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1.
Article in English | WPRIM | ID: wpr-828989

ABSTRACT

Objective@#Long-term seroprotection the hepatitis A vaccine is essential for the prevention of disease from the hepatitis A virus (HAV). Due to documented difficulties during decade-long follow-ups after receiving vaccines, statistical-modeling approaches have been applied to predict the duration of immune protection.@*Methods@#Based on five-year follow-up data from a randomized positive-controlled trial among Chinese children (1-8 years old) following a 0, 6 months vaccination schedule, a power-law model accounting for the kinetics of B-cell turnover, as well as a modified power-law model considering a memory-B-cell subpopulation, were fitted to predict the long-term immune responses induced by HAV vaccination (Healive or Havrix). Anti-HAV levels of each individual and seroconversion rates up to 30 years after vaccination were predicted.@*Results@#A total of 375 participants who completed the two-dose vaccination were included in the analysis. Both models predicted that, over a life-long period, participants vaccinated with Healive would have close but slightly higher antibody titers than those of participants vaccinated with Havrix. Additionally, consistent with previous studies, more than 90% of participants were predicted to maintain seroconversion for at least 30 years. Moreover, the modified power-law model predicted that the antibody titers would reach a plateau level after nearly 15 years post-vaccination.@*Conclusions@#Based on the results of our modeling, Healive may adequately induce long-term immune responses following a 0, 6 months vaccination schedule in children induction of memory B cells to provide stable and durable immune protection.


Subject(s)
Adolescent , Child , Child, Preschool , China , Female , Hepatitis A , Allergy and Immunology , Hepatitis A Antibodies , Blood , Hepatitis A Vaccines , Humans , Immunity, Active , Infant , Male , Models, Statistical , Vaccination
2.
Article in Chinese | WPRIM | ID: wpr-828024

ABSTRACT

To scientifically evaluate the intervention effect of Chinese medicine preventive administration(combined use of Huo-xiang Zhengqi Oral Liquid and Jinhao Jiere Granules) on community population in the case of coronavirus disease 2019(COVID-19), a large cohort, prospective, randomized, and parallel-controlled clinical study was conducted. Total 22 065 subjects were included and randomly divided into 2 groups. The non-intervention group was given health guidance only, while the traditional Chinese medicine(TCM) intervention group was given two coordinated TCM in addition to health guidance. The medical instructions were as follows. Huoxiang Zhengqi Oral Liquid: oral before meals, 10 mL/time, 2 times/day, a course of 5 days. Jinhao Jiere Granules: dissolve in boiling water and take after meals, 8 g/time, 2 times/day, a course of 5 days, followed up for 14 days, respectively. The study found that with the intake of medication, the incidence rate of TCM intervention group was basically maintained at a low and continuous stable level(0.01%-0.02%), while the non-intervention group showed an overall trend of continuous growth(0.02%-0.18%) from 3 to 14 days. No suspected or confirmed COVID-19 case occurred in either group. There were 2 cases of colds in the TCM intervention group and 26 cases in the non-intervention group. The incidence of colds in the TCM intervention group was significantly lower(P<0.05) than that in the non-intervention group. In the population of 16-60 years old, the incidence rate of non-intervention and intervention groups were 0.01% and 0.25%, respectively. The difference of colds incidence between the two groups was statistically significant(P<0.05). In the population older than 60 years old, they were 0.04% and 0.21%, respectively. The incidence of colds in the non-intervention group was higher than that in the intervention group, but not reaching statistical difference. The protection rate of TCM for the whole population was 91.8%, especially for the population of age 16-60(95.0%). It was suggested that TCM intervention(combined use of Huoxiang Zhengqi Oral Liquid and Jinhao Jiere Granules) could effectively protect community residents against respiratory diseases, such as colds, which was worthy of promotion in the community. In addition, in terms of safety, the incidence of adverse events and adverse reactions in the TCM intervention group was relatively low, which was basically consistent with the drug instructions.


Subject(s)
Adolescent , Adult , Betacoronavirus , Coronavirus Infections , Drug Therapy , Drugs, Chinese Herbal , Humans , Medicine, Chinese Traditional , Middle Aged , Pandemics , Pneumonia, Viral , Drug Therapy , Prospective Studies , Young Adult
3.
Article in English | WPRIM | ID: wpr-773365

ABSTRACT

OBJECTIVE@#To develop methods for determining a suitable sample size for bioequivalence assessment of generic topical ophthalmic drugs using crossover design with serial sampling schemes.@*METHODS@#The power functions of the Fieller-type confidence interval and the asymptotic confidence interval in crossover designs with serial-sampling data are here derived. Simulation studies were conducted to evaluate the derived power functions.@*RESULTS@#Simulation studies show that two power functions can provide precise power estimates when normality assumptions are satisfied and yield conservative estimates of power in cases when data are log-normally distributed. The intra-correlation showed a positive correlation with the power of the bioequivalence test. When the expected ratio of the AUCs was less than or equal to 1, the power of the Fieller-type confidence interval was larger than the asymptotic confidence interval. If the expected ratio of the AUCs was larger than 1, the asymptotic confidence interval had greater power. Sample size can be calculated through numerical iteration with the derived power functions.@*CONCLUSION@#The Fieller-type power function and the asymptotic power function can be used to determine sample sizes of crossover trials for bioequivalence assessment of topical ophthalmic drugs.


Subject(s)
Administration, Topical , Clinical Trials as Topic , Methods , Cross-Over Studies , Humans , Models, Theoretical , Ophthalmic Solutions , Pharmacokinetics , Sample Size , Therapeutic Equivalency
4.
Acta Pharmaceutica Sinica ; (12): 1402-1407, 2015.
Article in Chinese | WPRIM | ID: wpr-320069

ABSTRACT

Missing data is a common but unavoidable issue in clinical trials. It not only lowers the trial power, but brings the bias to the trial results. Therefore, on one hand, the missing data handling methods are employed in data analysis. On the other hand, it is vital to prevent the missing data in the trials. Prevention of missing data should take the first place. From the perspective of data, firstly, some measures should be taken at the stages of protocol design, data collection and data check to enhance the patients' compliance and reduce the unnecessary missing data. Secondly, the causes of confirmed missing data in the trials should be notified and recorded in detail, which are very important to determine the mechanism of missing data and choose the suitable missing data handling methods, e.g., last observation carried forward (LOCF); multiple imputation (MI); mixed-effect model repeated measure (MMRM), etc.


Subject(s)
Clinical Trials as Topic , Data Collection , Methods , Reference Standards , Humans , Models, Theoretical , Research Design
5.
Acta Pharmaceutica Sinica ; (12): 1464-1469, 2015.
Article in English | WPRIM | ID: wpr-320057

ABSTRACT

Testing of hypothesis was affected by statistical analysis set division which was an important data management work before data base lock-in. Objective division of statistical analysis set under blinding was the guarantee of scientific trial conclusion. All the subjects having accepted at least once trial treatment after randomization should be concluded in safety set. Full analysis set should be close to the intention-to-treat as far as possible. Per protocol set division was the most difficult to control in blinded examination because of more subjectivity than the other two. The objectivity of statistical analysis set division must be guaranteed by the accurate raw data, the comprehensive data check and the scientific discussion, all of which were the strict requirement of data management. Proper division of statistical analysis set objectively and scientifically is an important approach to improve the data management quality.


Subject(s)
Clinical Trials as Topic , Reference Standards , Databases, Factual , Research Design , Reference Standards , Statistics as Topic
6.
Chinese Journal of Epidemiology ; (12): 964-968, 2009.
Article in Chinese | WPRIM | ID: wpr-321087

ABSTRACT

R2) of the two models were 0.801,0.872 respectively. The fitting efficacy of the ARIMA-GRNN combination model was better than the single ARIMA, which had practical value in the research on time series data such as the incidence of scarlet fever.

7.
Article in Chinese | WPRIM | ID: wpr-352462

ABSTRACT

<p><b>OBJECTIVE</b>To explore several numerical methods of ordinal variable in one-way ordinal contingency table and their interrelationship, and to compare corresponding statistical analysis methods such as Ridit analysis and rank sum test.</p><p><b>METHODS</b>Formula deduction was based on five simplified grading approaches including rank_r(i), ridit_r(i), ridit_r(ci), ridit_r(mi), and table scores. Practical data set was verified by SAS8.2 in clinical practice (to test the effect of Shiwei solution in treatment for chronic tracheitis).</p><p><b>RESULTS</b>Because of the linear relationship of rank_r(i) = N ridit_r(i) + 1/2 = N ridit_r(ci) = (N + 1) ridit_r(mi), the exact chi2 values in Ridit analysis based on ridit_r(i), ridit_r(ci), and ridit_r(mi), were completely the same, and they were equivalent to the Kruskal-Wallis H test. Traditional Ridit analysis was based on ridit_r(i), and its corresponding chi2 value calculated with an approximate variance (1/12) was conservative. The exact chi2 test of Ridit analysis should be used when comparing multiple groups in the clinical researches because of its special merits such as distribution of mean ridit value on (0,1) and clear graph expression. The exact chi2 test of Ridit analysis can be output directly by proc freq of SAS8.2 with ridit and modridit option (SCORES =).</p><p><b>CONCLUSION</b>The exact chi2 test of Ridit analysis is equivalent to the Kruskal-Wallis H test, and should be used when comparing multiple groups in the clinical researches.</p>


Subject(s)
Biomedical Research , Methods , Statistics as Topic , Statistics, Nonparametric
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