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.

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.

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 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.

[Objective] To observe the dynamic changes of circulating immune complex (CIC) in monkeys infected by simian immunodeficiency virus (SIV). [Methods] Agglutination test of complement-sensitized yeast cell was used to determine the serum CIC level in 30 cases of monkeys, which were infected with SIVmac251 and sampled in different time-points after infection. Sixty-eight cases of normal monkeys were also examined as controls. [Results] After SIV infection, CIC can't be detected in all 30 monkeys until the 4th week, the total positive rate being 30% . In the 8th week, CIC were detected in 46.7% of these monkeys and then declined gradually in the following 12 weeks. Since the 20th week, the CIC in these monkeys maintained lower liter and lower positive rate which was close to that of the normal monkeys (about 10%). [Conclusion] CIC appeared and increased during the primary SIV infection and declined accompanying with the virus clearance from the circulalion. The formation of CIC may not benefit to the control of virus replication and the induction of anti-virus immunity; CIC has a role in the pathogenesis after SIV infection.