Consensus reporting items for studies in primary care (CRISP) is a newly developed measurement tool developed abroad to standardize primary health care research, so as to improve the quality of reporting and enhance the applicability, comprehensiveness, transparency and operability of reporting. The report contains 24 Entries that follow the Introduction, Methods, Results, Discussion (IMRaD) format, and is primarily concerned with describing the research team, the patients, the study subjects, the health status, the clinical experience, the health care team, the interventions, the study interventions, and the findings in the PHC study / implementation of results, etc. This article introduces and interprets the reporting guidelines to help researchers better understand and apply this statement to improve the quality of reporting in primary health care research
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.
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 potential value of clinical big data have been gradually realized, and disease prediction models have begun to become a hot spot in clinical research. Predictive models of different types of diseases play an increasingly important role in individual risk assessment. However, due to the lack of reporting specifications for studies on disease prediction model, the structure and quality of reports are mostly mixed. In 2015, BMJ published a paper entitled "Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement" stated that there should be a uniform study of predictive models for disease diagnosis and prognosis. This article interprets key contents of the statement to promote research and understanding of the report specification.
Objective The aim of this study is to construct reporting standards for acupuncture network meta-analysis, providing guidance to enhance the quality of evidence reported in acupuncture therapy research. Methods A Delphi questionnaire was developed based on the preliminary research and literature findings, 20 experts were selected for correspondence to determine the final checklists of items, and then finalized the list of report items. Results A total of two rounds of Delphi questionnaires were made. The expert positivity coefficient (100%), the expert familiarity (0.80) and the expert authority (0.83) were the same in both rounds, the Kendall's coordination coefficients were 0.117 (P<0.001) and 0.332 (P<0.001), respectively, which ultimately led to the formation of the 7 fields of title, abstract, introduction, methods, results, discussion and other, including 23 specific items of the acupuncture-related therapies NMA standards. Conclusion The PRINMA-A statement will help to improve the reporting quality of evidence on acupuncture-related therapies, promote the dissemination and translation of evidence on acupuncture-related therapies.
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.
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.
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.
Artificial intelligence has been extensively applied in healthcare services recently, and clinical decision support systems driven by artificial intelligence are one of the applications. Early-stage clinical evaluation of artificial intelligence (AI)-based clinical decision support systems lies between preclinical development (in silico), offline validation, and large-scale trials, but few AI-related clinical studies have addressed human factors evaluations and reported the implementation environment, user characteristics, selection process and algorithm identification of AI systems. In order to bridge the development-to-implementation gap in clinical artificial intelligence and to promote the transparent and standardized reporting of early-stage clinical studies of AI-based decision support systems. A reporting guideline for the developmental and exploratory clinical investigations of decision support systems driven by artificial intelligence (DECIDE-AI) was published in 2022. This paper aimed to interpret the background, development process and key items of the DECIDE-AI guideline and promote its understanding as well as dissemination in China.
ObjectiveTo select the key questions of the reporting quality of acupuncture therapy network meta-analysis. MethodsA question pool about reporting quality of acupuncture therapy network meta-analysis was conducted by preliminary literature research and qualitative systematic review. A correspondence questionnaire was designed and the selection of key questions was carried out through two rounds of expert consultation using the Delphi method. ResultsA total of 21 key questions were selected for the network meta-analysis report standard of acupuncture, including whether to report details of acupuncture interventions (e.g., needle type, acupoints used, number of needles inserted, depth of needle insertion, retention time, needling techniques, and treatment duration), diagnostic criteria for diseases or traditional Chinese medicine syndromes, and qualifications of acupuncture practitioners. Of these, the only three key questions answered by the preferred reporting items for systematic reviews and network meta-analysis (PRISMA-NMA) were summary, protocol and registration, and source of funding, while the remaining 19 were specific to acupuncture-related report standards. ConclusionThe conducted key question on reporting guideline of acupuncture network meta-analysis can improve the standardization and rigor of relevant research and better utilize its academic and clinical value.