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Clinical trial consent for protocols and their revisions should be transparent for patients and traceable for stakeholders. Our goal is to implement a process allowing for collection of patients' informed consent, which is bound to protocol revisions, storing and tracking the consent in a secure, unfalsifiable and publicly verifiable way, and enabling the sharing of this information in real time. For that, we build a consent workflow using a trending technology called Blockchain. This is a distributed technology that brings a built-in layer of transparency and traceability. From a more general and prospective point of view, we believe Blockchain technology brings a paradigmatical shift to the entire clinical research field. We designed a Proof-of-Concept protocol consisting of time-stamping each step of the patient's consent collection using Blockchain, thus archiving and historicising the consent through cryptographic validation in a securely unfalsifiable and transparent way. For each protocol revision, consent was sought again. We obtained a single document, in an open format, that accounted for the whole consent collection process: a time-stamped consent status regarding each version of the protocol. This document cannot be corrupted and can be checked on any dedicated public website. It should be considered a robust proof of data. However, in a live clinical trial, the authentication system should be strengthened to remove the need for third parties, here trial stakeholders, and give participative control to the peer users. In the future, the complex data flow of a clinical trial could be tracked by using Blockchain, which core functionality, named Smart Contract, could help prevent clinical trial events not occurring in the correct chronological order, for example including patients before they consented or analysing case report form data before freezing the database. Globally, Blockchain could help with reliability, security, transparency and could be a consistent step toward reproducibility.
The field of vascularized composite allografts (VCAs) has undergone significant advancement in recent decades, and VCAs are increasingly common and accepted in the clinical setting, bringing hope of functional recovery to patients with debilitating injuries. A major obstacle facing the widespread application of VCAs is the side effect profile associated with the current immunosuppressive regimen, which can cause a wide array of complications such as infection, malignancy, and even death. Significant concerns remain regarding whether the treatment outweighs the risk. The potential solution to this dilemma would be achieving VCA tolerance, which would allow recipients to receive allografts without significant immunosuppression and its sequelae. Promising tolerance protocols are being studied in kidney transplantation; four major trials have attempted to withdraw immunosuppressive treatment with various successes. The common theme in all four trials is the use of radiation treatment and donor cell transplantation. The knowledge gained from these trials can provide valuable insight into the development of a VCA tolerance protocol. Despite similarities, VCAs present additional barriers compared to kidney allografts regarding tolerance induction. VCA donors are likely to be deceased, which limits the time for significant pre-conditioning. VCA donors are also more likely to be human leukocyte antigen-mismatched, which means that tolerance must be induced across major immunological barriers. This review also explores adjunct therapies studied in large animal models that could be the missing element in establishing a safe and stable tolerance induction method.
High quality protocols facilitate proper conduct, reporting, and external review of clinical trials. However, the completeness of trial protocols is often inadequate. To help improve the content and quality of protocols, an international group of stakeholders developed the SPIRIT 2013 Statement (Standard Protocol Items: Recommendations for Interventional Trials). The SPIRIT Statement provides guidance in the form of a checklist of recommended items to include in a clinical trial protocol. This SPIRIT 2013 Explanation and Elaboration paper provides important information to promote full understanding of the checklist recommendations. For each checklist item, we provide a rationale and detailed description; a model example from an actual protocol; and relevant references supporting its importance. We strongly recommend that this explanatory paper be used in conjunction with the SPIRIT Statement. A website of resources is also available (www.spirit-statement.org). The SPIRIT 2013 Explanation and Elaboration paper, together with the Statement, should help with the drafting of trial protocols. Complete documentation of key trial elements can facilitate transparency and protocol review for the benefit of all stakeholders.
Clinical trials are an essential part of evidence-based medicine. Hence, to ensure transparency and accountability in these clinical trials, policies for registration have been framed with emphasis on mandatory submission of trial elements, specifically outcome measures. As these efforts evolve further, we sought to evaluate the current status of endpoint reporting in clinical trial registries.
Clinicians, patients, and policy-makers rely on published evidence from clinical trials to help inform decision-making. A lack of complete and transparent reporting of the investigated trial outcomes limits reproducibility of results and knowledge synthesis efforts, and contributes to outcome switching and other reporting biases. Outcome-specific extensions for the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT-Outcomes) and Consolidated Standards of Reporting Trials (CONSORT-Outcomes) reporting guidelines are under development to facilitate harmonized reporting of outcomes in trial protocols and reports. The aim of this review was to identify and synthesize existing guidance for trial outcome reporting to inform extension development.
Hypo-fractionation can be an effective strategy to lower costs and save time, increasing patient access to advanced radiation therapy. To demonstrate this potential in practice within the context of temporal evolution, a twenty-year analysis of a representative radiation therapy facility from 2003 to 2022 was conducted. This analysis utilized comprehensive data to quantitatively evaluate the connections between advanced clinical protocols and technological improvements. The findings provide valuable insights to the management team, helping them ensure the delivery of high-quality treatments in a sustainable manner.
Chronic obstructive pulmonary disease (COPD) has remained a leading cause of death worldwide and is expected to increase its burden on the healthcare system in the coming future. Numerous clinical trials have been conducted over the years and as a result, many drugs became a part of the treatment protocols of COPD. Currently, there are also several drugs under development. This review will help future researchers to grasp salient features of previous studies and use them in their future trials in order to reduce the morbidity and mortality of COPD. Randomized control trials provide strong evidence for any hypothesis in a research study. This review focuses on major COPD trials in the last two decades including TORCH, UPLIFT, POET, WISDOM, and TIOSPIR. It showcases the main clinical question, primary outcome, and result of these five trials.
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.
Antimicrobial photodynamic therapy (aPDT) has been proposed as an effective alternative method for the adjunctive treatment of all classes of oral infections. The multifactorial nature of its mechanism of action correlates with various influencing factors, involving parameters concerning both the photosensitizer and the light delivery system. This study aims to critically evaluate the recorded parameters of aPDT applications that use lasers as the light source in randomized clinical trials in dentistry.
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.
Genetics researchers and clinical professionals rely on diversity measures such as race, ethnicity, and ancestry (REA) to stratify study participants and patients for a variety of applications in research and precision medicine. However, there are no comprehensive, widely accepted standards or guidelines for collecting and using such data in clinical genetics practice. Two NIH-funded research consortia, the Clinical Genome Resource (ClinGen) and Clinical Sequencing Evidence-generating Research (CSER), have partnered to address this issue and report how REA are currently collected, conceptualized, and used. Surveying clinical genetics professionals and researchers (n = 448), we found heterogeneity in the way REA are perceived, defined, and measured, with variation in the perceived importance of REA in both clinical and research settings. The majority of respondents (>55%) felt that REA are at least somewhat important for clinical variant interpretation, ordering genetic tests, and communicating results to patients. However, there was no consensus on the relevance of REA, including how each of these measures should be used in different scenarios and what information they can convey in the context of human genetics. A lack of common definitions and applications of REA across the precision medicine pipeline may contribute to inconsistencies in data collection, missing or inaccurate classifications, and misleading or inconclusive results. Thus, our findings support the need for standardization and harmonization of REA data collection and use in clinical genetics and precision health research.
Background: Research collaboration of registered clinical trials for Coronavirus Disease 2019 (COVID-19) remains unclear. This study aimed to analyze research collaboration and distribution of outcome measures in registered interventional clinical trials (ICTs) of COVID-19 conducted in China. Methods: The International Clinical Trials Registry Platform, China Clinical Trials Registry, and Clinicaltrials.gov were searched to obtain COVID-19-registered ICTs up to May 25, 2020. Excel 2016 was used to perform a descriptive statistical analysis of the extracted information. VOSviewer 1.6.14 software was used to generate network maps for provinces and institutions and create density maps for outcomes. Results: A total of 390 ICTs were included, and the number of daily registrations fluctuated greatly. From 29 provinces in China, 430 institutions contributed to the registration of ICTs. The top three productive provinces were Hubei (160/390, 41.03%), Shanghai (60/390, 15.38%), and Beijing (59/390, 15.13%). The top three productive institutions were Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology (30/390, 7.69%), Zhongnan Hospital of Wuhan University (18/390, 4.62%), and Wuhan Jinyintan Hospital (18/390, 4.62%). Collaborations between provinces and institutions were not close enough. There were many interventions, but many trials did not provide specific drugs and their dosage and treatment duration. The most frequently used primary outcome was Chest/lung CT (53/390, 13.59%), and the most frequently used secondary outcome was hospital stay (33/390, 8.46%). There was a large difference in the number of outcomes, the expression of some outcomes was not standardized, the measurement time and tools for some outcomes were not clear, and there was a lack of special outcomes for trials of traditional Chinese medicine. Conclusions: Although there were some collaborations between provinces and institutions of the current COVID-19 ICT protocols in China, cooperation between regions should be further strengthened. The identified deficiencies in interventions and outcome measures should be given more attention by future researchers of COVID-19.
The number of reports on suspected drug-induced memory impairment submitted to the US Food and Drug Administration increased 30-fold from 2000 to 2022. Drugs are the most common cause of reversible dementia. However, there is very little research on drug-induced cognitive impairment. The aim of this study was to investigate if and how an assessment of cognitive safety was included in recent, registered, controlled, clinical drug trials.
Endometrial carcinoma (EC) is one of the most common gynecological malignancies in China and globally, accounting for the fourth-prevalent cancer in women. Although numerous studies have confirmed prognostic value of The Cancer Genome Atlas (TCGA) molecular subgroups, it is unclear how they are combined with histological features. The main objective of this study was to compare ProMisE and TCGA classification for the rapid and accurate prediction of prognosis within EC patients, together with the provision of a revised strategy for individualized diagnosis and treatment of patients.
A novel Protocol Ethics Tool Kit ('Ethics Tool Kit') has been developed by a multi-stakeholder group of the Multi-Regional Clinical Trials Center of Brigham and Women's Hospital and Harvard. The purpose of the Ethics Tool Kit is to facilitate effective recognition, consideration and deliberation of critical ethical issues in clinical trial protocols. The Ethics Tool Kit may be used by investigators and sponsors to develop a dedicated Ethics Section within a protocol to improve the consistency and transparency between clinical trial protocols and research ethics committee reviews. It may also streamline ethics review and may facilitate and expedite the review process by anticipating the concerns of ethics committee reviewers. Specific attention was given to issues arising in multinational settings. With the use of this Tool Kit, researchers have the opportunity to address critical research ethics issues proactively, potentially speeding the time and easing the process to final protocol approval.
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