A patient registry database is an important source of real-world data, and has been widely used in the assessment of drug and medical devices, as well as disease management. As the second part of the serial technical guidance for real-world data and studies, this paper introduces the concept and scope of potential uses of patient registry databases, proposes recommendations for planning and developing a patient registry database, and compares existing health and medical databases. This paper further develops essential quality indicators for developing a patient registry database, in expect to guide future studies.
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.
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 formation, evaluation and grade division of real-world evidence (RWE) are bottlenecks restricting the in-depth development and scientific application of real-world study methods. This paper briefly reviewed the design grade and evidence grade of clinical medical research, and proposed the key points of evidence grade of real-world clinical research, including emphasizing the comprehensive evaluation of internal authenticity and external authenticity, determining the "starting point" of real-world evidence, and using the real-world evidence quality evaluation method. Based on the internationally recognized "grading of recommendations assessment, development, and evaluation (GRADE)", combined with the classification and characteristics of real-world evidence, a preliminary grading scheme was formed. An example was given to illustrate the grading suggestion.
ObjectiveTo evaluate changes in operational effectiveness after the implementation of ambulatory surgical management in pars plana vitrectomy (PPV). MethodsA retrospective clinical study. 17 528 surgeries in 10 895 eyes of 10 895 patients who underwent minimally invasive PPV on an ambulatory and/or inpatient basis at Tianjin Medical University Eye Hospital from August 2015 to June 2023 were included in this study. Among them, 5 346 eyes in 5 346 cases were male; 5 549 eyes in 5 549 cases were female. The age ranged from 0 to 95 years, with the mean age of (57.74±13.15) years. 6 381 surgeries in 3 615 eyes from August 2015 to December 2018 (the initial period of day surgery) were used as the control group; 11 147 surgeries in 7 280 eyes from January 2019 to June 2023 (the expanded period of day surgery) were used as the observation group. According to the management mode of ambulatory surgery, the observation group was subdivided into the decentralized management group (January 2019 to December 2020) and the centralized management group (January 2021 to June 2023), with 2 905 and 4 375 eyes and 4 646 and 6 501 surgeries, respectively. Changes in the percentage of day surgery, average hospitalization days, and average unplanned reoperation rate were compared. The Mann-Whitney U test was used to compare numerical variables between groups; the chi-square test or Fisher's exact test was used to compare categorical variables. ResultsThe number of cases of daytime PPV performed in the observation group and control group was 7 852 (70.44%, 7 852/11 147) and 24 (0.38%, 24/6 381) cases, respectively, and the average hospitalization days were 1 (1) and 5 (3) d. Compared with the control group, the observation group had a significantly higher percentage of day surgery (χ2=8 051.01) and a considerably lower mean hospitalization day (Z=4 536 844.50), and the differences were statistically significant (P＜0.000 1). The mean hospitalization days in the decentralized and centralized management groups were 2 (3) and 1 (0) d, respectively, and unplanned reoperations were 34 (0.73%, 34/4 646) and 171 (2.63%, 171/6 501) eyes, respectively. Compared with the decentralized management group, average hospitalization days was significantly lower (Z=1 436.94) and unplanned reoperation rate was significantly higher (χ2=54.10) were significantly lower in the centralized management group, both of which were statistically significant (P＜0.000 1). ConclusionPPV ambulatory management model can significantly reduce the average hospitalization day, but also results in higher rates of unplanned reoperations.
As an important source for real-world data, existing health and medical data have gained wide attentions recently. As the first part of the serial technical guidance for real-world data and studies, this report introduced the concepts, features and potential applications of existing medical and health data, proposed recommendations for planning and developing a research database using existing health and medical data, and developed essential indicators for assessing the quality of such research databases. The technical guidance may standardize and improve the development of research database using existing health and medical data in China.
ObjectiveTo explore whether education and management of medical care integration can improve asthma control. MethodsA prospective, 12-month, cohort study was undertaken in a real-world setting based on Australasian severe asthma network (ASAN). A total of 516 patients with stable asthma were consecutively recruited, who received education and management of medical care integration, and step-wise anti-asthma regimens determined by physicians’ standard practice. Furthermore, inhaled corticosteroid (ICS) adherence, lung function, asthma symptom control and exacerbation were assessed at 1, 3, 6, and 12 months. ResultsAt the end of 12 months, ICS adherence (47.7% vs. 81.5%, P<0.05), lung function, and asthma symptoms were assessed by asthma control text (ACT) [20 (16, 23) vs. 23 (21, 24), P<0.05], which were significantly improved in comparison to the status at baseline, and 86.0% of patients achieved total/well-controlled level of asthma. The exacerbation (14.2% vs. 36.2%, P<0.01) and hospitalizations (8.5% vs. 15.3%, P<0.01) because of asthma for the following year significantly decreased compared with those in the past year. The multivariate regression analysis indicated that poor ICS adherence (RR=1.52, 95%CI 1.02 to 2.25, P=0.039), depression symptoms (RR=1.19, 95%CI 1.05 to 1.34, P=0.007), and exacerbation during the past year (RR=2.81, 95%CI 1.49 to 5.27, P=0.001) were associated with an increased risk of future exacerbation. ConclusionIn a real-world setting, most of asthmatics achieve total/well-controlled asthma by education and management of medical care integration including shared decision-making between physicians and patients and step-wise anti-asthma regimens. ICS adherence and depression symptoms independently predict asthma exacerbations, and strengthening education and management of medical care integration, esp. psychological nursing, would improve asthma control levels.
Evidence-based medicine is the methodology of modern clinical research and plays an important role in guiding clinical practice. It has become an integral part of medical education. In the digital age, evidence-based medicine has evolved to incorporate innovative research models that utilize multimodal clinical big data and artificial intelligence methods. These advancements aim to address the challenges posed by diverse research questions, data methods, and evidence sources. However, the current teaching content in medical schools often fails to keep pace with the rapidly evolving disciplines, impeding students' comprehensive understanding of the discipline's knowledge system, cutting-edge theories, and development directions. In this regard, this article takes the opportunity of graduate curriculum reform to incorporate real-world data research, artificial intelligence, and bioinformatics into the existing evidence-based medicine curriculum, and explores the reform of evidence-based medicine teaching in the information age. The aim is to enable students to truly understand the role and value of evidence-based medicine in the development of medicine, while possessing a solid theoretical foundation, a broad international perspective, and a keen research sense, in order to cultivate talents for the development of the evidence-based medicine discipline.
Research of generating real-world evidence using real world data has attracted considerable attention globally. Outcome research of treatment based on existing health and medical data or registries has become one of the most important topics. However, there exists certain confusions in this line of research on how to design and implement appropriate statistical analysis. Therefore, in the fourth chapter of the series technical guidance to develop real world evidence by China REal world data and studies Alliance (ChinaREAL), we aim to provide an guidance on statistical analysis in the study to assess therapeutic outcomes based on existing health and medical data or registries.In this chapter, we first emphasize the significance of pre-specified statistical analysis plan, recommending key components of the statistical analysis plan. We then summarize the issue of sample size calculation in this content and clarify the interpretation of statistical p-value. Secondly, we recommend procedures to be considered to tackle the issue related to the selection bias, information bias and most importantly, confounding bias. We discuss the multivariable regression analysis as well as the popular causal inference models. We also suggest that careful consideration should be made to deal with missing data in real-world databases. Finally, we list core content of the statistical report.
ObjectivesTo explore the characteristics of the international clinical studies using objective performance criteria (OPC) and provide a reference to design clinical trials and determine external controls.MethodsPubMed, The Cochrane Library and EMbase databases were searched for all clinical studies which used OPC. Two reviewers independently screened literature, extracted data and descriptive analysis was then performed.ResultsA total of 51 English language articles were included. Merely one was published in 2001, and others were published between 2010 and 2018. Twenty-seven articles (27/51, 52.9%) were published between 2017 and 2018, with accumulated impact factors of 411. In the article referring to the reasons for using the objective performance criteria, reasons for using OPC study was primarily the difficulties of randomization and comparison (8/11, 72.7%). Articles with cardiovascular disease and peripheral vascular disease accounted for 86%, and articles on the effectiveness or safety of medical devices accounted for 76.5%. Single-arm trial (40), randomized controlled trials (2), case-control studies (2), case series (5) and diagnostic tests (2) were included. OPCs were mostly derived from the data of clinical trials of other similar products, national standards, specialist association standard and meta-analysis of multiple clinical studies. A total of 27 articles (27/51, 52.9%) used hypothesis testing to compare research results with objective performance goal, and 24 articles (24/51, 47.1%) used the confidence interval method.ConclusionsOPC studies are primarily used for safety intervention and effect evaluation. OPC studies are developing very rapidly, especially in the field of cardiovascular studies. Methodological details are reported reasonably sufficient. Reasons for using OPC study are primarily the difficulties of randomization and comparison. Factors such as source of the OPC, sample size, and comparison method should be taken into account. The application of the OPC can not only solve the difficulties of the implementation of numerous clinical research, but also provide new insights for solving the practical difficulties of clinical research in the real-world.