Key Points

Question  What is the effect of electroacupuncture vs sham treatment on pain severity in adults with chronic low back pain?

Findings  In this randomized clinical trial including 121 adults with chronic low back pain, there was no significant difference between real and sham electroacupuncture conditions in reduction in pain scores 2 weeks after treatment; however, real electroacupuncture resulted in statistically and clinically greater reduction in back pain–specific disability compared with the sham control. Having coping strategies and not being White race were associated with treatment response to real electroacupuncture.

Meaning  This randomized clinical trial found no difference in pain reduction between real and sham electroacupuncture, but there was greater reduction in back pain–specific disability compared with sham control.

Abstract

Importance  Chronic low back pain has high societal and personal impact but remains challenging to treat. Electroacupuncture has demonstrated superior analgesia compared with placebo in animal studies but has not been extensively studied in human chronic pain conditions.

Objective  To evaluate the treatment effect of real electroacupuncture vs placebo in pain and disability among adults with chronic low back pain and to explore psychophysical, affective, and demographic factors associated with response to electroacupuncture vs placebo in treating chronic low back pain.

Design, Setting, and Participants  This double-blind randomized clinical trial was conducted between August 2, 2016, and December 18, 2018, at a single center in Stanford, California. Primary outcomes were collected at approximately 2 weeks before and after intervention. Participants included English-speaking adults with at least 6 months of chronic low back pain, pain intensity of at least 4 on a scale of 0 to 10, and no radiculopathy. Data analyses for this intent-to-treat study were conducted from June 2019 to June 2020.

Interventions  Twelve sessions of real or placebo (sham) electroacupuncture administered twice a week over 6 weeks.

Main Outcomes and Measures  The main outcome was change in pain severity from baseline to 2 weeks after completion of treatment, measured by the National Institutes of Health PROMIS pain intensity scale. A secondary outcome was change in the Roland Morris Disability Questionnaire (RMDQ). Baseline factors potentially associated with these outcomes included psychophysical testing (ie, thermal temporal summation, conditioned pain modulation, pressure pain threshold), participant’s self-report (ie, widespread pain, coping strategies, expectations, self-efficacy, and pain catastrophizing), and demographic characteristics (eg, age, sex, and race).

Results  A total of 121 adults were recruited to the study, among whom 59 participants (mean [SD] age, 46.8 [11.9] years; 36 [61.0%] women) were randomized to real electroacupuncture and 62 participants (mean [SD] age, 45.6 [12.8] years; 33 [53.2%] women) were randomized to sham electroacupuncture. At baseline, the mean (SD) PROMIS T-score was 50.49 (3.36) in the real electroacupuncture group and 51.71 (4.70) in the sham acupuncture group, and the mean (SD) RMDQ score was 10.16 (4.76) in the real electroacupuncture group and 10.03 (5.45) in the sham acupuncture group. After adjusting for baseline pain scores, there was no statistically significant difference between groups in change in T-scores 2 weeks after completion of treatment (real electroacupuncture: −4.33; 95% CI, −6.36 to −2.30; sham acupuncture: −2.90; 95% CI, −4.85 to −0.95; difference: −2.09; 95% CI, −4.27 to 0.09; P = .06). After adjusting for baseline RMDQ, there was a significantly greater reduction in RMDQ in the real electroacupuncture group (−2.77; 95% CI, −4.11 to −1.43) compared with the sham electroacupuncture group (−0.67; 95% CI, −1.88 to 0.55; difference: −2.11; 95% CI, −3.75 to −0.47; P = .01). Within the real electroacupuncture group, effective coping at baseline was associated with greater RMDQ reduction (r = −0.32; 95% CI, −0.54 to −0.05; P = .02), and White race was associated with worse outcomes in PROMIS score (β = 3.791; 95% CI, 0.616 to 6.965; P = .02) and RMDQ (β = 2.878; 95% CI, 0.506 to 5.250; P = .02).

Conclusions and Relevance  This randomized clinical trial found no statistically significant difference in change in PROMIS pain score in real electroacupuncture vs sham electroacupuncture. There was a statistically significant treatment effect for the secondary outcome of RMDQ compared with sham electroacupuncture. Effective coping skills and non-White race were associated with response to electroacupuncture.

Trial Registration  ClinicalTrials.gov Identifier: NCT02890810

Introduction

Chronic low back pain is a leading cause of disability in the United States, second only to ischemic heart disease and lung cancer.1 Pharmacological and surgical treatments for chronic low back pain are associated with adverse effects, such as addiction and surgical complications.2,3 Most clinical trials on acupuncture for chronic low back pain thus far involve manual acupuncture and found similar magnitudes of effect between real and sham (placebo) acupuncture.4-6 Preclinical studies suggest that electroacupuncture may lead to stronger analgesic outcomes than manual acupuncture.7,8 However, the few controlled clinical trials that evaluated electroacupuncture in chronic low back pain had methodological limitations, such as absence of blinding and small sample sizes,9,10 and have not examined factors associated with response.

It is important to identify factors associated with clinical response to acupuncture, because, although recent evidence established acupuncture as an effective treatment of chronic low back pain,11,12 the response rate to acupuncture is approximately 40% to 60%.5,6 As the US and other health care systems begin to rely on acupuncture as a mainstay of opioid-sparing therapy for chronic low back pain,13,14 early identification of responders would improve triaging and facilitate the pragmatic implementation of acupuncture. The existing knowledge on factors associated with clinical response to acupuncture is from research on manual acupuncture, mainly focused on baseline pain and function, demographic characteristics, and expectations of benefits, with limited overall predictive power.15-17

This randomized clinical trial investigated the effectiveness of electroacupuncture in treating chronic low back pain, but with the additional aim of identifying factors associated with treatment response using change in pain reduction and disability as clinical outcomes. The association between prespecified key factors associated with response and pain intensity formed the basis of our power calculation. Consistent with our aim to identify differential factors associated with response to electroacupuncture, we used the least active yet credible sham control (nonpenetrating Streitberger needles18 on off-meridian points without active stimulation)19 to better differentiate the real from the sham electroacupuncture models. To maximize generalizability to clinical practice, we administered the interventions at the clinics of multiple community acupuncturists near participants’ residences using a semistandardized treatment protocol.20

We examined a broad range of potential factors associated with clinical response. In addition to those previously examined, we evaluated impairment in central pain regulation as potential associated factors. We specifically focused on augmented ascending facilitation and reduced descending inhibition, which are considered key mechanisms in the development and maintenance of chronic pain21,22 and can be approximated by specific measures from quantitative sensory testing.23,24 We also examined psychological factors associated with chronic pain, including pain catastrophizing,25 self-efficacy in managing pain,26 and coping.27

Methods

Study Design and Participants

The Trial Protocol in Supplement 1 was reviewed and approved by the Stanford University institutional review board, and written informed consent was obtained from all participants before any experimental procedures. The reporting of the study follows the Consolidated Standards of Reporting Trials (CONSORT) reporting guideline.

We conducted a single-center, parallel-arm, randomized clinical trial comparing real vs sham electroacupuncture in treating patients with chronic low back pain. The main inclusion criteria were adults aged 21 to 65 years who were fluent in English, had chronic low back pain for at least 6 months (as defined by the National Institutes of Health Task Force on Research Standards for Chronic Low Back Pain28), and had back pain intensity of at least 4 on a 0 to 10 numerical rating scale in the past month. The main exclusion criteria were radicular pain due to disc compression or spinal stenosis evidenced by examination or magnetic resonance imaging, other pain conditions with an intensity greater than the low back pain, or recent acupuncture experience within the last 3 years (Figure). Additional eligibility details are listed in eAppendix 1 in Supplement 2.

Interventions

The real and sham treatments included twelve 45-minute sessions over 6 weeks. In both interventions, the participant was positioned comfortably in the prone position and received approximately 30 minutes of active or sham electrical stimulation after all needles were placed.20 The detailed treatment protocol is provided in the Trial Protocol in Supplement 1.

Participants were randomized with equal chances to receive real or sham treatments, stratified to 10 acupuncturists. A participant first selected an acupuncturist based on geographic preference and was then randomized to treatment arm by a person unrelated to the study, using the randomization table corresponding to the patient’s selected acupuncturist. Both the participant and the outcome assessor, but not the acupuncturist, were blinded to treatment assignment.

Outcome

Primary Clinical Outcome

The intensity of back pain was measured by the National Institutes of Health PROMIS pain intensity instrument, using T-scores calibrated to the general US population.29 The primary outcome was the change in T-score (posttreatment score – pretreatment score).

Secondary Clinical Outcome

Back pain–specific disability was measured by the Roland Morris Disability Questionnaire (RMDQ).30 The secondary outcome was the change in the total RMDQ score (posttreatement score – pretreatment score). The scoring of the RMDQ ranges from 0 to 24, in which 0 indicates no disability and 24, highest level of back-related disability.

Factors Associated With Response

The 14 prespecified potential factors associated with response with details of their measurement24,31-42 are presented in Table 1. Both PROMIS pain and RMDQ scores were collected at the pretreatment and posttreatment visits, approximately 2 weeks before the first treatment session and 2 weeks after the last treatment session. All variables were collected at the pretreatment visit.

Study Power

We powered the study to detect associations (correlations) between key baseline factors (eg, temporal summation [TS]) and the primary clinical outcome (ie, pain reduction). We first computed the number of participants needed to find an association between TS and pain reduction within the real electroacupuncture arm. We estimated that, with 80% power and .05 two-tailed α, 50 participants would be needed to detect a correlation of approximately 0.4, which represents a moderate but clinically meaningful association. This correlation is achievable based on previous findings of associations between pain reduction and TS,43 and separately, pressure pain threshold.44 Second, we assessed if the association is stronger in the real arm than the sham arm. Fifty patients per group would provide 80% power (with α = .05) to detect a difference between a correlation of 0.28 in the real condition and a correction of −0.28 in the sham condition. We would need approximately 60 participants per arm assuming 20% attrition.

Statistical Analysis

Treatment Effect Estimation and Blinding Assessment

We used analysis of covariance to estimate the effect of the treatment interventions on pain and RMDQ, adjusted to the baseline pain or RMDQ. We assessed the success of blinding at the end of the 12th treatment (Trial Protocol in Supplement 1) and its influence on treatment effect. The success of blinding was quantified by Bang blinding index within each arm.45,46 We then assessed the impact of blinding on the treatment effect by including a blinded variable (0 if the participant correctly guessed their treatment group and 1 otherwise) in the analysis of covariance.

Identification of Factors Associated With Response

We explored factors associated with treatment response via 3 steps, whereby the first 2 steps were used to reduce the number of factors in the multivariable models in the third step. First, we examined the associations between each factor and the 2 main outcomes separately within the real and sham conditions. For continuous variables, we estimated the partial correlation coefficients, and for the categorical variables (ie, sex and race) we tested linear regression models, adjusted for baseline pain and RMDQ scores. Second, we quantified the interaction between each factor and treatment allocation in linear regression models. Each model contained 4 covariates: baseline dependent variable, binary treatment indicator, factor of interest, and interaction between the factor of interest and treatment. We accounted for multiple testing by applying the Benjamin-Hotchberg procedure to control the family-wise type 1 error rate at the α = .05 level. Third, the factors of interest for the models were selected based on a cutoff P value of .05 from the first step to build models to estimate change in pain and RMDQ. Additionally, for the analyses based on the full sample, a treatment interaction term with the lowest P value from the second step was included.

Missing Values

The missingness of our data was examined by Little missing completely at random test47 from the BaylorEdPsych package in R statistical software version 3.5.2 (R Project for Statistical Computing). The P value for the Little missing completely at random test was .30, not suggesting any violation of the missing completely at random assumption. We thus performed complete-case analysis on our primary outcomes (ie, pain and RMDQ scores) according to the intention-to-treat (ITT) principle.48 Completion cases were defined as individuals who presented for both the pretreatment and posttreatment visits regardless of the number of treatment sessions they received.

Outlier and Sensitivity Analysis

Sensitivity analysis (eAppendix 2 in Supplement 2) identified a single outlier from the real electroacupuncture condition with change in pain score of more than 2 interquartile ranges above the third quartile49 and was singularly responsible for the 2 univariate associations involving change in pain. We therefore conducted analyses with and without this outlier.

Results

Participant Characteristics

A total of 121 participants were recruited. Of 59 individuals randomized to the real electroacupuncture condition (mean [SD] age, 46.8 [11.9] years; 36 [61.0%] women), 52 attended the assessment visits and were included in the ITT analysis (50 participants had ≥9 treatment sessions). Of 62 individuals randomized to the sham condition (mean [SD] age, 45.6 [12.8] years; 33 [53.2%] women), 54 attended the assessment visits and were included in the ITT analysis (53 participants had ≥9 treatment sessions). The baseline characteristics were comparable between conditions (eTable 1 in Supplement 2). At baseline, the mean (SD) T-score was 50.49 (3.36) in the real electroacupuncture condition and 51.71 (4.79) in the sham acupuncture condition. The mean (SD) RMDQ score was 10.16 (4.76) in the real electroacupuncture group and 10.03 (5.45) in the sham electroacupuncture group.

Treatment Effect

Pain T-Score and RMDQ

At the final assessment 2 weeks after completion of treatment, there was no statistically significant difference between groups in change in pain T-scores (real electroacupuncture: −4.33; 95% CI, −6.36 to −2.30; sham acupuncture: −2.90; 95% CI, −4.85 to −0.95; unadjusted difference: −1.50; 95% CI, −3.72 to 0.72; P = .18; adjusted difference: −2.09; 95% CI, −4.27 to 0.09; P = .06). However, there was a significant difference in the reduction of RMDQ scores between groups, with a greater reduction in the real electroacupuncture group (real electroacupuncture: −2.77; 95% CI, −4.11 to −1.43; sham electroacupuncture: −0.67; 95% CI, −1.88 to 0.55; unadjusted difference: −2.10; 95% CI, −3.89 to −0.31; P = .02), and the difference was unaffected by adjustment to the baseline RMDQ levels (adjusted difference: −2.11; 95% CI, −3.75 to −0.47; P = .01).

Blinding Assessment, Outlier, and Impact on Treatment Effect

Of 48 individuals assigned to the real electroacupuncture condition who provided data on blinding, 28 (58.3%) correctly guessed their treatment. Of 46 individuals assigned to the sham condition who provided data on blinding, 20 (42.5%) correctly guessed their assignment. The Bang blinding index was 0.50 (95% CI, 0.32 to 0.68) for the real electroacupuncture group and 0.20 (95% CI, −0.07 to 0.46) for the sham group. These indices suggest that the blinding for the sham condition was adequate while that for the real electroacupuncture condition was not (eTable 2 in Supplement 2). After accounting for the blinding status of each participant, the treatment effect on change in RMDQ remained significant (β = −2.23; 95% CI, −4.03 to −0.42; P = .02), while the treatment effect on change in PROMIS pain score remained not statistically significant (β = −2.09; 95% CI, −4.56 to 0.37; P = .10).

After removal of the single outlier, the treatment effect on both changes in PROMIS pain and RMDQ scores became significant (change in pain: β = −2.48, 95% CI, −4.51, −0.46; P = .02; change in RMDQ: β = −2.13; 95% CI, −3.79 to −0.48; P = .01). These treatment effects remained significant after accounting for blinding status (change in pain: β = −2.61; 95% CI, −4.90 to −0.33; P = .03; change in RMDQ: β = −2.24; 95% CI, −4.07 to −0.41; P = .02).

Analysis of Factors Associated With Treatment Response

Results from the univariate analysis in the real electroacupuncture condition are shown in Table 2. The partial correlation between coping and change in RMDQ remained significant regardless of the outlier, whereas the correlations between change in pain and TS or expectations disappeared on removal of the outlier. White race was associated with worse outcomes in pain with the outlier (β = 4.408; 95% CI, 0.880 to 7.936; P = .02) and excluding the outlier (β = 3.791; 95% CI, 0.616 to 6.965; P = .02) and in RMDQ (with outlier: β = 2.840; 95% CI, 0.507 to 5.172; P = .02; excluding outlier: β = 2.878; 95% CI, 0.506 to 5.250; P = .02). No relationships between the factors of interest and the outcomes were observed in the sham condition (eTable 3 in Supplement 2). Furthermore, in a post hoc analysis for the entire sample (excluding the outlier), we found that compared with participants who were not Asian, Asian participants experienced statistically significant, greater reductions in both pain (change, 2.85; 95% CI, 0.13 to 5.58; P = .04) and RMDQ (change, 2.45; 95% CI, 0.02 to 4.89; P = .049). None of the prespecified factors of interest demonstrated statistically significant interactions with treatment allocation (eTable 4 in Supplement 2). The results of the models, with or without the outlier, are shown in Table 3 for the real acupunctured condition and Table 4 for both conditions.

Adverse Effects

No serious adverse effects were reported by any participants in the study. eTable 5 in Supplement 2 provides details on minor adverse effects.

Discussion

This randomized clinical trial found no significant difference in chronic low back pain scores between real and sham electroacupuncture treatment. Post hoc analyses found a significant treatment effect of electroacupuncture in reducing disability associated with chronic low back pain. Consistent with previous research15-17 and likely related to regression to mean, participants in the real treatment arm who had greater pain intensity and RMDQ scores experienced greater improvement in RMDQ scores. Unique to this study was the association between effective coping and greater RMDQ reduction and between White race and less reduction in both pain and RMDQ. Finally, after eliminating a single outlier, the treatment effect became significant in RMDQ and pain scores.

Treatment Effect of Electroacupuncture

As one of the first randomized clinical trials evaluating electroacupuncture in treating chronic low back pain, our study found a treatment effect in RMDQ. This treatment effect (ie, between-arm difference in change in RMDQ) was present with or without the outlier and after accounting for blinding status. This finding was clinically significant, falling within the range of minimally clinically important difference of RMDQ (ie, 2-8 points).50-52 By comparison, the treatment effects discovered on previous trials was between 0.1 and 1.7 points.5,53,54

Consistent with our original intent to maximize the difference between the real and sham electroacupuncture conditions to facilitate differential model-building, we selected a strong real electroacupuncture protocol. It consisted of active electrical stimulation,7 more than 20 needles per session,55 and biweekly treatment frequency,56 all of which are supported by existing studies and likely contributed to the robust treatment effect in RMDQ observed in our study.

The between-arm difference in pain reduction was not statistically significant for the full sample. Existing literature suggests that clinically significant minimally clinically important difference of PROMIS pain instruments are between 2 to 3 points of change in T-score.57,58 We note that the between-arm difference in pain reduction became clinically and statistically significant on removal of the single outlier.

Finally, interpretation of our results on treatment effect should be tempered by the fact that our study was originally designed to capture univariate associations between patient characteristics and clinical outcomes in the real acupuncture arm. The treatment effect in RMDQ, although robust, was captured in post hoc analyses. Larger studies are needed to replicate our findings. Post hoc power calculation suggests we would need 72 participants per arm to detect treatment effect in RMDQ and 91 participants per arm to detect treatment effect in pain with 80% power.

Factors Associated With Treatment Response

Unique to our study is the finding of an association between positive coping strategies and functional improvement, seen both on the univariate and multivariate analyses. In a 2015 study, Bishop et al31 found a similar association in an observational cohort of patients with mixed back pain causes. Our study advances the understanding on the role of coping in response to acupuncture by confirming its association with RMDQ reduction in a randomized clinical trial in a homogenous participant sample of individuals with chronic low back pain.

Contrary to our original hypothesis, the association between TS and change in pain was unstable and vanished on removal of a single outlier. This, in contrast to the stable relationship between coping and change in RMDQ, may be explained by the paramount role of the so-called emotional brain in the development and maintenance of chronic pain.59,60 Psychological variables may be stronger factors associated with response and amplifiers of chronic pain than somatosensory variables, such as those measured by quantitative sensory testing. As such, future studies should continue to investigate cognitive-emotional factors associated with acupuncture response and may consider combining acupuncture with psychological interventions.61

Finally, we found that White race was associated with worse outcomes in pain and RMDQ in the real electroacupuncture condition. This racial influence may be driven by differences in cultural backgrounds, in that participants with backgrounds that include traditional Chinese medicine may be more likely to respond to acupuncture.62 Our study was conducted in Stanford, California, where most of the racial/ethnic minority population are of East Asian descent and are open to receiving acupuncture and for treatment of various conditions, including chronic pain. Future studies should confirm our results in larger multicultural samples and test the interaction between cultural background and treatment allocation.

Limitations

Our study has some limitations. First, our study does not quantify the specific effect of electroacupuncture vs manual acupuncture, which could be assessed in a 3-arm study that includes a placebo control, manual acupuncture, and electroacupuncture. Second, whereas, to our knowledge, ours is the first study on acupuncture for chronic low back pain that has assessed and accounted blinding status in analyses, only 48 of 52 participants in the real electroacupuncture condition and 46 of 54 participants in the sham condition provided blinding data at study completion. Although the missing blinding data were due to implementation imperfections and not to participants’ refusal to answer the questions, we cannot rule out the possibility that results may have been different if all participants had provided blinding data. However, our analysis did demonstrate a statistically significant treatment effect on RMDQ after accounting for the available blinding status in every individual. Thirdly, our outcome collection spanned approximately 10 weeks (2 weeks before and 2 weeks after 6 weeks of interventions). We designed our study in this manner to capture the largest possible treatment effect assuming most benefits emerge immediately after our interventions. Longer outcomes are more meaningful clinically and should be collected and analyzed in future studies.

Conclusions

This randomized clinical trial found no significant difference in change in pain scores between real and sham electroacupuncture. However, to our knowledge, this is the first study to demonstrate a statistically and clinically significant treatment effect of electroacupuncture on disability associated with chronic low back pain in a randomized clinical trial. Our study also contributes to current knowledge on the patient factors associated with clinical response to electroacupuncture treatment. If validated, these findings may help match people to treatment. For example, low scores on the coping strategies questionnaire could identify individuals who may need psychological intervention alone or as an augmentation to electroacupuncture.

Back to top

Article Information

Accepted for Publication: August 20, 2020.

Published: October 27, 2020. doi:10.1001/jamanetworkopen.2020.22787

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2020 Kong J-T et al. JAMA Network Open.

Corresponding Author: Jiang-Ti Kong, MD, Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, 1070 Arastradero Rd, Ste 200, Palo Alto, CA 94304 (jtkong@stanford.edu).

Author Contributions: Dr Kong had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Kong, Lee, Manber, Mackey.

Acquisition, analysis, or interpretation of data: Kong, Puetz, Tian, Haynes, Lee, Stafford.

Drafting of the manuscript: Kong, Puetz, Tian, Lee.

Critical revision of the manuscript for important intellectual content: Kong, Puetz, Haynes, Lee, Stafford, Manber, Mackey.

Statistical analysis: Kong, Puetz, Tian, Lee, Stafford.

Obtained funding: Kong, Mackey.

Administrative, technical, or material support: Kong, Puetz, Haynes, Lee, Mackey.

Supervision: Mackey.

Conflict of Interest Disclosures: Dr Kong reported receiving grants from National Center for Complementary and Integrative Health during the conduct of the study. Dr Mackey reported receiving grants from National Center for Complementary and Integrative Medicine during the conduct of the study. No other disclosures were reported.

Funding/Support: This study was supported by grant Nos. K23 AT008477 from (Dr Kong, Ms Puetz, Drs Haynes, and Lee), K24 DA029262 (Dr Mackey), and P01 AT006651 (Drs Mackey, Manber, Lu, and Kong) from the National Institutes of Health, and by the Chris Redlich Endowment (Dr Mackey).

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 3.

References

1.

Mokdad  AH, Ballestros  K, Echko  M,  et al; US Burden of Disease Collaborators.  The state of US health, 1990-2016: burden of diseases, injuries, and risk factors among US states.   JAMA. 2018;319(14):1444-1472. doi:10.1001/jama.2018.0158
ArticlePubMedGoogle ScholarCrossref

2.

Grotle  M, Småstuen  MC, Fjeld  O,  et al.  Lumbar spine surgery across 15 years: trends, complications and reoperations in a longitudinal observational study from Norway.   BMJ Open. 2019;9(8):e028743. doi:10.1136/bmjopen-2018-028743PubMedGoogle Scholar

3.

Chou  R, Deyo  R, Friedly  J,  et al.  Systemic pharmacologic therapies for low back pain: a systematic review for an American College of Physicians clinical practice guideline.   Ann Intern Med. 2017;166(7):480-492. doi:10.7326/M16-2458PubMedGoogle ScholarCrossref

4.

Brinkhaus  B, Witt  CM, Jena  S,  et al.  Acupuncture in patients with chronic low back pain: a randomized controlled trial.   Arch Intern Med. 2006;166(4):450-457. doi:10.1001/archinte.166.4.450
ArticlePubMedGoogle Scholar

5.

Cherkin  DC, Sherman  KJ, Avins  AL,  et al.  A randomized trial comparing acupuncture, simulated acupuncture, and usual care for chronic low back pain.   Arch Intern Med. 2009;169(9):858-866. doi:10.1001/archinternmed.2009.65
ArticlePubMedGoogle ScholarCrossref

6.

Haake  M, Müller  HH, Schade-Brittinger  C,  et al.  German Acupuncture Trials (GERAC) for chronic low back pain: randomized, multicenter, blinded, parallel-group trial with 3 groups.   Arch Intern Med. 2007;167(17):1892-1898. doi:10.1001/Archinte.167.17.1892
ArticlePubMedGoogle ScholarCrossref

7.

Langevin  HM, Schnyer  R, MacPherson  H,  et al; Executive Board of the Society for Acupuncture Research.  Manual and electrical needle stimulation in acupuncture research: pitfalls and challenges of heterogeneity.   J Altern Complement Med. 2015;21(3):113-128. doi:10.1089/acm.2014.0186PubMedGoogle ScholarCrossref

8.

Zheng  Z, Feng  SJ, Costa  Cd, Li  CG, Lu  D, Xue  CC.  Acupuncture analgesia for temporal summation of experimental pain: a randomised controlled study.   Eur J Pain. 2010;14(7):725-731. doi:10.1016/j.ejpain.2009.11.006PubMedGoogle ScholarCrossref

9.

Lehmann  TR, Russell  DW, Spratt  KF,  et al.  Efficacy of electroacupuncture and TENS in the rehabilitation of chronic low back pain patients.   Pain. 1986;26(3):277-290. doi:10.1016/0304-3959(86)90057-6PubMedGoogle ScholarCrossref

10.

Chou  R, Qaseem  A, Owens  DK, Shekelle  P; Clinical Guidelines Committee of the American College of Physicians.  Diagnostic imaging for low back pain: advice for high-value health care from the American College of Physicians.   Ann Intern Med. 2011;154(3):181-189. doi:10.7326/0003-4819-154-3-201102010-00008PubMedGoogle ScholarCrossref

11.

Berman  BM, Langevin  HM, Witt  CM, Dubner  R.  Acupuncture for chronic low back pain.   N Engl J Med. 2010;363(5):454-461. doi:10.1056/NEJMct0806114PubMedGoogle ScholarCrossref

12.

Vickers  AJ, Vertosick  EA, Lewith  G,  et al; Acupuncture Trialists’ Collaboration.  Acupuncture for chronic pain: update of an individual patient data meta-analysis.   J Pain. 2018;19(5):455-474. doi:10.1016/j.jpain.2017.11.005PubMedGoogle ScholarCrossref

13.

Mao  JJ, Davis  RT, Coeytaux  R,  et al.  Acupuncture for chronic low back pain: recommendations to Medicare/Medicaid from the Society for Acupuncture Research.   J Altern Complement Med. 2019;25(4):367-369. doi:10.1089/acm.2019.29067.jjmPubMedGoogle ScholarCrossref

14.

Rubin  R.  Medicare proposes coverage of acupuncture for lower back pain.   JAMA. 2019;322(8):716-716. doi:10.1001/jama.2019.11573
ArticlePubMedGoogle Scholar

15.

Sherman  KJ, Cherkin  DC, Ichikawa  L,  et al.  Characteristics of patients with chronic back pain who benefit from acupuncture.   BMC Musculoskelet Disord. 2009;10:114. doi:10.1186/1471-2474-10-114PubMedGoogle ScholarCrossref

16.

Witt  CM, Vertosick  EA, Foster  NE,  et al; Acupuncture Trialists’ Collaboration.  The effect of patient characteristics on acupuncture treatment outcomes: an individual patient data meta-analysis of 20,827 chronic pain patients in randomized controlled trials.   Clin J Pain. 2019;35(5):428-434. doi:10.1097/AJP.0000000000000691PubMedGoogle ScholarCrossref

17.

Witt  CM, Schützler  L, Lüdtke  R, Wegscheider  K, Willich  SN.  Patient characteristics and variation in treatment outcomes: which patients benefit most from acupuncture for chronic pain?   Clin J Pain. 2011;27(6):550-555. doi:10.1097/AJP.0b013e31820dfbf5PubMedGoogle ScholarCrossref

18.

Streitberger  K, Kleinhenz  J.  Introducing a placebo needle into acupuncture research.   Lancet. 1998;352(9125):364-365. doi:10.1016/S0140-6736(97)10471-8PubMedGoogle ScholarCrossref

19.

Wayne  PM, Krebs  DE, Macklin  EA,  et al.  Acupuncture for upper-extremity rehabilitation in chronic stroke: a randomized sham-controlled study.   Arch Phys Med Rehabil. 2005;86(12):2248-2255. doi:10.1016/j.apmr.2005.07.287PubMedGoogle ScholarCrossref

20.

Kong  JT, MacIsaac  B, Cogan  R,  et al.  Central mechanisms of real and sham electroacupuncture in the treatment of chronic low back pain: study protocol for a randomized, placebo-controlled clinical trial.   Trials. 2018;19(1):685. doi:10.1186/s13063-018-3044-2PubMedGoogle ScholarCrossref

21.

Sanzarello  I, Merlini  L, Rosa  MA,  et al.  Central sensitization in chronic low back pain: a narrative review.   J Back Musculoskelet Rehabil. 2016;29(4):625-633. doi:10.3233/BMR-160685PubMedGoogle ScholarCrossref

22.

Woolf  CJ.  Central sensitization: implications for the diagnosis and treatment of pain.   Pain. 2011;152(3)(suppl):S2-S15. doi:10.1016/j.pain.2010.09.030PubMedGoogle Scholar

23.

Kong  JT, Schnyer  RN, Johnson  KA, Mackey  S.  Understanding central mechanisms of acupuncture analgesia using dynamic quantitative sensory testing: a review.   Evid Based Complement Alternat Med. 2013;2013:187182. doi:10.1155/2013/187182PubMedGoogle Scholar

24.

Rolke  R, Baron  R, Maier  C,  et al.  Quantitative sensory testing in the German Research Network on Neuropathic Pain (DFNS): standardized protocol and reference values.   Pain. 2006;123(3):231-243. doi:10.1016/j.pain.2006.01.041PubMedGoogle Scholar

25.

Wertli  MM, Eugster  R, Held  U, Steurer  J, Kofmehl  R, Weiser  S.  Catastrophizing-a prognostic factor for outcome in patients with low back pain: a systematic review.   Spine J. 2014;14(11):2639-2657. doi:10.1016/j.spinee.2014.03.003PubMedGoogle Scholar

26.

Costa  LdaC, Maher  CG, McAuley  JH, Hancock  MJ, Smeets  RJ.  Self-efficacy is more important than fear of movement in mediating the relationship between pain and disability in chronic low back pain.   Eur J Pain. 2011;15(2):213-219. doi:10.1016/j.ejpain.2010.06.014PubMedGoogle Scholar

27.

Gatchel  RJ, Rollings  KH.  Evidence-informed management of chronic low back pain with cognitive behavioral therapy.   Spine J. 2008;8(1):40-44. doi:10.1016/j.spinee.2007.10.007PubMedGoogle Scholar

28.

Deyo  RA, Dworkin  SF, Amtmann  D,  et al.  Report of the NIH Task Force on research standards for chronic low back pain.   Pain Med. 2014;15(8):1249-1267. doi:10.1111/pme.12538PubMedGoogle Scholar

29.

Cook  KF, Dunn  W, Griffith  JW,  et al.  Pain assessment using the NIH Toolbox.   Neurology. 2013;80(11)(suppl 3):S49-S53. doi:10.1212/WNL.0b013e3182872e80PubMedGoogle Scholar

30.

Ostelo  RWJG, de Vet  HCW, Knol  DL, van den Brandt  PA.  24-item Roland-Morris Disability Questionnaire was preferred out of six functional status questionnaires for post-lumbar disc surgery.   J Clin Epidemiol. 2004;57(3):268-276. doi:10.1016/j.jclinepi.2003.09.005PubMedGoogle Scholar

31.

Bishop  FL, Yardley  L, Prescott  P, Cooper  C, Little  P, Lewith  GT.  Psychological covariates of longitudinal changes in back-related disability in patients undergoing acupuncture.   Clin J Pain. 2015;31(3):254-264. doi:10.1097/AJP.0000000000000108PubMedGoogle Scholar

32.

Zucker  NA, Tsodikov  A, Mist  SD, Cina  S, Napadow  V, Harris  RE.  Evoked pressure pain sensitivity is associated with differential analgesic response to verum and sham acupuncture in fibromyalgia.   Pain Med. 2017;18(8):1582-1592. doi:10.1093/pm/pnx001PubMedGoogle Scholar

33.

Price  DD, Hu  JW, Dubner  R, Gracely  RH.  Peripheral suppression of first pain and central summation of second pain evoked by noxious heat pulses.   Pain. 1977;3(1):57-68. doi:10.1016/0304-3959(77)90035-5PubMedGoogle Scholar

34.

Mackey  IG, Dixon  EA, Johnson  K, Kong  JT.  Dynamic quantitative sensory testing to characterize central pain processing.   J Vis Exp. 2017;(120):54452. doi:10.3791/54452PubMedGoogle Scholar

35.

Baeumler  PI, Conzen  P, Irnich  D.  High temporal summation of pain predicts immediate analgesic effect of acupuncture in chronic pain patients-a prospective cohort study.   Front Neurosci. 2019;13:498. doi:10.3389/fnins.2019.00498PubMedGoogle Scholar

36.

Yarnitsky  D.  Conditioned pain modulation (the diffuse noxious inhibitory control-like effect): its relevance for acute and chronic pain states.   Curr Opin Anaesthesiol. 2010;23(5):611-615. doi:10.1097/ACO.0b013e32833c348bPubMedGoogle Scholar

37.

Yarnitsky  D, Granot  M, Granovsky  Y.  Pain modulation profile and pain therapy: between pro- and antinociception.   Pain. 2014;155(4):663-665. doi:10.1016/j.pain.2013.11.005PubMedGoogle Scholar

38.

Younger  J, Gandhi  V, Hubbard  E, Mackey  S.  Development of the Stanford Expectations of Treatment Scale (SETS): a tool for measuring patient outcome expectancy in clinical trials.   Clin Trials. 2012;9(6):767-776. doi:10.1177/1740774512465064PubMedGoogle Scholar

39.

Linde  K, Witt  CM, Streng  A,  et al.  The impact of patient expectations on outcomes in four randomized controlled trials of acupuncture in patients with chronic pain.   Pain. 2007;128(3):264-271. doi:10.1016/j.pain.2006.12.006PubMedGoogle Scholar

40.

Anderson  KO, Dowds  BN, Pelletz  RE, Edwards  WT, Peeters-Asdourian  C.  Development and initial validation of a scale to measure self-efficacy beliefs in patients with chronic pain.   Pain. 1995;63(1):77-84. doi:10.1016/0304-3959(95)00021-JPubMedGoogle Scholar

41.

Lawson  K, Reesor  KA, Keefe  FJ, Turner  JA.  Dimensions of pain-related cognitive coping: cross-validation of the factor structure of the Coping Strategy Questionnaire.   Pain. 1990;43(2):195-204. doi:10.1016/0304-3959(90)91073-RPubMedGoogle Scholar

42.

Sullivan  MJ, Bishop  SR, Pivik  J.  The pain catastrophizing scale: development and validation.   Psychol Assess. 1995;7(4):524. doi:10.1037/1040-3590.7.4.524Google Scholar

43.

Harte  SE, Clauw  DJ, Napadow  V, Harris  RE.  Pressure pain sensitivity and insular combined glutamate and glutamine (Glx) are associated with subsequent clinical response to sham but not traditional acupuncture in patients who have chronic pain.   Med Acupunct. 2013;25(2):154-160. doi:10.1089/acu.2013.0965PubMedGoogle Scholar

44.

Eisenberg  E, Midbari  A, Haddad  M, Pud  D.  Predicting the analgesic effect to oxycodone by ‘static’ and ‘dynamic’ quantitative sensory testing in healthy subjects.   Pain. 2010;151(1):104-109. doi:10.1016/j.pain.2010.06.025PubMedGoogle Scholar

45.

Bang  H, Flaherty  S, Kolahi  J, Park  J.  Blinding assessment in clinical trials: a review of statistical methods and a proposal of blinding assessment protocol.   Clin Res Regul Aff. 2010;27:42-51. doi:10.3109/10601331003777444Google Scholar

46.

Bang  H, Ni  L, Davis  CE.  Assessment of blinding in clinical trials.   Control Clin Trials. 2004;25(2):143-156. doi:10.1016/j.cct.2003.10.016PubMedGoogle Scholar

47.

Little  RJ, Rubin  DB.  Statistical Analysis With Missing Data. Third edition. John Wiley & Sons; 2019.

48.

White  IR, Carpenter  J, Horton  NJ.  Including all individuals is not enough: lessons for intention-to-treat analysis.   Clin Trials. 2012;9(4):396-407. doi:10.1177/1740774512450098PubMedGoogle Scholar

49.

Tukey  J.  Exploratory Data Analysis. Pearson; 1977.

50.

Goldsmith  ES, Taylor  BC, Greer  N,  et al.  Focused evidence review: psychometric properties of patient-reported outcome measures for chronic musculoskeletal pain.   J Gen Intern Med. 2018;33(suppl 1):61-70. doi:10.1007/s11606-018-4327-8PubMedGoogle Scholar

51.

Kovacs  FM, Abraira  V, Royuela  A,  et al.  Minimal clinically important change for pain intensity and disability in patients with nonspecific low back pain.   Spine (Phila Pa 1976). 2007;32(25):2915-2920. doi:10.1097/BRS.0b013e31815b75aePubMedGoogle Scholar

52.

Lee  MK, Yost  KJ, McDonald  JS, Dougherty  RW, Vine  RL, Kallmes  DF.  Item response theory analysis to evaluate reliability and minimal clinically important change of the Roland-Morris Disability Questionnaire in patients with severe disability due to back pain from vertebral compression fractures.   Spine J. 2017;17(6):821-829. doi:10.1016/j.spinee.2017.01.002PubMedGoogle Scholar

53.

Cherkin  DC, Eisenberg  D, Sherman  KJ,  et al.  Randomized trial comparing traditional Chinese medical acupuncture, therapeutic massage, and self-care education for chronic low back pain.   Arch Intern Med. 2001;161(8):1081-1088. doi:10.1001/archinte.161.8.1081
ArticlePubMedGoogle Scholar

54.

Kennedy  S, Baxter  GD, Kerr  DP, Bradbury  I, Park  J, McDonough  SM.  Acupuncture for acute non-specific low back pain: a pilot randomised non-penetrating sham controlled trial.   Complement Ther Med. 2008;16(3):139-146. doi:10.1016/j.ctim.2007.03.001PubMedGoogle Scholar

55.

MacPherson  H, Maschino  AC, Lewith  G, Foster  NE, Witt  CM, Vickers  AJ; Acupuncture Trialists’ Collaboration.  Characteristics of acupuncture treatment associated with outcome: an individual patient meta-analysis of 17,922 patients with chronic pain in randomised controlled trials.   PLoS One. 2013;8(10):e77438. doi:10.1371/journal.pone.0077438PubMedGoogle Scholar

56.

Harris  RE, Tian  X, Williams  DA,  et al.  Treatment of fibromyalgia with formula acupuncture: investigation of needle placement, needle stimulation, and treatment frequency.   J Altern Complement Med. 2005;11(4):663-671. doi:10.1089/acm.2005.11.663PubMedGoogle Scholar

57.

Chen  CX, Kroenke  K, Stump  TE,  et al.  Estimating minimally important differences for the PROMIS pain interference scales: results from 3 randomized clinical trials.   Pain. 2018;159(4):775-782. doi:10.1097/j.pain.0000000000001121PubMedGoogle Scholar

58.

Lee  AC, Driban  JB, Price  LL, Harvey  WF, Rodday  AM, Wang  C.  Responsiveness and minimally important differences for 4 patient-reported outcomes measurement information system short forms: physical function, pain interference, depression, and anxiety in knee osteoarthritis.   J Pain. 2017;18(9):1096-1110. doi:10.1016/j.jpain.2017.05.001PubMedGoogle Scholar

59.

Baliki  MN, Chialvo  DR, Geha  PY,  et al.  Chronic pain and the emotional brain: specific brain activity associated with spontaneous fluctuations of intensity of chronic back pain.   J Neurosci. 2006;26(47):12165-12173. doi:10.1523/JNEUROSCI.3576-06.2006PubMedGoogle Scholar

60.

Vachon-Presseau  E, Centeno  MV, Ren  W,  et al.  The emotional brain as a predictor and amplifier of chronic pain.   J Dent Res. 2016;95(6):605-612. doi:10.1177/0022034516638027PubMedGoogle Scholar

61.

Beissner  F, Preibisch  C, Schweizer-Arau  A, Popovici  RM, Meissner  K.  Psychotherapy with somatosensory stimulation for endometriosis-associated pain: the role of the anterior hippocampus.   Biol Psychiatry. 2018;84(10):734-742. doi:10.1016/j.biopsych.2017.01.006PubMedGoogle Scholar

62.

Karst  M, Li  C.  Acupuncture: a question of culture.   JAMA Netw Open. 2019;2(12):e1916929-e1916929. doi:10.1001/jamanetworkopen.2019.16929
ArticlePubMedGoogle Scholar