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.

Objective:Randomized controlled trials (RCT) usually have strict implementation criteria. The included subjects' characteristics of the conditions for the intervention implementation are quite different from the actual clinical environment, resulting in discrepancies between the risk-benefit of interventions in actual clinical use and the risk-benefit shown in RCT. Therefore, some methods are needed to enhance the extrapolation of RCT results to evaluate the real effects of drugs in real people and clinical practice settings.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:A total of 12 articles were included. Three methods in the included literature focused on: ①improving the design of traditional RCT to increase population representation; ②combining RCT Data with real-world data (RWD) for analysis;③calibrating RCT results according to real-world patient characteristics.Conclusions:Improving the design of RCT to enhance the population representation can improve the extrapolation of the results of RCT. Combining RCT data with RWD can give full play to the advantages of data from different sources; the results of the RCT were calibrated against real-world population characteristics so that the effects of interventions in real-world patient populations can be predicted.

Objective:To construct a diabetes foot prediction model for adult patients with type 2 diabetes based on retrospective cohort study using data from a regional health data platform.Methods:Using Yinzhou Health Information Platform of Ningbo, adult patients with newly diagnosed type 2 diabetes from January 1, 2015 to December 31, 2022 were included in this study and divided randomly the train and test sets according to the ratio of 7∶3. LASSO regression model and bidirectional stepwise regression model were used to identify risk factors, and model comparisons were conducted with net reclassification index, integrated discrimination improvement and concordance index. Univariate and multivariate Cox proportional hazard regression models were constructed, and a nomogram plot was drawn. Area under the curve (AUC) was calculated as a discriminant evaluation indicator for model validation test its calibration ability, and calibration curves were drawn to test its calibration ability.Results:No significant difference existed between LASSO regression model and bidirectional stepwise regression model, but the better bidirectional stepwise regression model was selected as the final model. The risk factors included age of onset, gender, hemoglobin A1c, estimated glomerular filtration rate, taking angiotensin receptor blocker and smoking history. AUC values (95% CI) of risk outcome prediction at year 5 and 7 were 0.700 (0.650-0.749) and 0.715(0.668-0.762) for the train set and 0.738 (0.667-0.801) and 0.723 (0.663-0.783) for the test set, respectively. The calibration curves were close to the ideal curve, and the model discrimination and calibration powers were both good. Conclusions:This study established a convenient prediction model for diabetic foot and classified the risk levels. The model has strong interpretability, good discrimination power, and satisfactory calibration and can be used to predict the incidence of diabetes foot in adult patients with type 2 diabetes to provide a basis for self-assessment and clinical prediction of diabetic foot disease risk.

Objective:To develop a prediction model for the risk of diabetic retinopathy (DR) in patients with newly diagnosed type 2 diabetes mellitus (T2DM).Methods:Patients with new diagnosis of T2DM recorded in Yinzhou Regional Health Information Platform between January 1, 2015 and December 31, 2022 were included in the study. The predictor variables were selected by using Lasso-Cox proportional hazards regression model. Cox proportional hazards regression models were used to establish the prediction model for the risk of DR. Bootstrap method (500 resamples) was used for internal validation, and the performance of the model was assessed by C-index, the receiver operating characteristic curve and area under the curve (AUC), and calibration curve.Results:The predictor variables included in the final model were age of T2DM onset, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, estimated glomerular filtration rate, and history of lipid-lowering agent and angiotensin converting enzyme inhibitor uses. The C-index of the final model was 0.622, and the mean corrected C-index was 0.623 (95% CI: 0.607-0.634). The AUC values for predicting the risk of DR after 3, 5, and 7 years were 0.631, 0.620, and 0.624, respectively, with a high degree of overlap of the calibration curves with the ideal curves. Conclusion:In this study, a simple and practical risk prediction model for DR risk prediction was developed, which could be used as a reference for individualized DR screening and intervention in newly diagnosed T2DM patients.

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.

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 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 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.

Crisaborole, a phosphodiesterase-4 inhibitor, has been approved for the treatment of mild to moderate atopic dermatitis in China. In addition, crisaborole ointment has been reported for the successful treatment of other inflammatory skin disorders. This review summarizes mechanisms of action of crisaborole and its application to the treatment of atopic dermatitis, psoriasis, vitiligo, seborrheic dermatitis, inflammatory linear verrucous epidermal nevus, lichen simplex chronicus, prurigo pigmentosa, alopecia areata, plasma cell balanitis, and lichen planus.

Objective:To investigate the clinical features of 17q12 microdeletion cases before and after delivery, and provide a reference for prenatal diagnosis and genetic counseling.Methods:A retrospective analysis was conducted on five fetuses diagnosed with 17q12 microdeletion by single nucleotide polymorphism array in Quanzhou Women's and Children's Hospital between April 2020 and June 2023. Clinical data including prenatal ultrasonography findings, genetic causes, parental clinical features, and postnatal outcomes were summarized and analyzed using descriptive statistical analysis.Results:The five fetuses had normal results of karyotype analysis of amniotic fluid, but carried a microdeletion of 1.4 to 1.8 Mb in the 17q12 region of the chromosome, involving 20 genes listed in the Online Mendelian Inheritance in Man database. Pedigree verification was performed on all five cases and the results indicated one maternally inherited case with the mother having polycystic kidneys complicated by left hydronephrosis, one de novo case, and three paternally inherited cases with one father having multiple cysts in both kidneys and two fathers showing no abnormalities. Multiple abnormalities were found in the five fetuses by prenatal ultrasonography, including enhanced renal parenchymal echogenicity in four cases and pyelectasis in one case. Two cases chose to terminate the pregnancies, while the other three continued the pregnancies to full term. Postnatal follow-ups showed that one case was normal in growth and development with no abnormalities by renal ultrasound; one case developed polycystic kidney; one case with normal renal ultrasound findings had a speech disorder and symptoms of suspected autism at the age of three. Conclusions:The main manifestation of 17q12 microdeletion is enhanced renal parenchymal echogenicity in the fetal stage and postnatal polycystic kidney. In prenatally diagnosed cases, pedigree verification is necessary as an objective and scientific genetic counseling is helpful in pregnancy decision-making.