With the gradual standardization and improvement of the real-world study system, real-world evidence, as a supplement to evidence from classical randomized controlled trials, is increasingly used to evaluate the effectiveness and safety of pharmaceuticals and medical devices. High-quality real-world evidence is not only related to the quality of real-world data, but also depends on the type of study design. Therefore, as one of the important designs for pragmatic clinical trials, the Zelen design has received much attention from investigators in recent years. This paper discussed the implementation processes, subtypes of design, advantages, limitations, statistical concerns, and appropriate application scenarios of the Zelen design, on the basis of published papers, in order to clarify its application value, and to provide references for future research.
Given the growing importance of real-world data (RWD) in drug development, efficacy evaluation, and regulatory decision-making, establishing a scientific and systematic data quality regulatory framework has become a strategic priority for global pharmaceutical regulatory authorities. This paper analyzed the EU's advanced practices in RWD quality regulation, compared the RWD quality regulatory systems of China and the EU, and aimed to derive implications for enhancing China's own framework. The EU has made significant progress by promoting the interconnection, intercommunication, and efficient utilization of data resources, implementing a collaborative responsibility mechanism spanning the entire data lifecycle, developing a standardized, tool-based quality assessment system, and facilitating international cooperation and alignment of rules. While China has established an initial regulatory system for RWD quality, it still confronts challenges such as unclear mechanisms for data acquisition and utilization, underdeveloped operational standards, and unclear responsibility delineation. In contrast, by adapting relevant EU experience, China can refine its regulatory framework, establish mechanisms for the interconnection, intercommunication, and efficient utilization of RWD, develop more practical quality assessment toolkits, improve the lifecycle responsibility-sharing mechanism, and promote the alignment of RWD quality regulation with international standards. These enhancements will advance the standardization and refinement of RWD quality regulation in China, ultimately strengthening the scientific rigor and reliability of regulatory decisions.
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.
The application of economic tools to evaluate the cost and health benefits and screen out more cost-effective drugs and technologies is an important measure to improve efficiency of medical resource allocation in China. Given the inherent differences between strict clinical trials and clinical routine practice, using trial-based economic evaluations to guide relevant medical decisions may lead to a certain risk of value deviation. Recent development of real-world data provides opportunities to assess the cost-effectiveness of drugs under the practical utilization, and has gradually become a new research hotspot. However, the complexity of the actual clinical environment also puts higher demands on researchers and decision makers to construct, understand and apply real-world evidence. In order to further prompt the normalization of economic evaluation based on real-world data and promote the scientific application of real-world evidence in medical and health decision-making, this project aims at the crucial issues including scope, research design and quality evaluation, to clarify the key considerations on the using of real-world evidence in medical decision-making. Combined with the international guidelines, the latest advancement of relevant research areas and the advice and opinions from multidisciplinary experts, we aim to provide technical references and guidance for researchers and decision makers, and to strengthen the evidence base of management policies.
ObjectiveTo evaluate the efficacy and safety of dupilumab in the treatment of moderate-to-severe asthma. MethodsA retrospective study was conducted among patients with moderate-to-severe asthma who were treated with dupilumab and inhaled corticosteroids (ICS) combined with long acting beta-agonist (LABA) in Department of Respiratory, Beijing Chao-yang Hospital from May, 2021 to April, 2022. Paired t-test or Mann-Whitney U test was applied to compare the Asthma Control Test (ACT) scores, number of acute exacerbations per year, type 2 inflammatory biomarkers, blood total IgE and results of pulmonary function tests, including forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1), FEV1 as percentage of predicted (FEV1%pred), FEV1/FVC, peak expiratory flow (PEF), maximal expiratory flows (MEF) at 75% (MEF75), 50% (MEF50) and 25% (MEF25) of the vital capacity PEF, and maximal mid-expiratory flow (MMEF) or FEF25%-75%, at the end of follow-up with those before treatment. Adverse reactions were recorded during the treatment. ResultsA total of 47 patients with moderate-to-severe asthma were included in the study, among them 17 and 30 received treatment with dupilumab or ICS/LABA. At the time of 12 months after treatment with dupilumab, the patients' ACT score and pulmonary function tests were significantly increased compared with those at the baseline. In contrast, patients' fractional exhaled nitric oxide (FeNO), blood total IgE, blood basophil counts and annual acute exacerbations were significantly decreased in comparison with those at the baseline. The doses of oral corticosteroids added by 7 patients at the baseline was gradually reduced and finally discontinued after treatment of dupilumab. There were 4, 2, 1 and 1 patients developed injection site reaction, pruritus, erythema and fatigue, respectively, which were mild and recovered without treatment. There was no serious adverse reaction observed, and only 1 case developed herpes zoster which was recovered after treatment. ConclusionDupilumab shows marked efficacy in the treatment of moderate-to-severe asthma with favorable safety.
Focusing on research quality is a crucial aspect of modern evidence-based medical practice, providing substantial evidence to underpin clinical decision-making. The increase in real-world studies in recent years has presented challenges, with varying quality stemming from issues such as data integrity and researchers’ expertise levels. Although systematic reviews and meta-analyses are essential references for clinical decisions, their reliability is contingent upon the quality of the primary studies. Making clinical decisions based on inadequate research poses inherent risks. With the lack of a specialized tool for evaluating the quality of real-world studies within systematic reviews and meta-analyses, the Gebrye team has introduced a new assessment tool - QATSM-RWS. Comprising 5 modules and 14 items, this tool aims to improve real-world research evaluation. This article aims to elaborate on the tool’s development process and content, using this tool to evaluate a published real-world study as an example and providing valuable guidance for domestic researchers utilizing this innovative tool.
Diabetic retinopathy (DR), which is a common complication of diabetic and the main cause of blindness, brings not only a heavy economic burden to society, but also seriously threatens to the patients’ quality of life. Clinical researches on the therapies of DR are active at present, but how to perform a good clinical research with scientific design should be considered with high priority. The randomized controlled trial (RCT) is considered to be the gold standard for evidence-based medicine, but RCT is not always perfect. Limitations still exist in certain circumstance and the conclusions from RCTs also need to be interpreted by an objective point of view before clinical practice. Real world study (RWS) bridges the gap between RCT and clinical practice, in which the data can be easily collected without much cost, and results might be obtained within a short period. However, RWS is also faced with the challenge of not having standardized data and being susceptible to confounding bias. The standardized single disease database for DR and propensity score matching method can provide a wide range of data sources and avoid of bias for RWS in DR.
The artificial neural network has the ability of the information processing and storage, good adaptability, strong learning function, association function and fault tolerance function. The research on the artificial neural network is mostly focused on the dynamic properties due to fact that the applications of artificial neural networks are related to its dynamic properties. At present, the researches on the neural network are based on the hierarchical network which can not simulate the real neural network. As a high level of abstraction of real complex systems, the small world network has the properties of biological neural networks. In the study, the small world network was constructed and the optimal parameter of the small word network was chosen based on the complex network theory firstly. And then based on the regulation mechanism of the synaptic plasticity and the topology of the small world network, the small world neural network was constructed and dynamic properties of the neural network were analyzed from the three aspects of the firing properties, dynamic properties of synaptic weights and complex network properties. The experimental results showed that with the increase of the time, the firing patterns of excitatory and inhibitory neurons in the small world neural network didn’t change and the firing time of the neurons tended to synchronize; the synaptic weights between the neurons decreased sharply and eventually tended to be steady; the connections in the neural network were weakened and the efficiency of the information transmission was reduced, but the small world attribute was stable. The dynamic properties of the small world neural network vary with time, and the dynamic properties can also interact with each other: the firing synchronization of the neural network can affect the distribution of synaptic weights to the minimum, and then the dynamic changes of the synaptic weights can affect the complex network properties of the small world neural network.
ObjectiveTo explore the association between frailty and in-hospital mortality in older patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD). Methods Elderly patients who were hospitalized with AECOPD from June 2022 to December 2022 at a large tertiary hospital were selected. The independent prognostic factors including frailty status were determined by multivariate logistic regression analysis. Mediation effect analysis was used to evaluate the mediating relationships between C-reactive protein (CRP) and albumin and in-hospital death. ResultsThe training set included 1 356 patients (aged 86.7±6.6), 25.0% of whom were diagnosed with frailty. The multiple logistic regression analysis showed that frailty, mean arterial pressure, Charlson comorbidity index, neutrophil–lymphocyte ratio, interleukin-6, CRP, albumin, and troponin T were associated with in-hospital mortality. Furthermore, CRP and albumin mediated the associations between frailty and in-hospital mortality. ConclusionFrailty may be an adverse prognostic factor for older patients admitted with an AECOPD. CRP and albumin may be parts of mechanism between frailty and in-hospital death.
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.