Surrogate endpoints, defined as biomarkers or intermediate outcomes utilized in clinical trials to replace the ultimate targeted outcomes, have witnessed a growing prevalence in both clinical trials and drug-device approvals in recent years. To standardize the application and reporting of surrogate endpoints in clinical trial protocols and associated studies, relevant scholars published the SPIRIT-Surrogate and CONSORT-Surrogate reporting guidelines in the BMJ in July 2024. This article provides an interpretation of these guidelines in conjunction with published case studies, with the aim of offering references for domestic researchers, elevating the overall quality of related clinical trials, and eventually facilitating the enhancement of domestic healthcare level.
Purpose
To study the possibility of prevention of proliferative vitreoretinopathy（PVR） by transduction of exogenous gene in vivo．
Methods
PVR model of rabbits was induced by intravitreal injection of fibroblasts．beta;-galactosidase (lacZ) gene as a reporter gene was transfered into the vitreous of PVR model eyes mediated by retroviral vector, and the expression of the gene in eye tissues was determined ． Gene transfection was done on the 6th day after fibroblasts injection,and the dosage of intravitreal injection of reporter gene was 0．1ml PLXSN/lacZ serum-free supernatant (1．1times;106 cfu/ml)．
Results
lacZ gene expression was seen in proliferative membranes after gene transfection, and the expression was located maily at the surface of PVR membrane．The reporter gene expression lasted at least more than 30 days．No expression was found in retinal tissues．
Conclusions
Retrovirus mediated gene can be directionally transducted in PVR membrane,and might possess the feasibility of gene therapy for PVR．
(Chin J Ocul Fundus Dis, 2001,17:224-226)
Structured template and reporting tool for real world evidence (STaRT-RWE) was developed by a team led by professor Shirley V Wang of Brigham and Women's Hospital, Harvard Medical School, which is to plan and report on the implementation of real world evidence (RWE) studies on the safety and efficacy of treatments. The template, published in the journal BMJ in January 2021, has been endorsed by the International Society of PharmacoEpidemiology and the Transparency Initiative promoted by the International Society of Pharmacoeconomics and Outcome Research. This article interprets its entries to promote the understanding and application of STaRT-RWE by domestic scholars engaged in real world study, and help to improve the transparency, repeatability, and accuracy of RWE research.
This paper introduces the development and changes of clinical practice guidelines based on the enlightenment of the Reporting Items for Practice Guidelines in Health Care (RIGHT), and provides policy recommendations.
Objective
To evaluate the quality of randomized controlled trials (RCTs) of traditional Chinese medicine published inChinese Journal of Integrated Traditional and Western Medicine, and to analyze changes.
Methods
We searched CNKI to collect RCTs published inChinese Journal of Integrated Traditional and Western Medicine (CJITWM) in 2014. Reporting quality of RCTs was evaluated by using CONSORT 2010 checklist, the methodological quality and ethics requirements were also analyzed. The changes of quality was also analyzed by comparing with those of 2004.
Results
A total of 80 RCTs were included. The top three interventions were Chinese patent medicine, decoction, acupuncture. Items with high reporting rate (>80%) included abstract, participants, randomization sequences and informed consent. Items with reporting rate of 50% to 80% including introduction, interventions, harms and funding, and others were all less than 50%. Among them, the reporting quality of title, trial design, outcomes, sample size, type of randomization, allocation concealment, blinding, numbers analyzed, outcomes and estimation, generalizability, interpretation, registration and protocol was less than 10%. Compared with those of 2004, the quality of reporting, methodology, and ethics has all increased. Significant progress was made in items of structured summary, background and objectives, collecting participants, adverse reactions, quality control standards of TCM interventions, diagnostic evaluation criteria of TCM, follow-up, funding, ethical approval and informed consent. But small progress was made in randomization, allocation concealment and implementation, sample size, blinding and ITT. There has been no participant flow.
Conclusion
The quality of reporting, methodology, and ethics of RCTs published inChinese Journal of Integrated Traditional and Western Medicine have made some progress, however, trial design, outcomes selection, estimation of sample size, randomization, blinding, registration and participant flow are still needed to be further improved.
Objectives
To evaluate the reporting quality of Bland-Altman method consistency evaluation in China from 2014 to 2016.
Methods
WanFang Data, VIP and CNKI databases were electronically searched to collect literature about the application of Bland-Altman method from 2014 to 2016 in China. Two reviewers screened literature, extracted data, and the data were then statistically analyzed by SPSS 22.0 software.
Results
A total of 376 articles were included. The published articles on Bland-Altman method had major flaws (not conforming to reporting standards) in the application conditions, evaluation indexes, graphic depiction and so on. Merely 11.4% of the literature set the clinically acceptable consensus values in the pre-period studies. Merely one literature (0.3%) correctly compared the 95%CI of 95%LoA with the clinically acceptable threshold which had been set previously. The offer rates of the differences between the two measurements and the 95%CI, 95%LoA and 95%CI of 95%LoA in the figure were 95.9%, 9.5%, 94.6% and 4.4%, respectively.
Conclusions
The reporting quality of Bland-Altman method consistency evaluation in China is of low quality, specifically not conforming to reporting standards. We should strengthen the introduction of Bland-Altman methodology to improve the reporting quality.
With the increasingly prominent contradiction between limited health resources and the growing population, priority setting of health research, as a response, has received widespread attention from health systems worldwide. As the results of priority setting at different levels increase year by year, some questions in the results reporting are also constantly emerging. For example, the process of producing the results is vague, too dependent on individual subjective judgment, the participation of individual stakeholder groups is limited or lack of voice, unable to identify potential conflicts of interest, and so on. It does not only seriously affect the effectiveness and rationality of the results themselves, but also create intangible obstacles to their promotion and adoption. In 2019, BMC Medical Research Methodology published ‘Reporting guideline for priority setting of health research (REPRISE)’, which makes uniform specifications for more comprehensive and consistent reporting of results in priority areas. This paper interpreted the background, formulation process and key contents of the REPRISE guideline, with an aim to promote the application of the reporting guideline in China.
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.
