With increasing amount of attention being paid to single case randomized controlled trial (N-of-1 trials), sample size estimation has become an important issue for clinical researchers. This paper mainly introduces the model and hypothesis of N-of-1 trials. Based on the hypothetical model, sample size estimation methods of fixed model and random model are proposed. The premises of the model application, formulas and examples are then given. It is expected in case of conduction N-of-1 trials, the correct methods are used to estimate sample size and improve the research quality of N-of-1 trials.
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.
This paper mainly introduces the design, advantages, disadvantages and its application of single case of randomized controlled trials (N-of-1 trials), and also introduces the commonly used data analysis methods of N-of-1 trials including nonparametric test and parameter test methods (t-test, paired t-test, analysis of variance), mixed-effects model, and meta-analysis. N-of-1 trials are suitable for individualized treatment, and could be expected to be widely used in the research of modern medicine and traditional Chinese medicine.
It is potential for N-of-1 trials to evaluate economics of health care, however, it is still in the exploratory stage. With the advantage of accurate estimation of costs and effects, it is beneficial to promote the application of N-of-1 trials for economic evaluation in the era of precision medicine. In this study, we introduce the necessity, feasibility, selection, calculation of indicators and influence factors of N-of-1 trials for economic evaluation, and in order to provide references for researchers to perform related studies.
ObjectiveA simulation study was used to generate the multivariate normal distribution data with a residual effect based on series of N-of-1 trials. The statistical performance of paired t-test, mixed effect model and Bayesian mixed effect model were compared.MethodsThree-cycles N-of-1 trials were set, and the participants were randomly assigned to 2 different treatments in each cycle. The simulation study included the following procedures: producing six-dimensional normal distribution data, randomly allocating intervention methods and patients, adding residual effects, constructing and evaluating 3 models, and setting the parameters. The sample sizes were set as 3, 5, 8 and 10, and the correlation coefficients among different times were set as 0.0, 0.5 and 0.8. Different proportions of residual effects for the 2 groups were set. Type I error, power, mean error (ME), and mean square error (MSE) were used to compare the 3 models.ResultsWhen there was no residual effect in the 2 groups, type I errors of 3 models were approximately 0.05, and their MEs were approximately 0. Paired t-test had the highest power and the lowest MSE. When the residual effect existed in the 2 groups, the type I error of paired t-test increased, and its estimated value deviated from the true value (ME≠0). Type I errors of the mixed effect model and Bayesian mixed-effect model were approximately 0.05, and they had the same power. The estimated values of the two models were close to the true value (ME was approximately 0).ConclusionsWhen there is no residual effect (0% vs. 0%), paired t-test is suitable for data analysis of N-of-1 trials. When there is a residual effect, the mixed effect model and Bayesian mixed-effect model are suitable for data analysis of N-of-1 trials.
An N-of-1 trial was conducted in a single patient. Statistical analysis is one of the most important parts of N-of-1 trials. The methods of statistical analysis for N-of-1 trials were reported in some reviews. However, there was still a lack of comparative analysis of these methods. In this study, we introduced the characteristics of statistical methods commonly used as well as some statistical problems which should be paid attention in N-of-1 trials. It is useful to provide some reference for statistical methods in order to high quality N-of-1 trials.
N-of-1 trials are prospective clinical randomized cross-over controlled trials with multiple rounds of trial phase alternation designed with regard to a single patient. N-of-1 trials can provide clinical decision-makers with high-level evidence of the comparison of effect of intervention measures. Recently, an international team composed of many scholars published a SPIRIT extension for N-of-1 trials list (SPENT 2019) on the BMJ, with the purposes of clarifying the content design and improving the integrity and transparency of N-of-1 trial protocols. This article showed a detailed interpretation of the 14 main extension sub-items of the SPENT 2019 list with specific cases, aiming to further standardize the publication of domestic N-of-1 trials.
The method of evaluating clinical efficacy of traditional Chinese medicine is one of the hotspots in the field of traditional Chinese medicine in recent years. How to dynamically evaluate individual efficacy is one of the key scientific problems to explain the clinical efficacy of traditional Chinese medicine. At present, there are no recognized methods of evaluating individual efficacy of traditional Chinese medicine. In this study, we provided a method of dynamically evaluating individual efficacy of traditional Chinese medicine based on Bayesian N-of-1 trials after analyzing the current status of researches on methods of evaluating individual efficacy of traditional Chinese medicine. This method has the advantages of both N-of-1 trials and Bayesian multilevel models. It is feasible to evaluate individual efficacy of traditional Chinese medicine from the perspective of the design and analysis method. This study can provide an important basis for enriching and improving the methodology of evaluating individual efficacy of traditional Chinese medicine.
Bayesian N-of-1 trials is increasingly popular in recent years. This study introduced the principle, statistical requirements, application status, advantages and disadvantages of Bayesian N-of-1 trials. Although the application of Bayesian N-of-1 trials is still limited in small scale and some problems remain to be solved, but it can provide more posterior information, and it can be the most important type of N-of 1 trial in future.
N-of-1 trial design offers a methodologically sound approach to determining optimum treatment for an individual patient and solves some limitations of randomized controlled trials. This design could offer an efficient method of reaching a personal treatment regime tailored to suit individual needs and preferences. The paper introduces practical application, objects and the implementation process of N-of-1 trial, to explore its design points and implementation.