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Objectives A breakthrough seizure is one occurring after at least 12 months seizure freedom while on treatment. The Driver and Vehicle Licensing Agency DVLA allows an individual to return to driving once they have been seizure free for 12 months following a breakthrough seizure. This analysis considers whether the prescribed 1 year off driving following a breakthrough seizure is sufficient for this and stratifies risk according to clinical characteristics. Design, setting, participants, interventions and main outcome measures The multicentre UK-based Standard versus New Antiepileptic Drugs SANAD study was a randomised controlled trial assessing standard and new antiepileptic drugs for patients with newly diagnosed epilepsy. For participants aged at least 16 with a breakthrough seizure, data have been analysed to estimate the annual seizure recurrence risk following a period of 6, 9 and 12 months seizure freedom. Regression modelling was used to investigate how antiepileptic drug treatment and a number of clinical factors influence the risk of seizure recurrence. Conclusions This reanalysis of SANAD provides estimates of seizure recurrence risks following a breakthrough seizure that will inform policy and guidance about regaining an ordinary driving licence. Further guidance is needed as to how such data should be used. You will be able to get a quick price and instant permission to reuse the content in many different ways. This reanalysis of Standard versus New Antiepileptic Drugs SANAD provides estimates of seizure recurrence risks following a breakthrough seizure that will inform policy and guidance about regaining an ordinary driving licence. The SANAD data largely reflect patients with newly diagnosed epilepsy so we have been unable to explore longer-term patterns of seizures. Patients with epilepsy may elect not to report breakthrough seizures to their clinicians or the relevant driving authority which may lead to an underestimation of risk. A breakthrough seizure is defined as the first seizure after a minimum of 12 months seizure freedom while on treatment. This is summarised in guidance available on their website. This minimum level of risk is supported by other European Union member states 3 and has been adopted in the criteria determining minimum driving standards that are being harmonised across the European Union. In the USA, each individual state has its own legislation for driving with epilepsy and seizures. There are currently few published studies in which seizure recurrence risks are estimated and factors that modify risk investigated. Existing publications 5—8 have focused on recurrence immediately following a first seizure or recurrence after treatment withdrawal. Arm A recruited patients who were randomised to treatment with carbamazepine, gabapentin, lamotrigine, topiramate or oxcarbazepine. Arm B recruited patients who were randomised to lamotrigine, topiramate or valproate. Patients were followed up to the end of the study whether they remained on their randomised treatment or not, according to the intention-to-treat principle. Outcomes assessed included time to month remission, time to treatment failure and time to first seizure. Here, data from a subset of participants achieving month remission while on treatment followed by a breakthrough seizure have been analysed to estimate the subsequent risk of seizure recurrence. Modelling has been used to investigate how a number of clinical factors influence the outcome. Patients were recruited into arm A if the recruiting clinician considered carbamazepine to be the optimal standard treatment option. Between 1 December and 1 June , patients were allocated in a ratio of to carbamazepine, gabapentin, lamotrigine and topiramate. From 1 June to 31 August , an oxcarbazepine group was added to the trial and patients were randomly allocated in a ratio of to carbamazepine, gabapentin, lamotrigine, oxcarbazepine or topiramate. Patients were eligible for inclusion in arm B if the recruiting clinician regarded valproate the standard treatment option. Participants were randomly allocated in a ratio to valproate, lamotrigine or topiramate between 12 January and 31 August The two primary outcomes in SANAD were time to treatment failure from randomisation and time to the first period of 12 months of remission from seizures following randomisation. In this paper, the arm A and arm B data sets have been combined in order to undertake prognostic modelling stratifying by arm. In the original publications trial arms were analysed and reported separately as the primary purpose was to compare the effectiveness of new antiepileptic drugs with the standard treatments. Here the purpose is different, the aim being to assess the risk of a seizure recurrence following a breakthrough seizure, irrespective of the specific drug that the patient was on at randomisation, or the subsequent choice of treatment. Sixteen years of age was chosen as the lower cut-off as by the age 17, after 12 months of follow-up, they would be eligible for a provisional group 1 licence in the UK. Other European Union countries have a minimum driving age of 18 years 11 with some exceptions such as Hungary 12 and Southern Ireland, 13 where the limit is 17 years. In other words, patients with any decrease in dose either with an intention to withdraw, or not, were excluded as their seizure was likely to be due to antiepileptic drug withdrawal, which is handled differently in the legislation, and analyses informing legislation following antiepileptic drug withdrawal have been published. The outcome of interest is the probability of a seizure recurrence in the next 12 months given that the participants have been seizure free from the breakthrough seizure to the time point in question. Risks of recurrence in the next 12 months for other time points were calculated similarly using the Cox model. Variables associated with a higher risk of seizure recurrence were determined univariably and after adjusting for multiple variables using log-rank tests and Cox proportional hazards modelling methods. Continuous variables were investigated using log and fractional polynomial transformations. The predictive accuracy of the models was assessed using the c-statistic. Our list of potential prognostic factors included gender, febrile seizure history, first-degree relative with epilepsy, neurological insult, seizure type, epilepsy type, EEG result, CT or MRI result, total number of tonic—clonic seizures recorded prior to breakthrough seizure, age at breakthrough seizure, number of treatments required to achieve month remission prior to breakthrough seizure either monotherapy or polytherapy , time to achieve month remission prior to breakthrough seizure and breakthrough seizure treatment decision no change to treatment plan, increase dosage or decrease dosage for any reason. Patients were classified as having neurological insult if they had learning disabilities or neurological deficit, while EEG was classified as normal, not clinically indicated, non-specific abnormality or epileptiform abnormality focal or generalised spikes or spike and slow wave activity. Seizure types were classified according to the International League Against Epilepsy seizure classification. Figure 1 illustrates patient disposition of the patients recruited into both arms A and B of SANAD, and identifies patients relevant to this analysis; for the purposes of this analysis, data from both trial arms have been combined. Table 1 summarises the patient demographics for the patients under analysis. Of these patients, experienced at least one further seizure after breakthrough. Patients in arm A were followed up for a median of 1. In total, there were Figure 2 illustrates the risk of seizure recurrence after a breakthrough seizure. The median time to a further seizure following a breakthrough was 76 days IQR 57— days. The probability of a seizure by 12 months was Table 2 shows unadjusted month seizure recurrence risks at various time points after the breakthrough seizure. Kaplan-Meier curve for time to next seizure following a breakthrough seizure. Results for univariable and multivariable modelling of time to seizure recurrence are presented in table 3. In the univariable model, number of drugs required to achieve initial month remission and time to achieve a first month remission prior to breakthrough seizure were associated with seizure recurrence risk—patients requiring polytherapy to achieve remission were more likely to have a recurrence than those requiring monotherapy. Breakthrough seizure treatment decision was also associated with the outcome; patients having an increase in dose after their breakthrough seizure were more likely to have a recurrence than those not changing their treatment, which may be counterintuitive, but indicates clinicians are able to identify those at higher recurrence risk. The final multivariable model included number of drugs required to achieve initial remission, time to achieve initial month remission and breakthrough seizure treatment decision. There was no evidence to suggest that the proportional hazards assumption, underlying the Cox model, was invalid. The c-statistic for the model was 0. Breakthrough seizure treatment decision, although significantly associated with the outcome, should not be considered as a modifiable variable as clinicians will find it very difficult to use this information to inform treatment decisions for future patients. Therefore, the model was refitted excluding this covariate, and the resulting parsimonious model included number of drugs attempted to achieve initial month remission and time taken to achieve initial month remission. The direction of the effects remained unchanged table 3. The risk of recurrence at 12 months for patients with particular characteristics was estimated from the parsimonious multivariable regression model. Results can be seen in table 4. Risk of seizure recurrence in next 12 months estimated from multivariable model at specific seizure-free periods. Covariates significantly associated with the outcome were time taken to achieve an initial month remission, number of drugs required to achieve that remission and breakthrough seizure treatment decision. As expected, those patients who achieve a period of month remission quickly, and those patients who require only one drug to achieve remission, had a lower chance of a seizure recurrence. The decision to not change antiepileptic drug dose following a breakthrough seizure was associated with a lower risk of a recurrence than the decision to increase dosage. This result is potentially counterintuitive as one might expect an increase in dose to reduce seizure risk. However, it is likely that clinicians are able to identify patients at higher risk of recurrence and recommend treatment changes to reduce that risk, although additional relevant clinical factors have not been identified by our model, and this requires further investigation. It is important to highlight that in most cases the decision to increase dose was taken in between neurology clinic appointments at which follow-up data were collected, presumably at the advice of the general practitioner or neurologist. As a result, accurate dates of dose increase have not been recorded and it is possible that a subgroup of patients had further seizures following the initial breakthrough seizure, prompting the clinician to increase the antiepileptic drug dose. When breakthrough seizure treatment decision was removed from the list of candidate variables to reflect the fact that clinicians will find it very difficult to use this information to inform treatment decisions for future patients, the parsimonious model included covariates for number of drugs required to achieve an initial month remission and time taken to achieve initial month remission. This suggests that the current month time off driving is generally appropriate. Few publications have considered risk of a breakthrough seizure and tend to be focused on patients in the low-income, middle-income countries. Neither study considered outcomes following the breakthrough study. We are unaware of any studies looking at outcome after a breakthrough seizure. In particular, we have been unable to identify any prognostic models considering risk of seizure recurrence following a breakthrough seizure for patients of driving age in developed countries. Another analysis of SANAD for patients of driving age has considered risk of a second treatment failure after a first. Although the outcome under consideration in this article is breakthrough seizure after remission rather than first-ever seizure, the time off driving is fairly consistent across the papers. However, only a small subset of these patients was relevant to address the question of risk of a seizure recurrence following a breakthrough seizure for patients of driving age. The requirement of patients to achieve initial remission of at least 12 months and then have a breakthrough seizure to be included in this analysis also meant that the follow-up of patients after the breakthrough seizure was relatively short. This means that some CIs associated with the risk estimates are quite wide. We have therefore been unable to explore longer-term patterns. For example, if patients go into and out of remission then their seizure recurrence risks might change compared with these estimates. The subset of patients considered for this analysis may also have limited power to detect some prognostic effects as significant. Other important factors may exist which have not been analysed or collected. The SANAD study also indicated that lamotrigine was superior to carbamazepine in terms of seizure control for partial onset seizures. The multivariable model for risk of seizure recurrence included a continuous covariate—time to achieve initial month remission. Therefore, to estimate the risk of recurrence over the next 12 months for combinations of risk factors including this covariate, the variable had to be categorised which may not be the most efficient approach. Although these covariates may have changed by a breakthrough seizure, it is likely that any change occurred in only a small number of patients. EEG was also only recorded at baseline, and it is possible that EEG on treatment would be prognostic, although given the unpredictable nature of breakthrough seizures, it would not be feasible to undertake an EEG in order to inform risk. There is evidence to suggest that patients with epilepsy may elect not to report breakthrough seizures to their clinicians or the relevant driving authority. Increased patient counselling regarding the risks involved with driving, the need for driving regulations and the importance of compliance with these rules may only have a limited impact as the implications for patients losing their driving licence are potentially serious such as job losses and resulting lack of independence. The model developed here should ideally be validated in other similar data sets. However, no other similar data sets exist. The best match is a set of individual participant data we have collected. Therefore, alternative data sources are required. Twelve months appears to be an appropriate time off driving for patients of driving age who have experienced a period of at least 12 months initial seizure freedom followed by a breakthrough seizure. As discussed in depth in Bonnett, 7 the legislators and DVLA need to decide whether to base time off driving on unadjusted estimates only or whether they should consider estimates adjusted for important clinical factors. Although our unadjusted results suggest that 12 months off driving is sufficient time off driving, risk estimates differ substantially among groups. Evidence is inconclusive regarding whether drivers with epilepsy have higher rates of motor vehicle accidents than those without epilepsy. However, there is evidence that accidents are 26 times more likely to occur with drivers with other medical conditions compared with drivers with epilepsy. In fact, in practice time to achieve remission may be the only factor that could be incorporated into such an assessment as there is potential for manipulation of drugs in terms of number and doses to meet driving objectives. Contributors LJB undertook all analyses presented in this manuscript. All authors drafted and redrafted the manuscript. AGM is the guarantor for this work. Disclaimer The views expressed in this publication are those of the authors and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health. Provenance and peer review Not commissioned; externally peer reviewed. Statistical code is available on request from the corresponding author. Skip to main content. Log In More Log in via Institution. Log in via OpenAthens. Log in using your username and password For personal accounts OR managers of institutional accounts. Forgot your log in details? Register a new account? Forgot your user name or password? Search for this keyword. Advanced search. Latest content Archive For authors About Browse by collection. Log in via Institution. You are here Home Archive Volume 7, Issue 7 Risk of a seizure recurrence after a breakthrough seizure and the implications for driving: further analysis of the standard versus new antiepileptic drugs SANAD randomised controlled trial. Email alerts. Article Text. Article menu. Risk of a seizure recurrence after a breakthrough seizure and the implications for driving: further analysis of the standard versus new antiepileptic drugs SANAD randomised controlled trial. Abstract Objectives A breakthrough seizure is one occurring after at least 12 months seizure freedom while on treatment. Statistics from Altmetric. Introduction A breakthrough seizure is defined as the first seizure after a minimum of 12 months seizure freedom while on treatment. Statistical analysis The outcome of interest is the probability of a seizure recurrence in the next 12 months given that the participants have been seizure free from the breakthrough seizure to the time point in question. Results Figure 1 illustrates patient disposition of the patients recruited into both arms A and B of SANAD, and identifies patients relevant to this analysis; for the purposes of this analysis, data from both trial arms have been combined. Figure 1 Standard versus New Antiepileptic Drugs trial profile. View this table: View inline View popup. Table 1 Patient demographics. Figure 2 Kaplan-Meier curve for time to next seizure following a breakthrough seizure. Table 3 Effect estimates from univariable and multivariable models. Table 4 Risk of seizure recurrence in next 12 months estimated from multivariable model at specific seizure-free periods. Conclusions Twelve months appears to be an appropriate time off driving for patients of driving age who have experienced a period of at least 12 months initial seizure freedom followed by a breakthrough seizure. References 1. Driver and Vehicle Licensing Agency. Assessing fitness to drive - a guide for medical professionals. Driving and Motoring Group , ed. Epilepsy and driving in Belgium: proposals and justification. Acta Neurol Belg ; : 68 — Individual state driving restrictions for people with epilepsy in the US. Neurology ; 57 : — 5. OpenUrl CrossRef. 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Lancet ; : — The SANAD study of effectiveness of valproate, lamotrigine, or topiramate for generalised and unclassifiable epilepsy: an unblinded randomised controlled trial. Hungarian Driving Licences. Citizens Information. Categories of motor vehicles and minimum age of drivers. Cox DR , Oakes D. Analysis of Survival Data. London : Chapman and Hall Ltd , The conditional probability of survival of patients with primary malignant brain tumors: surveillance, epidemiology, and end results SEER data. Cancer ; 85 : — The conditional probabilities of survival in patients with anaplastic astrocytoma or glioblastoma multiforme. Surg Neurol ; 60 : — 6. Akaike H. A new look at the statistical model identification. Collett D. Modelling Survival Data in Medical Research. Boca Raton, Fla. The use of fractional polynomials to model continuous risk variables in epidemiology. Int J Epidemiol ; 28 : — Royston P , Altman DG. Regression using fractional polynomials of continuous covariates - Parsimonious Parametric modeling. Royston P , Sauerbrei W. Multivariable Model-Building - A pragmatic approach to regression analysis based on fractional polynomials for modelling continuous variables: wiley , Building multivariable regression models with continuous covariates in clinical epidemiology--with an emphasis on fractional polynomials. Methods Inf Med ; 44 : — Stone CJ. Comment: generalized additive models. Statistical Science ; 1 : 3. Schoenfeld D. Partial residuals for the proportional hazards regression model. Biometrika ; 69 : — Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med ; 15 : — Arch Neurol ; 49 : — 8. Hosmer DW , Lemeshow S. Applied Logistic regression. Second ed. Regression modelling strategies for improved prognostic prediction. Stat Med ; 3 : — Assessment of precipitating factors of breakthrough seizures in epileptic patients. The frequency and precipitating factors for breakthrough seizures among patients with epilepsy in Uganda. BMC Neurol ; 13 : 1 — 7. Treatment outcome after failure of a first antiepileptic drug. Neurology ; 83 : — When is it safe to return to driving following first-ever seizure? J Neurol Neurosurg Psychiatry ; 86 : 60 — 4. Dangers of using 'optimal' cutpoints in the evaluation of prognostic factors. J Natl Cancer Inst ; 86 : — Epilepsy, driving laws, and patient disclosure to physicians. Epilepsia ; 33 : — OpenUrl PubMed. Multiple treatment comparisons in epilepsy monotherapy trials. Trials ; 8 : Do drivers with epilepsy have higher rates of motor vehicle accidents than those without epilepsy? Epilepsy Behav ; 47 : — 4. Footnotes Contributors LJB undertook all analyses presented in this manuscript. Competing interests None declared. Read the full text or download the PDF:. Log in.

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