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Cochrane Database of Systematic Reviews Protocol - Intervention

Methadone for neuropathic pain in adults

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Abstract

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:

To assess the analgesic efficacy and adverse events of methadone for chronic neuropathic pain in adults.

Background

This review will replace an earlier review, 'Methadone for chronic non‐cancer pain in adults' (Haroutiunian 2012). This review will serve to update the original and will include only studies of neuropathic pain.

This protocol is based on a template for reviews of drugs used to relieve neuropathic pain. 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 2012; Appendix 1).

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), and based on a definition agreed at an earlier consensus meeting (Treede 2008). Neuropathic pain is a consequence of a pathological maladaptive response of the nervous system to 'damage' from a wide variety of potential causes. It is characterised by pain in the absence of a noxious stimulus and may be spontaneous (continuous or paroxysmal) in its temporal characteristics or be evoked by sensory stimuli (dynamic mechanical allodynia where pain is evoked by light touch of the skin). Neuropathic pain is associated with a variety of sensory loss (numbness) and sensory gain (allodynia) clinical phenomena, the exact pattern of which varies between people and disease, perhaps reflecting different pain mechanisms operating in individual people and therefore potentially predictive of response to treatment (Demant 2014; Helfert 2015; von Hehn 2012). Preclinical research hypothesises a bewildering array of possible pain mechanisms that may operate in people with neuropathic pain, which largely reflect pathophysiological responses in both the central and peripheral nervous systems, including neuronal interactions with immune cells (Baron 2012; Calvo 2012; von Hehn 2012). Overall, the treatment gains in neuropathic pain, to even the most effective of available drugs, are modest (Finnerup 2015; Moore 2013a), and a robust classification of neuropathic pain is not yet available (Finnerup 2013).

Neuropathic pain is usually divided according to the cause of nerve injury. There may be many causes, but some common causes of neuropathic pain include diabetes (painful diabetic neuropathy (PDN)), shingles (postherpetic neuralgia (PHN)), amputation (stump and phantom limb pain), neuropathic pain after surgery or trauma, stroke or spinal cord injury, trigeminal neuralgia, and HIV infection. Sometimes the cause is unknown.

Many people with neuropathic pain conditions are significantly disabled with moderate or severe pain for many years. Chronic pain conditions comprised five of the 11 top‐ranking conditions for years lived with disability in 2010 (Vos 2012), and are responsible for considerable loss of quality of life and employment, and increased healthcare costs (Moore 2014a). One US study found the healthcare costs were three‐fold higher for people with neuropathic pain than matched control participants (Berger 2004). One UK study and one German study showed a two‐ to three‐fold higher level of use of healthcare services in people with neuropathic pain than people without (Berger 2009; Berger 2012). For example, studies of PHN have demonstrated large loss of quality of life and substantial costs (Scott 2006; van Hoek 2009).

In systematic reviews, the overall prevalence of neuropathic pain in the general population is reported to be between 7% and 10% (van Hecke 2014), and about 7% in one systematic review of studies published since 2000 (Moore 2014a). In individual countries, prevalence rates have been reported as 3.3% in Austria (Gustorff 2008), 6.9% in France (Bouhassira 2008), and up to 8% in the UK (Torrance 2006). Some forms of neuropathic pain, such as PDN and postsurgical chronic pain (which is often neuropathic in origin), are increasing (Hall 2008; Moulin 2014). The prevalence of PHN is likely to fall if vaccination against the herpes virus becomes widespread.

Estimates of incidence vary between individual studies for particular origins of neuropathic pain, often because of small numbers of cases. In primary care in the UK, between 2002 and 2005, the incidences (per 100,000 person‐years' observation) were 28 (95% confidence interval (CI) 27 to 30) for PHN, 27 (95% CI 26 to 29) for trigeminal neuralgia, 0.8 (95% CI 0.6 to 1.1) for phantom limb pain, and 21 (95% CI 20 to 22) for PDN (Hall 2008). Other studies have estimated an incidence of 4 in 100,000 per year for trigeminal neuralgia (Katusic 1991; Rappaport 1994), and 12.6 per 100,000 person‐years for trigeminal neuralgia and 3.9 per 100,000 person‐years for PHN in one study of facial pain in the Netherlands (Koopman 2009). One systematic review of chronic pain demonstrated that some neuropathic pain conditions, such as PDN, can be more common than other neuropathic pain conditions, with prevalence rates up to 400 per 100,000 person‐years (McQuay 2007).

Neuropathic pain is difficult to treat effectively, with only a minority of people experiencing a clinically relevant benefit from any one intervention (Kalso 2013; Moore 2013a). A multidisciplinary approach is now advocated, combining pharmacological interventions with physical or cognitive (or both) interventions. The evidence for interventional management is very weak, or nonexistent (Dworkin 2013). Conventional analgesics such as paracetamol and nonsteroidal anti‐inflammatory drugs are not thought to be effective, but without evidence to support or refute that view (Moore 2015a). Some people may derive some benefit from a topical lidocaine patch or low‐concentration topical capsaicin, although evidence about benefits is uncertain (Derry 2012; Derry 2014). High‐concentration topical capsaicin may benefit some people with PHN (Derry 2013). Treatment is often by so‐called 'unconventional analgesics' (pain modulators) such as antidepressants (duloxetine and amitriptyline; Lunn 2014; Moore 2014b; Moore 2015b; Sultan 2008), or antiepileptic drugs (gabapentin or pregabalin; Moore 2009; Moore 2014c; Wiffen 2013). Evidence for efficacy of opioids is unconvincing (Gaskell 2016; Stannard 2016).

The proportion of people who achieve worthwhile pain relief (typically at least 50% pain intensity reduction; Moore 2013b) is small, generally only 10% to 25% more than with placebo, with numbers needed to treat for an additional beneficial outcome (NNTB) usually between 4 and 10 (Kalso 2013; Moore 2013a). Neuropathic pain is not particularly different from other chronic pain conditions in that only a small proportion of trial participants have a good response to treatment (Moore 2013a).

The current National Institute for Health and Care Excellence (NICE) guidance for the pharmacological management of neuropathic pain suggests offering a choice of amitriptyline, duloxetine, gabapentin, or pregabalin as initial treatment for neuropathic pain (with the exception of trigeminal neuralgia), with switching if the first, second, or third drugs tried are not effective or not tolerated (NICE 2013). This concurs with other recent guidance (Finnerup 2015).

Description of the intervention

Methadone belongs to the class of drugs known as opioids. While traditionally use for maintenance and detoxification of people with heroin and other opioid dependencies, it has undergone a resurgence as an analgesic, as it is inexpensive and has distinct pharmacological properties that may confer advantages over other opioids (Trafton 2009). Opioids are considered the cornerstone of therapy for moderate‐to‐severe acute pain or pain of similar intensity due to life‐threatening illnesses, but their long‐term use in noncancer pain is controversial. Meta‐analyses have provided efficacy data on opioids for the treatment of neuropathic pain (McNicol 2013).

In the US, the therapeutic use of opioids has risen significantly since the early 2000s, with 259 million prescriptions written for opioids in 2012 alone (CDC 2014). This has been accompanied by an increase in the rate of deaths due to opioid overdose. The annual mortality rate due to methadone overdose increased by six times in the decade up to 2009 (CDC 2012). Almost one third of the 15,500 deaths due to prescription opioids in the US in 2009 involved methadone, even though only 2% of opioid prescriptions (around four million) were written for this drug. This disproportionate rate has in part been attributed to diversion of the drug (i.e. deaths have occurred in people using methadone for nonmedical purposes). However, one large cohort study of participants receiving methadone for chronic noncancer pain estimated that those receiving methadone had a 46% increased risk of out‐of‐hospital mortality than those receiving an alternative opioid, morphine, suggesting that increased rates of death may be due to pharmacologic differences between methadone and other opioids (Ray 2015).

How the intervention might work

Opioids provide analgesia by binding to opioid receptors of the mu and kappa class and blocking the release of neurotransmitters such as substance P. Opioid receptors are expressed both centrally and peripherally (during the inflammatory response in injured tissue). Methadone is a synthetic opioid that shares many of the analgesic and unwanted effects typical of other opioids. However, it has pharmacokinetic and pharmacodynamic properties that distinguish it from other opioids (Trafton 2009).

  1. Unlike many other opioids, methadone has extensive oral bioavailability. Most opioids have less than 40% oral bioavailability (Trafton 2009).

  2. Methadone is metabolised in the liver via the cytochrome P‐450 system, and is excreted renally and via the faecal route. Dosage adjustment is not required in renal or hepatic insufficiency, or in haemodialysis. Additionally, methadone does not appear to produce active, potentially toxic metabolites. Methadone has a long, biphasic elimination half‐life. It may take up to 10 days to reach steady‐state serum levels. It is inherently long acting and is significantly less expensive than opioids that are pharmaceutically manipulated into controlled‐release formulations (Trafton 2009).

  3. N‐methyl‐D‐aspartate (NMDA) receptor antagonism. Activation of the NMDA receptor by excitatory amino acids, such as glutamate, has been implicated in the development of neuropathic pain and also appears to have a role in the development of opioid tolerance and opioid‐induced hyperalgesia. While the ability of methadone to block the NMDA receptor has been demonstrated in animal models, it is unclear if this has clinical relevance at normal doses. It is postulated that this property may lend methadone an advantage over other opioids when treating neuropathic pain, with less need for dosage escalations (Trafton 2009).

  4. Prolongation of the QT interval on electrocardiogram (ECG) at high doses. QT interval is the interval measured from the beginning of the QRS complex to the end of the T wave on ECG, measuring the time between depolarisation and repolarisation (or recovery) of the heart ventricles. Methadone binds in vitro to the cardiac HERG potassium ion channel (Kv11.1 potassium channel coded by human Ether‐à‐go‐go Related Gene) and has been shown to prolong cardiac depolarisation in a dose‐dependent manner. People with prolonged QT interval are at risk of developing torsades de pointes, a potentially life‐threatening ventricular tachyarrhythmia. Data indicate that methadone may be responsible for sudden cardiac death, even in concentrations that are considered therapeutic for most people (Chugh 2008; Krantz 2009). Intravenous methadone is associated with greater QTc interval prolongation than the oral preparation. This risk may also be increased with concurrent use of other QT interval‐prolonging medications.

These distinct properties suggest that methadone may have a different efficacy and safety profile than other commonly prescribed opioids.

Why it is important to do this review

The increase in prescribing of methadone in recent years and the accompanying increase in fatalities associated with its use constitutes a public health concern. Conversely, the potentially beneficial properties of methadone, such as NMDA receptor antagonism, may be responsible for increased effectiveness in certain people with neuropathic pain; therefore, it is important and timely to conduct this systematic review.

The standards used to assess evidence in chronic pain trials have changed substantially in recent years, 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 mean pain scores, or mean change in pain scores, to the number of people who have a large decrease in pain (by at least 50%) and who continue in treatment, ideally in trials of eight to 12 weeks' duration or longer. Pain intensity reduction of 50% or more correlates with improvements in comorbid symptoms, function, and quality of life.

Trials included and analysed will 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 NNTB is 4 or above; Moore 1998). This approach sets high standards and marks a departure from how reviews were conducted previously.

These standards are set out in the PaPaS Author and Referee Guidance for pain studies of the Cochrane Pain, Palliative and Supportive Care Group (PaPaS 2012). This Cochrane review will assess evidence using methods that make both statistical and clinical sense, and will use criteria for what constitutes reliable evidence in chronic pain (Moore 2010a).

Objectives

To assess the analgesic efficacy and adverse events of methadone for chronic neuropathic pain in adults.

Methods

Criteria for considering studies for this review

Types of studies

We will include randomised controlled trials (RCTs) with double‐blind assessment of participant outcomes following two weeks or more of treatment, although the emphasis of the review will be on studies with a duration of eight weeks or longer. We will 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 exclude short abstracts (usually meeting reports). We will exclude studies that are nonrandomised, studies of experimental pain, case reports, and clinical observations.

Types of participants

Studies will include adults aged 18 years and above with one or more chronic neuropathic pain condition including (but not limited to):

  1. cancer‐related neuropathy;

  2. central neuropathic pain;

  3. complex regional pain syndrome Type II;

  4. HIV neuropathy;

  5. painful diabetic neuropathy (PDN);

  6. phantom limb pain;

  7. postherpetic neuralgia (PHN);

  8. postoperative or traumatic neuropathic pain;

  9. spinal cord injury;

  10. trigeminal neuralgia.

Where we include studies of participants with more than one type of neuropathic pain, we will analyse results according to the primary condition. We will exclude studies of migraine and headache as they are the subject of another Cochrane review (Chronicle 2004). We will exclude studies with fewer than 10 participants in each arm.

Types of interventions

Methadone at any dose, by any route, administered for the relief of neuropathic pain and compared with placebo or any active comparator.

Types of outcome measures

We anticipate that studies will use a variety of outcome measures, with most studies using standard subjective scales (numerical rating scale or visual analogue scale) 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:

  1. at least 30% pain relief over baseline (moderate);

  2. at least 50% pain relief over baseline (substantial);

  3. much or very much improved on Patient Global Impression of Change scale (PGIC; moderate);

  4. very much improved on PGIC (substantial).

These outcomes are different from those used in most earlier reviews, 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% pain intensity reduction, and ideally having no worse than mild pain (Moore 2013b; O'Brien 2010).

Primary outcomes

  1. Participant‐reported pain relief of 30% or greater.

  2. Participant‐reported pain relief of 50% or greater.

  3. PGIC much or very much improved.

  4. PGIC very much improved.

Secondary outcomes

  1. Any pain‐related outcome indicating some improvement.

  2. Withdrawals due to lack of efficacy, adverse events, and for any cause.

  3. Participants experiencing any adverse event.

  4. Participants experiencing any serious adverse event. Serious adverse events typically include any untoward medical occurrence or effect that at any dose results in death, is life‐threatening, requires hospitalisation or prolongation of existing hospitalisation, results in persistent or significant disability or incapacity, is a congenital anomaly or birth defect, is an 'important medical event' that may jeopardise the person, or may require an intervention to prevent one of the above characteristics or consequences. While we will extract all data related to serious adverse events, we will pay particular attention to reports of respiratory depression and cardiovascular events.

  5. Specific adverse events, particularly somnolence and dizziness.

Search methods for identification of studies

Electronic searches

We will search the following databases, without language restrictions:

  1. Cochrane Central Register of Controlled Trials (CENTRAL);

  2. MEDLINE (via Ovid);

  3. Embase (via Ovid).

The search strategy for MEDLINE is shown in Appendix 2. We will adapt the MEDLINE search strategy for CENTRAL and Embase.

Searching other resources

We will review the bibliographies of any RCTs identified and review articles, and search ClinicalTrials.gov (ClinicalTrials.gov) and World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) (apps.who.int/trialsearch/) to identify additional published or unpublished data. We will not contact investigators or study sponsors.

Data collection and analysis

We will perform separate analyses according to particular neuropathic pain conditions. We will combine different neuropathic pain conditions in analyses for exploratory purposes only.

Selection of studies

We will determine eligibility by reading the abstract of each study identified by the search. We will eliminate studies that clearly do not satisfy the inclusion criteria, and we will obtain full copies of the remaining studies. Two review authors (EM and MF or RS) will read these studies independently and reach agreement by discussion. We will not anonymise the studies before assessment. We will create a PRISMA flow chart if appropriate.

Data extraction and management

Two review authors (two of EM, MF, and RS) will extract data independently using a standard form and check for agreement before entry into Review Manager 5 (RevMan 2014), 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 as the basis for inclusion (Jadad 1996), limiting inclusion to studies that are randomised and double‐blind as a minimum.

Two review authors (two of EM, MF, and RS) 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:

  1. Random sequence generation (checking for possible selection bias). We will assess the method used to generate the allocation sequence as: low risk of bias (i.e. any truly random process, for example random number table; computer random number generator); unclear risk of bias (when the method used to generate the sequence is not clearly stated). We will exclude studies at a high risk of bias that use a nonrandom process (for example, odd or even date of birth; hospital or clinic record number).

  2. 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 (for example, telephone or central randomisation; consecutively numbered, sealed, opaque envelopes); unclear risk of bias (when method not clearly stated). We will exclude studies that do not conceal allocation and are therefore at a high risk of bias (for example, open list).

  3. Blinding of participants and personnel (checking for possible performance bias), and blinding of outcome assessment (checking for possible detection bias). We will assess the methods used to blind study personnel and participants (all outcomes will be self‐assessed) from knowledge of which intervention a participant received. We will assess the methods as: low risk of bias (e.g. study states that it was blinded and describes the method used to achieve blinding, for example, 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). We will exclude studies at a high risk of bias that were not double‐blind.

  4. 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 (i.e. less than 10% of participants did not complete the study or used 'baseline observation carried forward' analysis, or both); unclear risk of bias (used 'last observation carried forward' (LOCF) analysis); or high risk of bias (used 'completer' analysis).

  5. Size of study (checking for possible biases confounded by small size). We will assess studies as being at low risk of bias (200 participants or more per treatment arm); unclear risk of bias (50 to 199 participants per treatment arm); or high risk of bias (fewer than 50 participants per treatment arm).

Measures of treatment effect

We will calculate NNTBs as the reciprocal of the absolute risk reduction (ARR; McQuay 1998). For unwanted effects, the number needed to treat becomes the number needed to treat for an additional harmful outcome (NNTH) and is calculated in the same manner. We will use dichotomous data to calculate risk ratio (RR) with 95% confidence intervals (CI) using a fixed‐effect model unless we find significant statistical heterogeneity (see Assessment of heterogeneity). We will not use continuous data in analyses.

Unit of analysis issues

We will split the control treatment arm between active treatment arms in a single study if the active treatment arms are not combined for analysis.

For cross‐over studies, we plan to use only the first period, if this is available. Where only combined data for both periods are reported, we will treat the study as if it was a parallel study, drawing attention to the potential bias that this confers, and interpreting the results accordingly (Elbourne 2002).

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 postbaseline assessment. Missing participants will be assigned zero improvement wherever possible.

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 the I2 value is greater than 50%, we will consider possible reasons for this.

Assessment of reporting biases

The aim of this review is to use dichotomous outcomes of known utility and of value to people (Hoffman 2010; Moore 2010b; Moore 2010c; Moore 2010d; Moore 2013b). The review will not depend on what the authors of the original studies chose to report or not, though clearly difficulties will arise in studies failing to report any dichotomous results. We will extract and use continuous data, which probably will reflect efficacy and utility poorly, and may be 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 required to make any result clinically irrelevant (usually taken to mean an NNTB of 10 or higher; Moore 2008).

Data synthesis

We plan to use a fixed‐effect model for meta‐analysis. We will use a random‐effects model for meta‐analysis if there is significant clinical heterogeneity and it is considered appropriate to combine studies. We will perform pooled analyses where there are data from at least 200 participants in the comparison to avoid problems with random chance effects (Moore 1998), or bias in small studies and data sets (Dechartres 2013; Dechartres 2014; Nüesch 2010).

Quality of the evidence

We will use the GRADE approach to assess the quality of evidence related to each of the key outcomes, and report our judgement on the quality of the evidence in the 'Summary of findings' table (chapter 12, Higgins 2011; Appendix 3). We will assess potential for publication bias, based on the amount of unpublished data required to make the result clinically irrelevant (Moore 2008).

In addition, there may be circumstances where the overall rating for a particular outcome needs to be adjusted as recommended by GRADE guidelines (Guyatt 2013a). For example, if there are so few data that the results are highly susceptible to the random play of chance, or if studies use LOCF imputation in circumstances where there are substantial differences in adverse event withdrawals, one would have no confidence in the result, and would need to downgrade the quality of the evidence by 3 levels, to very low quality. In circumstances where there were no data reported for an outcome, we would report the level of evidence as very low quality (Guyatt 2013b).

'Summary of findings' table

We will include a 'Summary of findings' table as set out in the Cochrane Pain, Palliative and Supportive Care Group (PaPaS) Author and Referee Guidance (PaPaS 2012), and recommended in the Cochrane Handbook for Systematic Reviews of Interventions (Chapter 11 Higgins 2011). The tables will include, where possible, outcomes equivalent to moderate or substantial benefit of at least 30% and at least 50% pain intensity reduction, PGIC (possibly at least substantial improvement and at least moderate improvement) (Dworkin 2008), withdrawals due to lack of efficacy, withdrawals due to adverse events, serious adverse events, and death (a particular serious adverse event).

Subgroup analysis and investigation of heterogeneity

We do not plan to perform subgroup analyses since experience of previous reviews indicates that there will be too few data for any meaningful subgroup analysis.

Sensitivity analysis

We do not plan to perform sensitivity analysis because the evidence base is known to be too small to allow reliable analysis; results from neuropathic pain of different origins will not be pooled in the primary analyses. We will examine details of dose escalation schedules in the unlikely situation that this could provide some basis for a sensitivity analysis.