Topiramate versus carbamazepine monotherapy for epilepsy: an individual participant data review.

Epilepsy is a common neurological condition in which abnormal electrical discharges from the brain cause recurrent unprovoked seizures. 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 shortly after starting drug therapy, the majority of which may be able to achieve remission with a single antiepileptic drug (AED).The correct choice of first-line antiepileptic therapy for individuals with newly diagnosed seizures is of great importance. It is important that the choice of AED for an individual is based on the highest-quality evidence available regarding the potential benefits and harms of various treatments. It is also important to compare the efficacy and tolerability of AEDs appropriate to given seizure types.Topiramate and carbamazepine are commonly used AEDs. Performing a synthesis of the evidence from existing trials will increase the precision of results of outcomes relating to efficacy and tolerability, and may help inform a choice between the two drugs.To assess the effects of topiramate monotherapy versus carbamazepine monotherapy for epilepsy in people with partial-onset seizures (simple or complex partial and secondarily generalised) or generalised onset tonic-clonic seizures (with or without other generalised seizure types).We searched the Cochrane Epilepsy Group Specialized Register (14 April 2016), the Cochrane Central Register of Controlled Trials (CENTRAL) (14 April 2016) and MEDLINE (Ovid, 1946 to 14 April 2016). We imposed no language restrictions. We also contacted pharmaceutical companies and trial investigators.Randomised controlled trials in children or adults with partial-onset seizures or generalised-onset tonic-clonic seizures with or without other generalised seizure types with a comparison of monotherapy with either topiramate or carbamazepine.This was an individual participant data (IPD) review. Our primary outcome was 'time to withdrawal of allocated treatment', and our secondary outcomes were 'time to first seizure post randomisation', 'time to 6-month remission, 'time to 12-month remission' and incidence of adverse events. We used Cox proportional hazards regression models to obtain trial-specific estimates of hazard ratios (HRs) with 95% confidence intervals (CIs), and used the generic inverse variance method to obtain the overall pooled HRs and 95% CIs.IPD were available for 1151 of 1239 eligible individuals from two of three eligible studies (93% of the potential data). A small proportion of individuals recruited into these trials had 'unclassified seizures;' for analysis purposes, these individuals are grouped with those with generalised onset seizures. For remission outcomes, a HR < 1 indicated an advantage for carbamazepine, and for first seizure and withdrawal outcomes, a HR < 1 indicated an advantage for topiramate.The main overall results, given as pooled HR adjusted for seizure type (95% CI) were: for time to withdrawal of allocated treatment 1.16 (0.98 to 1.38); time to first seizure 1.11 (0.96 to 1.29); and time to 6-month remission 0.88 (0.76 to 1.01). There were no statistically significant differences between the drugs. A statistically significant advantage for carbamazepine was shown for time to 12-month remission: 0.84 (0.71 to 1.00).The results of this review are applicable mainly to individuals with partial-onset seizures; 85% of included individuals experienced seizures of this type at baseline. For individuals with partial-onset seizures, a statistically significant advantage for carbamazepine was shown for time to withdrawal of allocated treatment (HR 1.20, 95% CI 1.00 to 1.45) and time to 12-month remission (HR 0.84, 95% CI 0.71 to 1.00). No statistically significant differences were apparent between the drugs for other outcomes and for the limited number of individuals with generalised-onset tonic-clonic seizures with or without other generalised seizure types or unclassified seizures.The most commonly reported adverse events with both drugs were drowsiness or fatigue, 'pins and needles' (tingling sensation), headache, gastrointestinal disturbance and anxiety or depression The rate of adverse events was similar across the two drugs.We judged the methodological quality of the included trials generally to be good; however, there was some evidence that the open-label design of the larger of the two trials may have influenced the withdrawal rate from the trial. Hence, we judged the evidence for the primary outcome of treatment withdrawal to be moderate for individuals with partial-onset seizures and low for individuals with generalised-onset seizures. For efficacy outcomes (first seizure, remission), we judged the evidence from this review to be high for individuals with partial-onset seizures and moderate for individuals with generalised-onset or unclassified seizures.For individuals with partial-onset seizures, there is evidence that carbamazepine is less likely to be withdrawn and that 12-month remission will be achieved earlier than with topiramate. No differences were found between the drugs in terms of the outcomes measured in the review for individuals with generalised tonic-clonic seizures with or without other seizure types or unclassified epilepsy; however, we encourage caution in the interpretation of these results due to the small numbers of participants with these seizure types.We recommend that future trials should be designed to the highest quality possible and take into consideration masking, choice of population, classification of seizure type, duration of follow-up, choice of outcomes and analysis, and presentation of results

Review and Comparison of Computational Approaches for Joint Longitudinal and Time‐to‐Event Models

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151312/1/insr12322.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151312/2/insr12322_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151312/3/Supplement_ReviewComputationalJointModels_final.pd

Individual patient data meta-analyses compared with meta-analyses based on aggregate data. (Review)

Background Meta‐analyses based on individual participant data (IPD‐MAs) allow more powerful and uniformly consistent analyses as well as better characterisation of subgroups and outcomes, compared to those which are based on aggregate data (AD‐MAs) extracted from published trial reports. However, IPD‐MAs are a larger undertaking requiring greater resources than AD‐MAs. Researchers have compared results from IPD‐MA against results obtained from AD‐MA and reported conflicting findings. We present a methodology review to summarise this empirical evidence . Objectives To review systematically empirical comparisons of meta‐analyses of randomised trials based on IPD with those based on AD extracted from published reports, to evaluate the level of agreement between IPD‐MA and AD‐MA and whether agreement is affected by differences in type of effect measure, trials and participants included within the IPD‐MA and AD‐MA, and whether analyses were undertaken to explore the main effect of treatment or a treatment effect modifier. Search methods An electronic search of the Cochrane Library (includes Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effectiveness, CENTRAL, Cochrane Methodology Register, HTA database, NHS Economic Evaluations Database), MEDLINE, and Embase was undertaken up to 7 January 2016. Potentially relevant articles that were known to any of the review authors and reference lists of retrieved articles were also checked. Selection criteria Studies reporting an empirical comparison of the results of meta‐analyses of randomised trials using IPD with those using AD. Studies were included if sufficient numerical data, comparing IPD‐MA and AD‐MA, were available in their reports. Data collection and analysis Two review authors screened the title and abstract of identified studies with full‐text publications retrieved for those identified as eligible or potentially eligible. A ‘quality’ assessment was done and data were extracted independently by two review authors with disagreements resolved by involving a third author. Data were summarised descriptively for comparisons where an estimate of effect measure and corresponding precision have been provided both for IPD‐MA and for AD‐MA in the study report. Comparisons have been classified according to whether identical effect measures, identical trials and patients had been used in the IPD‐MA and the AD‐MA, and whether the analyses were undertaken to explore the main effect of treatment, or to explore a potential treatment effect modifier. Effect measures were transformed to a standardised scale (z scores) and scatter plots generated to allow visual comparisons. For each comparison, we compared the statistical significance (at the 5% two‐sided level) of an IPD‐MA compared to the corresponding AD‐MA and calculated the number of discrepancies. We examined discrepancies by type of analysis (main effect or modifier) and according to whether identical trials, patients and effect measures had been used by the IPD‐MA and AD‐MA. We calculated the average of differences between IPD‐MA and AD‐MA (z scores, ratio effect estimates and standard errors (of ratio effects)) and 95% limits of agreement. Main results From the 9330 reports found by our searches, 39 studies were eligible for this review with effect estimate and measure of precision extracted for 190 comparisons of IPD‐MA and AD‐MA. We classified the quality of studies as ‘no important flaws’ (29 (74%) studies) or ‘possibly important flaws’ (10 (26%) studies). A median of 4 (interquartile range (IQR): 2 to 6) comparisons were made per study, with 6 (IQR 4 to 11) trials and 1225 (542 to 2641) participants in IPD‐MAs and 7 (4 to 11) and 1225 (705 to 2541) for the AD‐MAs. One hundred and forty‐four (76%) comparisons were made on the main treatment effect meta‐analysis and 46 (24%) made using results from analyses to explore treatment effect modifiers. There is agreement in statistical significance between the IPD‐MA and AD‐MA for 152 (80%) comparisons, 23 of which disagreed in direction of effect. There is disagreement in statistical significance for 38 (20%) comparisons with an excess proportion of IPD‐MA detecting a statistically significant result that was not confirmed with AD‐MA (28 (15%)), compared with 10 (5%) comparisons with a statistically significant AD‐MA that was not confirmed by IPD‐MA. This pattern of disagreement is consistent for the 144 main effect analyses but not for the 46 comparisons of treatment effect modifier analyses. Conclusions from some IPD‐MA and AD‐MA differed even when based on identical trials, participants (but not necessarily identical follow‐up) and treatment effect measures. The average difference between IPD‐MA and AD‐MA in z scores, ratio effect estimates and standard errors is small but limits of agreement are wide and include important differences in both directions. Discrepancies between IPD‐MA and AD‐MA do not appear to increase as the differences between trials and participants increase. Authors' conclusions IPD offers the potential to explore additional, more thorough, and potentially more appropriate analyses compared to those possible with AD. But in many cases, similar results and conclusions can be drawn from IPD‐MA and AD‐MA. Therefore, before embarking on a resource‐intensive IPD‐MA, an AD‐MA should initially be explored and researchers should carefully consider the potential added benefits of IPD

Joint models for longitudinal and time-to-event data: a review of reporting quality with a view to meta-analysis

Background Joint models for longitudinal and time-to-event data are commonly used to simultaneously analyse correlated data in single study cases. Synthesis of evidence from multiple studies using meta-analysis is a natural next step but its feasibility depends heavily on the standard of reporting of joint models in the medical literature. During this review we aim to assess the current standard of reporting of joint models applied in the literature, and to determine whether current reporting standards would allow or hinder future aggregate data meta-analyses of model results. Methods We undertook a literature review of non-methodological studies that involved joint modelling of longitudinal and time-to-event medical data. Study characteristics were extracted and an assessment of whether separate meta-analyses for longitudinal, time-to-event and association parameters were possible was made. Results The 65 studies identified used a wide range of joint modelling methods in a selection of software. Identified studies concerned a variety of disease areas. The majority of studies reported adequate information to conduct a meta-analysis (67.7% for longitudinal parameter aggregate data meta-analysis, 69.2% for time-to-event parameter aggregate data meta-analysis, 76.9% for association parameter aggregate data meta-analysis). In some cases model structure was difficult to ascertain from the published reports. Conclusions Whilst extraction of sufficient information to permit meta-analyses was possible in a majority of cases, the standard of reporting of joint models should be maintained and improved. Recommendations for future practice include clear statement of model structure, of values of estimated parameters, of software used and of statistical methods applied