ABSTRACT
Trials within cohorts （TwiCs） are design methods derived from randomized controlled trials （RCTS）. They have been widely used in chronic disease areas such as tumors and cardiovascular diseases. The basis of the TwiCs design is a prospective cohort of specific diseases. When RCTS need to be implemented， some patients meeting the inclusion and exclusion criteria are randomly sampled from the cohort to receive "trial interventions"， while the remaining patients in the cohort who meet the inclusion and exclusion criteria continue to receive conventional treatment as control groups. By comparing the efficacy differences between the intervention measures of the trial group and the control group， the efficacy of intervention measures was evaluated. Within the cohort， the same process could be repeated to carry out multiple RCTS， so as to evaluate different intervention measures or compare the efficacy of different doses or timing of interventions. Compared with classical RCTS， TwiCs make it easier to recruit patients from the cohort and have higher external validity， providing a new research paradigm for improving the efficiency and applicability of RCTS in clinical practice. However， TwiCs may also face the challenge of poor compliance of patients in the cohort. Researchers need to take effective measures to control these patients in the design and operation of TwiCs. This article focused on the methodological key points during the implementation of TwiCs， including multi-stage informed consent （patients are informed of consent at three stages： entering the cohort， entering the trial group， and after the trial）， randomization procedures （only random sampling of patients from the cohort to receive "trial interventions"）， sample size calculation， and statistical analysis methods. The article also compared the differences between TwiCs and traditional RCTS and illustrated TwiCs research design and analysis with examples， so as to provide new research ideas and methods for clinical researchers.
ABSTRACT
The quality evaluation of the blind method is to evaluate the clinical blind data obtained from clinical trials adopting the blind method and judge the effectiveness of the blind method by investigating the blind effect of different blind objects. A successful blind method can avoid the influence of subjective factors on the test results of subjects and researchers to a certain extent. The quality evaluation of the blind method can reflect not only the effectiveness of the blind method but also the accuracy and credibility of clinical trial results. In recent years， randomized controlled trials have been widely used in the evaluation of the clinical efficacy of traditional Chinese medicine （TCM）， but the quality of the implementation of blind methods is uneven， and the evaluation criteria have not yet been formed. In this paper， the data collection methods， calculation principles， advantages， and disadvantages of two quantitative quality evaluation methods of blind methods， namely James Blinding Index （JBI） and Bang Blinding Index （BBI）， were introduced. The two indexes were analyzed in a randomized controlled trial of acupuncture and moxibustion to relieve postoperative oral pain. The calculation process of the results was demonstrated by R software and visualized by forest map. At the same time， a tool table was designed to facilitate the collection of evaluation data of blind methods in TCM clinical trials at different stages. Finally， the necessity and feasibility of quality evaluation of blind method in TCM research were discussed to provide a basis for evaluating and improving the quality of blind method implementation in TCM clinical trials.