; (2) help patients understand treatment options and make treatment decisions; and (3) inform clinicians' discussions with patients regarding treatment options. In these ways, the PROTEUS Consortium promotes patient-centred research and care.

Factors influencing follow-up care post-TIA and minor stroke: a qualitative study using the theoretical domains framework.

BACKGROUND: Follow-up care after transient ischaemic attack (TIA) and minor stroke has been found to be sub-optimal, with individuals often feeling abandoned. We aimed to explore factors influencing holistic follow-up care after TIA and minor stroke. METHODS: Qualitative semi-structured interviews with 24 healthcare providers (HCPs): 5 stroke doctors, 4 nurses, 9 allied health professionals and 6 general practitioners. Participants were recruited from three TIA clinics, seven general practices and one community care trust in the West Midlands, England. Interview transcripts were deductively coded using the Theoretical Domains Framework and themes were generated from coded data. RESULTS: There was no clear pathway for supporting people with TIA or minor stroke after rapid specialist review in hospital; consequently, these patients had limited access to HCPs from all settings ('Environmental context and resources'). There was lack of understanding of potential needs post-TIA/minor stroke, in particular residual problems such as anxiety/fatigue ('Knowledge'). Identification and management of needs was largely influenced by HCPs' perceived role, professional training ('Social professional role and identity') and time constraints ('Environmental context and resources'). Follow-up was often passive - with onerous on patients to seek support - and predominantly focused on acute medical management ('Intentions'/'Goal'). CONCLUSIONS: Follow-up care post-TIA/minor stroke is currently sub-optimal. Through identifying factors which influence follow-up, we can inform guidelines and practical strategies to improve holistic healthcare.

Ethical Considerations for the Inclusion of Patient-Reported Outcomes in Clinical Research: The PRO Ethics Guidelines.

Importance: Patient-reported outcomes (PROs) can inform health care decisions, regulatory decisions, and health care policy. They also can be used for audit/benchmarking and monitoring symptoms to provide timely care tailored to individual needs. However, several ethical issues have been raised in relation to PRO use. Objective: To develop international, consensus-based, PRO-specific ethical guidelines for clinical research. Evidence Review: The PRO ethics guidelines were developed following the Enhancing the Quality and Transparency of Health Research (EQUATOR) Network's guideline development framework. This included a systematic review of the ethical implications of PROs in clinical research. The databases MEDLINE (Ovid), Embase, AMED, and CINAHL were searched from inception until March 2020. The keywords patient reported outcome* and ethic* were used to search the databases. Two reviewers independently conducted title and abstract screening before full-text screening to determine eligibility. The review was supplemented by the SPIRIT-PRO Extension recommendations for trial protocol. Subsequently, a 2-round international Delphi process (n = 96 participants; May and August 2021) and a consensus meeting (n = 25 international participants; October 2021) were held. Prior to voting, consensus meeting participants were provided with a summary of the Delphi process results and information on whether the items aligned with existing ethical guidance. Findings: Twenty-three items were considered in the first round of the Delphi process: 6 relevant candidate items from the systematic review and 17 additional items drawn from the SPIRIT-PRO Extension. Ninety-six international participants voted on the relevant importance of each item for inclusion in ethical guidelines and 12 additional items were recommended for inclusion in round 2 of the Delphi (35 items in total). Fourteen items were recommended for inclusion at the consensus meeting (n = 25 participants). The final wording of the PRO ethical guidelines was agreed on by consensus meeting participants with input from 6 additional individuals. Included items focused on PRO-specific ethical issues relating to research rationale, objectives, eligibility requirements, PRO concepts and domains, PRO assessment schedules, sample size, PRO data monitoring, barriers to PRO completion, participant acceptability and burden, administration of PRO questionnaires for participants who are unable to self-report PRO data, input on PRO strategy by patient partners or members of the public, avoiding missing data, and dissemination plans. Conclusions and Relevance: The PRO ethics guidelines provide recommendations for ethical issues that should be addressed in PRO clinical research. Addressing ethical issues of PRO clinical research has the potential to ensure high-quality PRO data while minimizing participant risk, burden, and harm and protecting participant and researcher welfare.

Development of a Core Outcome Set for Clinical Trials in Non-infectious Uveitis of the Posterior Segment.

PURPOSE: To develop an agreed upon set of outcomes known as a "core outcome set" (COS) for noninfectious uveitis of the posterior segment (NIU-PS) clinical trials. DESIGN: Mixed-methods study design comprising a systematic review and qualitative study followed by a 2-round Delphi exercise and face-to-face consensus meeting. PARTICIPANTS: Key stakeholders including patients diagnosed with NIU-PS, their caregivers, and healthcare professionals involved in decision-making for patients with NIU-PS, including ophthalmologists, nurse practitioners, and policymakers/commissioners. METHODS: A long list of outcomes was developed based on the results of (1) a systematic review of clinical trials of NIU-PS and (2) a qualitative study of key stakeholders including focus groups and interviews. The long list was used to generate a 2-round Delphi exercise of stakeholders rating the importance of outcomes on a 9-point Likert scale. The proportion of respondents rating each item was calculated, leading to recommendations of "include," "exclude," or "for discussion" that were taken to a face-to-face consensus meeting of key stakeholders at which they agreed on the final COS. MAIN OUTCOME MEASURE: Items recommended for inclusion in the COS for NIU-PS. RESULTS: A total of 57 outcomes grouped in 11 outcome domains were presented for evaluation in the Delphi exercise, resulting in 9 outcomes directly qualifying for inclusion and 15 outcomes being carried forward to the consensus meeting, of which 7 of 15 were agreed on for inclusion. The final COS contained 16 outcomes organized into 4 outcome domains comprising visual function, health-related quality of life, treatment side effects, and disease control. CONCLUSIONS: This study builds on international work across the clinical trials community and our qualitative research to construct the world's first COS for NIU-PS. The COS provides a list of outcomes that represent the priorities of key stakeholders and provides a minimum set of outcomes for use in all future NIU-PS clinical trials. Adoption of this COS can improve the value of future uveitis clinical trials and reduce noninformative research. Some of the outcomes identified do not yet have internationally agreed upon methods for measurement and should be the subject of future international consensus development.

Past and Current Practice of Patient-Reported Outcome Measurement in Randomized Cancer Clinical Trials: A Systematic Review.

OBJECTIVES: In our systematic review, we assessed past and current practice of patient-reported outcome (PRO) measurement in cancer randomized, controlled trials (RCTs). METHODS: We included RCTs with PRO endpoints evaluating conventional medical treatments, conducted in patients with the most prevalent solid tumor types (breast, lung, colorectal, prostate, bladder, and gynecological cancers) and either published in 2004 to 2018 or registered on clinicaltrials.gov and initiated in 2014 to 2019. Frequency of use of individual PRO measures was assessed overall, over time, and by cancer site. RESULTS: Screening of 42 095 database records and 3425 registered trials identified 480 published and 537 registered trials meeting inclusion criteria. Among published trials, the European Organisation for Research and Treatment of Cancer (EORTC) measures were used most often (54.8% of trials), followed by the Functional Assessment of Chronic Illness Therapy (FACIT) measures (35.8%), the EQ-5D (10.2%), the SF-36 (7.3%), and the MD Anderson Symptom Inventory (MDASI; 2.5%). Among registered trials, the EORTC measures were used in 66.1% of the trials, followed by the FACIT measures (25.9%), the EQ-5D (23.1%), the SF-36 (4.8%), the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE; 2.2%), the Patient-Reported Outcomes Measurement Information System (PROMIS) measures (1.7%), and the MDASI measures (1.1%). CONCLUSION: The PRO measures most frequently used in RCTs identified in our review differ substantially in terms of content and domains, reflecting the ongoing debate among the scientific community, healthcare providers, and regulators on the type of PRO to be measured. Current findings may contribute to better informing the development of an internationally agreed core outcome set for future cancer trials.

Health-related quality of life, uncertainty and coping strategies in solid organ transplant recipients during shielding for the COVID-19 pandemic.

Strict isolation of vulnerable individuals has been a strategy implemented by authorities to protect people from COVID-19. Our objective was to investigate health-related quality of life (HRQoL), uncertainty and coping behaviours in solid organ transplant (SOT) recipients during the COVID-19 pandemic. A cross-sectional survey of adult SOT recipients undergoing follow-up at our institution was performed. Perceived health status, uncertainty and coping strategies were assessed using the EQ-5D-5L, Short-form Mishel Uncertainty in Illness Scale (SF-MUIS) and Brief Cope, respectively. Interactions with COVID-19 risk perception, access to health care, demographic and clinical variables were assessed. The survey was completed by 826 of 3839 (21.5%) invited participants. Overall, low levels of uncertainty in illness were reported, and acceptance was the major coping strategy (92%). Coping by acceptance, feeling protected, self-perceived susceptibility to COVID-19 were associated with lower levels of uncertainty. Health status index scores were significantly lower for those with mental health illness, compromised access to health care, a perceived high risk of severe COVID-19 infection and higher levels of uncertainty. A history of mental health illness, risk perceptions, restricted healthcare access, uncertainty and coping strategies was associated with poorer HRQoL in SOT recipients during strict isolation. These findings may allow identification of strategies to improve HRQoL in SOT recipients during the pandemic.

International guidance on the selection of patient-reported outcome measures in clinical trials: a review.

PURPOSE: Patient-reported outcomes (PROs) are increasingly used in clinical trials to provide patients' perspectives regarding symptoms, health-related quality of life, and satisfaction with treatments. A range of guidance documents exist for the selection of patient-reported outcome measures (PROMs) in clinical trials, and it is unclear to what extent these documents present consistent recommendations. METHODS: We conducted a targeted review of publications and regulatory guidance documents that advise on the selection of PROMs for use in clinical trials. A total of seven guidance documents from the US Food and Drug Administration, European Medicines Agency, and scientific consortia from professional societies were included in the final review. Guidance documents were analyzed using a content analysis approach comparing them with minimum standards recommended by the International Society for Quality of Life Research. RESULTS: Overall there was substantial agreement between guidance regarding the appropriate considerations for PROM selection within a clinical trial. Variations among the guidance primarily related to differences in their format and differences in the perspectives and mandates of their respective organizations. Whereas scientific consortia tended to produce checklist or rating-type guidance, regulatory groups tended to use more narrative-based approaches sometimes supplemented with lists of criteria. CONCLUSION: The consistency in recommendations suggests an emerging consensus in the field and supports use of any of the major guidance documents available to guide PROM selection for clinical trials without concern of conflicting recommendations. This work represents an important first step in the international PROTEUS Consortium's ongoing efforts to optimize the use of PROs in clinical trials.