A Series of N-of-1 Trials of Traditional Chinese Medicine Based on Bayesian Method

Quality of Life Clinical Trial

Official title: A Series of N-of-1 Trials on Bronchiectasis Treated With Traditional Chinese Medicine Based on Bayesian Model

Status Recruiting

Clinical Trial Summary

The guiding role of parallel randomized controlled trials in clinical practice is limited due to the insufficiency of individual information. Our previous studies showed that Single case randomized controlled trials (referred to as N-of-1 trials) could reflect the individualized characteristics of traditional Chinese medicine (TCM) syndrome differentiation with good feasibility, but the sensitivity was low.

This study aims to compare the efficacy of treatment based on syndrome differentiation with controlled decoctions (placebo, and the method of strengthening the body resistance and removing phlegm) among patients with stable bronchiectasis through a series of N-of-1 trials (single-patient, double-blind, randomized, multiple crossover design), with the 7 point-likert scale of the most concerned symptoms as the main outcome. Hierarchical Bayesian statistical methods and some parameters and variables will be introduced, such as TCM syndrome type, potential residue effect of TCM, etc. The sensitivity and applicability of various mathematical models (Hierarchical Bayesian, paired t-test and Meta-analysis) for N-of-1 trials of TCM will be tested, for the purpose of improving the sensitivity and applicability of N-of-1 trials of TCM both on individual and group levels.

Clinical Trial Description

TCM has made great progress in the context of modern science and technology, but compared with the rapid development of modern medicine, the development of TCM has been relatively slow. The randomized controlled trial based on population is incompatible with the characteristics of TCM syndrome differentiation. The lack of reliable efficacy evaluation methods based on evidence-based medicine has hindered the internationalization and development of TCM.

The clinical trial (International clinicaltrials.gov Identifier: NCT03147443) the investigators just finished found that the improved mixed effects model can detect the residual effect of TCM in the N-of-1 trials and improve the sensitivity of group data statistics. However, the sensitivity of this study method is low at the individual statistical level due to the inherent nature of N-of-1 trials, and more cases need to be studied for further improvement. Now that hierarchical Bayesian statistical method has become one of the major statistical methods in a series of N-of-1 trials. Compared with the frequentist statistical methods, the advantages of Bayesian method are as follows: (1) the integration analysis of both individual and group data can be carried out at the same time; (2) it is easy to introduce confounding variables, such as the physique or gene type of different subjects, or different TCM syndrome types (which are helpful to distinguish different TCM syndrome types and the difference of the effects); (3) in addition, there is a special advantage: if a large number of patients have completed similar N-of-1 trials with the variance within an individual patient greater than that between the patients, through "borrowing from strength" , the results of other patients can be used to improve the accuracy of an individual result, that is, to improve the sensitivity of N-of-1 trials, without the need to increase the pairs of N-of-1 trials. At present, this statistic method is rarely used in N-of-1 trials of TCM, so it is worth using for reference in our future research.

The key hypothesis of this study is that: (1) the efficacy of syndrome differentiation will be better than placebo in patients with stable bronchiectasis through N-of-1 trials. (2) the efficacy of syndrome differentiation will be better than the same prescription minus heat-clearing Chinese herbs in patients with stable bronchiectasis through N-of-1 trials. However, at the individual level, with the severity of individual phlegm heat, the efficacy will be different, reflecting the effect of individual treatment based on syndrome differentiation of Chinese medicine. (3) Hierarchical Bayesian statistical model will improve the sensitivity and applicability of N-of-1 trials of TCM both on individual and group levels.

In this study, the investigators will conduct a single center N-of-1 trials in 71 patients with stable bronchiectasis without hemoptysis and respiratory failure. These N-of-1 trials will be randomized, double-blind, crossover comparisons of individualized herbal decoction with control decoction within individual patients. Each N-of-1 trial will have 3 pairs of treatment periods. The duration of each treatment period will be 4 weeks. The investigators will compare: (1) the efficacy of syndrome differentiation (individualized decoction) with placebo, (2) the efficacy of syndrome differentiation (individualized decoction) with the same prescription minus heat-clearing Chinese herbs, in patients with stable bronchiectasis through a series of N-of-1 trials. The primary outcome is patient self-reported symptoms (such as cough, expectoration, shortness of breath, chest pain, and fatigue) scores on a 7 point likert scale. Secondary outcomes are 24-hour sputum volume and the chronic obstructive pulmonary disease (COPD) Assessment Test (CAT) scores. Hierarchical Bayesian statistical methods and some parameters and variables will be introduced, such as TCM syndrome type, potential residue effect of TCM, etc. The sensitivity and applicability of various mathematical models (Hierarchical Bayesian, paired t-test and Meta-analysis) for N-of-1 trials of TCM will be tested, for the purpose of improving the sensitivity and applicability of N-of-1 trials of TCM both on individual and group levels. ;

Related Conditions & MeSH terms

• Bronchiectasis
• Individuality
• Quality of Life
• Sputum
• Symptoms
• Traditional Chinese Medicine

• NCT number: NCT04601792
• Study type: Interventional
• Source: Shanghai University of Traditional Chinese Medicine
• Contact: Haiyin Huang, M.D.
• Phone: 008602165161782
• Email: huanghaiyin@shyueyanghospital.com
• Status: Recruiting
• Phase: Phase 4
• Start date: December 1, 2019
• Completion date: December 31, 2022