Objective To improve the sensitivity and broaden the applicability of N-of-1 trials in traditional Chinese medicine (TCM), the clinical application and methodology of single-case experimental designs (N-of-1trials, multiple-baseline designs; MBDs) were expounded, compared, and discussed. Methods This paper introduced the current utility of N-of-1 trials in TCM research, introduced MBDs, and compared the methodologies of N-of-1 trials, MBDs and crossover design. Finally, two design schemes to improve the sensitivity and applicability of N-of-1 trials were illustrated. Results N-of-1 trials conformed to the TCM concept of treatment based on syndrome differentiation; however, due to the complex composition of TCM, the results were easily affected by carryover effect. In MBDs, the intervention was introduced in a staggered way, no washout period was needed, and the required sample size was small. MBDs were generally used to preliminarily indicate the effect of intervention; however, the statistical analysis was relatively complicated, and there were few MBDs used in clinical trials of TCM at present. Compared with crossover trials, single-case experimental designs had advantages and disadvantages. N-of-1 trials might best reflect the individualized treatment of TCM and a suitable statistical model (e.g., hierarchical Bayesian statistical method) was expected to improve the sensitivity and applicability of N-of-1 trials in TCM. Combining clinical trial designs (e.g., the combination of N-of-1 trials and MBDs) would complement the limitations of N-of-1 trials, and expand the scope of conditions applicable for study. Conclusion N-of-1 trials have both advantages and disadvantages in TCM research. Improved statistical models or combined study designs will improve the sensitivity and broaden the applicability of N-of-1 trials in TCM.
ObjectiveA series of single-case randomized controlled trials (N-of-1 trials), with placebo Chinese herbs used as a control, were conducted to observe the efficacy of the syndrome differentiation treatment formula in the stable phase of bronchiectasis by using a modified mixed-effects model (MEM) to detect the "carryover effects" of Chinese herbs, and to explore the establishment of an N-of-1 trial method that reflects the characteristics of syndrome differentiation treatment in traditional Chinese medicine (TCM). MethodsA single-center clinical trial was conducted in which a single case was studied in a multiple crossover, randomized controlled, and blinded manner. There were three rounds of the trial, each with two observation periods (treatment period and control period) of 4 weeks each. In the treatment period, an individualized formula based on syndrome differentiation was given, and in the control period, a placebo formula was administered. The primary indicator was the patients’ self-rated 7-point symptom Likert scale score, and other indicators included chronic obstructive pulmonary disease assessment test (CAT) score, 24 h sputum volume, TCM syndrome score, and safety index. Paired t test was used to analyze single case data and MEM designed for "carryover effects" was used to analyze group data. ResultsA total of 21 subjects were formally enrolled, and 15 (75%) completed three rounds of N-of-1 trials. Three of the cases showed statistically significant differences in overall symptom Likert scale score. At the group level, the MEM designed for "carryover effects" found statistically significant residual effects on three indicators (overall symptom score, respiratory symptom score, and CAT score). After excluding the "carryover effects", the model analyzed the statistically significant differences between the intervention effects of the two formulas on the overall symptom score, respiratory symptom score, CAT score and TCM syndrome score. The sensitivity of the MEM was higher than that of the meta-analysis when residual effects existed in the N-of-1 trials. ConclusionThe N-of-1 trials of Chinese herbs designed in this study can well demonstrate the characteristics of TCM syndrome differentiation and treatment. The modified MEM can detect the residual effects of TCM and improve the sensitivity of data statistics. However, due to the inherent nature of N-of-1 trials, the sensitivity of this study method at the individual level is low and more cases and diseases need to be studied for further improvement.
Objective A series of N-of-1 trials were conducted to evaluate the effect of traditional Chinese medicine (TCM) individualized syndrome differentiation on stable bronchiectasis, and to explore a clinical trial method that is consistent with the characteristics of TCM. Methods The original plan was for 3 cycles, with each cycle consisting of two observation periods: experimental and control. Take the medication for 3 weeks each period and then stop for 1 week. Because the results were not as expected, another cycle of trials was added (a total of 4 cycles). The trial period was treated with individualized syndrome differentiation prescription and the control period was treated with placebo. The outcome measures were Likert scale score of general symptoms (primary outcome), Likert scale score of respiratory symptoms, CAT score, 24h sputum volume and TCM symptom score. Data analysis (including residual effects and stage effects analysis) used group-designed independent sample t tests, paired t tests or non-parametric tests, mixed effects models, and Bayesian analysis. Results A total of 31 participants were formally enrolled, with 24 completing all four cycles. Independent sample t-tests and mixed-effects models showed no significant period or carryover effects. Bayesian analysis showed that there were residual effects on some outcome measures of some individuals. Six participants showed statistically significant differences in overall symptom Likert scale scores (P<0.05). Bayesian analysis found that TCM was more effective than placebo in more individuals. No significant differences were found between individualized TCM and placebo at the group level for all outcome measures. Conclusion This study method highly simulates the clinical practice of TCM, with good operability and patient compliance, and has no obvious residual effect of TCM on the whole, which can provide the best individualized evidence-based medicine evidence of short-term efficacy of TCM. Bayesian analysis can improve the sensitivity of individual statistics.