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The influence of demographics and comorbidity on persistence with anti-seizure medication

Open AccessPublished:March 30, 2022DOI:https://doi.org/10.1016/j.seizure.2022.03.019

      Highlights

      • Persistence to anti-seizure medication affected by a range of factors.
      • Younger and more deprived patients more likely to discontinue medication.
      • Patients with higher rates of comorbidity or polypharmacy more likely to persist.
      • Newer medications associated with higher rates of persistence compared to older.

      Abstract

      Purpose

      To examine the rate of persistence with anti-seizure medications (ASMs) in a cohort of patients with epilepsy, and to investigate the impact of a range of clinical and demographic factors on persistence

      Methods

      Patients receiving ASMs for epilepsy were identified from linked, routinely collected data within the NHS Greater Glasgow and Clyde health board area between January 2011 and August 2019. Persistence with individual ASMs at 365-days after initiation was assessed using a 90-day allowable gap between individual prescriptions. Univariate logistic regression was used to estimate the association between 1-year persistence with ASM and demographic characteristics, comorbidities, and medication characteristics.

      Results

      In total, 6,449 patients with epilepsy were identified – 1,631 were new users of ASMs at baseline and 4,818 had been prescribed at least one ASM prior to baseline. Persistence with individual ASMs ranged 11.8% to 78.6%. Persistence was significantly lower in younger patients and patients who had previously been non-persistent to ASMs. Persistence was higher amongst those with cardiac comorbidities, previous stroke, or higher overall comorbidity, as well as those prescribed newer ASMs.

      Conclusion

      Persistence varied widely. Demographic factors, previous non-persistence and overall number of comorbidities were more important determinants of persistence to anti-seizure medications than specific individual comorbidities. Interventions to improve persistence should be targeted at younger patients from more deprived backgrounds and those who have previously been non-persistent with ASMs.

      Keywords

      1. Introduction

      Epilepsy is among the most common neurological disorders, affecting an estimated 50 million people worldwide [
      World Health Organisation
      Epilepsy - fact sheet.
      ]. The National Institute for Health and Care Excellence (NICE) estimated the prevalence of active epilepsy (i.e. patients with continuing seizures or continued need for treatment) in the UK to be 500–1000 cases per 100,000 population, and the incidence of newly diagnosed epilepsy to be 50 per 100,000 population per year [
      National Institute for Health and Care Excellence
      Epilepsies: diagnosis and management.
      ].
      Epilepsy is most frequently managed through the use of anti-seizure medications (ASMs); the specific treatment plan typically taking into account the patient's seizure type, syndrome, comorbidities, and concomitant medications. Around two-thirds of patients achieve seizure freedom early in the course of their condition through the use of ASMs [
      National Institute for Health and Care Excellence
      Epilepsies: diagnosis and management.
      ]. Patients not attaining control will require further ongoing modifications under clinical supervision.
      Gaining good seizure control is important, since recurrent seizures are associated with reduced quality of life, reduced employment and education, and higher risk of injury and death [
      • O'Rourke G.
      • O'Brien J.J.
      Identifying the barriers to antiepileptic drug adherence among adults with epilepsy.
      ,
      • Faught E.
      • Duh M.S.
      • Weiner J.R.
      • Guerin A.
      • Cunnington M.C.
      Nonadherence to antiepileptic drugs and increased mortality findings from the RANSOM Study.
      ]. Poor engagement with the therapeutic process is a frequent cause of poor seizure control, and ensuring patients are taking the recommended ASM should be a mainstay of the management of epilepsy [
      • Jin J.
      • Sklar G.E.
      • Min Sen Oh V.
      • Chuen Li S.
      Factors affecting therapeutic compliance: a review from the patient's perspective.
      ]. Identifying when patients are not persistent is difficult and poor persistence will not always be recognised in the clinic. Identifying risk factors associated with poor persistence allows health care professionals to design services to meet the needs of those at highest risk to reduce the risk associated with poorly controlled epilepsy.
      Persistence to a medication can be measured as the length of time between first prescription and the discontinuation of treatment with that medication [
      • Cramer J.A.
      • Roy A.
      • Burrell A.
      • Fairchild C.J.
      • Fuldeore M.J.
      • Ollendorf D.A.
      • et al.
      Medication compliance and persistence: terminology and definitions.
      ]. Patient persistence to ASMs reflects both their efficacy and tolerability. Studies have identified several potential factors associated with ASM persistence and discontinuation. The use of older ASMs such as carbamazepine, valproate and phenytoin has been shown to be associated with shorter persistent time and higher risk of discontinuation compared to newer ASMs such as levetiracetam and lamotrigine [
      • Jacob L.
      • Hamer H.M.
      • Kostev K.
      Persistence with antiepileptic drugs in epilepsy patients treated in neurological practices in Germany.
      ]. Additionally, one study highlighted that persistence was higher where ASMs were taken as monotherapy than as part of polytherapy [
      • Bautista R.E.D.
      • Rundle-Gonzalez V.
      Effects of antiepileptic drug characteristics on medication adherence.
      ].
      People with epilepsy have been shown to have greater levels of comorbidity than the general population [
      • Weatherburn C.J.
      • Heath C.A.
      • Mercer S.W.
      • Guthrie B.
      Physical and mental health comorbidities of epilepsy: population-based cross-sectional analysis of 1.5 million people in Scotland.
      ,
      • Tellez-Zenteno J.F.
      • Patten S.B.
      • Jette N.
      • Williams J.
      • Wiebe S.
      Psychiatric comorbidity in epilepsy: a population-based analysis.
      ], but the influence of comorbidities on persistence to ASMs is not fully elucidated. Understanding the clinical or demographic features associated with non-persistence to ASMs may help improve the therapeutic partnership between people with epilepsy and their clinicians, allowing clinicians to provide a service that meets individual needs.
      By utilising routinely generated health data from a validated regional epilepsy register, we aimed to examine the rates of persistence with different ASMs and to examine the impact of different demographic and clinical factors on persistence. We assessed persistence among those who recently commenced ASM therapy (‘new users’) as well as those who had been on long-term treatment for epilepsy (‘existing users’).

      2. Methods

      2.1 Study population

      Each individual registered with a primary care practitioner in Scotland has a unique ten-digit community health index (CHI) number. This is appended to all health-care encounters within NHS Scotland services and allows linkage of routinely collected data related to the same individual. Patients who attended hospitals in NHS Greater Glasgow and Clyde (NHS GGC) between January 2011 and August 2019 inclusive were identified. Patients were included if they had attended the regional neurology center as an outpatient and/or had an epilepsy-related inpatient hospitalisation or admission to A&E and were dispensed at least 1 prescription for an ASM over the study period. Patients who were younger than 16 years at baseline or had only ever been prescribed gabapentin monotherapy during the study period were excluded. Patients were censored if they died or moved out of the NHS GGC health board area during the study period, identified through National Records Scotland (NRS) death records and data confirming patient registration with an out of health board GP, respectively.

      2.2 Definition of exposure, outcome, and covariates

      The demographic factors of interest were age, sex, and area-based socioeconomic status at baseline. Age was treated as an ordinal variable and Scottish Index of Multiple Deprivation (SIMD) was derived from postcode of residence and converted into general population quintiles.
      ASMs were defined as those compounds appearing in sub-section 04.08.01 of the British National Formulary (BNF). Patients were classified as new users of ASMs if they did not have a dispensed ASM in the year prior to their index date. Existing users were classified as previously non-persistent if they had no ASM prescriptions within the 90 days prior to their index date. Patients were classified as being dispensed ASM monotherapy or combination therapy at baseline based on whether they were dispensed one ASM or two or more ASMs on their index date. The primary outcome of interest in this study was persistence at 365 days after initiation. Persistence to ASMs was inferred if there was a gap between prescriptions of less than 90 days, with rates of persistence determined for each medication and summarised for the whole cohort and for the sub-groups described above. The 90-day allowable gap between prescriptions was chosen based on 30- or 60- day supply of ASMs per prescription being the most common, and to allow for a level of non-adherence. Only patients’ first periods of persistent use for each medication were considered. For patients dispensed at least one additional medication during follow-up, their first additional medication was classified as an add-on therapy if their duration of polytherapy exceeded 90 days, and a switch from their index medication if there was an overlap of less than 90 days or no overlap.
      Comorbidities were identified at baseline using hospitalisation, general practice, and dispensing records during the one-year period before the patient's index date (see Appendix 1 - Definition of morbidities). Comorbidity count was based on the groupings shown in Appendix 2. Polypharmacy count was calculated as the number of individual medications (not including ASM) that the patients received during the one-year lookback period and only included medication where there was at least 90 days between the first and last prescription. The characteristics of each ASM were used as covariates, including generation (three categories based on date of licencing), potential for neuropsychiatric side-effects (defined as yes or no), and mechanism of action (dichotomised into sodium channel blocking or other) (Table A3).

      2.3 Statistical analyses

      Statistical differences between new and existing users were identified using t-tests for continuous variables and chi-2 tests for categorical variables. Univariate logistic regression analysis based on generalised estimating equations (GEE) was used to estimate the association between one-year persistence to ASMs and demographic factors, comorbidities, previous non-persistence to ASM, and medication characteristics. A separate, univariate sub-group analysis of patients prescribed ASMs with neuropsychiatric side effects (Table A3) to determine if there was a significant difference in persistence to these drugs in patients with and without mood disorders at baseline.
      Only patients who were new users of ASMs or previously non-persistent existing users who were starting new periods of treatment after a period of 90 days with no prescriptions were included in this. All analyses were conducted in R 3.5.0 using RStudio v1.1.453.

      3. Results

      Between January 2011 and August 2019, 10,742 people with epilepsy attended NHS GGC outpatient clinics or A&E departments with a clinical code for epilepsy. Of these patients, 6449 received at least one prescription for ASM during the study period. At baseline, 1631 (25.3%) patients were new users of ASM and 4818 (74,7%) had received a prescription for an ASM in the previous 12 months. Of the existing users, 713 (14.8%) were previously non-persistent at baseline, with the remaining 4105 (85.2%) continuing a previous period of persistent use of at least 1 ASM. At baseline, 5055 (78.4%) of the whole cohort were prescribed one ASM, 1058 (16.4%) were prescribed two and 336 (5.2%) were prescribed three or more. The median length of follow-up was 7.37 years.
      There were significantly more female patients who were existing users of ASMs at baseline than were new users, and there were significant differences between the two groups of patients in both age and SIMD. Length of follow-up was significantly longer for existing users than new users.

      3.1 Demographics

      Patient demographics are outlined in Table 1. The mean age at baseline was 52.7 years. More than half (52.6%) of PWE were in the most deprived quintile of the general population.
      Table 1Demographic characteristics of cohort as a whole and patients split into new and existing users of ASMs at baseline.
      All patients (N = 6449)New users (N = 1631)Existing users (N = 4818)p
      GenderFemale297746.2%69242.4%228547.4%<0.001
      Male347253.8%93957.6%253352.6%
      Age (years)16–191862.9%694.2%1172.4%<0.05
      20–296339.8%20512.6%4288.9%
      30–3979612.3%22914.0%56711.8%
      40–49119818.6%27316.7%92519.2%
      50–591.26119.6%26116.0%100020.8%
      60–69107216.6%22713.9%84517.5%
      70–7982512.8%19512.0%63013.1%
      80–894787.4%17210.5%3066.4%
      SIMD1 (most deprived)339052.6%82650.6%256453.2%
      2112217.4%30918.9%81316.9%<0.05
      383412.9%20112.3%63313.1%
      45648.7%16510.1%3998.3%
      55398.4%1308.0%4098.5%

      3.2 Comorbidity

      At baseline, 33.8% of PWE had a least one comorbid chronic condition and thus can be defined as having multimorbidity and 22.6% had at least two comorbidities. Details of additional comorbidities are shown in Table 2.
      Table 2Frequency of comorbidity at baseline for the full cohort and for new and existing ASM users.
      ConditionAll patientsNew usersExisting usersP
      Asthma128920.0%27917.1%101021.0%<0.05
      COPD5148.0%1207.4%3948.2%0.4
      Cancer1933.0%161.0%1182.5%<0.05
      Hypertension154023.9%35922.0%118124.6%0.09
      Coronary heart disease5688.8%1167.1%4529.4%<0.05
      Atrial fibrillation1902.9%895.5%1012.1%<0.001
      Peripheral vascular disease410.6%150.9%260.5%0.12
      Heart failure1402.2%422.6%982.0%0.19
      Stroke80512.5%28017.2%52510.9%<0.001
      Diabetes4366.8%1167.1%3206.7%0.44
      Chronic kidney disease881.4%593.6%290.6%<0.001
      Liver disease360.6%161.0%200.4%<0.05
      Depression178127.6%49430.3%128726.8%<0.05
      Anxiety92714.4%20012.3%72715.1%<0.05
      Schizophrenia921.4%241.5%681.4%0.89
      Bipolar disorder460.7%181.1%280.6%<0.05
      Substance abuse77912.1%32519.9%4549.4%<0.001
      Learning difficulties2183.4%161.0%1893.9%<0.001
      Total0191229.6%45728.0%145530.2%
      1218233.8%49330.2%168935.1%
      2146022.6%37923.2%108122.5% <0.001
      36389.9%21713.3%4218.8%
      4+2574.0%855.2%1723.6%
      The most common physical health comorbidities were hypertension and asthma. One of the most striking findings is the frequency of mental health and/ or substance-related comorbidities in PWE. Forty eight percent (48%) of PWE met the definition for depression during follow-up, with 31.5% classified as having significant anxiety. Addictions were also increasingly recognised amongst all cohort patients across the duration of follow up, with alcohol dependence noted in 19.1% and other psychoactive substance abuse in 7%.
      Amongst new users there were significantly more patients with higher overall comorbidity than amongst the existing users. Additionally, there were a higher proportion of new with atrial fibrillation, previous stroke, chronic kidney disease, liver disease, depression, bipolar disorder and substance abuse, and a lower proportion of new users with asthma, cancer, coronary heart disease, anxiety and learning difficulties compared to existing ASM users at baseline.

      4. New user persistence

      4.1 Overall persistence

      Of the 1631 new users, 736 (45.1%) were persistent with the index ASM at 12 months. One hundred and sixty-one (9.9%) new users did not persist with any medication for at least 365 days during the study period. Of these non-persistent patients, 143 were never prescribed any alternative medications.
      Seven hundred and fifty-seven (46.4%) new users were prescribed at least one additional medication during the study period, with an even split in the first additional drugs between continuation of the index therapy alongside the new medication (n = 377) and replacement of the index therapy with the new medication (n = 380).
      The persistence rates with additional ASMs were similar, with around 40% of PWE continuing therapy at 365 days (Table 3).
      Table 3Persistence to ASM by order of therapy for new users.
      NPersistent N (%)
      Index drug163173645.1%
      First addition75731842.0%
      Second addition29713244.4%
      Third addition1175244.4%

      4.2 New user prescribing and persistence to ASM

      Among the 1631 new users the most commonly prescribed monotherapy was levetiracetam (n = 559, 34.3%) followed by lamotrigine (n = 389, 23.9%). Persistence ranged from 25.7% for topiramate to 78.6% for lacosamide (Fig. 1).
      Fig. 1
      Fig. 1Persistence rates for common ASM when prescribed as index or additional medication for new users .

      5. Existing user persistence

      5.1 Overall persistence

      Among the 4818 existing users, 2657 (55.1%) received no additional medications beyond those already prescribed at baseline, 1249 (25.9%) were prescribed one additional ASM during the study period, 516 (10.7%) were prescribed two, and 396 (8.2%) were prescribed three or more.

      5.2 Prescribing in existing users and persistence to ASM

      Patients who were persistent with additional medications ranged from 11.7% for retigabine to 54.0% for phenytoin. A summary of ASM prescribing and persistent rates at 365 days for the most commonly prescribed drugs is presented in Fig. 2. Only patients who were previously non-persistent during the lookback period are included in the persistence rates for index drugs, as the initiation dates for users who were persistent throughout the lookback period could not be confirmed.
      Fig. 2
      Fig. 2Persistence rates for common ASM when prescribed as index medications to previously non-persistent existing users or additional medication for all existing users.

      6. Factors influencing persistence to ASM

      The influence of clinical and demographic variables and the one-year persistence to index ASM in new and previously non-persistent existing users are summarised in Table 4.
      Table 4Univariate associations between 1-year persistence to index ASM and demographic characteristics, comorbidity, and drug-related factors.
      OR95% CIp
      Sex (referent category female)1.030.861.220.775
      Age (referent category 60–69) (years)
      16–190.640.391.050.077
      20–290.540.390.750.000
      30–390.560.400.770.000
      40–490.810.601.090.164
      50–590.760.561.020.071
      70–791.090.781.510.626
      80+0.820.581.150.252
      SIMD Quintile (referent category 1)
      21.200.951.500.129
      30.880.671.150.353
      41.501.122.010.007
      51.391.011.900.042
      Comorbidity
      Cardiac1.431.181.720.000
      Cancer0.830.531.280.395
      Mood1.190.991.420.058
      Respiratory0.940.761.150.547
      Substance issues0.940.761.160.563
      Stroke1.551.231.970.000
      Diabetes1.120.811.560.490
      Liver disease1.060.422.680.894
      Chronic kidney disease1.480.882.470.137
      Learning disabilities1.630.863.060.132
      Physical comorbidity count
      11.281.061.560.011
      21.571.212.040.001
      31.320.911.930.144
      4+1.070.492.320.869
      Psychiatric comorbidity count
      11.050.881.260.585
      21.240.921.680.164
      Total comorbidity count
      11.030.831.280.775
      21.431.131.820.003
      31.320.981.780.064
      4+1.551.032.320.034
      Total comorbidity (continuous)1.131.051.220.001
      Previous non-persistence (vs. new user)0.600.500.730.000
      Combo therapy at baseline (vs. mono)1.421.081.890.014
      Polypharmacy count
      10.800.601.080.141
      20.870.641.180.361
      31.180.861.620.313
      4+1.571.291.920.000
      Number of ASMs at baseline
      21.361.011.830.041
      31.540.743.210.245
      Sodium channel blockers0.790.601.040.088
      Neuropsychiatric side effects1.110.941.320.227
      ASM generation (referent category 1st gen)
      21.261.081.490.004
      31.640.753.560.212

      6.1 Demographics

      A number of demographic factors were associated with poor persistence. Age appeared to be an important determinant of persistence. Younger age groups (20–39 years) were significantly less likely to be persistent in comparison to those aged 60–69 years. In addition, socio-economic disadvantage was a significant factor; with more affluent patients more likely to be persistent than those most deprived.

      6.2 Comorbidity and polypharmacy

      Perhaps counterintuitively, patients with more comorbidities demonstrated better persistence. This was particularly true for those with cardiac comorbidities and those who have previously had a stroke. In addition, those on four or more additional medications were more likely to persist with ASM treatment.

      6.3 Additional clinical factors

      Previously non-persistent users were less likely to be persistent at 365 days in comparison to new users. Use of newer ASMs was associated with higher rates of persistence, with patients prescribed second-generation ASMs more likely to be persistent than patients prescribed first-generation ASMs.

      6.4 ASMs with potential neuropsychiatric adverse effects.

      Amongst the 1046 patients prescribed an ASM with recognised potential for neuropsychiatric adverse effects, 315 (31%) had at least one mood-related psychiatric comorbidity at baseline. A separate, univariate analysis of these patients found no significant difference in persistence rates for ASMs with known neuropsychiatric adverse effects (OR 0.96, 95%CI 0.71–1.31).

      7. Discussion

      The aim of this study was to examine the rates of ASM persistence in a cohort of patients with epilepsy and investigate the associations between persistence and demographic and clinical features. Despite the increasing number of ASMs available to clinicians over the last 20 years more than 50% of new users of ASMs were not persistent at one year, much of which may not be recognised by the treating clinician.
      We would argue that this study provides important information to help identify those patients more likely to demonstrate poor persistence and allow a different therapeutic approach and early intervention for those at highest risk. A small but significant proportion of new users were never persistent for a period of one year during the study period. Without medication, such patients are at higher risk of ongoing seizures and their attendant complications. Our assessment determined some demographic features associated with lower rates of persistence. In general, younger and most deprived adults were less likely to persist with ASMs. This highlights that additional service provision and/or clinical engagement may be required to meet the needs of these groups.
      This study highlighted the burden of chronic poor health experienced by many PWE. More than 70% of those include in the cohort had multimorbidity. Overall, the frequency of physical comorbidities amongst this cohort was similar to those seen in a previous study of multimorbidity in patients with epilepsy in Scotland [
      • Weatherburn C.J.
      • Heath C.A.
      • Mercer S.W.
      • Guthrie B.
      Physical and mental health comorbidities of epilepsy: population-based cross-sectional analysis of 1.5 million people in Scotland.
      ] but an higher frequency of psychiatric and psychological comorbidities was illustrated. Depression, anxiety, alcohol abuse and other psychoactive substance misuse were more common at baseline in this cohort in comparison to the larger, nationwide prevalence study. This may be due in part to the larger proportion of patients in this cohort from more deprived areas as social deprivation has previously been linked with increased prevalence of psychiatric comorbidity [
      • Barnett K.
      • Mercer S.W.
      • Norbury M.
      • Watt G.
      • Wyke S.
      • Guthrie B.
      Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study.
      ]. In this cohort, 52.6% of patients in this cohort were from the most deprived SIMD quintile compared with 14.6% in the previous studies – this is expected, as Glasgow has a generally high level of social deprivation, with over a third of the most deprived areas in the country being in Glasgow based on the 2012 SIMD [
      Scottish Government
      Scottish index of multiple deprivation 2012 - executive summary.
      ]. The reported cumulative rate of depression, anxiety, and alcohol and psychoactive drug abuse highlighted the potential complexity faced by clinicians involved in the delivery of care to PWE, particularly within inner cities [
      • Tellez-Zenteno J.F.
      • Patten S.B.
      • Jette N.
      • Williams J.
      • Wiebe S.
      Psychiatric comorbidity in epilepsy: a population-based analysis.
      ,
      • Selassie A.W.
      • Wilson D.A.
      • Martz G.U.
      • Smith G.G.
      • Wagner J.L.
      • Wannamaker B.B.
      Epilepsy beyond seizure: a population-based study of comorbidities.
      ], and supports the call for regular screening of mental health as part of routine clinical practice, particularly within the out-patient setting.
      In clinical practice, the choice of ASM may be influenced by fear of exacerbating existing underlying psychiatric conditions using particular ASMs. From the data presented, there was no supporting evidence to suggest that clinicians should wholly avoid prescribing ASMs associated with neuropsychiatric side effects in patients with mood disorders at baseline compared to those without. This finding needs to be replicated in other larger cohort studies.
      We found no association between comorbidity/multi-morbidity and low rates of persistence. There are several potential explanations to account for this. The first is that an individual's persistence is not greatly influenced by number or type of comorbidities. An alternative explanation is that clinicians working within regional epilepsy clinics have the experience to consider the importance of comorbidity prior to recommending certain classes of ASM and are more cautious when prescribing certain ASM to those with additional comorbidity. The presence of multimorbidity was associated with increasing rates of persistence to ASM. Although this may appear to be counter intuitive, the same finding has been reported for other chronic conditions [
      • Baggarly S.A.
      • Kemp R.J.
      • Wang X.J.
      • Magoun A.D.
      Factors associated with medication adherence and persistence of treatment for hypertension in a Medicaid population.
      ,
      • O'Shea M.P.
      • Teeling M.
      • Bennett K
      An observational study examining the effect of comorbidity on the rates of persistence and adherence to newly initiated oral anti-hyperglycaemic agents.
      ] and there are a number of potential explanations including the recognition that multimorbidity is often associated with the need for formal support and assistance with self-care, including the dispensing of medication.
      The overall persistence to ASMs at one year among both new and existing users was around 40% for each therapy. This finding is relatively encouraging to both patients and health care professionals suggesting that each additional trial of therapy is not necessarily futile with many patients remaining on the additional ASM for more than one year. More clinical outcome measures such as admission rates or seizure freedom would be desirable and will be available as the dataset is developed further. Although the rate of persistence varied across different drugs, newer drugs including levetiracetam, lamotrigine, lacosamide and zonisamide had higher rates of persistence. This is particularly apparent in comparison to the oldest, first generation ASMs. As was demonstrated in previous publications, second generation ASMs have higher rates of persistence than first generation ASMs particularly among new users [
      • Jacob L.
      • Hamer H.M.
      • Kostev K.
      Persistence with antiepileptic drugs in epilepsy patients treated in neurological practices in Germany.
      ,
      • Lai E.C.C.
      • Hsieh C.Y.
      • Su C.C.
      • Yang Y.H.K.
      • Huang C.W.
      • Lin S.J.
      • et al.
      Comparative persistence of antiepileptic drugs in patients with epilepsy: a STROBE-compliant retrospective cohort study.
      ].
      This study has a number of strengths. Within Scotland, the vast majority of health care for epilepsy patients is provided by the NHS thus the data are likely to be representative of the population of PWE. In addition, all encounters with NHS services can be accurately linked using their CHI number ensuring complete data capture [

      Scottish Government. The use of the CHI (community health index) to support integrated care across the NHS in Scotland Scotland: scottish Government eHealth division; 2013 [1.1:[Available from: https://www.ehealth.scot/resources/information-governance/publications/, last accessed 13/06/2020.

      ]. All patients included were reviewed within a regional epilepsy center ensuring a relatively robust diagnosis and previous validation work within this cohort has demonstrated the search parameters show a high positive predictive value. The study is, however, not without limitations. Additional clinical factors such as epilepsy classification would have been desirable to provide a more complete phenotype. Persistence measurements here are all proxy measures derived from routinely collected data and may be subject to classification bias. It is also important to note that while pharmacy data indicate that a patient has been dispensed a medication they only give a maximum level of persistence (medicines might be collected but not ingested). Based on the available data, we were also unable to account for cases where non-persistence was a result of the patient ceasing taking their medications per their physician's instructions after a period of seizure freedom. It is likely that this would only account for a limited proportion, if any, of the discontinuation of therapy reported here these results, as current NICE guidance recommends that discontinuation of ASM therapy be discussed with patients who have been seizure free for at least 2 years, and our main time point of interest was 1-year after initiation of each medication [
      National Institute for Health and Care Excellence
      Epilepsies: diagnosis and management.
      ]. As described above, there are some differences in the demographic and clinical characteristics of this Glasgow cohort compared to a previous nationwide epilepsy cohort, and not all results will be generalisable to the whole population. Further research using a larger, nationwide cohort and incorporating information on medication adherence or more specific clinical features may help refine the findings from this study.

      8. Conclusion

      At present, these results highlight that demographic factors seem to be more important than individual comorbidities when predicting persistence. The risks emerging with inadequate control would suggest that additional input and support for those who are least likely to remain on ASM at one year should be considered with particular support aimed at younger patients from socially disadvantaged backgrounds. In an attempt address this issue within NHS GGC, routine dispensing data has been made available to clinicians within the Epilepsy out-patient clinic. This potentially allow HCP to identify those not engaging with the therapeutic process and to allow an enhanced level of care, support, and education. If successful, we hope to replicate this in the neighbouring health boards.

      Supplementary material

      persistence_appendix.docx

      Declaration of Competing Interest

      none

      Appendix. Supplementary materials

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