This protocol is based on a template for reviews of drugs used to relieve neuropathic pain and fibromyalgia. The aim is for all reviews to use the same methods, based on new criteria for what constitutes reliable evidence in chronic pain (Moore 2010a; Moore 2012b; Appendix 1). A Cochrane review of pregabalin in neuropathic pain and fibromyalgia demonstrated different response rates for different types of chronic pain (higher in diabetic neuropathy and postherpetic neuralgia and lower in central pain and fibromyalgia) (Moore 2009a). This indicates that different neuropathic pain conditions should be treated separately from one another, and that pooling should not be done unless there are good grounds for doing so. While fibromyalgia is considered to have a different aetiology from chronic neuropathic pain, it is a condition that responds to the same therapies. Because of limitations in the number of available clinical trials, it is convenient to consider fibromyalgia together with neuropathic pain. We make no presumption to pool data across individual neuropathic pain conditions or fibromyalgia, but will consider each condition separately.
Opioids for neuropathic pain is the subject of a previous Cochrane review (Eisenberg 2006). The current review is part of a move to evaluate individual opioid drugs in separate reviews according to dose and individual pain conditions.
Description of the condition
The 2011 International Association for the Study of Pain definition of neuropathic pain is "pain caused by a lesion or disease of the somatosensory system" (Jensen 2011) based on an earlier consensus meeting (Treede 2008). Neuropathic pain may be caused by nerve damage, but is often followed by changes in the central nervous system (CNS) (Moisset 2007). Neuropathic pain tends to be chronic and may be present for months or years. It is complex (Apkarian 2011; Tracey 2011), and neuropathic pain features can be found in patients with joint pain (Soni 2013).
Fibromyalgia is defined as widespread pain for longer than three months with pain on palpation at 11 or more of 18 specified tender points (Wolfe 1990), and is frequently associated with other symptoms such as poor sleep, fatigue, and depression. More recently, a definition of fibromyalgia has been proposed based on symptom severity and the presence of widespread pain (Wolfe 2010). The cause, or causes, are not well understood, but it has features in common with neuropathic pain, including changes in the CNS. Moreover, patients with neuropathic pain and those with fibromyalgia experience similar sensory phenomena (Koroschetz 2011). Many people with these conditions are significantly disabled with moderate or severe pain for many years.
In primary care in the United Kingdom (UK), the incidences per 100,000 person-years' observation have been reported as 28 (95% confidence interval (CI) 27 to 30) for postherpetic neuralgia, 27 (26 to 29) for trigeminal neuralgia, 0.8 (0.6 to 1.1) for phantom limb pain, and 21 (20 to 22) for painful diabetic neuropathy (Hall 2008). Estimates vary between studies, often because of small numbers of cases. The incidence of trigeminal neuralgia has been estimated at 4 in 100,000 per year (Katusic 1991; Rappaport 1994), while more recently, a study of facial pain in The Netherlands found incidences per 100,000 person-years of 12.6 for trigeminal neuralgia and 3.9 for postherpetic neuralgia (Koopman 2009). A systematic review of chronic pain demonstrated that some neuropathic pain conditions, such as painful diabetic neuropathy, can be more common, with prevalence rates up to 400 per 100,000 person-years (McQuay 2007). The prevalence of neuropathic pain was reported as being 3.3% in Austria (Gustorff 2008), 6.9% in France (Bouhassira 2008) and as high as 8% in the UK (Torrance 2006), and about 7% in a systematic review of studies published since 2000 (Moore 2013a). Some forms of neuropathic pain, such as diabetic neuropathy and post surgical chronic pain (which is often neuropathic in origin) are increasingly common (Hall 2008). Fibromyalgia is common, especially in women, with an all-age prevalence of 12%, and a female to male ratio of 6:1 (McNally 2006).
Neuropathic pain and fibromyalgia are known to be difficult to treat effectively, with only a minority of individuals experiencing a clinically relevant benefit from any one intervention. A multidisciplinary approach is now advocated, with pharmacological interventions being combined with physical and/or cognitive interventions. Conventional analgesics are usually not effective. Some patients with neuropathic pain may derive some benefit from topical lidocaine patch or low concentration topical capsaicin, although evidence of benefit is uncertain (Derry 2012; Khaliq 2007). High concentration topical capsaicin may benefit some patients with postherpetic neuralgia (Derry 2013). Treatment is more usually by so-called unconventional analgesics such as antidepressants like duloxetine and amitriptyline (Lunn 2009; Moore 2012a; Sultan 2008) or antiepileptics like gabapentin or pregabalin (Moore 2009a; Moore 2011a). The proportion of patients who achieve worthwhile pain relief (typically defined as at least 50% pain intensity reduction (Moore 2013b)) is small, typically 10% to 25% more than with placebo, with numbers needed to treat for an additional beneficial outcome (NNTs) usually between 4 and 10.
Description of the intervention
Oxycodone is a strong opioid agonist, developed in the early 20th century, and chemically related to codeine (Olkkola 2013). It is considered to be comparable to morphine for efficacy, and similar for adverse events, with the exception of hallucinations, which tend to occur rarely with oxycodone (Poyhia 1993). Like morphine, it can be administered via a variety of routes including oral or rectal, and intramuscular, intravenous, or subcutaneous injection. Its analgesic potency makes it useful for the management of severe pain, usually acute postoperative, post-traumatic, or cancer pain. In acute postoperative pain, oxycodone 15 mg alone compared with placebo, had an NNT for at least 50% pain relief of 4.6 (2.9 to 11) (Gaskell 2009).
Various strands of evidence, mainly from studies in rodents, indicate that oxycodone may exert its opioid effects through the mu-opioid receptor and the kappa-opioid receptor (Kalso 2007). Oral oxycodone is widely used to treat cancer pain and chronic noncancer pain, and individual titration of doses to effect is indicated, especially in older people, as pharmacokinetics may be age-dependent and highly individual (Olkkola 2009).
Repeated administration of oxycodone can cause dependence and tolerance, and its potential for abuse is well known. Regulation of supply varies between countries, but in many, all oxycodone preparations are controlled substances. There have been indications that oxycodone is abused, and some reformulation to prevent crushing may reduce this (Butler 2013). There are other general concerns about long-term use of opioids, cognitive impairment and immune and endocrine effects (Brennan 2013), as well as mortality (Dhalla 2009).
How the intervention might work
Opioids like oxycodone bind to specific opioid receptors in the nervous system and other tissues; there are three principal classes of receptors (mu, kappa, and delta) though others have been suggested, and subtypes of receptors are considered to exist. Binding of opioid agonists like oxycodone to receptors brings about complex cellular changes, outcomes of which include decreased perception of pain, decreased reaction to pain, and increased pain tolerance. Opioids from plant sources have been used for thousands of years to treat pain.
Why it is important to do this review
The standards used to assess evidence in chronic pain trials have changed substantially, with particular attention being paid to trial duration, withdrawals, and statistical imputation following withdrawal, all of which can substantially alter estimates of efficacy. The most important change is the move from using average pain scores, or average change in pain scores, to using the number of patients who have a large decrease in pain (by at least 50%); this level of pain relief has been shown to correlate with improvements in comorbid symptoms, function, and quality of life. These standards are set out in the reference guide for pain studies (AUREF 2012) and reflect what patients with chronic pain want from treatment (Moore 2013a).
This Cochrane review will assess evidence in ways that make both statistical and clinical sense, and will use developing criteria for what constitutes reliable evidence in chronic pain (Moore 2010a). Trials included and analysed will need to meet a minimum of reporting quality (blinding, randomisation), validity (duration, dose and timing, diagnosis, outcomes, etc), and size (ideally at least 500 participants in a comparison in which the (NNT) is four or more (Moore 1998)). This approach does set high standards and marks a departure from how reviews have been done previously.
This is particularly important for opioids in chronic noncancer pain. Opioids in clinical trials in noncancer pain are associated with very high withdrawal rates of up to 60% over about 12 weeks (Moore 2010b). Many withdrawals occur within the first few weeks, when patients experience pain relief but cannot tolerate the drug. The common practice of using the last observed results carried forward to the end of the trial many weeks later (last observation carried forward (LOCF)) can therefore produce results based largely on patients no longer in the trial, and who in the real world could not achieve pain relief because they could not take the tablets. The newer standards, outlined in Appendix 1, would not allow this and can produce very different results. For example, oxycodone was judged effective in a large analysis of pooled data from trials in osteoarthritis and chronic low back pain conducted over about 12 weeks; an analysis of the same data using the new patient-centred standards showed oxycodone to be significantly worse than placebo (Lange 2010).
A previous Cochrane review has demonstrated the limitations of our knowledge about opioids in neuropathic pain, except in short duration studies of 24 hours or less (Eisenberg 2006), and a review specific to oxycodone, one of the most widely used opioids, is timely.
- To assess the analgesic efficacy of oxycodone for chronic neuropathic pain and fibromyalgia in adults.
- To assess the adverse events associated with the clinical use of oxycodone for chronic neuropathic pain and fibromyalgia in adults.
Criteria for considering studies for this review
Types of studies
We will include studies if they are randomised controlled trials (RCTs) with double-blind assessment of participant outcomes following two weeks of treatment or longer, although the emphasis of the review will be on studies of eight weeks or longer. We require full journal publication, with the exception of online clinical trial results, summaries of otherwise unpublished clinical trials, and abstracts with sufficient data for analysis. We will not include short abstracts (usually meeting reports). We will exclude studies that are non-randomised studies of experimental pain, case reports and clinical observations.
Types of participants
Studies should include adult participants aged 18 years and above. Participants may have one or more of a wide range of chronic neuropathic pain conditions including:
- painful diabetic neuropathy;
- postherpetic neuralgia;
- trigeminal neuralgia;
- phantom limb pain;
- postoperative or traumatic neuropathic pain;
- complex regional pain syndrome;
- cancer-related neuropathy;
- human immunodeficiency virus (HIV) neuropathy;
- spinal cord injury;
We will include studies of participants with more than one type of neuropathic pain; in such cases we will analyse results according to the primary condition.
Types of interventions
Oxycodone at any dose, by any route, administered for the relief of neuropathic pain or fibromyalgia and compared to placebo or any active comparator. Oxycodone in fixed dose combination with naloxone will not be considered.
Types of outcome measures
We anticipate that studies will use a variety of outcome measures, with the majority of studies using standard subjective scales (numerical rating scale (NRS) or visual analogue scale (VAS)) for pain intensity or pain relief, or both. We are particularly interested in Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT) definitions for moderate and substantial benefit in chronic pain studies (Dworkin 2008). These are defined as at least 30% pain relief over baseline (moderate), at least 50% pain relief over baseline (substantial), much or very much improved on Patient Global Impression of Change (PGIC) (moderate), and very much improved on PGIC (substantial). These outcomes are different from those used in most earlier reviews (e.g. Eisenberg 2006), concentrating as they do on dichotomous outcomes where pain responses do not follow a normal (Gaussian) distribution. People with chronic pain desire high levels of pain relief, ideally more than 50%, and with pain not worse than mild (O'Brien 2010).
We will include a 'Summary of findings' table as set out in the author guide (AUREF 2012). The Summary of findings table will include outcomes of at least 50% and at least 30% pain intensity reduction, PGIC, adverse event withdrawals, serious adverse events, and death.
- Participant-reported pain relief of 50% or greater.
- Participant-reported pain relief of 30% or greater.
- Participant-reported global impression of clinical change (PGIC) much or very much improved.
- Participant-reported global impression of clinical change (PGIC) very much improved.
- Any pain-related outcome indicating some improvement.
- Withdrawals due to lack of efficacy.
- Participants experiencing any adverse event.
- Participants experiencing any serious adverse event.
- Withdrawals due to adverse events.
- Specific adverse events, particularly somnolence and dizziness.
Search methods for identification of studies
The following databases will be searched.
- Cochrane Central Register of Controlled Trials (CENTRAL) (via The Cochrane Library).
- MEDLINE (via Ovid).
- EMBASE (via Ovid).
The search strategy that will be used to search MEDLINE is shown in Appendix 2. It will be amended, where necessary, to search the other databases listed. No language or date restrictions will be applied.
Searching other resources
We will review the bibliographies of any randomised trials and review articles identified, contact the authors and known experts in the field, and search www.clinicaltrials.gov and apps.who.int/trialsearch/ to identify additional published or unpublished data.
Data collection and analysis
Selection of studies
We will determine eligibility by reading the title and abstract of studies identified by the search. Studies that clearly do not satisfy inclusion criteria will be eliminated, and we will obtain full copies of the remaining studies. Two review authors will read these studies independently and reach agreement by discussion. We will not anonymise the studies in any way before assessment. We plan to include a PRISMA study flow diagram in the full review (Liberati 2009) to document the screening process, as recommended in Part 2, Section 11.2.1 of the Cochrane Handbook (Higgins 2011).
Data extraction and management
Review authors will independently extract data using a standard form and check for agreement before entry into RevMan 5 (RevMan 2012) or any other analysis tool. We will include information about the pain condition and number of participants treated, drug and dosing regimen, study design (placebo or active control), study duration and follow-up, analgesic outcome measures and results, withdrawals and adverse events (participants experiencing any adverse event or serious adverse event).
Assessment of risk of bias in included studies
We will use the Oxford Quality Score (Jadad 1996) as the basis for inclusion, limiting inclusion to studies that are randomised and double-blind as a minimum.
Two review authors will independently assess risk of bias for each study, using the 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, with any disagreements resolved by discussion. 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). Studies using a non-random process (e.g. odd or even date of birth; hospital or clinic record number) will be excluded.
- Allocation concealment (checking for possible selection bias). The method used to conceal allocation to interventions before 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). Studies that do not conceal allocation (e.g. open list) will be excluded.
- 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 this was achieved). Studies that were not double-blind will be excluded.
- 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 of bias (< 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).
Measures of treatment effect
We will calculate numbers needed to treat to benefit (NNTs) as the reciprocal of the absolute risk reduction (ARR) (McQuay 1998). For unwanted effects, the NNT becomes the number needed to treat to harm (NNH) and is calculated in the same manner. We will use dichotomous data to calculate risk ratio (RR) with 95% confidence intervals (CIs) using a fixed-effect model unless significant statistical heterogeneity is found (see below). Continuous data will not be used in analyses.
Unit of analysis issues
The control treatment arm will be split between active treatment arms in a single study if the active treatment arms are not combined for analysis.
Dealing with missing data
We will use intention-to-treat (ITT) analysis where the ITT population consists of participants who were randomised, took at least one dose of the assigned study medication, and provided at least one post-baseline assessment. Missing participants will be assigned zero improvement.
Assessment of heterogeneity
We will deal with clinical heterogeneity by combining studies that examine similar conditions. We will assess statistical heterogeneity visually (L'Abbé 1987) and with the use of the I² statistic. When I² is greater than 50%, we will consider possible reasons.
Assessment of reporting biases
The aim of this review is to use dichotomous data of known utility (Moore 2010d). The review does not depend on what authors of the original studies chose to report or not, although clearly difficulties will arise in studies failing to report any dichotomous results. We will extract and use continuous data, which probably poorly reflect efficacy and utility, if useful, for illustrative purposes only.
We will assess publication bias using a method designed to detect the amount of unpublished data with a null effect that would be required to make any result clinically irrelevant (usually taken to mean an NNT of 10 or more in these conditions) (Moore 2008).
We plan to analyse according to individual painful conditions because placebo response rates with the same outcome can vary between conditions, as can the drug-specific effects (Moore 2009a). We will use a fixed-effect model for meta-analysis; a random-effects model will be used if there is significant clinical heterogeneity and it is considered appropriate to combine studies. We plan to include a ‘Summary of Findings’ table according to recommendations described in Chapter 10 of the Cochrane Handbook (Higgins 2011).
We plan to analyse data for each painful condition in two tiers, according to outcome and freedom from known sources of bias.
- The first tier will use data meeting current best standards, where studies report the outcome of at least 50% pain intensity reduction over baseline (or its equivalent), without the use of LOCF or other imputation method for dropouts, report an ITT analysis, last 8 to 12 weeks or longer, have a parallel-group design, and where there are at least 200 participants (preferably at least 400) in the comparison. These top-tier results will be reported first.
- The second tier will use any available data, but where one or more of first tier conditions are not met, for example reporting at least 30% pain intensity reduction, using LOCF or a completer analysis, lasting 4 to 8 weeks, and where the numbers of participants and studies are small.
Subgroup analysis and investigation of heterogeneity
We will analyse separately data for different pain conditions and dosing regimens.
No sensitivity analyses are planned.
Institutional support was provided by the Oxford Pain Relief Trust.
Appendix 1. Methodological considerations for chronic pain
There have been several recent changes in how efficacy of conventional and unconventional treatments is assessed in chronic painful conditions. The outcomes are now better defined, particularly with new criteria of what constitutes moderate or substantial benefit (Dworkin 2008); older trials may only report participants with "any improvement". Newer trials tend to be larger, avoiding problems from the random play of chance. Newer trials also tend to be longer, up to 12 weeks, and longer trials provide a more rigorous and valid assessment of efficacy in chronic conditions. New standards have evolved for assessing efficacy in neuropathic pain, and we are now applying stricter criteria for inclusion of trials and assessment of outcomes, and are more aware of problems that may affect our overall assessment. To summarise some of the recent insights that must be considered in this new review:
- Pain results tend to have a U-shaped distribution rather than a bell-shaped distribution. This is true in acute pain (Moore 2011b; Moore 2011c), back pain (Moore 2010d), arthritis (Moore 2010c), as well as in fibromyalgia (Straube 2010); in all cases average results usually describe the experience of almost no-one in the trial. Data expressed as averages are potentially misleading, unless they can be proven to be suitable.
- As a consequence, we have to depend on dichotomous results (the individual either has or does not have the outcome) usually from pain changes or patient global assessments. The Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT) group has helped with their definitions of minimal, moderate, and substantial improvement (Dworkin 2008). In arthritis, trials shorter than 12 weeks, and especially those shorter than eight weeks, overestimate the effect of treatment (Moore 2009b); the effect is particularly strong for less effective analgesics, and this may also be relevant in neuropathic-type pain.
- The proportion of patients with at least moderate benefit can be small, even with an effective medicine, falling from 60% with an effective medicine in arthritis, to 30% in fibromyalgia (Straube 2008Sultan 2008Moore 2009a; Moore 2010c; Straube 2008; Sultan 2008). A Cochrane review of pregabalin in neuropathic pain and fibromyalgia demonstrated different response rates for different types of chronic pain (higher in diabetic neuropathy and postherpetic neuralgia and lower in central pain and fibromyalgia) (Moore 2009a). This indicates that different neuropathic pain conditions should be treated separately from one another, and that pooling should not be done unless there are good grounds for doing so.
- Finally, presently unpublished individual patient analyses indicate that patients who get good pain relief (moderate or better) have major benefits in many other outcomes, affecting quality of life in a significant way (Moore 2010e).
Appendix 2. Search strategy for MEDLINE via Ovid
- exp PAIN/
- exp PERIPHERAL NERVOUS SYSTEM DISEASES/
- exp SOMATOSENSORY DISORDERS/
- ((pain* or discomfort*) adj10 (central or complex or rheumat* or muscl* or muscul* or myofasci* or nerv* or neuralg* or neuropath*)).mp.
- (fibromyalgi* or fibrosti* or FM or FMS).mp.
- ((neur* or nerv*) adj6 (compress* or damag*)).mp.
- 1 or 2 or 3 or 4 or 5 or 6 or 7
- (oxycodone or OxyNorm or OxyContin or Dinarkon or Endone or Endocodone or Oxygesic or OxyFast or Proladone or Percolone or Roxicodone or Supeudol or Tylox).mp.
- 9 or 10
- 8 and 11
- randomized controlled trial.pt.
- controlled clinical trial.pt.
- drug therapy.fs.
- exp animals/ not humans.sh.
- 21 not 22
- 23 and 12
Contributions of authors
SD and RAM wrote the protocol.
HG and SD will search for and select studies for inclusion and will carry out data extraction. All review authors will be involved in the analysis and in writing the full review.
Declarations of interest
RAM and SD have received research support from charities, government, and industry sources at various times. RAM has consulted for various pharmaceutical companies and has received lecture fees from pharmaceutical companies related to analgesics and other health care interventions. HG and CS have no interests to declare.
Sources of support
- Oxford Pain Relief Trust, UK.General institutional support
- No sources of support supplied