Description of the condition
The International Association for the Study of Pain (IASP) classifies neuropathic pain according to three features: the underlying disease, the site of the lesion (i.e. a peripheral nerve lesion or spinal cord) and the underlying mechanism (IASP 2006). It is defined as "Pain arising as a direct consequence of a lesion or disease affecting the somatosensory system" (IASP 2006). Unlike nociceptive pain, such as gout and other forms of arthritis, neuropathic pain is caused by nerve damage, often accompanied by anatomical and physiological changes in the central nervous system (CNS) or peripheral nervous system (PNS). The pain can be described as burning, tingling, shooting, stabbing or shocking. Injury to the brain, brain tumours, diabetic neuropathy and herpes zoster are all examples of conditions that may cause this type of pain.
Neuropathic pain can be very difficult to treat, with only 40% to 60% of patients achieving partial relief (Dworkin 2007), fewer than those experiencing nociceptive pain. Determining the best treatment for individual patients remains challenging, with favoured treatments including certain antidepressants (e.g. tricyclics and selective serotonin-norepinephrine reuptake inhibitors (SNRIs)), anticonvulsants (especially pregabalin (Lyrica) and gabapentin (Neurontin)) and topical lidocaine.
A US study carried out in 1998 reported that approximately four million people suffered from neuropathic pain (Dickson 2010). The highest prevalence rates were observed for peripheral diabetic neuropathy and postherpetic neuralgia, with an estimated prevalence of 600,000 and 500,000 respectively, based on a population of 270 million (Bennett 1998). In Europe, neuropathic pain is estimated to affect between 3% and 8% of individuals, with 5% of these people reporting moderate to severe pain leading to significant reductions in quality of life (Bouhassira 2008; Gustorff 2008; Torrance 2006). In the UK, the prevalence of neuropathic pain is as high as 8% (Torrance 2006) with estimates for specific conditions indicating incidences per 100,000 person-years observation of 34 to 40 for postherpetic neuralgia, 27 to 400 for trigeminal neuralgia, one for phantom limb pain, 15 to 400 for painful diabetic neuropathy and 2000 for fibromyalgia. Rates for phantom limb pain and postherpetic neuralgia appear to have decreased in recent years, but increased for painful diabetic neuropathy (Hall 2006; McQuay 2007).
Fibromyalgia is characterised by long-lasting, widespread pain combined with general symptoms such as sleep disturbance, fatigue, irritable bowel syndrome, headache and mood disorders. Its cause is not well understood, but it has features in common with neuropathic pain, including changes in the CNS. Anatomical and physiological changes in the CNS include age-dependent total grey matter volume decrease, reduced presynaptic dopamine activity, disruption of dopaminergic neurotransmission resulting in increased pain and discomfort, hippocampus dysfunction, and metabolite and cerebral metabolite ratio abnormalities, all of which demonstrate CNS dysfunction (Emad 2008; Kuchinad 2007; Petrou 2008; Wood 2007a; Wood 2007b; Wood 2009). Both neuropathic and fibromyalgia chronic pain patients display features of the central hypersensitivity responsible for enhanced neuronal excitability and increased pain (Curatolo 2006).
The initial classification criteria for fibromyalgia were published in 1990 (Wolfe 1990) and emphasised a tender point examination, however the American College of Rheumatology (ACR) published new fibromyalgia diagnostic criteria in 2010 (Wolfe 2010). These were suitable for the primary care setting and incorporated both peripheral pain (via a widespread pain index) and somatic symptoms (symptom checklist). More recently, the ACR criteria have been further simplified to a survey format for use in epidemiological studies (Garg 2012).
The impetus to classify fibromyalgia as a neuropathic pain comes from multiple lines of research suggesting that widespread pain and tenderness are associated with chronic sensitisation of the CNS. Therefore, for the purpose of this review, whilst both neuropathic pain and fibromyalgia have features in common and may respond to similar interventions, the definition of 'neuropathic pain' will be restricted to those disorders with a primary aetiology clearly related to the peripheral or CNS.
Pharmacological interventions include unconventional analgesics such as antidepressants and anticonvulsants, in addition to conventional medications such as strong opioids. Most of these agents have significant side effects and as one of the first-line treatment options there are concerns about the associated costs to the health service (NICE 2010). There is evidence from population-based surveys that people with chronic neurological pain and fibromyalgia are likely to try complementary and alternative (CAM) therapies such as herbal treatments (Kanodia 2010; Metcalfe 2010; Thomas 2004). For this reason it is important for policy makers to become aware of the impact these products may have.
Description of the intervention
Oral herbal remedies include standardised extracts (encapsulated or tablet form), tinctures (e.g. alcohol, glycerine), dried herbs (encapsulated or tablet form), raw whole herb infusions (e.g. tea) and decoctions (e.g. boiled down tea). Topical herbal applications include ointments, essential oils, creams (petroleum or glycerine based), powders, plasters and poultices. Constituents of a single plant or of herbal mixtures are claimed to work synergistically to produce a greater effect than the sum of the effects of a single constituent. It is also claimed that the combined actions of the various constituents reduce the toxicity of the extract compared with single, isolated constituents (Ernst 2001). Both these synergistic and buffering effects extend to the use of different plant extracts in combination preparations.
Three definitions of herbal medicines have been identified to inform this review. Ernst 2001 has previously defined herbal medicine as "The medical use of preparations that contain exclusively plant material'. Gagnier 2011 defined herbal treatments as all or part of a plant used for medicinal purposes, administered orally (ingestion) or applied topically. This definition does not include plant substances that are smoked (e.g. Cannabis sativa), individual chemicals that are derived from plants or synthetic chemicals that are based on constituents of plants. However, we will consider Cannabis sativa, or other plants that can be smoked, to be herbal medicines for this review. The European Medicines Agency Directive (2004/24/EC) defines a herbal medicinal product as "Any medicinal product, exclusively containing as active ingredients, one or more herbal substances or one or more herbal preparations, or one or more such herbal substances in combination with one or more such herbal preparations". Herbal preparations are defined as preparations obtained by subjecting herbal substances to treatments such as extraction, distillation, expression, fractionation, purification, concentration or fermentation.
In the current review, we will include herbal preparations which contain whole plants, parts of plants, or comminuted or powdered herbal substances, tinctures, extracts, essential oils, expressed juices, processed exudates, infusions or decoctions. To clarify, we will include preparations exclusively containing plant material that are ingested, applied topically or smoked, at any dose and which contain active ingredients of one or more herbal substance or preparation. We will define herbal preparations as outlined by the EMA Directive above.
Current guidelines on the treatment and management of neuropathic pain and fibromyalgia do not report on the use of herbal products for pain relief, possibly due to a lack of research studies. However, there is some preliminary evidence that capsaicin is beneficial for pain relief in patients with fibromyalgia (pilot study by McCarty 1994) and also in some neuropathic pain conditions, as demonstrated in two recent Cochrane reviews (Derry 2012; Derry 2013). Based on limited evidence, the authors of this review concluded that capsaicin, when applied repeatedly at a lower dose (six studies; 389 patients) and applied once at a higher dose (two studies; 709 patients), may provide a degree of pain relief. This was based on eight studies of adequate methodological quality and involved pooling of the neuropathic conditions (postherpetic neuralgia, diabetic neuropathy, HIV neuropathy, postmastectomy pain and postsurgical cancer pain). Whole essential oils have also been reported to have analgesic effects in neuropathic pain in a randomised, double-blind, placebo-controlled trial of 60 participants (Li 2010) and in fibromyalgia patients in a pilot study (Ko 2007). These preliminary results appear promising for the use of herbal products/preparations in the treatment of neuropathic pain and fibromyalgia, however more robust evidence is required before definitive guidance on their use can be recommended.
Why it is important to do this review
Neuropathic pain is a complex and often disabling condition; many people suffer moderate or severe pain for many years, leading to significant reductions in quality of life. Conventional analgesics are usually not effective in alleviating the symptoms, although opioids may be effective in some individuals. Treatment is therefore usually by unconventional analgesics such as antidepressants or antiepileptics. However, there has been negative publicity surrounding the side effects associated with current pharmacological treatments for specific types of neuropathic pain (BNF 2006; Glassman 1998; Peretti 2000) and evidence from population-based surveys has shown that people with chronic pain and fibromyalgia are likely to try herbal treatments. It is therefore important to determine the efficacy and safety of herbal medicines in the treatment of such conditions.
New standards have evolved for assessing efficacy in neuropathic pain and fibromyalgia. More strict criteria for the inclusion of trials and assessment of outcomes are now applied and researchers are more aware of problems that may affect overall assessment. For this reason, a review applying these new standards to an assessment of the efficacy of herbal medicinal products or preparations in neuropathic pain and fibromyalgia is necessary.
- To assess the analgesic efficacy and effectiveness of herbal medicinal products or preparations for neuropathic pain and fibromyalgia.
- To assess the adverse events associated with the use of herbal medicinal products or preparations for neuropathic pain and fibromyalgia.
Criteria for considering studies for this review
Types of studies
Randomised and quasi-randomised controlled trials (including cross-over designs) of double-blind design, which assess the efficacy and effectiveness of herbal medicinal products or preparations for neuropathic pain and fibromyalgia.
We will apply no restriction with regard to language.
Types of participants
We will include adult participants aged 18 years and above. Participants will be suffering from fibromyalgia, or one or more neuropathic pain conditions, or both, for 3 months or more. Neuropathic pain conditions include (but are not limited to) the following.
- Painful diabetic neuropathy (PDN)
- Post-herpetic neuralgia (PHN)
- Trigeminal neuralgia
- Phantom limb pain
- Postoperative or traumatic neuropathic pain
- Complex regional pain syndrome (CRPS)
- Cancer-related neuropathy
- HIV neuropathy
- Spinal cord injury
We will include studies of participants with more than one type of neuropathic pain. We will analyse results according to the primary condition.
We will apply no restrictions based on gender.
We will exclude studies of headache or migraine as these are acute conditions.
Types of interventions
For the purpose of this review, we will include studies that investigate the effects of herbal medicinal products or preparations administered in the form of whole plants, parts of plants or extracts for the relief of neuropathic pain and fibromyalgia, compared to placebo, no intervention or any other active comparator. These preparations may be administered topically, orally or by smoking. No restriction will be made on dose.
- No intervention
- Any other active comparator
We will also extract data from dose comparison studies.
We will also include studies monitoring other analgesic consumption, alongside herbal medicinal products.
- We will exclude studies monitoring the effects of isolated, single substances within the plant from this review.
- We will exclude studies monitoring the effects of traditional Chinese medicine from this review as this involves complex mixtures of plant products individualised for the patient.
Types of outcome measures
Studies must report pain assessment as either the primary or secondary outcome. The majority of studies are expected to use standard subjective scales for pain intensity or pain relief, or both.
Attention will be paid to the IMMPACT definitions of moderate and substantial benefit in chronic pain studies (Dworkin 2008).
- Patient-reported pain relief of 30% or greater, over baseline (moderate)
- Patient-reported pain relief of 50% or greater, over baseline (substantial)
- Patient-reported global impression of clinical change (PGIC) much or very much improved (moderate)
- Patient-reported global impression of clinical change (PGIC) very much improved (substantial)
- Any pain-related outcome indicating some improvement
- Withdrawals: for any reason, due to lack of efficacy, due to adverse event
- Adverse events: patient reporting of any adverse event, patient reporting of any serious adverse event, death
- Undefined improvement
We will collect outcome assessment data for all treatment durations and report the extracted data.
Search methods for identification of studies
To identify studies for inclusion in this review, we will develop detailed search strategies for each electronic database to be searched. These will be based on the search strategy developed for MEDLINE but revised appropriately for each database. The search strategy will combine the subject search with phase one and two of the Cochrane highly sensitive search strategy for randomised controlled trials (RCTs) (as published in Appendix 5c in the Cochrane Handbook for Systematic Review of Interventions) and will be developed with the assistance of the Trials Search Co-ordinator of the Cochrane Pain, Palliative & Supportive Care Review (PaPaS) Group. We will undertake the final search in December 2013. The subject search will use a combination of controlled vocabulary and free-text terms based on the search strategy for searching MEDLINE (Appendix 1).
We will search the Cochrane Central Register of Controlled Trials (CENTRAL) in The Cochrane Library (current issue), in addition to the Cochrane Database of Systematic Reviews (CDSR) in The Cochrane Library (current issue), MEDLINE (mid 1950s to present), EMBASE (1980 to present), CINAHL (1982 to present) and AMED (1985 to present).
Searching other resources
We will screen any systematic reviews on the effectiveness or efficacy (or both) of herbal medicinal products or preparations for neuropathic pain and fibromyalgia for additional references. We will identify additional studies from the reference lists of the retrieved papers.
We will search the metaRegister of controlled trials (mRCT) (www.controlled-trials.com/mrct), Clinicaltrials.gov (www.clinicaltrials.gov) and the WHO International Clinical Trials Registry platform (ICTRP) (http://apps.who.int/trialsearch/) for ongoing trials.
We will contact experts in the field (identified by personal contacts, lead authors in published studies, world wide web searching) for relevant data in terms of published, unpublished or ongoing studies, to identify other relevant articles which may have been missed by the electronic search.
The search will attempt to identify all relevant studies irrespective of language. We will assess non-English papers and, if necessary, translate them with the assistance of a native speaker.
We will supplement the electronic search strategy by using the Science Citation Index to perform citation tracking of the RCTs identified in the first step.
We will attempt to identify medicinal herbal products or preparations being used without sufficient evidence of effectiveness (unpublished data) by contacting experts in the field of complementary and alternative medicine.
Data collection and analysis
Selection of studies
Two review authors (AB, CB) will independently select trials for inclusion. We will screen the titles and abstracts of publications obtained by the search strategy. If no abstract is available we will obtain and assess the full paper. We will retrieve all trials classified as relevant by either of the authors for further assessment. Based on the information within the full reports, we will use a standardised form to select the trials eligible for inclusion in the review. Where necessary, we will contact primary authors for clarification of study characteristics. Disagreement between authors will be resolved by consensus, or third party adjudication (SMcD).
Data extraction and management
Two review authors (AB, DH) will extract data independently using a customised form, tested prior to use. This will be used to extract relevant data on methodological issues, eligibility criteria, interventions (including the pain condition, number of participants treated, herbal medicinal product/preparation, dosing regimen, study design, study duration and follow-up, comparisons, outcome measures and results, withdrawals and adverse events). Any disagreement will again be resolved by consensus, or third party adjudication (SMcD). We will contact all primary study authors to clarify any omitted data or study characteristics. To perform intention-to-treat analysis, we will extract data according to the original allocation groups, and note losses to follow-up where possible.
Where data seem to be missing from a study we will, if possible, obtain these data through correspondence with the study authors.
There will be no blinding to study author, institution or journal at this stage.
Assessment of risk of bias in included studies
Two authors (AB and CB) will independently assess risk of bias for each study, using the 'Risk of bias' tool available in the Review Manager 5 (RevMan) software (RevMan 2012) criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011) and adapted from those used by the Cochrane Pregnancy and Childbirth Group. Any disagreements will be resolved by discussion with SMcD acting as third party adjudicator. We will assess the following for each study:
Random sequence generation (checking for possible selection bias). We will assess the method used to generate the allocation sequence as: low risk of bias (any truly random process, e.g. random number table; computer random number generator); unclear risk of bias (method used to generate sequence not clearly stated) or high risk of bias (studies using a non-random process such as odd or even date of birth).
Allocation concealment (checking for possible selection bias). The method used to conceal allocation to interventions prior to assignment determines whether intervention allocation could have been foreseen in advance of, or during recruitment, or changed after assignment. We will assess the methods as: low risk of bias (e.g. telephone or central randomisation; consecutively numbered sealed opaque envelopes); unclear risk of bias (method not clearly stated) or high risk of bias (studies that do not conceal allocation).
Blinding of outcome assessment (checking for possible detection bias). We will assess the methods used to blind study participants and outcome assessors from knowledge of which intervention a participant received. We will assess the methods as: low risk of bias (study states that it was blinded and describes the method used to achieve blinding, e.g. identical tablets; matched in appearance and smell); unclear risk of bias (study states that it was blinded but does not provide an adequate description of how it was achieved) or high risk of bias (studies that were not double-blind).
Incomplete outcome data (checking for possible attrition bias due to the amount, nature and handling of incomplete outcome data). We will assess the methods used to deal with incomplete data as: low risk (< 10% of participants did not complete the study and/or used ‘baseline observation carried forward’ analysis); unclear risk of bias (used 'last observation carried forward' analysis); high risk of bias (used 'completer' analysis).Size of study (checking for possible biases confounded by small size). We will assess studies as being at low risk of bias (≥ 200 participants per treatment arm); unclear risk of bias (50 to 199 participants per treatment arm); high risk of bias (< 50 participants per treatment arm).
We will regard differences in treatment intervention detail (e.g. type of herbal product/preparation, dosage of herbal product/preparation or different pain condition) as a potential source of bias and address this in the subgroup analysis, as there is evidence of different effects in different neuropathic pain conditions for some interventions (Moore 2009).
Measures of treatment effect
For each study, we will calculate risk ratio (RR) and 95% confidence intervals (CI) for dichotomous outcomes, and mean differences and 95% CI for continuous outcomes. Where continuous outcomes are pooled on different scales, we will use standardised mean differences. Where available, we will use changes from baseline (mean change scores) in preference to follow-up scores.
Unit of analysis issues
We will collect outcome assessment data for all treatment durations and report extracted data as close to eight weeks as possible but not less than four weeks. Where longer-duration outcomes are available we will also extract these data. Where multiple observations of the same outcome occur, we will extract data at clinically relevant time points. When available this will reflect short-term (immediately after the intervention), medium-term (closest to 12 weeks) and long-term (24 weeks or more) outcomes.
We will split the control treatment arm between active treatment arms in a single study if the active treatment arms were not combined for analysis, in order to determine individual treatment effects.
Dealing with missing data
We will use intention-to-treat (ITT) analysis wherever possible. The ITT population will consist of participants who were randomised, took the assigned herbal product/preparation and provided at least one post baseline assessment. If necessary, we will contact the original investigators and make requests for any missing data. Depending on the nature of the data, we will make assumptions on whether the data are missing at random or not missing at random. We will not impute replacement values where data are deemed not missing at random. Where data are deemed to be missing at random, this will be assigned zero improvement (baseline observation carried forward, BOCF) where possible (European Medicines Agency 2011). We are aware that imputation methods might be problematic and we will examine trial reports for information about this. We will consider missing data during sensitivity analyses.
If standard deviations are missing from continuous data, we will scan data for any other statistics such as confidence intervals, standard errors and P values, which allow for their calculation. If there are a large number of missing standard deviations then we will not carry out imputation.
Assessment of heterogeneity
Initially, we will qualitatively assess clinical diversity across studies. We will assess clinical heterogeneity in the included RCTs by considering whether the studies are similar for intervention (dosage and duration), type of participant, outcomes assessed and follow-up time. We will combine studies examining similar conditions. If two or more studies are deemed to be clinically homogenous according to the above terms, then we will assess the data for statistical heterogeneity using RevMan 5. We will use the I² statistic to assess this and will consider values of I² that are greater than 50% to represent substantial heterogeneity (Higgins 2003), in which case we will seek the reasons for this.
Assessment of reporting biases
We will not formally assess publication bias as the methods are unreliable. We will attempt to identify medicinal herbal products or preparations being used without sufficient evidence of effectiveness (unpublished data) by contacting experts in the field of complementary and alternative medicine. Should it become apparent that a large enough body of hidden data (patients or trials) does exist, we will carry out a calculation based on the PaPaS AUREF guide (AUREF 2012), to determine whether publication is a threat.
In order to assess the effectiveness of the intervention we will attempt to extract the dichotomous data from the included studies. We will use these data to calculate risk ratio (RR) or benefit with 95% confidence intervals (CIs) together with numbers needed to treat to benefit (NNTs) (Cook 1995), using a fixed-effect model, provided there is no evidence of heterogeneity of effect. However, if there is evidence of statistical heterogeneity, we will use a random-effects model. We will also consider the causes of this heterogeneity with regard to clinical characteristics and the magnitude and direction of effects. We will calculate the number needed to treat to benefit (NNT) for pain and the number needed to treat to harm (NNH), where appropriate, if data are available. For unwanted effects, the NNT becomes the NNH and we will calculate this in the same way. We will calculate the NNH for both minor and major adverse events. Major adverse events are those that lead to withdrawal from the study. We will report the number and type of adverse events.
Continuous data will probably not be used because it is inappropriate when there is an underlying skewed distribution. If continuous data are used, we will use RevMan 5 to report on summary continuous data where available and appropriate. We will undertake a meta-analysis using a fixed-effect model again in the event of no evident heterogeneity of effect.
In the event of too much heterogeneity among the studies to make quantitative meta-analysis possible, we will subject the selected studies to a qualitative descriptive analysis according to the type of intervention and participants. We will carry out a 'best evidence' synthesis in this situation by attributing levels of evidence based on the assessment of methodological quality. This may occur due to the wide range of clinical conditions and interventions included in this review.
Subgroup analysis and investigation of heterogeneity
Subgroup analysis is planned for:
- type of herbal product/preparation;
- dose of herbal product/preparation;
- concurrent analgesia;
- different painful conditions.
It is expected that no sensitivity analysis will be carried out due to a small evidence base and difficulty in determining the potency of the herbal products or preparations. We will not pool results for different neuropathic pain conditions, in addition to fibromyalgia. However, should it become apparent that sensitivity analysis is necessary to check whether including or excluding high risk of bias studies affects the effectiveness between comparison groups, we will do this according to predefined criteria.
The authors would like to acknowledge the Health and Social Care Research and Development Division of the Public Health Agency (Northern Ireland) for their funding of a Cochrane Fellowship.
Appendix 1. MEDLINE search strategy
1. Herbal Medicine/
2. Medicine, Traditional/
3. Plant Extracts/
4. exp Plant Preparations/
5. Complementary Therapies/
7. (herb or herbs or herbal).ab,kw,ti.
8. (herbal adj5 medicine$).ab,kw,ti.
9. (traditional adj5 medicine$).ab,kw,ti.
10. (plant$ adj5 extract$).ab,kw,ti.
11. (plant$ adj5 preparation$).ab,kw,ti.
12. (herb$ adj5 tea$).ab,kw,ti.
13. (plant$ adj5 oil$).ab,kw,ti.
14. (complementary adj5 therap$).ab,kw,ti.
15. (alternative adj5 therap$).ab,kw,ti.
16. (phytotherap$ or homeopath$).ab,kw,ti.
17. (herbal adj5 drug$).ab,kw,ti.
18. (medicinal adj5 herb$).ab,kw,ti.
19. 1 or 2 or 3 or 4 or 5 or 6 or 7 or 8 or 9 or 10 or 11 or 12 or 13 or 14 or 15 or 16 or 17 or 18
20. exp PAIN/
21. exp PERIPHERAL NERVOUS SYSTEM DISEASES/
22. exp SOMATOSENSORY DISORDERS/
23. FIBROMYALGIA/ or exp MYOFASCIAL PAIN SYNDROMES/ or POLYMYALGIA RHEUMATICA/
24. ((pain* or discomfort*) adj10 (central or complex or rheumat* or muscl* or muscul* or myofasci* or nerv* or neuralg* or neuropath*)).mp.
25. (fibromyalgi* or fibrosti* or FM or FMS).mp.
26. ((neur* or nerv*) adj6 (compress* or damag*)).mp.
27. 20 or 21 or 22 or 23 or 24 or 25 or 26
28. randomized controlled trial.pt.
29. controlled clinical trial.pt.
32. drug therapy.fs.
36. 28 or 29 or 30 or 31 or 32 or 33 or 34 or 35
37. exp animals/ not humans.sh.
38. 36 not 37
Contributions of authors
AB, SMcD and CB wrote the protocol. AB and CB will carry out searches and assess studies for inclusion. AB and DH will extract data. SMcD will
act as arbitrator. All authors reviewed the protocol and will be involved in writing the review. AB will draft final write-up. AB will be responsible for updating the review. PB and JMcV will act as content experts.
Declarations of interest
There are no conflicts of interest with this review for Dr Adele Boyd, Dr Chris Bleakley, Dr Chris Gill, Dr Mary Hannon-Fletcher, Dr Deirdre Hurley-Osing or Professor Suzanne McDonough.
Sources of support
- New source of support, Not specified.
- Health and Social Care Research and Development Division of the Public Health Agency (Northern Ireland) - Cochrane Fellowship, UK.