The research on brain functional mechanism and cognitive status based on brain network has the vital significance. According to a time–frequency method, partial directed coherence (PDC), for measuring directional interactions over time and frequency from scalp-recorded electroencephalogram (EEG) signals, this paper proposed dynamic PDC (dPDC) method to model the brain network for motor imagery. The parameters attributes (out-degree, in-degree, clustering coefficient and eccentricity) of effective network for 9 subjects were calculated based on dataset from BCI competitions IV in 2008, and then the interaction between different locations for the network character and significance of motor imagery was analyzed. The clustering coefficients for both groups were higher than those of the random network and the path length was close to that of random network. These experimental results show that the effective network has a small world property. The analysis of the network parameter attributes for the left and right hands verified that there was a significant difference on ROI2 (P = 0.007) and ROI3 (P = 0.002) regions for out-degree. The information flows of effective network based dPDC algorithm among different brain regions illustrated the active regions for motor imagery mainly located in fronto-central regions (ROI2 and ROI3) and parieto-occipital regions (ROI5 and ROI6). Therefore, the effective network based dPDC algorithm can be effective to reflect the change of imagery motor, and can be used as a practical index to research neural mechanisms.
Objective Risk factors for real-word immune checkpoint inhibitor-related pneumonitis in patients with lung cancer were analyzed by systematic analysis. Methods Computerized retrieval of PubMed, EMbase, Web of Science, the Cochrane Library , WanFang Data, CNKI and VIP databases was carried out. Studies were collected from the database establishment to March 2023. Three researchers independently screened the literature, extracted data, and evaluated the risk of bias in the included studies. Meta-analysis was performed using RevMan5.4.1software. Results A total of 18 studies were included with a total of 4 990 patients. The results of meta-analysis showed that, interstitial pneumonia [odds ratio (OR)=9.32, 95% confidence interval (CI) 4.66 - 18.67, P<0.01], smoking history (OR=2.39, 95%CI 1.29 - 4.45, P<0.01), chronic obstructive pulmonary disease (COPD) (OR=5.54, 95%CI 2.96 - 10.36, P<0.01), chest radiotherapy (OR=2.74, 95%CI 1.80 - 4.19, P<0.01), pulmonary fibrosis (OR=7.46, 95%CI 4.25 - 13.09, P<0.01), high programmed death ligand 1 (PD-L1) expression (OR=2.98, 95%CI 1.71 - 5.22, P<0.01), high absolute eosinophil count (AEC) (OR=3.92, 95%CI 2.17 - 7.08, P<0.01) and pembrolizumab (OR=2.90, 95%CI 1.56 - 5.37, P<0.01) were independent risk factors for immune checkpoint inhibitor-related pneumonitis in lung cancer patients. Conclusions Interstitial pneumonia, smoking history, COPD, Chest radiotherapy, pulmonary fibrosis, high PD-L1expression, high AEC and pembrolizumab are independent risk factors for immune checkpoint inhibitor-related pneumonitis in lung cancer patients. Due to insufficient evidence on the risk factors of low albumin, more studies are needed to further identify it.
Assessing the clinical value of pharmaceuticals is crucial for comprehensive evaluation in clinical practice and plays a vital role in supporting decision-making for drug supply assurance. Real-world data (RWD) offers valuable insights into the actual diagnosis and treatment processes, serving as a significant data source for evaluating the clinical demand, effectiveness, and safety of drugs. This technical guidance aims to elucidate the scope of application of RWD for the clinical value assessment of pharmaceuticals, as well as the key considerations for conducting value assessment research. These considerations include identifying the dimensions of clinical value that necessitate RWD and effectively utilizing RWD for evaluation purposes. Additionally, this guidance provides essential points for implementing pharmaceutical clinical value assessment based on real-world data, with a specific focus on study design and statistical analysis. By doing so, this guidance assists researchers in accurately comprehending and standardizing the utilization of real-world research in conducting pharmaceutical clinical research.
Real-world data studies have experienced rapid development in recent years, however, misunderstandings persist. This paper aims to improve practice and promote standardization by updating the categorization of real-world data, proposing two conceptual frameworks for conducting real-world data studies, developing the concepts of research data infrastructure and clarifying the misconceptions on registry database, and discussing future development.
ObjectivesTo analyze the active areas of real world studies on traditional Chinese medicine in China.MethodsCBM, CNKI, WanFang Data, PubMed and EMbase databases were electronically searched to collect real world studies on traditional Chinese medicine in China from inception to 26th April, 2018. The main research contents (research direction, data sources, and research methods) by Excel were extracted, together with the primary information by BICOMS-2 software and production of the network figures by NetDraw 2.084 software.ResultsEventually, 373 real world studies in traditional Chinese medicine were included, in which the initial one was punished in 2008. The top three ranking of authors involved in real world studies on traditional Chinese were Xie Yanming, Zhuang Yan, Yang Wei, and the top three ranking of institutions were Institute of Basic Research in Clinical Medicine of China Academy of Chinese Medical Sciences, School of Statistics of Renmin University of China, and the PLA Navy General Hospital. The amount of related studies in Beijing accounted for 74.26%. It was found that the active areas involve real world, hospital information system, real world study, drug combination, and propensity score method. In terms of the main studied contents on the use of traditional Chinese medicine in the real world, in which the top three were Fufang Kushen injection, Dengzhanxixin injection, and Shuxuetong injection. Digestive system disease, nervous system disease and cardiovascular disease received the highest attention rate, specifically stroke, coronary heart disease, virus hepatitis and hypertension. 58.18% studies were retrospective studies, 49.60% of the information were from the hospital information system, and 56.30% studies used data mining to carry out statistical analysis.ConclusionsMost real world studies on traditional Chinese medicine are based on HIS, and use data mining to study Chinese medicine preparations. The research attention on Chinese medicine is higher than that of the method of diagnosis and treatment, similarly the Chinese medicine preparations is higher than traditional Chinese medicine. In future, attention should be paid to traditional Chinese medicine, prescription and traditional methods of diagnosis and treatment, such as moxibustion and scraping.
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.
Randomized controlled trials are considered as the gold standard for determining the causality, and are usually used to evaluate the efficacy and safety of medical interventions. However, in some cases it is not feasible to conduct a randomized controlled trial. In recent years, a framework called “target trial emulation study” has been formally established to guide the design and analysis of observational studies based on real-world data. This framework provides an effective method for causal inference based on observational studies. In order to facilitate domestic scholars to understand and apply the framework to solve related clinical problems, this article introduces it from the basic concept, framework structure and implementation steps, development status, and prospects.
ObjectiveTo analyze the status of real world studies (RWS) through registration information of the Chinese Clinical Trials Registry (ChiCTR). MethodsThe website of ChiCTR was searched with the real world as the search term to collect relevant registered items in the real world from inception to May 4, 2022. Descriptive analysis method was used. ResultsA total of 642 registered items were included. The median sample size was 482 cases. RWS were mainly observational studies, and the number of intervention studies was increasing year by year. There were 267 studies (41.59%) at the stage of post-marketing drugs or phase Ⅳ clinical trials. Most of the main measures were endpoints (56.23%), and the most commonly used was overall survival (15.79%). 62.15% of the registered projects met the minimum requirements for registration. ConclusionThe number of RWS registered by ChiCTR shows an increasing trend. At present, the research purpose of RWSs is unclear, and the completeness of registered studies and the overall content compliance of the studies need to be improved.
Traditional Chinese medicine (TCM) has a long history. In the process of fighting against diseases, TCM has formed a unique theoretical system and the way to think and diagnose. The holistic thinking, and the treatment according to syndrome differentiation are the most prominent characteristics of TCM, which matches with advanced medical concept and direction. The clinical efficacy has always been the basis for the advancement of TCM. However, issues such as the lagging behind of modern research on the evaluation of TCM curative effect, as well as lacking high-quality scientific research evidence, impede the development and promotion of the TCM toward the world. To address the above problems, recent progress in real-word study (RWS) has provided the opportunity for TCM researches, especially for the post-marketing evaluation of Chinese patent medicine (CPM). The formulation of this technical guidance for RWS of CPM is helpful to researchers in carrying out standardized, reasonable and scientific researches, to improve the quality of production and use of real-word evidence, and to promote the advancement of the TCM industry.
Objectives To evaluate the clinical outcomes and identify its associated factors in patients with acute coronary syndromes (ACS) in Tianjin city. Methods Data were obtained from Tianjin urban employee basic medical insurance database. Adult patients who were discharged alive after the first ACS-related hospitalization (the index hospitalization) during January, 2012 to December, 2014 and without malignant tumor were included. Clinical outcomes were measured by subsequent major adverse cardiovascular events (MACE) including hospitalization for myocardial infarction (MI) or stroke, all-cause death, or their composite endpoint. Cox model was used to explore the factors associated with MACE. Results 22 041 patients were identified, in which 9.5% experienced MACE during follow-up with a mean number of 1.3 MACEs. 3.1% of patients had MI, 5.7% had stroke and 1.4% had all-cause death. Among patients who experienced MACEs, the average time from index discharge to the 1st MACE was 143.2 days. Patients being older, male or had higher Charlson Comorbidity Index (CCI) were more likely to experience MACE. Patients who had prior stroke and prior all-cause hospitalization were also more likely to experience MACE, whereas patients who had prior angina, prior β-blockers utilization and received percutaneous coronary intervention (PCI) during index event were less likely to experience MACE. Conclusion Stroke is the most common type of MACE among ACS patients in Tianjin, China. Almost half of the 1st MACE occur within the 3 months after ACS. Patients who are older, male, have higher CCI or have prior stroke are at higher risk of MACE.