Skip to main content

Efficacy, acceptability, and safety of antidepressants for low back pain: a systematic review and meta-analysis

Abstract

Background

Antidepressant medicines are used to manage symptoms of low back pain. The efficacy, acceptability, and safety of antidepressant medicines for low back pain (LBP) are not clear. We aimed to evaluate the efficacy, acceptability, and safety of antidepressant medicines for LBP.

Methods

We searched CENTRAL, MEDLINE, Embase, CINAHL, ClinicalTrials.gov, the EU Clinical Trials Register, and the WHO International Clinical Trial Registry Platform from inception to May 2020. We included published and trial registry reports of RCTs that allocated adult participants with LBP to receive an antidepressant medicine or a placebo medicine. Pairs of authors independently extracted data in duplicate. We extracted participant characteristics, study sample size, outcome values, and measures of variance for each outcome. We data using random-effects meta-analysis models and calculated estimates of effects and heterogeneity for each outcome. We formed judgments of confidence in the evidence in accordance with GRADE. We report our findings in accordance with the PRISMA statement. We prespecified all outcomes in a prospectively registered protocol. The primary outcomes were pain intensity and acceptability. We measured pain intensity at end-of-treatment on a 0–100 point scale and considered 10 points the minimal clinically important difference. We defined acceptability as the odds of stopping treatment for any reason.

Results

We included 23 RCTs in this review. Data were available for pain in 17 trials and acceptability in 14 trials. Treatment with antidepressants decreased pain intensity by 4.33  points (95% CI − 6.15 to − 2.50) on a 0–100 scale, compared to placebo. Treatment with antidepressants increased the odds of stopping treatment for any reason (OR 1.27 [95% CI 1.03 to 1.56]), compared to placebo.

Conclusions

Treatment of LBP with antidepressants is associated with small reductions in pain intensity and increased odds of stopping treatment for any reason, compared to placebo. The effect on pain is not clinically important. The effect on acceptability warrants consideration. These findings provide Level I evidence to guide clinicians in their use of antidepressants to treat LBP.

Trial registration

We prospectively registered the protocol for this systematic review on PROSPERO (CRD42020149275).

Peer Review reports

Background

Low back pain (LBP) is the leading cause of disability worldwide [1]. The most common interventions for LBP are medicines that aim to reduce symptoms [2,3,4,5,6,7]. Clinical guidelines for LBP recommend that medicines should be prescribed for those who fail to respond to non-pharmacological interventions [8,9,10,11] and restricted to short-term use due to the potential for adverse effects and abuse [11]. Common medicines prescribed for LBP include non-steroidalanti-inflammatories (NSAIDs), opioids, muscle relaxants, and antidepressants [3, 12,13,14].

Antidepressants are a broad group of medicines classified according to their presumed action [15]. The mechanism of their analgesic effects is not well understood [16, 17]. Antidepressants are prescribed for LBP to provide pain relief, improve sleep, or reduce co-morbid depressive symptoms [18]. There is evidence that prescription rates of antidepressants to manage LBP are increasing [14, 19].

Evidence to support the efficacy and safety of antidepressants for LBP is unclear. Findings from systematic reviews are inconsistent [20,21,22,23]. The most recent review found inconclusive evidence for the effect of antidepressant medicines on pain intensity, disability or depression [23], and inadequate evidence to evaluate the acceptability and safety of antidepressants for LBP. The most recently published clinical guidelines for LBP provide conflicting advice on the use of antidepressants for LBP. The American College of Physicians guideline endorses duloxetine for chronic LBP [11] whereas the National Institute for Health and Care Excellence (UK) guideline advises against the use of any antidepressant for LBP [9].

The aim of this systematic review was to evaluate the efficacy, acceptability, and safety of antidepressant medicines compared to placebo for LBP, using data from published and trial registry reports.

Methods

We prospectively registered the protocol [24] for this systematic review on PROSPERO (CRD42020149275) and report our findings according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline [25] (Checklist S1 in Additional file 1).

Primary outcomes

The primary outcomes were pain intensity and acceptability. Pain intensity was measured at the follow-up assessment closest to the end of treatment. Acceptability, defined as overall acceptability of the medicine, was measured using all-cause discontinuation during treatment [15, 26].

Secondary outcomes

The secondary outcomes included low back-specific function, symptoms of depression, safety, harm, and tolerability. Low back-specific function and symptoms of depression were measured at the follow-up assessment closest to the end of treatment. Safety and harm, defined as the incidence of adverse effects and serious adverse effects [27], were measured by reports of adverse effects and serious adverse effects during treatment. Tolerability was defined as the tolerability of adverse effects sustained during treatment, measured by reports of discontinued treatment due to adverse effects.

Data sources

We used comprehensive search strategies to search electronic databases and clinical trial registries for records of randomized clinical trials of antidepressant medicines in LBP (Appendix S1 in Additional file 2) [28, 29]. We piloted the strategies using records of trials included in a previous systematic review [23]. We searched the Cochrane Back and Neck Group’s Trials Register and the Cochrane Central Register of Controlled Trials (CENTRAL) (Cochrane Library), MEDLINE, Embase (Ovid), and CINAHL (EBSCO) databases from inception to May 15, 2020. We searched ClinicalTrials.gov (ClinicalTrials.gov), the EU Clinical Trials Register (www.clinicaltrialsregister.eu), and the WHO International Clinical Trial Registry Platform (apps.who.int/trialsearch/Default.aspx) from inception to May 15, 2020. We included records written in English, Italian, Spanish, Portuguese, German, and French.

We included published and trial registry reports of randomized controlled trials (RCTs) that allocated adult participants with LBP to receive (i) a systemically administered dose of an antidepressant medicine or (ii) a sham (placebo) medicine, (iii) continuation of usual care, (iv) a waiting list, or (v) no-treatment. LBP was defined as pain of any duration between the 12th rib and buttock crease, with or without associated leg pain [30]. Trials that only included participants with symptoms of nerve root compromise (sciatica) [31] or LBP due to specific medical conditions (e.g., spinal fracture, inflammatory disease, aortic dissection, malignancy, or infection) were excluded. We included trials of mixed samples (e.g., non-specific LBP and LBP with sciatica, or non-specific LBP and large joint osteoarthritis) if separate data for the non-specific LBP sample were available. We included trials that tested the efficacy of selective serotonin reuptake inhibitors (SSRIs), serotonin and norepinephrine reuptake inhibitors (SNRIs), tricyclic antidepressants (TCAs), tetracyclic antidepressants (TeCA), heterocyclic antidepressants (HCAs), monoamine oxidase inhibitors (MAOIs), or atypical antidepressants, provided they were listed on the WHO ATC [32] and licensed in at least one of the following jurisdictions: USA (FDA) [33], Australia (TGA) [34], UK (MHRA) [35], or Europe (EMA) [36].

We screened records for inclusion in two stages. Pairs of authors from a team of six (MCF, MAW, AGC, MDJ, HBL, RRNR) independently screened record titles and abstracts in duplicate. The full texts of potentially eligible records were retrieved and independently screened again (MCF, MAW) to confirm inclusion. Disagreements were resolved through discussion or recourse to a third author (MKB or JHM).

We linked records to identify unique studies using a hierarchy. Records that were published and reported the results of a trial were classified as primary records, followed by other published records of a trial (e.g., secondary analyses), conference abstracts, and lastly, trial registry records. We classified the trial registry record as the primary record if there was no evidence of publication.

Data extraction and risk of bias assessment

Pairs of authors (MCF, MAW, AGC, HBL, RRNR, and MDJ) independently extracted data using standardized, piloted, data extraction forms and assessed study-level risk of bias using the Cochrane “Risk of bias” tool (version 5.1.0) [37] and published recommendations [38, 39]. Outcomes were rated as low overall risk when three or fewer domains are rated “unclear” risk, and no domains were rated “high”; moderate risk if a single domain was rated as “high” risk, but four or more were rated as “unclear” and high overall risk in all other instances. We resolved conflicts by consensus or, where necessary, through arbitration with a third author (MKB, JHM). We extracted, for each trial, the following: participant age, sex, duration of symptoms, and sample size; outcome value and measure of variance for pain intensity, function, and symptoms of depression; number of adverse and serious adverse effects; and the number of participants that discontinued treatment for any reason or due to adverse effects. We used an established hierarchy to preference data from continuous measures of pain, function, and symptoms of depression and converted all outcome data to a 0–100-point scale [24]. We used recommended methods [40, 41] to calculate standard deviations when these were not available.

Effect measures and interpretation

We used the difference in means and accompanying 95% confidence intervals for analyses of effects of antidepressant medicines on continuous outcomes (pain, function, symptoms of depression). We followed recommended guidance for trials with multiple arms by dividing the control group sample size by the number of arms in the study (Cochrane Handbook, Version 6) [42]. For cross-over trials where we were unable to obtain the first phase outcome data from the study authors, we included the overall effect (reflecting both phases) adjusted to correct for the correlation between the two phases [41]. The minimal clinically important difference in means is established as 10 points on a common 0–100-point scale for both pain and function [42]. We used the odds ratio and accompanying 95% confidence intervals for analyses of effects of antidepressant medicines on binary outcomes (acceptability, safety, harm, tolerability).

Data synthesis

Main analysis

We synthesized the data for each outcome using frequentist random-effectsmeta-analysis models. We fit the models using Restricted Maximum Likelihood (REML) in the R (version 3.6.2) package metafor (version 2.4-0) [43, 44]. We calculated the Q statistic to estimate heterogeneity, the estimate of between-study variance (τ2), and the proportion of this variance not due to sampling error (I2). We calculated the 95% prediction interval for the pooled effect and displayed this on the forest plot alongside the pooled effect estimate and 95% confidence interval.

Investigation of heterogeneity

We specified symptom duration, medicine type, and dose as covariates for investigation of important heterogeneity in the main analyses. Symptom duration had three levels: 0–6 weeks, 6–12 weeks, and > 12 weeks. Medicine type had seven levels: atypical, HCA, MAOI, SSRI, SNRI, TCA, TeCA. We included an additional level of medicine dose, compared to the protocol: standard dose range (SDR), less than SDR, and above SDR according to the Prescriber’s Digital Reference [45]. We conducted subgroup analyses, using the covariate levels as strata.

Sensitivity analyses

We tested the effect of the definition of non-specific LBP and of imputing missing measures of variance by repeating the main analyses with and without the relevant studies.

Influence of a hypothetical RCT

We constructed extended funnel plots using Stata (version 14.2) [46] to simulate the influence of hypothetical parameters of a future RCT on the pooled effect estimate for pain intensity [47, 48]. The extended funnel plot augments a funnel plot with overlays to provide an illustration of the impact of a new trial on a given meta-analysis [48]. We used 10 points on a 0–100 pain intensity scale as the threshold for the smallest worthwhile effect. We did not perform this analysis for acceptability as there is no known smallest worthwhile effect for this outcome.

Confidence in cumulative evidence

Two authors (MCF, MAW) used the Grading of Recommendations Assessment Development and Evaluation (GRADE) [49] framework to develop judgements of high, moderate, low, or very low confidence in the evidence for each outcome. We assessed the domains of study limitations, inconsistency, imprecision, and publication bias, using planned criteria [24]. Publication bias was evaluated using visual assessment of funnel plot symmetry, and Egger’s tests where 10 or more studies were available for an outcome [50].

Results

Search results

The search identified 2598 records. We removed 371 duplicates and screened the titles and abstracts of 2227 records for inclusion. We excluded 2104 records and retrieved the full-texts of 123 potentially eligible records (Fig. 1). We excluded 63 records and included 60 records that comprised 23 unique trials [51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69] (Table 1).

Fig. 1
figure 1

PRISMA flow diagram of the record selection process

Table 1 Characteristics of included studies

Eighteen trials used a parallel design, and five trials used crossover designs. Four trials were reported in trial registries. We identified a single ongoing trial, a single withdrawn trial, and a single terminated trial. Seventeen trials provided data for inclusion in the meta-analysis. These 17 trials randomized a total 2517 participants to one or more of 11 different antidepressant medicines or placebo. We did not identify any trials of antidepressant medicines compared to waiting list, usual care or no-treatment. The analyses presented below are for the effect of antidepressant medicines compared to placebo.

Risk of bias

We assessed completed trials (n = 20) for overall risk of bias (Table S1 in Additional file 2); 15 were assessed as high risk, four at moderate risk, and a single trial at low risk of bias. All twenty trials reported an appropriate method of blinding. Fourteen trials reported either high dropout rates or differences in dropouts between arms. Seven trials reported that they maintained complete control over the publication of results or had no funding-related conflicts of interests.

Assessment of publication bias

Visual inspection of funnel plots for each outcome suggested that the effects were evenly distributed around the mean (Figures S1-14 in Additional file 2). For all outcomes, visual inspection of contour-enhanced funnel plots provided no evidence of effects clustered around the threshold for statistical significance. Egger’s tests were conducted for outcomes with 10 studies; only a single study indicated statistically significant asymmetry. A single completed trial report from a trial registry (NCT01225068) was included in our analyses.

Confidence in evidence

The GRADE assessment of confidence in the evidence for each main analysis is presented in Appendix S2 in Additional file 2 and referred to below.

Main analysis

Primary outcome: pain

Sixteen of the 23 included trials reported data for pain. We downgraded confidence in the evidence by two levels due to trial limitations. There is low confidence that the pooled effect of antidepressant medicines compared to placebo is − 4.33 [95% CI − 6.15 to − 2.50; Tau2 = 2.20] on a 0–100 point scale (Fig. 2).

Fig. 2
figure 2

Effect of antidepressants compared to placebo on pain intensity (0–100 scale) for patients with LBP. Negative values for mean outcomes indicate change from baseline. Negative values for mean difference indicate effect favors drug compared to placebo. NA= group SD data not available; between-group summary statistics used in meta-analysis

Primary outcome: acceptability

Fourteen of the 23 included trials reported data for acceptability (all-cause discontinuation). We downgraded confidence in the evidence by two levels due to trial limitations. There is low confidence that the odds of all-cause discontinuation are higher for antidepressants than for placebo: odds ratio 1.27 [95% CI 1.03 to 1.56; Tau2 = 0] (Fig. 3).

Fig. 3
figure 3

All-cause discontinuation (acceptability) of antidepressants compared to placebo for patients with LBP. Odds ratio greater than 1 indicates greater odds of discontinuation in antidepressant group (i.e., effect favors placebo)

Secondary outcome: function

Six of the 23 included trials reported data for function. We downgraded confidence in the evidence by two levels due to trial limitations. There is low confidence that the pooled effect of antidepressants compared to placebo is − 3.22 [95% CI − 4.96 to − 1.48, Tau2 = 0] on a 0–100 point scale (Figure S15 in Additional file 2).

Secondary outcome: symptoms of depression

Four of the 23 included trials reported data for symptoms of depression. We downgraded confidence in the evidence by two levels for trial limitations and an additional level for imprecision. There is very low confidence that the pooled effect of antidepressants compared to placebo is − 1.72 [95% CI − 3.88 to 0.44; Tau2 = 0] (Figure S16 in Additional file 2) on a 0–100 point scale.

Secondary outcome: safety

Nine of the 23 included trials reported data for safety (adverse effects). We downgraded confidence in the evidence by two levels for trial limitations. There is low confidence that the odds of experiencing an adverse effect are higher for antidepressants than for placebo: odds ratio 1.58 [95% CI 1.28 to 1.93; Tau2 = 0] (Figure S17 in Additional file 2).

Secondary outcome: harm

Six of the 23 included trials reported data for harm (serious adverse effects). We downgraded confidence in the evidence by two levels for trial limitations and an additional level for imprecision. There is very low confidence that the odds of experiencing a serious adverse effect are higher for antidepressants than for placebo: odds ratio 1.29 [95% CI 0.56 to 2.94; Tau2 = 0] (Figure S18 in Additional file 2).

Secondary outcome: tolerability

Ten of the 23 included trials reported data for tolerability (discontinuation due to adverse effects). We downgraded confidence in the evidence by two levels for trial limitations. There is low confidence that the odds of discontinuing treatment due to an adverse effect are higher for antidepressants than for placebo: odds ratio 2.39 [95% CI 1.71 to 3.34; Tau2 = 0] (Figure S19 in Additional file 2).

Other analyses

Subgroup analyses

We conducted subgroup analyses for pain by antidepressant type and dose to provide additional clinical information (Fig. 4). There were no trials that evaluated the efficacy of HCA or MAOI antidepressants on LBP symptoms. The results for additional subgroup and sensitivity analyses are presented in Supplementary results with corresponding forest plots in Figures S20-23 in Additional file 2.

Fig. 4
figure 4

Effect of antidepressant class compared to placebo on pain intensity (0–100 scale) for patients with LBP. Negative values for mean outcomes indicate change from baseline. Negative values for mean difference indicate effect favors drug compared to placebo. NA = group SD data not available; between-group summary statistics used in meta-analysis

Influence of further research on results

The extended funnel plots (Figures S24, S25 in Additional file 2) suggest the upper bound of the confidence interval for the pooled effect would cross the threshold for clinical meaningfulness if the meta-analysis included an additional hypothetical trial with approximately 400 participants per arm and an effect for pain of approximately − 30 on a 0–100 scale (antidepressants more favorable than placebo).

Post hoc effects of duloxetine

Duloxetine is noted in the 2017 American College of Physicians guideline to have small effects on pain and function compared to placebo, for chronic LBP [11]. We repeated the main analyses on five trials that evaluated duloxetine compared to placebo. The effect of duloxetine on pain intensity post-treatment was − 5.87 [95% CI − 7.88 to − 3.86; Tau2 = 0] (Figure S26 in Additional file 2). The odds ratio for all-cause discontinuation of duloxetine compared to placebo was 1.17 [95% CI 0.90 to 1.52; Tau2 = 0] (Figure S27 in Additional file 2). The odds ratio for experiencing adverse effects of duloxetine compared to placebo was 1.50 [95% CI 1.21 to 1.85; Tau2 = 0] (Figure S28 in Additional file 2). The odds ratio for experiencing serious adverse effects of duloxetine compared to placebo was 1.35 [95% CI 0.56 to 3.27; Tau2 = 0] (Figure S29 in Additional file 2). The odds ratio for discontinuing treatment due to adverse effects of duloxetine compared to placebo was 2.53 [95% CI 1.70 to 3.77; Tau2 = 0] (Figure S30 in Additional file 2).

Post hoc sensitivity analyses

The REML estimator may underestimate between-study variance for binary outcomes when events are rare [70]. We repeated the analyses for acceptability, safety, harm, and tolerability using DerSimonian-Laird, Paule and Mandel and Mantel-Haenszel methods of estimation (Table S2 in Additional file 2). A single additional post hoc sensitivity analysis is reported in Supplementary Results and Figure S31 in Additional file 2.

Discussion

We conducted a systematic review to evaluate the effect of antidepressant medicines for patients with LBP. We included 23 trials in the systematic review and up to 17 in the meta-analyses. There is low confidence in evidence that, on average, patients with LBP treated with antidepressant medicines will experience a small improvement in pain and function and no improvement in symptoms of depression, compared to placebo. These effects are not clinically important [42, 71]. There is low confidence in evidence that patients are at increased odds of experiencing an adverse or serious adverse effect and at increased odds of stopping treatment due to an adverse effect or another reason, compared to placebo. Taken together, these data indicate treatment of LBP symptoms with antidepressants has no important benefit; is less acceptable, less safe and less tolerable; and may be harmful, compared to treatment with a placebo medicine.

A recent overview of clinical guidelines reported that 6 of 8 international guidelines recommend the use of antidepressants for chronic LBP where necessary [72]. The current American College of Physicians clinical guideline for the management of LBP [11] recommends the use of duloxetine for chronic LBP as second-line therapy where non-pharmacological therapy has been unsuccessful. This might be reconsidered in view of our findings. The analyses of duloxetine specifically showed a small effect on pain that is unlikely clinically important [73] and higher odds of adverse effects and dropout due to adverse effects compared to placebo.

Our work has a number of strengths. We adhered to a prospectively registered protocol and reported findings in line with recommendations [74]. Our searches are extensive and up to date and we included data from trial registry reports [29, 75, 76]. We also evaluated the acceptability, safety, harm, and tolerability of antidepressant medicines, in addition to effects on symptoms. This addresses limitations of the most recent review, which included 11 fewer trials and did not evaluate adverse effects [23]. The observed low heterogeneity across all outcomes, together with the improved precision of the estimates, substantiates our findings and interpretation. We determined that different methods of estimation did not influence these observations and note that similar homogeneity for binary outcomes has been reported in other large meta-analyses for antidepressant medicines [15]. We estimated parameters for a hypothetical future trial that would meaningfully impact the effect estimate for pain, to assist readers’ interpretation of the need for further trials.

We were unable to estimate effects for the long-term efficacy and acceptability of antidepressants because such data were reported in a single trial [61]. We were also unable to evaluate the effects of antidepressants in patients with acute LBP because we identified no usable data. The hypothetical future trial parameters estimated with the extended funnel plot do not consider risk of bias and are not estimable for binary outcomes.

Conclusion

This review demonstrates that treatment of LBP symptoms with antidepressants has no important benefit; is less acceptable, less safe, and less tolerable; and may be harmful, compared to treatment with a placebo medicine. This evidence is supported by homogenous, precise effect sizes across outcomes. These findings provide Level I evidence to guide clinicians in their use of antidepressants to treat LBP.

Availability of data and materials

The dataset used and analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

BDI:

Beck Depression Inventory

BDI-II:

Beck Depression Inventory II

BPI:

Brief Pain Inventory

DDS:

Descriptor Differential Scale

GRADE:

Grading of Recommendations Assessment Development and Evaluation

HCA:

Heterocyclic antidepressant

HDRS:

Hamilton Depression Rating Scale

LBP:

Low back pain

MADRS:

Montgomery Asberg Depression Rating Scale

MAOI:

Monoamine oxidase inhibitor

NRS:

Numerical rating scale

NSAID:

Non-steroidal anti-inflammatory

PRISMA:

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

RCT:

Randomized controlled trial

REML:

Restricted maximum likelihood

RMDQ:

Roland Morris Disability Questionnaire

SBPQ:

Short Back Pain Questionnaire

SNRI:

Serotonin and norepinephrine reuptake inhibitor

SSRI:

Selective serotonin reuptake inhibitor

TCA:

Tricyclic antidepressant

TeCA:

Tetracyclic antidepressant

VAS:

Visual analog scale

References

  1. James SL, Abate D, Abate KH, Abay SM, Abbafati C, Abbasi N, et al. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;392(10159):1789–858.

    Article  Google Scholar 

  2. Gore M, Tai KS, Sadosky A, Leslie D, Stacey BR. Use and costs of prescription medications and alternative treatments in patients with osteoarthritis and chronic low back pain in community-based settings. Pain Pract. 2012;12(7):550–60.

    Article  PubMed  Google Scholar 

  3. Hart OR, Uden RM, McMullan JE, Ritchie MS, Williams TD, Smith BH. A study of National Health Service management of chronic osteoarthritis and low back pain. Prim Health Care Res Dev. 2015;16(02):157–66.

    Article  PubMed  Google Scholar 

  4. Piccoliori G, Engl A, Gatterer D, Sessa E, in der Schmitten J, Abholz H-H. Management of low back pain in general practice – is it of acceptable quality: an observational study among 25 general practices in South Tyrol (Italy). BMC Fam Pract. 2013;14(1):148.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Ivanova JI, Birnbaum HG, Schiller M, Kantor E, Johnstone BM, Swindle RW. Real-world practice patterns, health-care utilization, and costs in patients with low back pain: the long road to guideline-concordant care. Spine J. 2011;11(7):622–32.

    Article  PubMed  Google Scholar 

  6. Williams CM, Maher CG, Hancock MJ, McAuley JH, McLachlan AJ, Britt H, et al. Low back pain and best practice care. Arch Intern Med. 2010;170(3):271.

    Article  PubMed  Google Scholar 

  7. Bishop P, Wing P. Compliance with clinical practice guidelines in family physicians managing worker’s compensation board patients with acute lower back pain. Spine J. 2003;3(6):442–50.

    Article  PubMed  Google Scholar 

  8. Almeida M, Saragiotto B, Richards B, Maher CG. Primary care management of non-specific low back pain: key messages from recent clinical guidelines. Med J Aust. 2018;208(6):272–5.

    Article  PubMed  Google Scholar 

  9. National Institute for Health and Care Excellence (NICE) 2016. Low back pain and sciatica in over 16 s: assessment and management (NG59). https://www.nice.org.uk/guidance/ng59. Accessed 20 February 2020.

    Google Scholar 

  10. Wambeke P, Desomer A, Ailliet L, Berquin A, Demoulin C, Depreitere B, et al. Low back pain and radicular pain: assessment and management. Belgian Health Care Knowledge Centre (KCE). 2017.

    Google Scholar 

  11. Qaseem A, Wilt TJ, McLean RM, Forciea MA. Noninvasive treatments for acute, subacute, and chronic low back pain: a clinical practice guideline from the American college of physicians. Ann Intern Med. 2017;166(7):514.

    Article  PubMed  Google Scholar 

  12. Shmagel A, Ngo L, Ensrud K, Foley R. Prescription medication use among community-based U.S. adults with chronic low back pain: a cross-sectional population based study. J Pain. 2018;19(10):1104–12.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Thackeray A, Hess R, Dorius J, Brodke D, Fritz J. Relationship of opioid prescriptions to physical therapy referral and participation for medicaid patients with new-onset low back pain. J Am Board Fam Med. 2017;30(6):784–94.

    Article  PubMed  Google Scholar 

  14. Mathieson S, Valenti L, Maher CG, Britt H, Li Q, McLachlan AJ, et al. Worsening trends in analgesics recommended for spinal pain in primary care. Eur Spine J. 2018;27(5):1136–45.

    Article  PubMed  Google Scholar 

  15. Cipriani A, Furukawa TA, Salanti G, Chaimani A, Atkinson LZ, Ogawa Y, et al. Comparative efficacy and acceptability of 21 antidepressant drugs for the acute treatment of adults with major depressive disorder: a systematic review and network meta-analysis. Lancet. 2018;391(10128):1357–66.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Harmer CJ, Duman RS, Cowen PJ. How do antidepressants work? New perspectives for refining future treatment approaches. The Lancet Psychiatry. 2017;4(5):409–18.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Cohen SP, Abdi S. New developments in the use of tricyclic antidepressants for the management of pain. Curr Opin Anaesthesiol. 2001;14(5):505–11.

    Article  CAS  PubMed  Google Scholar 

  18. Koes BW, Backes D, Bindels PJE. Pharmacotherapy for chronic non-specific low back pain: current and future options. Expert Opin Pharmacother. 2018;19(6):537–45.

    Article  CAS  PubMed  Google Scholar 

  19. Mafi JN, McCarthy EP, Davis RB, Landon BE. Worsening trends in the management and treatment of back pain. JAMA Intern Med. 2013;173(17):1573.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Salerno SM, Browning R, Jackson JL. The effect of antidepressant treatment on chronic back pain. Arch Intern Med. 2002;162(1):19.

    Article  CAS  PubMed  Google Scholar 

  21. Staiger TO, Gaster B, Sullivan MD, A Deyo R. Systematic review of antidepressants in the treatment of chronic low back pain. Spine. 2003;28(22):2540–5.

    Article  PubMed  Google Scholar 

  22. Schnitzer TJ, Ferraro A, Hunsche E, Kong SX. A comprehensive review of clinical trials on the efficacy and safety of drugs for the treatment of low back pain. J Pain Symptom Manage. 2004;28(1):72–95.

    Article  CAS  PubMed  Google Scholar 

  23. Urquhart DM, Hoving JL, Assendelft WJ, Roland M, van Tulder MW. Antidepressants for non-specific low back pain. Cochrane Database Syst Rev. 2008;44(8):085201.

    Google Scholar 

  24. Ferraro MC, Bagg MK, Folly de Campos T, McAuley JH. RADICAL: Systematic review of anti-depressant medicines if considered analgesics for low back pain. 2019. https://osf.io/6gurb/

    Google Scholar 

  25. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ. 2009;339:b2535.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Cipriani A, Furukawa TA, Salanti G, Geddes JR, Higgins JP, Churchill R, et al. Comparative efficacy and acceptability of 12 new-generation antidepressants: a multiple-treatments meta-analysis. Lancet. 2009;373(9665):746–58.

    Article  CAS  PubMed  Google Scholar 

  27. United States Food and Drugs Administration. Code of Federal Regulations Title 21. 2018. https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/cfrsearch.cfm?fr = 314.80. Accessed 31 July 2019

    Google Scholar 

  28. Bagg MK, McLachlan AJ, Maher CG, Kamper SJ, Williams CM, Henschke N, et al. Paracetamol, NSAIDS and opioid analgesics for chronic low back pain: a network meta-analysis. Cochrane Database Syst Rev. 2018(6):CD013045.

  29. Bagg MK, O’Hagan E, Zahara P, Wand BM, Hübscher M, Moseley GL, et al. Systematic reviews that include only published data may overestimate the effectiveness of analgesic medicines for low back pain: a systematic review and meta-analysis. J Clin Epidemiol. 2020;124:149-159.

  30. Dionne CE, Dunn KM, Croft PR, Nachemson AL, Buchbinder R, Walker BF, et al. A consensus approach toward the standardization of back pain definitions for use in prevalence studies. Spine. 2008;33(1):95–103.

    Article  PubMed  Google Scholar 

  31. Koes BW, van Tulder MW, Peul WC. Diagnosis and treatment of sciatica. BMJ. 2007;334(7607):1313–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. WHO Collaborating Centre for Drug Statistics Methodology. ATC/DDD Index. 2020. https://www.whocc.no/atc_ddd_index/. Accessed 31 July 2019

    Google Scholar 

  33. U.S. Food and Drug Administration. Drugs@FDA. 2020. https://www.fda.gov/drugs. Accessed 31 July 2019

    Google Scholar 

  34. Australian Government Department of Health Therapeutic Goods Administration. Australian Register of Therapeutic Goods. 2020. https://www.tga.gov.au/searching-australian-register-therapeutic-goods-artg. Accessed 31 July 2019

    Google Scholar 

  35. Medicines and Healthcare Products Regulatory Agency. MHRA Products. 2020 https://products.mhra.gov.uk. Accessed 31 July 2019

    Google Scholar 

  36. European Medicines Agency. Medicines. 2020. https://www.ema.europa.eu/en/medicines. Accessed 31 July 2019

    Google Scholar 

  37. Higgins J, Green S. Cochrane handbook for systematic reviews of interventions version 5.1.0 (updated March 2011). Cochrane Collaboration; 2011.

    Google Scholar 

  38. Furlan AD, Malmivaara A, Chou R, Maher CG, Deyo RA, Schoene M, et al. 2015 updated method guideline for systematic reviews in the cochrane back and neck group. Spine. 2015;40(21):1660–73.

    Article  PubMed  Google Scholar 

  39. Furukawa TA, Salanti G, Atkinson LZ, Leucht S, Ruhe HG, Turner EH, et al. Comparative efficacy and acceptability of first-generation and second-generation antidepressants in the acute treatment of major depression: protocol for a network meta-analysis. BMJ Open. 2016;6(7):e010919.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Wan X, Wang W, Liu J, Tong T. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC Med Res Methodol. 2014;14(1):135.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, et al., Cochrane Handbook for Systematic Reviews of Interventions Version 6.0. Wiley; 2019.

    Book  Google Scholar 

  42. Busse JW, Bartlett SJ, Dougados M, Johnston BC, Guyatt GH, Kirwan JR, et al. Optimal strategies for reporting pain in clinical trials and systematic reviews: recommendations from an OMERACT 12 workshop. J Rheumatol. 2015;42(10):1962–70.

    Article  CAS  PubMed  Google Scholar 

  43. R Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2019. https://www.r-project.org/

  44. Viechtbauer W. Conducting meta-analyses in R with the metafor package. J Stat Softw. 2010;36(3):1–48.

    Article  Google Scholar 

  45. PDR LLC. Prescriber’s digital reference. 2020. https://www.pdr.net. Accessed 24 February 2020

    Google Scholar 

  46. StataCorp LLC. Stata Statistical Software. College Station, TX; 2019.

    Google Scholar 

  47. Ferreira ML, Herbert RD, Crowther MJ, Verhagen A, Sutton AJ. When is a further clinical trial justified? BMJ. 2012;345:e5913.

    Article  PubMed  Google Scholar 

  48. Langan D, Higgins JPT, Gregory W, Sutton AJ. Graphical augmentations to the funnel plot assess the impact of additional evidence on a meta-analysis. J Clin Epidemiol. 2012;65(5):511–9.

    Article  PubMed  Google Scholar 

  49. Guyatt GH, Oxman AD, Vist GE, Kunz R, Falck-Ytter Y, Alonso-Coello P, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ. 2008;336(7650):924–6.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Sterne JAC, Sutton AJ, Ioannidis JPA, Terrin N, Jones DR, Lau J, et al. Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials. BMJ. 2011;343:d4002.

    Article  PubMed  Google Scholar 

  51. Alcoff J, Jones E, Rust P, Newman R. Controlled trial of imipramine for chronic low back pain. J Fam Pract. 1982;14(5):841–6.

    CAS  PubMed  Google Scholar 

  52. Atkinson JH, Slater MA, Capparelli EV, Wallace MS, Zisook S, Abramson I, et al. Efficacy of noradrenergic and serotonergic antidepressants in chronic back pain. J Clin Psychopharmacol. 2007;27(2):135–42.

    Article  CAS  PubMed  Google Scholar 

  53. Konno S, Oda N, Ochiai T, Alev L. Randomized, double-blind, placebo-controlled phase III trial of duloxetine monotherapy in Japanese patients with chronic low back pain. Spine. 2016;41(22):1709–17.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Pheasant H, Bursk A, Goldfarb J, Azen SP, Weiss JN, Borelli L. Amitriptyline and chronic low-back pain: a randomized double-blind crossover study. Spine. 1983;8(5):552–7.

    Article  CAS  PubMed  Google Scholar 

  55. Schliessbach J, Siegenthaler A, Bütikofer L, Limacher A, Juni P, Vuilleumier PH, et al. Effect of single-dose imipramine on chronic low-back and experimental pain. A randomized controlled trial. PLoS One. 2018;13(5):e0195776.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  56. Schukro RP, Oehmke MJ, Geroldinger A, Heinze G, Kress H-G, Pramhas S. Efficacy of duloxetine in chronic low back pain with a neuropathic component. Anesthesiology. 2016;124(1):150–8.

    Article  CAS  PubMed  Google Scholar 

  57. Skljarevski V, Desaiah D, Liu-Seifert H, Zhang Q, Chappell AS, Detke MJ, et al. Efficacy and safety of duloxetine in patients with chronic low back pain. Spine. 2010;35(13):E578–85.

    Article  PubMed  Google Scholar 

  58. Skljarevski V, Ossanna M, Liu-Seifert H, Zhang Q, Chappell A, Iyengar S, et al. A double-blind, randomized trial of duloxetine versus placebo in the management of chronic low back pain. Eur J Neurol. 2009;16(9):1041–8.

    Article  CAS  PubMed  Google Scholar 

  59. Skljarevski V, Zhang S, Desaiah D, Alaka KJ, Palacios S, Miazgowski T, et al. Duloxetine versus placebo in patients with chronic low back pain: a 12-week, fixed-dose, randomized, double-blind trial. J Pain. 2010;11(12):1282–90.

    Article  CAS  PubMed  Google Scholar 

  60. Treves R, Montane De La Roque P, Dumond JJ, Bertin P, Arnaud M, Desproges-Gotteron R. Prospective study of the analgesic action of clomipramine versus placebo in refractory low back pain and sciatica (68 cases). Rev Rhum Mal Osteoartic. 1991;58(7):549–52.

    CAS  PubMed  Google Scholar 

  61. Urquhart DM, Wluka AE, van Tulder M, Heritier S, Forbes A, Fong C, et al. Efficacy of low-dose amitriptyline for chronic low back pain. JAMA Intern Med. 2018;178(11):1474–81.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Atkinson JH, Slater MA, Wahlgren DR, Williams RA, Zisook S, Pruitt SD, et al. Effects of noradrenergic and serotonergic antidepressants on chronic low back pain intensity. Pain. 1999;83(2):137–45.

    Article  CAS  PubMed  Google Scholar 

  63. Atkinson JH, Slater MA, Williams RA, Zisook S, Patterson TL, Grant I, et al. A placebo-controlled randomized clinical trial of nortriptyline for chronic low back pain. Pain. 1998;76(3):287–96.

    Article  CAS  PubMed  Google Scholar 

  64. Dickens C, Jayson M, Sutton C, Creed F. The relationship between pain and depression in a trial using paroxetine in sufferers of chronic low back pain. Psychosomatics. 2000;41(6):490–9.

    Article  CAS  PubMed  Google Scholar 

  65. Goodkin K, Gullion CM, Agras WS. A randomized, double-blind, placebo-controlled trial of trazodone hydrochloride in chronic low back pain syndrome. J Clin Psychopharmacol. 1990;10(4):269–78.

    Article  CAS  PubMed  Google Scholar 

  66. Gould HM, Atkinson JH, Chircop-Rollick T, DʼAndrea J, Garfin S, Patel SM, et al. A randomized placebo-controlled trial of desipramine, cognitive behavioral therapy, and active placebo therapy for low back pain. Pain. 2020;161(6):1341–9.

    Article  CAS  PubMed  Google Scholar 

  67. Jenkins DG, Ebbutt AF, Evans CD. Tofranil in the treatment of low back pain. J Int Med Res. 1976;4(2):28–40.

    CAS  PubMed  Google Scholar 

  68. Johnson K, Chatterjee N, Noor N, Crowell A, McCue R, Mackey S. Effects of duloxetine and placebo in patients with chronic low back pain. J Pain. 2011;12(4):P49.

    Article  Google Scholar 

  69. Katz J, Pennella-Vaughan J, Hetzel RD, Kanazi GE, Dworkin RH. A randomized, placebo-controlled trial of bupropion sustained release in chronic low back pain. J Pain. 2005;6(10):656–61.

    Article  CAS  PubMed  Google Scholar 

  70. Veroniki AA, Jackson D, Viechtbauer W, Bender R, Bowden J, Knapp G, et al. Methods to estimate the between-study variance and its uncertainty in meta-analysis. Res Synth Methods. 2016;7(1):55–79.

    Article  PubMed  Google Scholar 

  71. Chou R, Deyo R, Friedly J, Skelly A, Weimer M, Fu R, 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.

    Article  PubMed  Google Scholar 

  72. Oliveira CB, Maher CG, Pinto RZ, Traeger AC, Lin C-WC, Chenot J-F, et al. Clinical practice guidelines for the management of non-specific low back pain in primary care: an updated overview. Eur Spine J. 2018;27(11):2791–803.

    Article  PubMed  Google Scholar 

  73. Dworkin RH, Turk DC, Wyrwich KW, Beaton D, Cleeland CS, Farrar JT, et al. Interpreting the clinical importance of treatment outcomes in chronic pain clinical trials: IMMPACT recommendations. J Pain. 2008;9(2):105–21.

    Article  PubMed  Google Scholar 

  74. Lee H, Lamb SE, Bagg MK, Toomey E, Cashin AG, Moseley GL. Reproducible and replicable pain research: a critical review. Pain. 2018;159(9):1683–9.

    Article  PubMed  Google Scholar 

  75. Baudard M, Yavchitz A, Ravaud P, Perrodeau E, Boutron I. Impact of searching clinical trial registries in systematic reviews of pharmaceutical treatments: methodological systematic review and reanalysis of meta-analyses. BMJ. 2017;356:j448.

    Article  PubMed  PubMed Central  Google Scholar 

  76. Hart B, Lundh A, Bero L. Effect of reporting bias on meta-analyses of drug trials: reanalysis of meta-analyses. BMJ. 2012;344:d7202.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

No acknowledgements.

Funding

No external funding was received for this study. MCF is supported by an Australian Medical Research Future Fund Grant GNTID1170205. MKB is supported by a NeuRA PhD Candidature Scholarship and Supplementary Scholarship and was additionally funded during this work by an Australian Government Research Training Program Scholarship and a UNSW Research Excellence Award. MAW is supported by a University Postgraduate Award and School of Medical Sciences Top-Up Scholarship from the University of New South Wales, and a Postgraduate Scholarship from the National Health and Medical Research Council of Australia. AGC is supported by the University of New South Wales Prince of Wales Clinical School Postgraduate Research Scholarship and a NeuRA PhD Candidature Supplementary Scholarship. HBL is supported by Australian Government post-graduate award. RRNR is supported by the University of New South Wales School of Medical Sciences Postgraduate Research Scholarship and a NeuRA PhD Candidature Supplementary Scholarship. The funders/sponsors 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.

Author information

Authors and Affiliations

Authors

Contributions

MCF had full access to all of the data in the study and takes full responsibility for the integrity of the data and the accuracy of the data analysis. JHM and MKB conceived the study idea and designed the study; MCF, MKB, and MAW created the search terms and conducted the database searches; MCF, MAW, AGC, HBL, RRNR, and MDJ extracted the data; MCF and MAW analyzed the data; MCF drafted and revised the manuscript; MKB, JHM, CKL, RD, and SMG made substantial contributions to the interpretation of results and critical revision of the manuscript. All authors approved the final version of the manuscript.

Corresponding author

Correspondence to Matthew K. Bagg.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1.

PRISMA 2009 Checklist.

Additional file 2.

 Supplementary Content.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ferraro, M.C., Bagg, M.K., Wewege, M.A. et al. Efficacy, acceptability, and safety of antidepressants for low back pain: a systematic review and meta-analysis. Syst Rev 10, 62 (2021). https://doi.org/10.1186/s13643-021-01599-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s13643-021-01599-4

Keywords