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Center for Global Research Data

Antiepileptic drug monotherapy for epilepsy: an updated Cochrane review and individual participant data network meta-analysis

Lead Investigator: Sarah Nevitt, University of Liverpool
Title of Proposal Research: Antiepileptic drug monotherapy for epilepsy: an updated Cochrane review and individual participant data network meta-analysis
Vivli Data Request: 5291
Funding Source: Yes: The update of the Cochrane IPD-NMA of antiepileptic drugs will be funded by the National Institute for Health Research (UK) upon receipt of the completed work (NIHR 129904 £19,950.42)
Potential Conflicts of Interest: None

Summary of the Proposed Research:

Epilepsy is a common neurological condition, believed to account for 1% of the total global burden of disease. People with epilepsy experience recurrent, unprovoked seizures are caused by abnormal electrical discharges from the brain. There are two types of epileptic seizures which will be studied within this updated review, focal seizures that start in one area of the brain, and generalised onset tonic‐clonic seizures that start in both cerebral hemispheres simultaneously. It is believed that with effective drug treatment, up to 70% of individuals with active epilepsy have the potential to become seizure free and go into long-term remission of seizures shortly after starting therapy with a single antiepileptic drug (AED monotherapy). Currently in the UK, National Institute for Health and Care Excellence (NICE) guidelines for adults and children recommend carbamazepine or lamotrigine as the first treatment options to try for individuals with newly diagnosed focal seizures and sodium valproate for individuals with newly diagnosed generalised tonic‐clonic seizures. However, a range of other AEDs are available.

The choice of the first antiepileptic drug for an individual with newly diagnosed seizures is of great importance and should be made taking into account high‐quality evidence of how effective the drugs are at controlling seizures and whether they are associated with side effects. It is also important that drugs appropriate for different seizure types are compared to each other.

Our previous Cochrane review results supported current NICE guidelines, and also demonstrated that newer AED levetiracetam may be a good alternative treatment. New studies comparing AEDs have been published since our previous review was published in 2017. Therefore we will update our previous review with new evidence. NICE guidelines within the UK are in the process of being updated. The results of our updated review will provide up to date and high quality evidence to directly inform these guidelines within the UK for future individuals with newly diagnosed seizures and will provide wider evidence to inform a choice for decision makers, clinicians or individuals with epilepsy between appropriate drugs available for the initial treatment of epilepsy.

Statistical Analysis Plan:

Pairwise and network meta-analysis

All time-to-event outcomes will be summarised using the hazard ratio (HR) and 95% Confidence Interval (CI) as the measure of treatment effect.

For all time-to-event outcomes, the relationship between the time-to-event and treatment effect of the anti-epileptic drugs will be investigated. Cox proportional hazards regression models will be used stratified by trial to preserve the within‐trial randomisation, to the entire individual participant dataset, resulting in a dataset for NMA with trial‐specific estimates of treatment effect (log HR), the associated variance of the treatment effect and covariances where applicable (i.e. correlation between treatment effects for trials with more than two treatment arms).

We will calculate direct pairwise treatment effect estimates (where possible) and pool trial‐specific log hazard ratios from the Cox proportional hazards model as described above in pairwise meta-analysis.

NMA will be performed in a frequentist, multivariate framework assuming equal heterogeneity for all comparisons (i.e. a between‐study covariance structure (variance‐covariance matrix) proportional to unknown parameter tau- squared). It is necessary to make an assumption regarding the between‐study covariance structure for a network without pairwise comparisons between all treatments of interest. NMA provides treatment effect estimates combining direct and indirect evidence.

Treatment covariate interaction

There are strong clinical beliefs that certain AEDs are more effective in certain seizure types than others, for example carbamazepine is more effective in focal onset seizures and sodium valproate is more effective in generalised onset seizures, suggesting that there is a treatment‐by‐seizure type (focal or generalised) interaction.

To account for this, we will conduct all analyses separately by epilepsy type (focal onset or generalised onset) according to the classification of main seizure type at baseline and performed all NMA with a treatment‐by‐epilepsy‐type interaction. We classified focal seizures (simple or complex) and focal secondarily generalised seizures as focal epilepsy. We classified primarily generalised seizures as generalised epilepsy.

Where possible, we will also explore other participant covariates such as age, sex, seizure frequency before randomisation (time since first ever seizure and/or number of seizures before randomisation) and aetiology of seizures (if known according to pre‐treatment investigations such as EEG, CT and/or MRI scan).

Investigation of heterogeneity

In the first instance, we will use a fixed-effect model for all pairwise and NMA as we anticipate that our specific inclusion criteria will result in eligible studies of a similar design and populations and our use of IPD will standardise definitions of outcomes.

For each pairwise comparison and for NMA, we will assess the presence of heterogeneity statistically using the I-squared statistic with the following interpretation:

  • 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.

For pairwise meta-analysis, we will also assess the presence of heterogeneity by visually inspecting forest plots, particularly in terms of the magnitude and direction of effects. If substantial or considerable heterogeneity (i.e. I-squared of 50% or over) is found to be present within pairwise meta-analysis, which we are not able to explain by differences in characteristics of the trials and participants, we planned to perform NMA with a random-effects model.

For NMA, we will also present an estimate of tau-squared (an estimate of the between-study variance in random-effects meta-analysis) for each analysis and take into account both tau-squared and I-squared when interpreting the presence of any important heterogeneity in the treatment network.

Investigation of consistency in network meta-analysis

A key assumption made in NMA is that treatment effect is ‘exchangeable’ across all included trials; in other words, the indirect comparison made between two treatments is a feasible comparison to make (known as the transitivity assumption) and that the indirect evidence is consistent with the direct evidence where a comparison exists (known as the consistency assumption).

Transitivity requires that all treatments are “jointly randomisable”; in other words, all 12 AEDs could feasibly be randomised in the same trial and those that are not treatment arms in any given trial are “missing at random.” This assumption cannot be formally tested statistically; transitivity must be judged by careful consideration of trial settings and characteristics, treatment mechanisms and participant demographics to investigate if any differences would be expected to modify relative treatment effects. Given that all of the 12 drugs within this network are licenced as monotherapy treatments for individuals with newly diagnosed focal onset seizures or generalised onset tonic‐clonic seizures (with or without other generalised seizure types) and have all been used within trials of similar designs, we have no concerns over this transitivity assumption in this network.

The consistency assumption can be evaluated statistically comparing the difference between the direct treatment effect estimate and the indirect estimate for each loop of evidence. Given the complexity of the network model to be fitted (with treatment-by-epilepsy type interaction) and the number of multi‐arm trials that will be included in analysis, we will perform node splitting to formally estimate differences between direct and indirect evidence for each comparison. In order to examine any clinical inconsistency (i.e. important differences in numerical results between direct, indirect and network results), we will present HR estimates for direct evidence, indirect evidence (from the node splitting model) and direct plus indirect evidence from the network models for each pairwise comparison via forest plots and discuss the potential origins and implications of any apparent inconsistency. Secondly, we will also fit a ‘design‐by‐treatment’ inconsistency model; this method evaluates both loop and design inconsistencies, particularly within multi‐arm trials

Sensitivity analysis

Where any minor inconsistences or missing data are present in IPD provided, we will include the data in analyses and pursue sensitivity analyses to test the robustness of results included in these data.

Where possible, if IPD are not available for analysis or if we are not able to download IPD provided within remote analysis environments, and incorporate these estimates into NMA and compare the results of these sensitivity analyses to those of the primary analysis.

Presentation of results

For clinical interest and relevance, we have presented HR estimates from the network model (direct and indirect evidence combined) for each AED in the network compared to the current recommended first‐line treatments (carbamazepine or lamotrigine for focal onset seizures and sodium valproate for generalised onset seizures) and for all comparisons by epilepsy type in the main results of this review via forest plots.

Requested Studies:

A Multi-Center, Open-label, Randomized Study to Evaluate the Long Term Effectiveness of Levetiracetam as Monotherapy in Comparison With Oxcarbazepine in Subjects With Newly or Recently Diagnosed Partial Epilepsy
Sponsor: Korea UCB Co., Ltd.
Study ID: NCT01498822
Sponsor ID: N01367

A Multicenter, Double-blind, Double-dummy, Randomized, Positive- Controlled Study Comparing the Efficacy and Safety of Lacosamide (200 to 600 mg/Day) to Controlled Release Carbamazepine (400 to 1200 mg/Day), Used as Monotherapy in Subjects (≥ 16 Years) Newly or Recently Diagnosed With Epilepsy and Experiencing Partial-onset or Generalized Tonic-clonic Seizures.
Sponsor: UCB
Study ID: NCT01243177
Sponsor ID: SP0993

(Note: Below study was denied due to being subject to legal, contractual or consent provisions that prevent further sharing of clinical data)

An Open-label, Randomized, Parallel-group, Active-controlled Study Comparing the Efficacy and Safety of Levetiracetam to Carbamazepine Used as Monotherapy in Subjects Newly or Recently Diagnosed as Epilepsy and Partial-onset Seizures
Sponsor: UCB Pharma SA
Study ID: NCT01954121
Sponsor ID: N01364

Public Disclosure:

Nevitt SJ, Sudell M, Cividini S, Marson AG, Tudur Smith C. Antiepileptic drug monotherapy for epilepsy: a network meta‐analysis of individual participant data. Cochrane Database of Systematic Reviews 2022, Issue 4. Art. No.: CD011412. doi: 10.1002/14651858.CD011412.pub4.