Types of studies

We included studies if they were randomised controlled trials (RCTs) with at least 10 participants per treatment group and double‐blind (participant and observers) assessment of participant‐reported outcomes, following two weeks of treatment or longer, although the emphasis of the review is on studies of six weeks or longer. We required full journal publication, with the exception of extended abstracts of otherwise unpublished clinical trials (for example, detailed information from PDFs of posters that typically included all important details of methodology used and results obtained). We did not include short abstracts (usually meeting reports with inadequate or no reporting of data). We excluded studies of experimental pain, case reports, and clinical observations.

In the earlier review, we excluded studies of lamotrigine used to treat pain produced by other drugs; in this version we have included one study for chemotherapy‐induced pain, but have not combined results from this study in the analysis (Rao 2008).

Types of participants

Studies included adult participants aged 18 years and above. Participants could have one or more of a wide range of chronic neuropathic pain conditions including (but not limited to):

• cancer‐related neuropathy;

• central neuropathic pain;

• complex regional pain syndrome (CRPS) Type II;

• human immunodeficiency virus (HIV) neuropathy;

• painful diabetic neuropathy;

• phantom limb pain;

• postherpetic neuralgia;

• postoperative or traumatic neuropathic pain;

• spinal cord injury;

• trigeminal neuralgia;

and

• fibromyalgia;

• CRPS Type I.

Types of interventions

Lamotrigine in any dose, by any route, administered for the relief of neuropathic pain or fibromyalgia, and compared to placebo, no intervention or any other active comparator.

Types of outcome measures

We anticipated that studies would 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 were 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 set out in the earlier review (Wiffen 2007), 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 include a 'Summary of findings' table as set out in the Cochrane Pain, Palliative and Supportive Care Group author guide (AUREF 2012). The 'Summary of findings' table includes outcomes of at least 30% and at least 50% pain intensity reduction, PGIC, adverse event withdrawals, serious adverse events and death (summary of findings Table for the main comparison).

Electronic searches

We identified studies by several methods. For the original review we identified RCTs of lamotrigine (and key brand names Lamictal, Lamictin, Neurium) in acute and chronic pain in the Cochrane Central Register of Controlled Trials (CENTRAL, 2010, Issue 12), MEDLINE (via Ovid) from 1966 to January 2011, and EMBASE (via Ovid) from 1994 to January 2011.

For this update we searched for new studies in chronic neuropathic pain and fibromyalgia in:

• Cochrane Central Register of Controlled Trials (CENTRAL, 2013, Issue 11 in The Cochrane Library);

• MEDLINE (via Ovid) (January 2010 to 26 November 2013);

• EMBASE (via Ovid) (January 2010 to 26 November 2013);

• PhRMA clinical study results database (clinicaltrials.gov) to 26 November 2013;

• WHO International Clinical Trials Registry Platform (apps.who.int/trialsearch) to 26 November 2013.

Given the limited literature in this area, we undertook a sensitive search strategy. See Appendix 2 for the MEDLINE search strategy, Appendix 3 for the EMBASE search strategy, and Appendix 4 for the CENTRAL search strategy.

Searching other resources

For the original review, we identified additional studies from the reference lists of the retrieved papers and by contacting study authors. We applied no language restrictions.

Selection of studies

Two review authors independently read the titles and abstracts of all studies identified by the search, and the full text of all potentially relevant studies. We reached agreement on eligibility by discussion. We did not anonymise the studies in any way before assessment.

Data extraction and management

Two review authors extracted data using a standard form, and agreed data before entry into Review Manager 5 (RevMan 2012) or any other analysis method. Data extracted included information about the pain condition and number of participants treated, drug and dosing regimen, study design, study duration and follow‐up, analgesic outcome measures and results, withdrawals and adverse events (participants experiencing any adverse event or a serious adverse event).

Assessment of risk of bias in included studies

We independently scored each study for quality using a three‐item scale (Jadad 1996) and agreed a 'consensus' score for each study. Scores of two and below have been associated with greater estimates of efficacy than studies of higher quality (Khan 1996). Quality scores were not used to weight the results in any way.

We used the 'Risk of bias' tool to assess the likely impact on the strength of the evidence of various study characteristics relating to methodological quality (randomisation, allocation concealment, blinding, freedom from selective reporting), study validity (duration, outcome reporting, and handling of missing data), and size (Moore 2010a).

Two review authors independently assessed risks 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 assessed the following for each study.

• Random sequence generation (checking for possible selection bias). We assessed the method used to generate the allocation sequence as: low risk of bias (any truly random process, eg random number table; computer random number generator); unclear risk of bias (method used to generate sequence not clearly stated). We excluded studies using a non‐random process (eg odd or even date of birth; hospital or clinic record number).

• 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 assessed the methods as: low risk of bias (eg telephone or central randomisation; consecutively numbered sealed opaque envelopes); unclear risk of bias (method not clearly stated). We excluded studies that did not conceal allocation (eg open list).

• Blinding of outcome assessment (checking for possible detection bias). We assessed the methods used to blind study participants and outcome assessors from knowledge of which intervention a participant received. We assessed the methods as: low risk of bias (study states that it was blinded and describes the method used to achieve blinding, eg 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). We excluded 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 assessed the methods used to deal with incomplete data as: low risk of bias (< 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); high risk of bias (used 'completer' analysis).

• Size of study (checking for possible biases confounded by small size). We assessed 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 used the risk ratio (relative risk, RR) to establish statistical difference. We used numbers needed to treat for an additional beneficial outcome (NNT) or for an additional harmful outcome (NNH) and pooled percentages as absolute measures of benefit or harm.

The following terms are used to describe adverse outcomes in terms of harm or prevention of harm:

• When significantly fewer adverse outcomes occurred with lamotrigine than with control (placebo or active) we used the term the number needed to treat to prevent one event (NNTp);

• When significantly more adverse outcomes occurred with lamotrigine compared with control (placebo or active) we used the term the number needed to harm or cause one event (NNH).

Unit of analysis issues

The control treatment arm would be split between active treatment arms in a single study if the active treatment arms were not combined for analysis.

Dealing with missing data

We used intention‐to‐treat (ITT) analysis. The ITT population consisted of participants who were randomised, took the assigned study medication and provided at least one post‐baseline assessment. Missing participants were assigned zero improvement where this could be done. We were aware that imputation methods might be problematical and examined trial reports for information about them.

Assessment of heterogeneity

We dealt with clinical heterogeneity by combining studies that examined similar painful conditions, and not combining results from dissimilar painful conditions. We assessed statistical heterogeneity visually (L'Abbe 1987) and with the use of the I² statistic (Higgins 2003).

Assessment of reporting biases

The aim of this review was to use dichotomous data of known utility (Moore 2010a). The review did not depend on what authors of the original studies chose to report or not report, though clearly there were difficulties with studies failing to report any dichotomous results. We extracted continuous data, which probably poorly reflected efficacy and utility, and used them only when useful for illustrative purposes.

We undertook no statistical assessment of publication bias.

Data synthesis

We considered individual painful conditions separately because placebo response rates with the same outcome can vary between conditions, as can the drug‐specific effects (Moore 2009a).

We analysed data for each painful condition in three tiers, according to outcome and freedom from known sources of bias.

• The first tier uses 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 last observation carried forward (LOCF) or other imputation method for dropouts, report an intention‐to‐treat (ITT) analysis, last eight or more weeks, have a parallel‐group design, and have at least 200 participants (preferably at least 400) in the comparison (Moore 2010a; Moore 2012b). These top‐tier results are reported first.

• The second tier uses data from at least 200 participants but where one or more of the above conditions is not met (for example reporting at least 30% pain intensity reduction, using LOCF or a completer analysis, or lasting four to eight weeks).

• The third tier of evidence relates to data from fewer than 200 participants, or where there are expected to be significant problems because, for example, of very short duration studies of less than four weeks, where there is major heterogeneity between studies, or where there are shortcomings in allocation concealment, attrition, or incomplete outcome data. For this third tier of evidence, no data synthesis is reasonable, and may be misleading, but an indication of beneficial effects might be possible.

We used dichotomous data to calculate risk ratio for benefit with 95% confidence intervals (CIs), using a fixed‐effect model, together with numbers needed to treat for an additional beneficial outcome (NNTs) (Cook 1995). This was done for effectiveness, for adverse effects, and for drug‐related study withdrawal. We also undertook meta‐analysis when appropriate data were available. We calculated NNTs as the reciprocal of the absolute risk reduction (McQuay 1998). For unwanted effects, the NNH (number needed to treat for an additional harmful outcome) is calculated in the same way. In the absence of dichotomous data, we have reported summary continuous data where available and appropriate, but did not carry out any analysis. We undertook meta‐analysis using a fixed‐effect model.

Subgroup analysis and investigation of heterogeneity

We planned no subgroup analyses, beyond separate analysis of different conditions, as we expected that there would be insufficient study data.

Sensitivity analysis

We planned no sensitivity analyses because we knew the evidence base to be too small to allow reliable analysis.