The major obstacle to optimizing the design of rare disease coverage is the fragmented decision-making process among medical services, pharmaceuticals, and medical insurance departments. There is an urgent need to realize data sharing and digital empowerment, as well as to adopt top-level design and systematic decision-making. It is also crucial to establish mechanisms, facilitated by digital intelligence, for sharing power and responsibilities, and assessing rewards and punishments. Furthermore, there is an urgent need to incorporate the theories of collaborative governance, digital governance, and the full life cycle into the entire process, which includes patient classification, diagnosis and treatment, medical assistance, medication protection, and health insurance fund management for rare diseases. This integration aims to provide theoretical reference for the effective linkage of medical services, pharmaceuticals, and medical insurance, and to improve the efficiency and equity of resource allocation in the public sector.

Objective:To analyze the epidemiological characteristics and economic burden of palmoplantar pustulosis (PPP) in China.Methods:A population-based retrospective study was conducted using the data from China′s Urban Basic Medical Insurance data from January 1, 2012, to December 31, 2016. International Classification of Diseases code and diagnoses in Chinese for PPP were used to identify cases and estimate the prevalence, incidence, and cost. Subgroup analyses were performed according to age and sex, and sensitivity analyses were conducted to evaluate the robustness of the results. Age-adjusted prevalence rates were calculated based on the 2010 national census data.Results:The crude prevalence and incidence rate of PPP in 2016 were 2.730/100 000 (95% CI: 2.218/100 000-3.242/100 000) and 1.556/100 000 (95% CI: 1.154/100 000-1.958/100 000), and the prevalence rate of females (2.910/100 000) was higher than that of males (2.490/100 000, χ2=97.48, P=0.001). The incidence rate of females (1.745/100 000) was also higher than that of males (1.418/100 000, χ2=85.02, P=0.001). The age peak of incidence and prevalence of patients with PPP was in the 30-39-year age group and a small peak existed in the 0-3-year age group among people under 20 years old. From 2012 to 2016, the average number of visits was (2.44±0.04) per patient, and the total per-capita cost per year was (982.40±39.19) yuan. Conclusion:In 2016, the prevalence and incidence rate of PPP in China were higher in females than in males, and the highest age peak was in the 30-39-year age group.

Objective:To construct a risk prediction model for diabetes kidney disease (DKD).Methods:Patients newly diagnosed with type 2 diabetes mellitus (T2DM) between January 1, 2015, and December 31, 2022, were selected as study subjects from the Yinzhou Regional Health Information Platform in Ningbo City. The Lasso method was used to screen the risk factors, and the DKD risk prediction model was established using Cox proportional hazard regression models. Bootstrap 500 resampling was applied for internal validation.Results:The study included 49 706 subjects, with an median ( Q1, Q3) age of 60.00 (50.00, 68.00) years old, and 55% were male. A total of 4 405 subjects eventually developed DKD. Age at first diagnosis of T2DM, BMI, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, past medical history (hyperuricemia, rheumatic diseases), triglycerides, and estimated glomerular filtration rate were included in the final model. The final model's C-index was 0.653, with an average of 0.654 after Bootstrap correction. The final model's area under the receiver operating characteristic curve for predicting 4-year, 5-year, and 6-year was 0.657, 0.659, and 0.664, respectively. The calibration curve was closely aligned with the ideal curve. Conclusions:This study constructed a DKD risk prediction model for newly diagnosed T2DM patients based on real-world data that is simple, easy to use, and highly practical. It provides a reliable basis for screening high-risk groups for DKD.

Epidemiology and medical statistics are essential courses for undergraduate students majoring in clinical medicine. By studying the two courses, they can obtain the core skills for their future clinical practice. High-level medical schools both at home and abroad have accumulated successful experiences in curriculum, teaching methods and teaching models of the two disciplines. These colleges have also carried out the exploration of the curriculum reform centering on "organ systems integration". This paper summarizes the current status of epidemiology and medical statistics teaching and curriculum integration in representative medical schools both at home and abroad, and puts forward suggestions for deepening teaching reform and optimizing the curriculum system to provide reference for the integration of epidemiology and medical statistics curriculums for undergraduate students majoring in clinical medicine in China.

Objective:Diabetic retinopathy (DR) has been reported as the leading cause of blindness among diabetic adults, which is closely related to poor quality of life and increased burden of disability. This study aimed to aggregate the optimally available evidence on modifiable risks of DR.Methods:Until June 2023, PubMed, Cochrane Library, CNKI, and Wanfang databases were used to retrieve Meta-analysis about various risk factors for DR, and Meta-analysis were analyzed and summarized. R 4.3.2 software was used for each Meta-analytic association to calculate the effect size, 95% CI, heterogeneity, small-study effects, excess significance bias, and 95% prediction intervals. The credibility of significant evidence was graded. Results:We captured 23 eligible papers (72 associations) covering a wide range of medication use, concomitant diseases, daily intervention, biomarkers, lifestyle, and physical measurement index. Among them, higher HbA1c variability ( RR=1.45, 95% CI: 1.26-1.66) and urine microalbumin positive ( OR=2.44, 95% CI: 1.99-2.97) were convincing (grade Ⅰ) evidence, and insulin use ( RR=3.48, 95% CI: 2.14-5.67) was highly suggestive (grade Ⅱ) evidence. Moreover, hypertension ( OR=2.03, 95% CI: 1.06-3.97), poor glycemic control ( OR=4.35, 95% CI: 1.47-12.85), positive macroalbuminuria ( OR=8.42, 95% CI: 3.52-20.15), long sleep duration ( OR=2.05, 95% CI: 1.37-3.05), vitamin D deficiency ( OR=2.02, 95% CI: 1.17-3.50), periodontitis ( OR=4.51, 95% CI: 1.76-11.55) were the main risk factors for DR. Intensive blood pressure intervention ( RR=0.78, 95% CI: 0.65-0.94), dietary control ( OR=0.64, 95% CI: 0.47-0.89) and moderate intensity physical activity ( RR=0.76, 95% CI: 0.59-0.97) yielded significant protective associations with DR. Conclusions:Intensive blood pressure glycemic control, and a healthy lifestyle pattern could reduce the risk of DR. This study provides the evidence to identify high-risk populations and recommends rational treatment options and healthy living interventions.

Objective To assess the association between Metformin use and the risk of dementia in patients with type 2 diabetes mellitus(T2DM).Methods The research data came from the big medical data platform of Yinzhou District,and we constructed a cohort of T2DM patients who had initiated treatment of Metformin or sulfonylurea since January 1,2009.The inverse probability of treatment weighting(IPTW)was used to control the baseline confounding factors,and the Cox regression model was used to estimate the HR(95%CI)of the association between Metformin use and dementia risk.Results The incidence rate of dementia in new users of Metformin(41181 persons)and sulfonylureas(38092 persons)was 128.4 per 100000 person years and 142.3 per 100000 person years respectively.Compared with sulfonylureas,the crude analysis with no adjustment for confounding factors showed that there was a negative association between the use of Metformin and the incidence of dementia,with an HR(95%CI)0.930(0.800～1.090).After adjusting for potential confounders with IPTW,Metformin was not significantly associated with the risk of dementia HR(95%CI)1.040(0.890～1.220).The subgroup analysis results for different baseline characteristics were consistent with the primary analysis results,and there were no statistically significant associations between Metformin and dementia incidence risk in all subgroups.Conclusions There is no significant association between the use of Metformin and the risk of dementia in T2DM patients in the Yinzhou District.

ObjectiveTo explore the research status and trends of cohort studies on traditional Chinese medicine （TCM） efficacy evaluation from 2017 to 2022 and provide ideas and references for research in this field. MethodsSix databases including Pubmed， Web of Science， Embase， Scopus， Cochrane Library and CNKI were searched from January 1st， 2017 to December 31st， 2022. The total number of annual publications， journals， highly cited literatures， and keywords were quantitatively and visually analyzed by Bibliometrix. ResultsA total of 328 articles were included， which were published in 141 journals. The number of articles published in this field showed an overall upward trend， and retrospective cohort studies （282 papers， 85.98%） accounted for the largest proportion. A total of 151 cohort studies （46.04%） were conducted based on the database and showed an overall upward trend. The subjects were mainly patients with tumors （77 papers， 23.48%）， and cardiovascular and cerebrovascular diseases （64 papers， 19.51%）. The top 3 highly cited literatures mainly explore the association between TCM and survival outcome and quality of life in patients with malignant tumors. Fourteen and twenty-five high-frequency keywords were included in Chinese and English literature respectively， which formed 3 clusters such as research methods， statistical analysis and diseases. ConclusionIt was the current status to focus on retrospective cohort studies and focus on patients with tumors or cardiovascular and cerebrovascular diseases. Using observational database to conduct cohort studies of TCM efficacy evaluation could be the future research direction.

This paper briefly introduces the definition, classification and significance of effect modification in epidemiological studies, summarizes the difference between effect modifier and confounders, and analyze the influence as well as the role of effect modification in epidemiological studies and Meta-analysis. In this paper, the possible scenarios of effect modification and related analysis strategy in Meta-analysis are indicated by graphics, aiming to arouse researchers' attention to effect modification. This paper also demonstrates how to identify and deal with effect modification in Meta-analysis through a study case of "Efficacy of sodium-glucose cotransporter 2 inhibitors in patients with type 2 diabetes", and shows the analysis process and interpretation of results of subgroup analysis and Meta-regression methods respectively. The advantages and disadvantages of these two methods are summarized to provide reference for the method selection of future research.

This paper briefly introduces the characteristics, research significance, and global reporting status of effect modification in network Meta-analysis, demonstrates the heterogeneity caused by effect modification in network Meta-analysis, and emphasizes the importance of exploring effect modification in network Meta-analysis. This paper also summarizes the normalized description and analysis strategies of effect modification in network Meta-analysis. Finally, by the case of "comparison of efficacy of three new hypoglycemic drugs in reducing body weight in type 2 diabetes patients", this paper demonstrates the realization of subgroup analysis and network Meta-regression in exploring effect modification, summarizes the advantages and disadvantages of the two methods, to provide references for future researchers.

Objective:Differences between randomized controlled trial (RCT) results and real world study (RWS) results may not represent a true efficacy-effectiveness gap because efficacy-effectiveness gap estimates may be biased when RWS and RCT differ significantly in study design or when there is bias in RWS result estimation. Secondly, when there is an efficacy- effectiveness gap, it should not treat every patient the same way but assess the real-world factors influencing the intervention's effectiveness and identify the subgroup likely to achieve the desired effect.Methods:Six databases (PubMed, Embase, Web of Science, CNKI, Wanfang Data, and VIP) were searched up to 31 st December 2022 with detailed search strategies. A scoping review method was used to integrate and qualitatively describe the included literature inductively. Results:Ten articles were included to discuss how to use the RCT research protocol as a template to develop the corresponding RWS research protocol. Moreover, based on correctly estimating the efficacy-effectiveness gap, evaluate the intervention effect in the patient subgroup to confirm the subgroup that can achieve the expected benefit-risk ratio to bridge the efficacy-effectiveness gap.Conclusion:Using real-world data to simulate key features of randomized controlled clinical trial study design can improve the authenticity and effectiveness of study results and bridge the efficacy-effectiveness gap.