Recently, real world studies (RWS) have received increasing attentions. Such studies typically involve patient information, and their results may have potentially significant impact on patient well-being and safety. When reviewing the protocol of real world studies, ethical issues should be carefully considered and assessed. This paper discussed three issues, including the overview of bioethics and its application to classic clinical trials, key features of RWS, and medical ethical considerations on RWS.
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.
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.
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.
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.
Objective To develop an artificial intelligence (AI)-driven lung cancer database by structuring and standardizing clinical data, enabling advanced data mining for lung cancer research, and providing high-quality data for real-world studies. Methods Building on the extensive clinical data resources of the Department of Thoracic Surgery at Peking Union Medical College Hospital, this study utilized machine learning techniques, particularly natural language processing (NLP), to automatically process unstructured data from electronic medical records, examination reports, and pathology reports, converting them into structured formats. Data governance and automated cleaning methods were employed to ensure data integrity and consistency. Results As of September 2024, the database included comprehensive data from 18 811 patients, encompassing inpatient and outpatient records, examination and pathology reports, physician orders, and follow-up information, creating a well-structured, multi-dimensional dataset with rich variables. The database’s real-time querying and multi-layer filtering functions enabled researchers to efficiently retrieve study data that meet specific criteria, significantly enhancing data processing speed and advancing research progress. In a real-world application exploring the prognosis of non-small cell lung cancer, the database facilitated the rapid analysis of prognostic factors. Research findings indicated that factors such as tumor staging and comorbidities had a significant impact on patient survival rates, further demonstrating the database’s value in clinical big data mining. Conclusion The AI-driven lung cancer database enhances data management and analysis efficiency, providing strong support for large-scale clinical research, retrospective studies, and disease management. With the ongoing integration of large language models and multi-modal data, the database’s precision and analytical capabilities are expected to improve further, providing stronger support for big data mining and real-world research of lung cancer.
ObjectiveTo systematically review the difference in 30-day readmission rates among acute heart failure patients between real-world studies vs. randomized controlled trials (RCTs). MethodsPubMed, EMbase, The Cochrane Library, CNKI, CBM, VIP and WanFang Data databases were electronically searched to collect clinical studies on 30-day readmission rates in patients with acute heart failure from inception to April 12th, 2021. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies. Meta-analysis was then performed using Stata 16.0 software. ResultsA total of 33 real-world studies and 11 RCTs involving 106 722 subjects were included. The results of meta-analysis showed that the 30-day heart failure-related readmission rates in the real-world studies and RCTs were 10.8% (95%CI 9.3% to 12.3%) and 6.9% (95%CI 5.3% to 8.4%), respectively. The 30-day all-cause readmission rates in real-world studies and randomized controlled studies were 18.6% (95%CI 15.7% to 21.4%) and 14.2% (95%CI 12.0% to 16.3%), respectively. There were statistically significant differences between two kinds of studies (P<0.05). ConclusionsCurrent evidence suggests that the 30-day heart failure-related and all-cause readmission rates in patients of acute heart failure in real-world studies are significantly higher than those in patients of RCTs. Due to the limited quality and quantity of included studies, more high-quality studies are required to verify the above conclusions.
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.
ObjectiveTo compare the effectiveness of haemocoagulase agkistrodon and tranexamic acid and sodium chloride in the prevention and treatment of perioperative bleeding in a real world setting. MethodsA research database was constructed based on the records of inpatient visits using haemocoagulase agkistrodon and tranexamic acid and sodium chloride according to the SuValue® database from January 1, 2016 to December 31, 2020. The patients were divided into two groups according to the different interventions. After matching with a 1∶1 propensity score, the effectiveness of two groups was compared. ResultsA total of 858 patients were included in each of the two groups, and there was no statistically significant difference in baseline characteristics between the two groups (P>0.05). Research results showed that patients using haemocoagulase agkistrodon had significantly reduced length of hospital stay, decrease in hematocrit, average estimated surgical bleeding, and decrease in hemoglobin (P<0.01). ConclusionHaemocoagulase agkistrodon has better effectiveness than tranexamic acid and sodium chloride for reducing perioperative blood loss based on current real world evidence.
Retrospective chart review (RCR) is a type of research that answers specific research questions based on the existing patient medical records or related databases through a series of research processes including data extraction, data collation, statistical analysis, etc. Relying on the development of medical big data, as well as the relatively simple implementation process and low cost of information acquisition, RCR is increasingly used in the medical research field. In this paper, we conducted the visual analysis of high-quality RCR published in the past five years, and explored and summarized the current research status and hotspots by analyzing the characteristics of the number of publications, national/regional and institutional cooperation networks, author cooperation networks, keyword co-occurrence and clustering networks. We further systematically combed the methodological core of this kind of research from eight aspects: research question and hypothesis, applicability of chart, study design, data collecting, statistical analysis, interpretation of results, and reporting specification. By summarizing the shortcomings, unique advantages and application prospects of RCR, providing guidance and suggestions for the standardized application of RCR in the medical research field in the future.