Background: Recurrent pregnancy loss undermines the physical and mental health of women. Recent randomized controlled trials have reported some effects of traditional Chinese medicine (TCM); however, whether various TCM methods have different effectiveness remains unclear. Objective: To comprehensively evaluate the efficacy and adverse events of TCM for patients with RPL and to explore whether various TCM methods have different effectiveness. Methods: Ten databases were searched up to May 27, 2024. The risk of bias was assessed using the RoB2 tool. The certainty of the evidence was evaluated using the grading of Recommendations, Assessment, Development, and Evaluation tool. Pairwise and network analyses were conducted using Stata 18.0. Results: A total of 47 randomized controlled trials enrolling 6678 women with RPL were included. Pairwise analysis showed that use of TCM had a significantly lower miscarriage rate (RR 0.50 [95% CI 0.45, 0.55]), lower preterm birth rate (RR 0.81 [95% CI 0.67, 0.98), and lower adverse event rate (RR 0.46 [95% CI 0.37, 0.58]). Moreover, use of TCM was associated with a higher alive-fetus rate (RR 1.21 [95% CI 1.15, 1.26]), live-birth rate (RR 1.20 [95% CI 1.15, 1.25]), and full-term rate (RR 1.37 [95% CI 1.23, 1.53]) compared with nonuse of TCM. Network analysis demonstrated that Bushenshugan combined with conventional Western medicine was ranked the best for the reduction of miscarriage rate. Discussion: Use of TCM is more likely to improve pregnancy outcomes and reduce adverse events compared with nonuse of TCM in patients with RPL. Different TCM methods have differences in reducing the miscarriage rate. The Bushenshugan method might be a potential optimal TCM therapy, but more high-quality evidence is needed to further validate and evaluate the efficacy and safety.

It has been not been updated for nearly 5 years since the Pharmacoepidemiology Professional Committee of the Chinese Pharmaceutical Association released the Guide on Methodological Standards in Pharmacoepidemiology in China(1st edition)in 2019,and an update is urgently needed.This study adopts a systematic review approach to comprehensively search for global pharmacoepidemiology methodological guidelines and analyze their development status.By extracting the frameworks and key elements of the guidelines,the China's guide was compared with other included guidelines,its shortcomings were analysed,and pragmatic and feasible suggestions for improvement in line with China's national conditions,were proposed in order to provide references for updating China's guide.A systematic search was conducted by searching PubMed,Embase,CNKI,WanFang Data and 17 official websites of international academic organizations for pharmacoepidemiology and regulatory agencies from countries or regions including Europe,the United States,Japan,and China,etc.,and relevant guidelines or standards were screened based on predefined inclusion and exclusion criteria,resulting in the inclusion of 33 methodological guidelines or standards for pharmacoepidemiological studies.A qualitative synthesis approach was then employed to extract core elements from the guidelines through thematic categorization and content summarization,followed by a descriptive comparative analysis.The results indicate that the 1st edition of the China's guide provides relatively comprehensive guidance on adverse drug reaction reporting and publication of research findings.However,there are gaps in study protocol development,data analysis during study implementation,study reporting,and specific study scenarios.By integrating and drawing upon the latest international pharmacoepidemiology methodology guidelines while balancing comprehensiveness,practicality,and user-friendliness,this study provides recommendations for updating the China's guide.

Appropriate data sources are the cornerstone of pharmacoepidemiological research.Based on the Guide on Methodological Standards in Pharmacoepidemiology in China(2nd edition),hereinafter referred to as"the Guideline(2nd edition)",this article provides an in-depth interpretation of the classification and selection of data sources in pharmacoepidemiological research.It begins with a brief overview of the evolution of data sources in pharmacoepidemiological studies,followed by a detailed analysis of the definitions,applicable scopes,conditions of use,and strengthens and limitations of primary and secondary data sources.It further introduces the characteristics of common data sources and relevant classic domestic and international databases.Subsequently,integrating aspects of the Guideline(2nd edition),including research questions,study design,study population,sample size,exposure or intervention,outcomes,and covariates,the article discusses the criteria and strategies for choosing data sources in pharmacoepidemiological research.Ultimately,a data source selection methodology is established based on clear classification,guided by research questions,tailored to research methods,and supported by data quality,aiming to promote the development of high-quality pharmacoepidemiological research in China.

Pharmacovigilance impact research(PIR),as an important application field of pharmacoepidemiology,has attracted continuous attention in recent years from drug regulatory authorities,pharmaceutical manufacturers,and the academic community both domestically and internationally.This paper provides an interpretation of PIR based on the Guide for Methodology in Pharmacoepidemiologic Research(2nd edition).First,an overview of the implications of PIR will be provided,focusing on the pathways of pharmacovigilance activities and the significant importance of conducting PIR.Second,it reviews commonly used study designs and presents illustrative case examples.Building on this,the specific statistical considerations relevant to PIR were discussed.Finally,the challenges and prospects of conducting pharmacovigilance impact studies in a scientific and standardized manner are summarized.Compared with the previous edition,the 2nd edition has expanded the application scenarios of pharmacoepidemiology to include new areas such as PIR.Drawing on the guideline content and practical experience,this paper provides a detailed introduction and case analysis of PIR,serving as a reference for researchers engaged in this field.

Objective:To describe the epidemiological characteristics of 22 common respiratory patho-gens in patients with pneumonia in Yinzhou,Ningbo,from January 1,2015 to December 21,2024.Methods:The test data of 22 common respiratory pathogens in patients diagnosed with pneumonia or lung infection in the Yinzhou Regional Health Information Platform from January 1,2015 to December 21,2024 were collected.The positive cases,positive rates,and positive proportions were calculated.The epidemiological characteristics were described by the year,sex,age group,season,and coronavirus disease 2019(COVID-19)pandemic period.Results:A total of 77 531 pneumonia patients were included,with 492 696 respiratory pathogen tests performed.The number of respiratory pathogen tests and positive cases of pneumonia patients in Yinzhou showed an upward trend.In the study,34.63％of the pneumo-nia patients tested positive for at least one pathogen,and the pathogen non-detection rate decreased from 79.44％in 2015 to 58.38％in 2024.The overall pathogen positive rate was 9.12％,which decreased during the COVID-19 pandemic and had not returned to the historical level after the COVID-19 pande-mic.The positive rate was highest in children aged 6-17 years(13.99％),and lowest in the elderly over 60 years(4.16％).The top 3 highest number of positive cases was Mycoplasma pneumoniae,influenza A virus,and influenza B virus;the top 3 highest positive rates of pathogen tests were Mycoplasma pneu-moniae(25.26％),rhinovirus(12.02％),and Bordetella pertussis(11.66％).The pathogen spectrum proportion in men was similar to that in women,only showing a higher ratio of Mycobacterium tuberculosis and a slightly lower ratio of Mycoplasma pneumoniae(P＜0.001).Mycoplasma pneumoniae,respiratory syncytial virus,and rhinovirus infections were more common in children,while influenza virus,Mycobac-terium tuberculosis,and Streptococcus pyogenes infections were more common in adults and the elderly(P＜0.001).Influenza virus and human metapneumovirus infections were more common in winter,rhi-novirus and Bordetella pertussis infections were more common in spring,and Mycoplasma pneumoniae in-fections were relatively more common in fall(P＜0.001).After the COVID-19 pandemic,the propor-tions of rhinovirus,respiratory syncytial virus,and human metapneumovirus infections in the pneumonia patients increased signi-ficantly,reaching 7.53％,4.26％,and 2.25％,respectively,while the propor-tions of influenza B virus and Mycobacterium tuberculosis infections decreased to 4.14％and 2.80％,re-spectively(P＜0.001).Conclusion:In the past decade,the scale of respiratory pathogen infection in the pneumonia population in Yinzhou had expanded significantly,and there were differences in distribu-tion by the year,gender,age group,and season.The respiratory pathogen spectrum in pneumonia pa-tients after the COVID-19 pandemic had a trend of diversification.

Objective:To describe the epidemiological characteristics and changes of febrile seizure(FS)among children under 6 years old in Ningbo City,Zhejiang Province from 2015 to 2021.Methods:Based on the Ningbo Regional Health Information Platform,a dynamic cohort was established using vacci-nation registration information,and the cases of FS were identified by the diagnostic results of Chinese terms or International Classification of Diseases 10th revision(ICD-10)R56.0 code in the electronic medical records.The first visit of FS during the observation period was defined as a new case,and a re-currence case was defined as the case with a visit interval of more than 7 days.The 95％confidence in-terval(CI)of FS incidence density was calculated by the Poisson distribution.Results:From January 2015 to June 2020,there were 1.3 million children under 6 years old in Ningbo,with male accounting for 52.87％.The median follow-up time was 2.83(1.55-4.00)years.During the follow-up period,12 776 new onset cases had FS,with more males than females,with an overall incidence density of 4.34(95％CI:4.27-4.40)/1 000 person-years and a recurrence rate of 21.63％.There was a higher inci-dence density in children who were male,born in Ningbo and of non-mobility.The incidence density of FS was higher in urban areas than in rural and rural-urban fringe areas,and the incidence density was different among districts and counties.The peak density was found in children aged 18-23 months[8.42(95％CI:8.11-8.74)/1 000 person-years].From 2015 to 2019,the incidence density in-creased with calendar year(Ptrend＜0.001),and the highest was 5.62(95％CI:5.43-5.81)/1 000 person-years.The incidence density of FS decreased significantly during the period between 2020 and 2021.The incidence density was higher in winter.Conclusion:From 2015 to 2019,the overall inci-dence density of FS in children under 6 years old in Ningbo City presented an increasing trend.More at-tention should be paid to the health education,the improvement of the health maintenance model,the en-hancement of the cognition of FS,the identification and treatment of FS among high-risk population and regions so as to prevent its recurrence and reduce the disease burden during the corona virus disease 2019(COVID-19)epide-mic.

Objective:To analyze the characteristics of Hashimoto thyroiditis(HT)and Graves disease(GD),two autoimmune thyroid diseases aged 10-59 in Qingdao City from 2022 to 2024,and to provide scientific basis for making targeted prevention and treatment measures.Methods:A cross-sectional study design was adopted,based on the data of the Regional Health Information Platform in Qingdao,the con-firmed cases of HT and GD from 2022 to 2024 were included,and combined with the data of the seventh population census,the three-year and annual prevalence rates of HT and GD were calculated,and the time trend of annual prevalence was analyzed by Cochran-Armitage trend test.The distribution characte-ristics of HT and GD prevalence in different age groups and regions were analyzed,and Chi-square test was used to compare the differences between the groups.Results:The total number of HT patients among women aged 10-59 in Qingdao City from 2022 to 2024 was 40 362.The proportion of HT patients in 30-34 years old was the highest(19.83％).The proportion of HT patients in Huangdao District was the highest(17.72％).The three-year prevalence of HT was 1 206.53/100 000.In 2022-2024,the annual prevalence of HT increased significantly(P＜0.001),from 385.32/100 000 in 2022 to 1 206.32/100 000 in 2024.The three-year prevalence of HT was significantly different in age distribution(P＜0.001).The three-year prevalence of HT in 25-29 years(2 354.44/100 000)and 35-39 years(2 022.20/100 000)was higher than that in other age groups,showing a bimodal distribution.There were significant differences in the three-year prevalence of HT in different regions(P＜0.001),among which the three-year prevalence of HT in Shinan District was the highest(2 392.90/100 000),followed by Licang Dis-trict(1 492.41/100 000),and Laixi City was the lowest(659.940/100 000).The total number of GD patients was 2 095,among which the proportion of GD patients in the 35-39 age group was the highest(15.42％),and the proportion of GD patients from Jimo District was the highest(12.27％).From 2022 to 2024,the three-year prevalence rate of GD was 62.63/100 000,and the annual prevalence rate of GD showed an increasing trend(P＜0.001),from 20.33/100 000 in 2022 to 62.63/100 000 in 2024.There were significant differences in the prevalence of GD by age(P＜0.001).The three-year prevalence of GD reached the highest value in the 25-29 age group(98.90/100 000),followed by the 35-39 age group(85.21/100 000),and the lowest in the 10-14 age group(14.43/100 000).In the regional distribution,there were significant differences in the 3-year prevalence of GD(P＜0.001).Laoshan District had the highest three-year prevalence of GD(107.58/100 000),followed by Shinan District(97.83/100 000)and Huangdao District(28.92/100 000).Conclusion:The three-year pre-valence of HT and GD in females aged 10-59 years in Qingdao City from 2022 to 2024 is low,but the annual prevalence is on the rise,and the three-year prevalence of HT and GD in females aged 25-39 years is higher than that in other age groups,so it is necessary to strengthen the screening and monitoring of this population.

The selection of an appropriate control group is a critical component of pharmacoepidemiologic research.This article provides an interpretation of the control selection methods outlined in the Guide on Methodological Standards in Pharmacoepidemiology in China(2nd edition).According to the 2nd edition,studies are categorized into interventional and non-interventional research.In interventional research,control group options include placebo controls,no-treatment controls,active controls,and dose-response controls.For non-interventional research,the gold standard design is the active comparator new user(ACNU)design.When the ACNU design is not feasible,alternative control group strategies should be selected based on the research objective,data sources,exposure characteristics,and potential confounding.These alternatives may include non-user comparators,prevalent user comparators,self-controlled comparators,and external controls.Finally,this article compares the applicability,strengths,and limitations of various control group types.It aims to provide methodological guidance for the scientific selection of control groups in pharmacoepidemiologic studies and to support the conduct of high-quality research.

Objective:To comprehensively evaluate the application of Common Data Model (CDM) of Observational Medical Outcomes Partnership (OMOP) in China, and provide reference for the implementation of data standardization and evidence sharing in China.Methods:PubMed, Embase, Web of Science, CNKI, VIP, WanFang and SinoMed databases were used for literature retrieval to collect the research papers of OMOP CDM application for data standardization in China until March 15, 2023. The information about institutions, types and numbers of patients were extracted.Results:A total of 14 research papers, including 9 in English and 5 in Chinese, were selected. The research papers published since 2018 were collected, which focused on patients with hypertension, diabetes, and depression. A total of 12 institutions or platforms transformed data into OMOP CDM. Jiangsu Provincial People's Hospital was the first one to apply the CDM and demonstrated its feasibility in China. Additionally, the regional information system in Yinzhou District of Ningbo, Zhejiang Province, standardized the multi-dimensional data of patients with diabetes and hypertension. Based on this platform, a series of prediction models for complications in patients with diabetes were constructed. Another major database in Beijing Anding Hospital applied OMOP CDM to analyze the characteristics of patients with late-life depression and dementia.Conclusions:This study analyzed the application of OMOP CDM in China. Through in-depth analysis of specific cases, the study provided guidance for the future cross-regional evidence sharing and collaboration.

Objective:To systematically review the progress in the method development and application of distributed learning in the estimation of epidemiological effect and provide methodological reference for multi-center studies.Methods:We conducted a literature retrieval for English papers published up to December 31, 2023 by using keywords of "health/medical big data" and "distributed/federated learning". After consulting experts, we set criteria of paper inclusion and exclusion and created a framework for data extraction. We collected information about basic study details, including method, application, and evaluation. Two researchers independently screened the papers and extracted information. We used EndNote 20 for the management of literatures and EpiData for the management of data.Results:A total of 3 444 papers were collected, and 29 papers were included in the final analysis. Most of the papers (25, 86.2%) were published in or after 2019, and the papers were mainly from the United States (21/29, 72.4%). For the estimation of epidemiological effects, 22 distributed learning methods had been developed, including methods for logistic regression (8), Cox regression (8), Poisson regression (2), and generalized linear mixed model (GLMM) (4), as well as three platforms for distributed analysis (VLP, Vantage6, AusCAT). The 29 papers described 45 applications, with 20 (44.4%) focusing on the establishment of prediction model and 25 (55.6%) on association analysis. Importantly, except for GLMM, current distributed learning methods can estimate effects with little bias in 1-3 rounds of communication. These methods show less bias compared with meta-analysis, especially in the address of data heterogeneity and rare outcomes. However, less studies examined how differences in data structure and sparse data affect results, an area that requires further research.Conclusion:While distributed learning shows promise in epidemiological effect estimation, it is still in early development, requiring further research on data heterogeneity handling and communication efficiency improvement.