Auricular Acupoint Selection Patterns for Knee Osteoarthritis Pain Relief: A Systematic Review and Data Mining...

Area of Science:

• Integrative Medicine
• Traditional Chinese Medicine
• Neuroscience

Background:

• Knee osteoarthritis (KOA) is a prevalent degenerative joint disease causing significant pain and disability.
• Auricular therapy, a component of Traditional Chinese Medicine (TCM), involves stimulating specific points on the ear to treat various conditions.
• Systematic evaluation of auricular therapy for KOA pain and data-driven exploration of acupoint selection are needed.

Purpose of the Study:

• To systematically evaluate randomized controlled trials (RCTs) on auricular therapy for knee osteoarthritis pain.
• To identify and analyze acupoint selection patterns in auricular therapy for KOA using data mining techniques.

Main Methods:

• A comprehensive search of eleven Chinese and English databases was conducted up to September 1, 2025.
• Eligible RCTs were screened, assessed for methodological quality, and analyzed using descriptive statistics, frequency analysis, association rule mining, and hierarchical cluster analysis.
• Data mining techniques were employed to identify commonly used auricular points and their combinations for KOA treatment.

Main Results:

• Thirty-six studies involving 3,105 participants were included, with moderate overall quality and noted limitations in blinding and allocation reporting.
• The most frequently utilized acupoints included Shenmen (TF4), Xi (AH4), Jiaogan (AH6a), and Pizhixia (AT4).
• Association rule mining revealed Shenmen (TF4)-Pizhixia (AT4) as the most frequent co-occurring pair, while Cluster analysis identified three synergistic acupoint groups linked to nerve regulation, zang-fu organ function, and adjunctive regulation.

Conclusions:

• Auricular therapy demonstrates promising acupoint selection patterns for knee osteoarthritis pain relief, consistent with TCM principles and neurophysiological mechanisms.
• Methodological limitations, heterogeneity in protocols, and the exploratory nature of data mining necessitate cautious interpretation of current findings.
• Future research should focus on rigorously designed, preregistered RCTs with standardized protocols and transparent reporting to validate these patterns and assess clinical efficacy.