An intervention with clinical application must be effective and safe, therefore, when evaluating interventions, the benefit-harm ratio should be considered, and only those interventions with more benefits than harms have application value. To evaluate the benefits and harms of an intervention evidence of both benefits and harms should be reported in clinical trials. To promote better reporting of harms in randomized controlled trials, the CONSORT group had added an entry on harms in the 2001 version of the CONSORT statement, and then in 2004, the CONSORT group developed the CONSORT Harms extension; however, it has not been consistently applied and needs to be updated, the reporting of harms is still inadequate. The CONSORT group has updated《Better reporting of harms in randomized trial: an extension of the CCONSORT statement.》, published《CONSORT Harms 2022 statement, explanation, and elaboration: updated guideline for the reporting of harms in randomized trials》. This article presents and explains the Harms 2022, with the aim of helping researchers better understand and use the statement, with a view to improving the reporting quality of harms in clinical trials.
In recent years, the number of randomized controlled trials using cohorts and routinely collected data (e.g., electronic health records, administrative databases, and health registries) has increased. Such trials can ease the challenges of conducting research and save cost and time. Accordingly, to standardize such trials and increase the transparency and completeness of research reports, an international panel of experts developed the CONSORT-ROUTINE (2021) reporting guideline. The reporting guideline was published in 2021 in the BMJ. To help understand and formally apply the reporting guideline and improve the overall quality of this type of study, the present paper introduced and interpreted the development process and reporting checklist of the CONSORT-ROUTINE.
The burgeoning application of large language models (LLM) in healthcare demonstrates immense potential, yet simultaneously poses new challenges to the standardization of research reporting. To enhance the transparency and reliability of medical LLM research, an international expert group published the TRIPOD-LLM reporting guideline in Nature Medicine in January 2024. As an extension of the TRIPOD+AI guideline, TRIPOD-LLM provides detailed reporting items specifically tailored to the unique characteristics of LLMs, including general foundational models (e.g., GPT-4) and domain-specific fine-tuned models (e.g., Med-PaLM 2). It addresses critical aspects such as prompt engineering, inference parameters, generative evaluation, and fairness considerations. Notably, the guideline introduces an innovative modular design and a "living guideline" mechanism. This paper provides a systematic, item-by-item interpretation and example-based analysis of the TRIPOD-LLM guideline. It is intended to serve as a clear and practical handbook for researchers in this field, as well as for journal reviewers and editors responsible for assessing the quality of such studies, thereby fostering the high-quality development of medical LLM research in China.
ObjectiveTo investigate the application status of survival analysis in studies published in Chinese oncology journals, and assess their reporting quality and summarize the existing problems, so as to promote the application of survival analysis and reporting quality.
MethodsStudies that used survival analysis were collected from 1 492 studies published in Chinese Journal of Oncology, Chinese Journal of Clinical Oncology, Chinese Journal of Radiation Oncology and Chinese Journal of Cancer Prevention and Treatment in 2013. The application status of survival analysis of included studies was analysed and their reporting quality was evaluated.
ResultsA total of 242 survival analysis studies were included. Among them, the utilization rates of Kaplan-Meier method, life table method, log-rank test, Breslow test and Cox proportional hazards model were 91.74%, 3.72%, 78.51%, 0.41% and 46.28%, respectively. 112 studies did multivariate analysis through Cox proportional hazards model. A total of 396 end points and 10 different types of survival time were reported. Overall survival (OS) was reported in 233 studies (92.15%). Survival terms were defined to 158 end points (39.90%) of 103 studies (42.56%). The follow-up rates were mentioned in 155 studies (64.05%), of which 4 studies were under 80% and the lowest was 75.25%, 55 studies were 100%. The main problems of survival analysis studies published in Chinese journals were as follows:None of the studies which used Cox proportional hazards model reported the proportional hazards assumption. None of the studies used the method of parametric survival analysis. 130 studies (53.72%) did not use the method of multiple factor analysis. 139 studies (57.44%) did not define the survival terms. Only 11 of 100 studies which reported loss to follow-up had stated how to treat it in the analysis. None of the studies reported the methods of calculating sample size. None of the studies reported the censoring proportion.
ConclusionThe methods of survival analysis are used in a low rate in studies published in Chinese oncology journals, and the overall reporting quality of survival analyses is poor. So the reporting guideline of survival analysis should be developed and the authors should be encouraged to cooperate with professional statisticians, in order to improve the design, analysis and reporting quality of survival analysis studies.
In order to standardize the reporting of sham acupuncture and improve the quality of reporting of sham acupuncture, Beijing University of Chinese Medicine has developed a specific reporting guideline for sham acupuncture: SHam Acupuncture REporting (SHARE) which contains ten categories with nineteen items. This paper introduces the development methods and main contents of the guidelines to provide a reference for researchers to correctly understand and reasonably apply the guidelines.
Chinese medicine case report, a special method, records the experience of practitioners and guides students to inherit and develop Chinese medicine. It can transfer a large amount of medical and humanistic information and contribute to the development of Chinese medicine. It is a literary style that has been widely accepted and helps to document and disseminate the culture of Chinese medicine. With the advent of big data and information, more Chinese medicine case reports have been published. However, many have insufficient quality to properly guide and apply in the clinical practice, which might be caused by little guidance of Chinese medicine case report standards published. This paper summarized the case report standards, synthesized and appraised the feasibility and problems specific for improving the quality of Chinese medicine case reports, and proposed suggestions and guidance for developing the standardization of Chinese medicine medical case reports.
This study aimed to provide suggestions for future researchers to select and optimize sham acupuncture reporting guidelines in acupuncture clinical trials. Through qualitative analysis, we compared the basic information and concrete contents between Acupuncture Controls gUideline for Reporting humAn Trials and Experiments (ACURATE) and SHam Acupuncture REporting guidelines in clinical trials (SHARE) developed by researchers from China and Korea. In addition, the similarities and differences of the two guidelines were illustrated through a specific case. We found that the two guidelines had their own characteristics and emphasis in content, but both emphasized the reports of detailed information and background factors of sham acupuncture compared with the previous STRICTA and TIDieR-Placebo checklist. In terms of item division, we found that the ACURATE split the same topic into several items to emphasize the importance of each item content. SHARE emphasized the comprehensive reports of sham acupuncture by combining several items into a single item. In terms of item content, ACURATE also focused on combination therapy, the information regarding sham acupuncture provided to participants, and any differences in treatment settings between versus/sham acupuncture, which had some referential meaning for setting sham acupuncture control. SHARE also focused on sham acupuncture detailed information, practitioner, and modifications, etc. Case analysis showed that there were some "not reported" or "partially reported" items in both guidelines. Therefore, it is suggested that researchers can use the above two guidelines to complement and learn from each other to report sham acupuncture. In addition, it is necessary for researchers to verify the operability and practicability of the above two guidelines, and provide suggestions for optimizing and updating them in the future.
To standardize and improve the reporting quality of implementation studies, BMJ published the standards for reporting implementation studies (StaRI). This paper introduces the background and process of StaRI development, and interprets the core content of StaRI. It is expected that StaRI will provide support for domestic researchers to carry out implementation studies and writing implementation research reports.
Clinical prediction models typically utilize a combination of multiple variables to predict individual health outcomes. However, multiple prediction models for the same outcome often exist, making it challenging to determine the suitable model for guiding clinical practice. In recent years, an increasing number of studies have evaluated and summarized prediction models using the systematic review/meta-analysis method. However, they often report poorly on critical information. To enhance the reporting quality of systematic reviews/meta-analyses of prediction models, foreign scholars published the TRIPOD-SRMA reporting guideline in BMJ in March 2023. As the number of such systematic reviews/meta-analyses is increasing rapidly domestically, this paper interprets the reporting guideline with a published example. This study aims to assist domestic scholars in better understanding and applying this reporting guideline, ultimately improving the overall quality of relevant research.
To improve the comprehensive and accurate of overviews of reviews, BMJ published the guideline for overviews of reviews of healthcare interventions: the PRIOR statement. This paper explained the background and core contents of PRIOR statement and interpreted each item with examples to provide references for domestic scholars to write overviews of reviews.
