Reconciling Methodological Paradigms Toward More Accurate Evaluation of Personalized Traditional Chinese Medicine (TCM) Intervention in Standardized Trials: Introducing the TRIPLE-TCM Trial Framework

协调方法论范式,以期在标准化试验中更准确地评估个性化中医干预:引入TRIPLE-TCM试验框架

阅读:2

Abstract

Traditional Chinese Medicine (TCM) prioritizes highly individualized diagnosis and treatment, a principle that inherently conflicts with the standardized protocols of explanatory randomized controlled trials (RCTs). While pragmatic RCTs have been proposed to better reflect real-world TCM practice, their reliance on unblinded designs raises concerns about placebo effects and potential confounding biases, particularly for interventions like acupuncture. These methodological tensions highlight the need for innovative trial designs that can preserve TCM's personalized ethos while meeting the rigorous standards of evidence-based research. In response, we propose the T rans-paradigm Randomized-Individualized-Preference-Linked Efficacy/Effectiveness Evaluation for TCM (TRIPLE-TCM) framework-a hybrid trial design integrating explanatory RCTs, pragmatic RCTs, and partially randomized patient preference trials. TRIPLE-TCM employs a five-step procedure: (1) TCM pattern-guided recruitment to ensure diagnostic homogeneity; (2) hybrid randomization accommodating patient preferences; (3) semi-standardized interventions combining fixed core prescriptions with individualized adjustments; (4) a clinician-patient co-assessment model incorporating TCM-specific outcomes and validated biomarkers; and (5) cost-utility analyses to inform policy. This framework aims to balance internal and external validity while maintaining fidelity to TCM theory and clinical practice, providing a methodological bridge for TCM's broader acceptance. Further studies should validate its feasibility, reproducibility, and cross-cultural generalizability across diverse disease contexts and healthcare settings, advancing evidence-based integration of acupuncture and Chinese herbal medicine into global healthcare systems.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。