To solve the problems such as the incomplete and non-standard reporting outcomes in clinical trials, international methodologists have simultaneously launched guidelines for reporting outcomes in trial protocols and reports in 2022 on the basis of the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) 2013 and the Consolidated Standards of Reporting Trials (CONSORT) statement 2010. The SPIRIT-Outcomes 2022 extension and CONSORT-Outcomes 2022 extension recommend outcome-specific reporting items should be included prospectively in trial protocols and reports, regardless of trial design or population. This paper introduces and interprets the two guidelines for reporting outcomes, and discusses their significance and enlightenment to the research in the field of traditional Chinese medicine. For example, using the outcome reporting guidelines will help clinical researchers comprehensively consider issues related to outcomes when reporting protocols or results, which may improve the quality of research design and reporting. For core outcome set, the five core elements of outcomes may help researchers extracting and analyzing outcomes, which will standardize research; the explanation of medical terminology in the outcome reporting guidelines will contribute to the improvement of methodology in the field of traditional Chinese medicine.
This paper summarizes the methodological quality assessment tools of artificial intelligence-based diagnostic test accuracy studies, and introduces QUADAS-AI and modified QUADAS-2. Moreover, this paper summarizes reporting guidelines of these studies as well, and then introduces specific reporting standards in AI-centred research, and checklist for AI in dental research.
This paper summarizes the methodological quality assessment tools of artificial intelligence-based diagnostic test accuracy studies, and introduces QUADAS-AI and modified QUADAS-2. Moreover, this paper summarizes reporting guidelines of these studies as well, and then introduces specific reporting standards in AI-centred research, and checklist for AI in dental research.
The utilisation of statistical analysis plan (SAP) has the potential to enhance the reliability, transparency, and impartiality of statistical analysis procedures in the context of clinical studies. These plans are primarily designed for late phase clinical studies, namely phase Ⅱ and phase Ⅲ randomised controlled trials. The extended SAP reporting guidelines for early phase clinical studies, i.e., phase Ⅰ clinical studies and phase Ⅱ non-randomised controlled trials, have been expanded from the original reporting guidelines in six key areas: trial purpose, design, Bayesian statistics, data simulation, sample size, and the application of ICH E9(R1). The expanded reporting guidelines facilitate the standardisation of SAP for early phase clinical trials, enhance the transparency and reproducibility of early phase clinical studies, and thereby improve the quality of early phase clinical studies. This, in turn, plays a pivotal role in later phase clinical studies.