Criteria for considering studies for this review
Types of studies
We will include randomised controlled trials (RCTs).
Types of participants
The target population will be adults (≥ 18 years old) diagnosed with non-specific or specific (e.g. lumbar/sacral radiculopathies and pathological causes of back pain) chronic low-back pain. Low-back pain is defined as pain in the lumbar region, with or without pain in the sacral region, gluteal regions and radiation to the lower extremities.
We will include trials of patients with multiple or generalised pain conditions if > 50% of participants had chronic low-back pain or study authors reported results separately.
Types of interventions
We will include clinical trials of orally administered anticonvulsants, such as gabapentin, pregabalin, carbamazepine, phenytoin, topiramate, without restrictions regarding type of anticonvulsant, dose or frequency. Anticonvulsants will be compared to placebo, no intervention, or other active treatments including both non-pharmacologic or pharmacologic treatments. We will also consider studies in which combinations of anticonvulsants or anticonvulsants plus another drug or non-pharmacologic strategy was the intervention (e.g. opioids, anti-inflammatories, antidepressants).
Types of outcome measures
We will categorise duration of follow-up as less than 4 weeks, 1 to 3 months, 4 to 8 months and greater than 9 months for all the outcomes.
Pain, measured as the percentage of patients with pain relief defined as at least 50% of improvement using a numerical scale, or as mean improvement on a continuous scale measured by any validated or non-validated measurement scale (e.g. Visual Analogue Scale (VAS), Verbal Rating and Numeric Rating Scales, McGill Pain Questionnaire) (Dworkin 2005).
Global measure of improvement (e.g. overall improvement, proportion of patients recovered, subjective improvement of symptoms).
Back-specific disability (expressed on a back-specific index, such as the Roland Disability Questionnaire or the Oswestry Disability Index).
Neurological deficits (motor and sensory).
Generic health status or well-being (SF-36 Health Survey), return to work (measured as the number of days of sick leave or the proportion of patients returned to work).
Patient satisfaction measured by self report or an assessor.
Side effects (e.g. nausea, vomiting, drowsiness, somnolence, weight gain).
The Beck Depression Inventory.
Search methods for identification of studies
We will use the methods recommended by Furlan 2009 and the Cochrane Handbook, Chapter 6 "Searching for Studies" (Higgins 2011) to guide the identification of relevant trials.
Trials will be obtained from the following sources: the Cochrane Central Register of Controlled Trials (CENTRAL, latest version), which includes the Back Review Group's Trials Register, MEDLINE (OVID SP, 1966 to present), MEDLINE In-Process & Other Non-Indexed Citations (latest version), EMBASE (OVID SP, 1980 to present), Web of Science (1864 to present), and LILACS (1982 to present). ClinicalTrials.gov and the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP http://apps.who.int/trialsearch/Default.aspx) will be searched for on-going registered trials. There will be no language restrictions.
The search strategies will be developed by the Trials Search Coordinator of the Cochrane Back Review Group. Strategies will consist of controlled vocabulary terms and keywords to describe the condition, the intervention, and a filter to identify randomized controlled trials. The boolean operator "OR" will be used to combine terms within each concept and the operator "AND" will be used to combine the concepts together. See Appendix 1 for a draft Medline strategy. The strategy will be replicated as closely as possible across the other databases.
Searching other resources
We will check the reference lists of the identified studies for additional citations. We will contact pharmaceutical companies, study authors and experts about unpublished data. We will also make a request to the U.S. Food and Drug Administration for data from unpublished trials.
Data collection and analysis
Selection of studies
Two authors (FBF and GAMB) will independently screen the trials identified by the literature search. We will resolve disagreements regarding eligibility by consulting with an additional author (RED).
Data extraction and management
Two authors (FBF and GAMB) will independently extract data. Any discrepancies in the extracted data will be resolved by discussion. We will use a standard data extraction form to extract the following information: characteristics of the study (design, method of randomisation), participants, interventions and outcomes (types of outcome measures, adverse events). We will then check for accuracy before entering the data into the Cochrane Collaboration statistical software, Review Manager 5.2 (Review Manager 2011).
Clinical relevance assessment
We will assess the clinical relevance of each study based on the criteria recommended by the Cochrane Back Review Group (van Tulder 2003). These criteria consist of five questions that relate to key factors, such as patients, interventions and outcomes. Each factor is scored as “yes”, “no”, or “unsure” to indicate whether the study provides sufficient information to determine the relevance of the study’s results to the patient population in question.
Assessment of risk of bias in included studies
For the assessment of study quality, we will follow the guidance of the Cochrane Collaboration (Higgins 2011) and the Cochrane Back Review Group (Furlan 2009). Criteria for assessing risk of bias are listed in Appendix 2.
Initially, we will copy information relevant for making a judgement on a criteria from the original publication into an assessment table. If additional information is available from study authors, we will also enter this in the table along with an indication that this is unpublished information.
Two review authors (FBF and GAMB) will independently make a judgement as to whether the risk of bias for each criteria is considered to be 'low', 'unclear', or 'high'. Consensus will be reached with a third author (RED). We will resolve disagreements by discussion. We will consider trials which are classified as low risk of bias in sequence generation, allocation concealment, blinding, incomplete data and selective outcome reporting as overall low bias-risk trials.
Measures of treatment effect
When possible, the analyses of treatment effects will be conducted separately for chronic low-back pain, with and without radiculopathy.
(a) Binary outcomes
For dichotomous data, we will use relative risk (RR) and absolute risk reduction (ARR) as the effect measures with 95% confidence intervals (CI).
(b) Continuous outcomes
For continuous data, we will present the results as mean differences (MD) with 95% confidence intervals (CI). When pooling data across studies we will estimate the mean difference if the outcomes are measured in the same way between trials.
Unit of analysis issues
The unit of analysis will be each patient recruited into the trials.
Dealing with missing data
We will analyse studies on an intention-to-treat (ITT) basis, i.e. we will analyse patients according to the intervention they were allocated, whether they received the intervention or not. We will impute a poor outcome for a drop-out rate of > 5%. We will also perform a sensitivity analysis imputing a favourable outcome for patients who dropped out from the studies.
For each trial we will report whether or not the investigators stated if the analysis was performed according to the ITT principle.
Assessment of heterogeneity
We will look for clinical heterogeneity by examining the study details to determine the appropriateness of combining studies quantitatively, and test for statistical heterogeneity between trial results using the Chi2 test and the I2 statistic when they are combined (see Chapter 9 of The Cochrane Handbook of Systematic Reviews of Interventions) (Higgins 2011). We will classify heterogeneity using the following I2 values:
• 0 to 40%, might not be important;
• 30% to 60%, may represent moderate heterogeneity;
• 50% to 90%, may represent substantial heterogeneity;
• 75% to 100%, considerable heterogeneity.
If substantial heterogeneity exists we will explore reasons for this through sensitivity and subgroup analyses on factors related to risk of bias, study design, patient and intervention characteristics.
Assessment of reporting biases
Apart from assessing the risk of selective outcome reporting, considered under assessment of risk of bias in included studies, we will assess the likelihood of potential publication bias using funnel plots, provided that there are at least 10 trials (Sterne 2011). Although small sample effects in a funnel plot can be a marker of publication bias, other causes will be considered including: selection biases, poor methodological quality, heterogeneity, artefactual and chance. Furthermore, we will contact drug companies and authors also as a strategy to assess reporting bias.
Dichotomous outcomes will be analysed by calculating the relative risk (RR) and absolute risk reduction (ARR). Continuous outcomes will be analysed by calculating the mean difference (MD) when the same instrument is used to measure outcomes, or the standardised mean difference (SMD) when different instruments are used to measure the outcomes. The degree of uncertainty will be expressed with 95% confidence intervals (95% CI). The outcome measures from the individual trials will be combined through meta-analysis when appropriate (based on the clinical comparability of population, intervention and outcomes between trials) using a random-effects model. A P value of less than 0.05, using the Chi2 test, indicates significant statistical heterogeneity.
If a meta-analysis is not possible or appropriate, the results from clinically comparable trials will be described qualitatively in the text.
Summary of findings (SoF) tables
We will use the principles of the GRADE system (Guyatt 2008), as recommended in The Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011) and adapted in the updated Cochrane Back Review Group method guidelines (Furlan 2009) to assess the quality of the body of evidence associated with specific outcomes (pain, global measure of improvement, back-specific disability, neurological deficits and side effects) in our review and construct a SoF table using the GRADE software. The main comparison will be anticonvulsants compared to other active treatments including both non-pharmacologic or pharmacologic treatments.
Factors that may decrease the quality of the evidence include the following:
Risk of bias: Is a judgement made on the basis of the chance that bias in included studies have influenced the estimate of effect?
Imprecision: Is a judgement made on the basis of the chance that the observed estimate of effect could change completely?
Indirectness: Is a judgement made on the basis of the differences in characteristics of how the study was conducted and how the results are actually going to be applied?
Inconsistency: Is a judgement made on the basis of the variability of results across the included studies?
Publication bias: Is a judgement made on the basis of the question whether all the research evidence has been taken to account?
The quality of the evidence for a specific outcome will be reduced by a level, according to the performance of the studies against these five factors. There are five levels of evidence:
High quality evidence: there are consistent findings among at least 75% of RCTs with low risk of bias, consistent, direct and precise data and no known or suspected publication biases. Further research is unlikely to change either the estimate or our confidence in the results.
Moderate quality evidence: one of the domains is not met. Further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate.
Low quality evidence: two of the domains are not met. Further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate.
Very low quality evidence: three of the domains are not met. We are very uncertain about the results.
No evidence: no RCTs were identified that addressed this outcome.
Subgroup analysis and investigation of heterogeneity
In the case of excessive statistical heterogeneity (I2 > 50%), we will use subgroup analysis to evaluate for potential sources of heterogeneity. Subgroup analyses are secondary analyses in which the participants are divided into groups according to shared characteristics and outcome analyses are conducted to determine if any significant treatment effect occurs according to that characteristic. If data permit, we will carry out the following subgroup analyses:
1. different type of anticonvulsants (such as calcium (e.g. pregabalin) versus sodium (e.g. carbamazepine) channel blockers;
2. different type of drug as the associated intervention (e.g. opioids versus antidepressants);
3. most prominent component of pain (i.e. neuropathic versus nociceptive);
4. age (e.g. 18 to 60 years old versus > 60 years old).
If there are an adequate number of studies, we will perform the following sensitivity analyses:
1. restricting the analysis to studies of high quality and low risk of bias;
2. cross-over design versus non-cross-over;
3. for those studies assessing multiple and generalised pain conditions (e.g. fybromyalgia), we also intend to perform a sensitivity analysis of the primary outcome of the treatment of chronic low-back pain with anticonvulsants according to the presence or absence of multiple or generalised pain conditions.