Acupuncture is increasingly recognized as a viable treatment option for chronic pain, yet a significant challenge in clinical practice is the variability in individual responses to this therapy. Recent neuroimaging research indicates that baseline characteristics of the brain might act as objective biomarkers for predicting how different patients respond to acupuncture. Some studies have reported classification accuracies surpassing 80%, which highlights the potential of these biomarkers to enhance clinical decision-making.
This systematic review seeks to fill the gap in existing literature by evaluating whether pre-treatment neuroimaging biomarkers can effectively forecast treatment responses to acupuncture in adults suffering from chronic pain. Systematic synthesis of these results is crucial, as it has not been previously conducted.
The protocol for this systematic review aligns with the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) guidelines. The search will encompass various databases, including MEDLINE, Embase, Cochrane Central Register of Controlled Trials, PubMed, and four Chinese databases – China National Knowledge Infrastructure, Wanfang Data, VIP Database, and Chinese Biomedical Literature.
Eligibility criteria necessitate a focus on adult participants (≥18 years) with chronic pain lasting three months or longer. All selected studies must include baseline neuroimaging modalities such as functional MRI, structural MRI, positron emission tomography (PET), or single-photon emission computed tomography (SPECT), coupled with acupuncture interventions and relevant clinical outcomes post-treatment.
Two independent reviewers will screen studies, extract data, and assess the risk of bias using respected tools, including the Prediction model Risk Of Bias Assessment Tool and Newcastle-Ottawa Scale. The primary outcomes will focus on predictive metrics such as accuracy, sensitivity, and specificity, along with identifying brain regions associated with predictive efficacy.
Meta-analysis will employ random-effects models if sufficient homogeneous studies exist. In instances where responder classification is possible, diagnostic test accuracy meta-analysis will be conducted to pool sensitivity and specificity across studies.
Since the review involves a secondary analysis of existing published data, ethical approval is not required. Outcomes and insights derived from this review will be disseminated through peer-reviewed publications and presented at relevant conferences. The findings aim to support the development of neuroimaging-based clinical decision tools and establish priorities for future research in biomarker validation related to acupuncture treatment.
Inclusion criteria will encompass adults aged 18 years or older experiencing chronic pain conditions, such as chronic low back pain, osteoarthritis, migraines, and neuropathic pain. All studies must implement baseline neuroimaging pre-treatment and include needle-based acupuncture interventions conducted by qualified practitioners. Comparator groups may vary, including sham acupuncture or usual care. Studies will be excluded if they involve unhealthy volunteers, acute pain, or lack treatment outcome data.
Searching will occur across multiple electronic databases without date restrictions. This will include substantial contributions from both English-language sources and Chinese literature due to the significant body of acupuncture research published in Chinese. By incorporating both types of databases, the aim is to capture the breadth of existing evidence pertaining to neuroimaging and acupuncture efficacy in managing chronic pain.
A comprehensive search strategy will be devised in consultation with a medical librarian to ensure optimal specificity and coverage across disciplines. Controlled vocabulary terms and free-text keywords will be used to explore acupuncture techniques, neuroimaging modalities, chronic pain conditions, and biostatistics relevant to predicting treatment responses. This strategy will broaden the inclusiveness of the search and enhance the study's comprehensiveness.
The insights gained from this review will not only substantiate the clinical utility of neuroimaging biomarkers in predicting acupuncture efficacy but will also pave the way for advancements in precision pain medicine that can lead to more individualized treatment strategies for chronic pain sufferers.