Standardized research reporting is crucial for the translation of pharmacoepidemiology research findings,and visual reporting can significantly enhance the clarity,understandability,and transparency of research results.Based on the Guide on Methodological Standards in Pharmacoepidemiology(2nd edition),this article systematically explains the key points for writing each component of a research report(including title,abstract,introduction,research methods,research results,discussion and conclusions,acknowledgments,conflict of interest statement,and references).This article also summarizes recognized international and domestic standards for pharmacoepidemiology research reporting,providing a reference for researchers.Furthermore,real-world cases will be used to demonstrate common forms of visualized reports and their interpretation methods.Finally,it further explores strategies for communicating research results.This study aims to provide pharmacoepidemiology researchers with detailed guidance on visually presenting research results and writing high-quality research reports,thereby enhancing the integrity and impact of their research.

AIM:To evaluate the application effec-tiveness of a Bayesian mixture model based on the principal stratum strategy for estimating the com-plier average causal effect(CACE)in clinical trials with non-compliance.METHODS:Using a non-infe-riority randomized controlled trial investigating a novel drug for primary type 2 diabetes mellitus(non-inferiority margin:-0.4)as a case study,the primary analysis applied a Bayesian mixture model under the monotonicity assumption to estimate CACE of between-group differences in glycated he-moglobin(HbA1c)changes within the compliant stratum,followed by non-inferiority testing.Sensi-tivity analyses included a Bayesian mixture model relaxing the monotonicity assumption and compar-ing results with per-protocol set(PPS)analysis.RE-SULTS:In the primary analysis,the posterior mean of CACE for HbA1c change in the compliant stratum was 0.081％,with a one-sided 97.5％credible inter-val lower bound of-0.124,exceeding the non-infe-riority margin(-0.4％),supporting the non-inferiori-ty efficacy of the novel drug in the compliant stra-tum(P(H1|Data)=1).Consistent findings were ob-served in PPS analyses(estimated effect:0.136％;one-sided 97.5％credible interval lower bound:-0.069％),further validating methodological robust-ness.CONCLUSION:In clinical trials with noncom-pliance as an intercurrent event,the Bayesian mix-ture model under the principal stratum strategy ef-fectively adjusts for compliance-related bias and yields conservative,robust estimates of causal ef-fects,supporting its value in efficacy evaluation un-der complex compliance scenarios.

To explore the application of sequential analysis in post-market safety dynamic surveillance of vaccines. Under the dynamic monitoring data of vaccines post-market approval, this research introduces the fundamental principles of maximizing sequential probability ratio test (MaxSPRT) and Bayesian sequential analysis, employing R software. Through an example of dynamic safety monitoring data of vaccines post-market approval, we analyze using the MaxSPRT and Bayesian sequential analysis. The MaxSPRT identified a safety signal in week 4 ( P<0.05), while Bayesian sequential analysis indicated that the 95% highest density interval for the RR value at week 4 is 1.13-3.27, suggesting the first appearance of a safety signal at week 4. The MaxSPRT and Bayesian sequential analysis effectively leverage continuously accumulating dynamic monitoring data, thereby serving as a valuable method for post-market safety surveillance of vaccines.

In epidemiological research, accurate estimation of prevalence is important for understanding disease distribution, evaluating the effectiveness of interventions, and allocating health resources. However, the prevalence estimation is often influenced by misclassification bias. Quantitative bias analysis (QBA) can comprehensively evaluate the potential impact of bias on outcomes from three dimensions: bias type, level, and uncertainty. Although QBA research has been developed rapidly in the world in recent years, the introduction of QBA design principles, evaluation methods, and application cases is still insufficient in China. In our previous study, we introduced a new method for adjusting misclassification bias of prevalence and suggested the corresponding analytical tools. Based on the results of previous studies, this paper introduces the principles of QBA design, evaluation indexes, and the application of Bayesian methods in bias adjustment, which provide methodological support for epidemiologists conducting research in this field.

To explore the application of sequential analysis in post-market safety dynamic surveillance of vaccines. Under the dynamic monitoring data of vaccines post-market approval, this research introduces the fundamental principles of maximizing sequential probability ratio test (MaxSPRT) and Bayesian sequential analysis, employing R software. Through an example of dynamic safety monitoring data of vaccines post-market approval, we analyze using the MaxSPRT and Bayesian sequential analysis. The MaxSPRT identified a safety signal in week 4 ( P<0.05), while Bayesian sequential analysis indicated that the 95% highest density interval for the RR value at week 4 is 1.13-3.27, suggesting the first appearance of a safety signal at week 4. The MaxSPRT and Bayesian sequential analysis effectively leverage continuously accumulating dynamic monitoring data, thereby serving as a valuable method for post-market safety surveillance of vaccines.

In epidemiological research, accurate estimation of prevalence is important for understanding disease distribution, evaluating the effectiveness of interventions, and allocating health resources. However, the prevalence estimation is often influenced by misclassification bias. Quantitative bias analysis (QBA) can comprehensively evaluate the potential impact of bias on outcomes from three dimensions: bias type, level, and uncertainty. Although QBA research has been developed rapidly in the world in recent years, the introduction of QBA design principles, evaluation methods, and application cases is still insufficient in China. In our previous study, we introduced a new method for adjusting misclassification bias of prevalence and suggested the corresponding analytical tools. Based on the results of previous studies, this paper introduces the principles of QBA design, evaluation indexes, and the application of Bayesian methods in bias adjustment, which provide methodological support for epidemiologists conducting research in this field.

Standardized research reporting is crucial for the translation of pharmacoepidemiology research findings,and visual reporting can significantly enhance the clarity,understandability,and transparency of research results.Based on the Guide on Methodological Standards in Pharmacoepidemiology(2nd edition),this article systematically explains the key points for writing each component of a research report(including title,abstract,introduction,research methods,research results,discussion and conclusions,acknowledgments,conflict of interest statement,and references).This article also summarizes recognized international and domestic standards for pharmacoepidemiology research reporting,providing a reference for researchers.Furthermore,real-world cases will be used to demonstrate common forms of visualized reports and their interpretation methods.Finally,it further explores strategies for communicating research results.This study aims to provide pharmacoepidemiology researchers with detailed guidance on visually presenting research results and writing high-quality research reports,thereby enhancing the integrity and impact of their research.

AIM:To evaluate the application effec-tiveness of a Bayesian mixture model based on the principal stratum strategy for estimating the com-plier average causal effect(CACE)in clinical trials with non-compliance.METHODS:Using a non-infe-riority randomized controlled trial investigating a novel drug for primary type 2 diabetes mellitus(non-inferiority margin:-0.4)as a case study,the primary analysis applied a Bayesian mixture model under the monotonicity assumption to estimate CACE of between-group differences in glycated he-moglobin(HbA1c)changes within the compliant stratum,followed by non-inferiority testing.Sensi-tivity analyses included a Bayesian mixture model relaxing the monotonicity assumption and compar-ing results with per-protocol set(PPS)analysis.RE-SULTS:In the primary analysis,the posterior mean of CACE for HbA1c change in the compliant stratum was 0.081％,with a one-sided 97.5％credible inter-val lower bound of-0.124,exceeding the non-infe-riority margin(-0.4％),supporting the non-inferiori-ty efficacy of the novel drug in the compliant stra-tum(P(H1|Data)=1).Consistent findings were ob-served in PPS analyses(estimated effect:0.136％;one-sided 97.5％credible interval lower bound:-0.069％),further validating methodological robust-ness.CONCLUSION:In clinical trials with noncom-pliance as an intercurrent event,the Bayesian mix-ture model under the principal stratum strategy ef-fectively adjusts for compliance-related bias and yields conservative,robust estimates of causal ef-fects,supporting its value in efficacy evaluation un-der complex compliance scenarios.

Objective To study the diagnostic value of miR-571 for liver fibrosis by detecting miR-571 expression in the peripheral blood of patients with liver fibrosis.Methods From December 2022 to September 2023,40 patients with liver fibrosis,40 patients with chronic hepatitis,and 40 healthy controls were chosen as research subjects.The expression level of miR-571 in peripheral blood was detected using a real-time quantitative polymerase chain reaction,and the relative expression of miR-571 in each group was evaluated.The Spearman correlation method was utilized to examine the relationship between miR-571 and clinical detection indices.To assess the capacity of miR-571 and the multivariate diagnostic model to identify liver fibrosis,binary logistic regression was used to create a multivariate diagnostic model,and ROC curves were generated.Results The expression of miR-571 was significantly higher in the liver fibrosis group than in the healthy control and hepatitis groups,and the difference was statistically significant(P<0.001).The expression level of miR-571 was positively connected with ALT,APRI score,and FIB-4 index(r = 0.23,0.30,0.22,P<0.05)and negatively correlated with PLT(r =-0.19,P<0.05)according to Spearman correlation analysis.Logistic regression research revealed that miR-571 and the FIB-4 index were independent risk factors for liver fibrosis.The AUC for miR-571 to diagnose fibrosis was 0.91(95%CI:0.85～0.96),while the AUC for miR-571 paired with the FIB-4 index was 0.94(95%CI:0.90～0.98).Conclusion MiR-571 expression was shown to be considerably higher in the peripheral blood of hepatic fibrosis patients,and the combined FIB-4 index offers some clinical diagnostic value for hepatic fibrosis.

Objective To make the cost-effectiveness analysis of pembrolizumab and platinum chemotherapy as the first-line treatment for advanced non-small cell lung cancer(NSCLC)in the population with tumor proportion score(TPS)≥1%of PD-L1,and provide some reference for the clinical use and future price negotiation of pembrolizumab.Methods Based on Pubmed database,the published RCT literatures of pembrolizumab were analyzed,and the survival data were extracted,combined with the treatment plan of a tertiary hospital,the Markov model were established to simulate the cost and health effectiveness of patients for twenty years,and the stability of the model was tested by one-way sensitivity analysis and probability sensitivity analysis.Results Twenty years later,the cost-effectiveness ratio of pembrolizumab group and chemotherapy group was ￥58 517.60/quality adjusted life month(QALM)and ￥41 213.08/QALM.Compared with the chemotherapy group,the incremental cost effective ratio(ICER)was ￥104 485.36/QALM.Conclusion When the willingness to pay(WTP)value was ￥30 902/QALM,the pembrolizumab therapy was not more cost-effective advantages than platinum chemotherapy,and the sensitivity analysis showed that the results of the model were relatively stable.