Patterns of treatment response in newly diagnosed epilepsy.
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ABSTRACT: Objective
To delineate the temporal patterns of outcome and to determine the probability of seizure freedom with successive antiepileptic drug regimens in newly diagnosed epilepsy.Methods
Patients in whom epilepsy was diagnosed and the first antiepileptic drug prescribed between July 1, 1982, and April 1, 2006, were followed up until March 31, 2008. Outcomes were categorized into 4 patterns: (A) early and sustained seizure freedom; (B) delayed but sustained seizure freedom; (C) fluctuation between periods of seizure freedom and relapse; and (D) seizure freedom never attained. Probability of seizure freedom with successive drug regimens was compared. Seizure freedom was defined as no seizures for ≥1 year.Results
A total of 1,098 patients were included (median age 32 years, range 9-93). At the last clinic visit, 749 (68%) patients were seizure-free, 678 (62%) on monotherapy. Outcome pattern A was observed in 408 (37%), pattern B in 246 (22%), pattern C in 172 (16%), and pattern D in 272 (25%) patients. There was a higher probability of seizure freedom in patients receiving 1 compared to 2 drug regimens, and 2 compared to 3 regimens (p < 0.001). The difference was greater among patients with symptomatic or cryptogenic than with idiopathic epilepsy. Less than 2% of patients became seizure-free on subsequent regimens but a few did so on their sixth or seventh regimen.Conclusions
Most patients with newly diagnosed epilepsy had a constant course which could usually be predicted early. The chance of seizure freedom declined with successive drug regimens, most markedly from the first to the third and among patients with localization-related epilepsies.
SUBMITTER: Brodie MJ
PROVIDER: S-EPMC3348850 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Epilepsy is a chronic neurological disease with a variable therapeutic response. To design effective treatment strategies for epilepsy, it is important to understand treatment responses and predictive factors. However, limited data are available in Africa, including Ethiopia. The aim of this study was therefore to assess treatment response and identify prognostic predictors among patients with epilepsy at Jimma university medical center, Ethiopia. We conducted a retrospective cohort study of 404 newly diagnosed adult epilepsy patients receiving antiepileptic treatment between May 2010 and May 2015. Demographic, clinical, and outcome data were collected for all patients with a minimum follow-up of two years. Cox proportional hazards model was used to identify predictors of poor seizure remission. Overall, 261 (64.6%) of the patients achieved seizure remission for at least one year. High number of pre-treatment seizures (adjusted hazard ratios (AHR)?=?0.64, 95% CI: 0.49-0.83) and poor adherence (AHR?=?0.57, 95% CI: 0.44-0.75) were significant predictors of poor seizure remission. In conclusion, our study showed that only about two-thirds of patients had achieved seizure remission. The high number of pre-treatment seizures and non-adherence to antiepileptic medications were predictors of poor seizure remission. Patients with these characteristics should be given special attention.
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Project description:ImportanceSelection of antiseizure medications (ASMs) for epilepsy remains largely a trial-and-error approach. Under this approach, many patients have to endure sequential trials of ineffective treatments until the "right drugs" are prescribed.ObjectiveTo develop and validate a deep learning model using readily available clinical information to predict treatment success with the first ASM for individual patients.Design, setting, and participantsThis cohort study developed and validated a prognostic model. Patients were treated between 1982 and 2020. All patients were followed up for a minimum of 1 year or until failure of the first ASM. A total of 2404 adults with epilepsy newly treated at specialist clinics in Scotland, Malaysia, Australia, and China between 1982 and 2020 were considered for inclusion, of whom 606 (25.2%) were excluded from the final cohort because of missing information in 1 or more variables.ExposuresOne of 7 antiseizure medications.Main outcomes and measuresWith the use of the transformer model architecture on 16 clinical factors and ASM information, this cohort study first pooled all cohorts for model training and testing. The model was trained again using the largest cohort and externally validated on the other 4 cohorts. The area under the receiver operating characteristic curve (AUROC), weighted balanced accuracy, sensitivity, and specificity of the model were all assessed for predicting treatment success based on the optimal probability cutoff. Treatment success was defined as complete seizure freedom for the first year of treatment while taking the first ASM. Performance of the transformer model was compared with other machine learning models.ResultsThe final pooled cohort included 1798 adults (54.5% female; median age, 34 years [IQR, 24-50 years]). The transformer model that was trained using the pooled cohort had an AUROC of 0.65 (95% CI, 0.63-0.67) and a weighted balanced accuracy of 0.62 (95% CI, 0.60-0.64) on the test set. The model that was trained using the largest cohort only had AUROCs ranging from 0.52 to 0.60 and a weighted balanced accuracy ranging from 0.51 to 0.62 in the external validation cohorts. Number of pretreatment seizures, presence of psychiatric disorders, electroencephalography, and brain imaging findings were the most important clinical variables for predicted outcomes in both models. The transformer model that was developed using the pooled cohort outperformed 2 of the 5 other models tested in terms of AUROC.Conclusions and relevanceIn this cohort study, a deep learning model showed the feasibility of personalized prediction of response to ASMs based on clinical information. With improvement of performance, such as by incorporating genetic and imaging data, this model may potentially assist clinicians in selecting the right drug at the first trial.
| S-EPMC9425285 | biostudies-literature
Project description:PurposeTreatment for epilepsy primarily involves antiseizure medications (ASMs), which can be characterized using the clinical data warehouse (CDW) database. In this study, we compared retention rates and time to successful treatment for various ASMs to reflect both efficacy and adverse effects in patients with newly diagnosed epilepsy.Materials and methodsWe identified newly diagnosed epilepsy patients with ASM treatment for more than 12 months using CDW of a tertiary referral hospital. Clinical characteristics were compared between groups with successful and unsuccessful treatment. Cox regression analysis was performed to evaluate independent variables of age, sex, comorbidities, and attributes of ASM regimens.ResultsOf 2515 eligible participants, 46.2% were successfully treated with the first ASM regimen, and 74.7% with all ASM regimens with the median time-to-treatment success of 14 months. Participants with second-generation ASM as the first ASM were more likely to be successfully treated with the first regimen compared to those with first-generation ASM (51.6% vs. 42.3%, p<0.001) and more successfully treated [hazard ratio (HR)=1.26; 95% confidence interval (CI): 1.15-1.39]. Overall, valproic acid was the most common ASM across a wide range of ages under 65 years, while levetiracetam in patients aged over 65 years or lamotrigine in female adult patients. Clinical factors associated with less favorable treatment outcomes included renal disease (HR=0.78; 95% CI: 0.66-0.92), liver disease (HR=0.65; 95% CI: 0.52-0.81), depression (HR=0.70; 95% CI: 0.57-0.84), and mechanical ventilation (HR=0.58; 95% CI: 0.50-0.67).ConclusionSecond-generation ASMs have the advantage of more successful treatment with fewer ASM regimen changes compared with first-generation drugs. Various comorbid conditions as well as age and sex should be considered when selecting ASMs.
| S-EPMC10827640 | biostudies-literature
Project description:The aim of this study was to investigate whether volumes of the corpus callosum could predict a response to antiepileptic drugs in patients with newly diagnosed focal epilepsy.Fifty-three patients with newly diagnosed focal epilepsy of unknown etiology and healthy subjects were enrolled in this study. First, we analyzed the differences in the volumes of the corpus callosum between patients with epilepsy and healthy subjects. Second, we divided patients with epilepsy into antiepileptic drug responders and drug nonresponders groups, according to their seizure controls, and evaluated the differences in the volumes of the corpus callosum between the groups. Third, we conducted correlation analyses between the volumes of the corpus callosum and mean diffusion measures in healthy subjects.The volumes of the corpus callosum in patients with epilepsy were significantly lower than those in normal controls (p = .0001). Among epilepsy patients, the volumes of the corpus callosum were significantly lower in antiepileptic drug responders compared with nonresponders (p = .0481), which was the only independent variable for predicting antiepileptic drug response (OR = 10.07, p = .0434). In addition, we found that the volumes of the corpus callosum were significantly correlated with the mean diffusion measures (fractional anisotropy, r = .408, p = .0027; mean diffusivity, r = -0.403, p = .0028) in normal controls.We demonstrated that the volumes of the corpus callosum were different according to antiepileptic drug responses in patients with newly diagnosed focal epilepsy, which might suggest that the volumes of the corpus callosum could be a new biomarker for predicting responses to antiepileptic drugs.
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Project description: Not available
| S-EPMC4189633 | biostudies-literature
Project description:ObjectivesTo estimate first-year health care charges for youth with newly diagnosed epilepsy seen within an interdisciplinary pediatric epilepsy team and examine demographic, clinical, and psychosocial predictors of annual charges.MethodsRetrospective chart review was conducted to extract medical, hospital, and physician billing data from the year following an epilepsy diagnosis for 258 patients (aged 2-18 years) seen in a New Onset Seizure Clinic between July 2011 and December 2012. Descriptive statistics were used to estimate per-patient total first-year charges and health care utilization patterns (e.g., hospitalizations, emergency department visits, outpatient visits). Univariate analyses examined differences in health care charges between demographic, clinical, and psychosocial factors. Predictors of health care charges were examined using hierarchical multiple regression analysis.ResultsThe estimated per-patient total first-year health care charge was $20,084 (95% confidence interval [CI] $16,491-$23,677). Charges were higher for patients who reported having seizures since diagnosis ($25,509; 95% CI $20,162-$30,856) and were associated with more antiepileptic drug side effects (r = 0.18; 95% CI 0.03-0.32). Controlling for demographic and clinical factors, poorer baseline health-related quality of life was associated with higher per-patient health care charges (B = -445.40; 95% CI -865 to -25).ConclusionsThe economic impact of pediatric epilepsy in the year following diagnosis is substantial. Cost reduction efforts would be optimized by improving seizure control and targeting health-related quality of life, an outcome amenable to behavioral intervention.
| S-EPMC4540245 | biostudies-literature
Project description:Abstract BACKGROUND Healthy brain tissue responses to radiotherapy (pseudoprogression/radiation necrosis) may bias MRI-based tumor response evaluations. To understand these changes specifically after high doses of radiotherapy, we analyzed MRIs of patients of the INTRAGO study, a phase I/II dose-escalation trial on intraoperative radiotherapy in glioblastoma. METHODS Patients enrolled in INTRAGO (NCT02104882) received an intraoperative boost of 20-40 Gy followed by standard adjuvant radiochemotherapy and maintenance chemotherapy. In the present analyses, only patients who received per-protocol therapy and those, who underwent standardized serial MRI follow-ups including DSC-PWI, were included and assessed with special focus on perilesional enhancement pattern, volume, and mean rCBV. Mean leakage-corrected rCBV within enhancing lesions was computed for all MRI follow-ups. RESULTS Overall, 12/15 (80%) patients (median age 60.5 [range 46-73] years) were included in the analysis. Distant failure was the predominant failure pattern (7/12 [58.3%]) leading to salvage therapy after a median follow-up of 372.5 days (range: 72-991 days), while local tumor recurrence was observed in one case (8.3%). On the first follow-up MRI all patients demonstrated perilesional enhancement of varying extent: in 3/12 (25%) patients thin linear, in 1 (8.3%) nodular, in 7 (58.3%) combined linear and nodular, and in 1 (8.3%) voluminous, indistinct, mesh-like. In the course, most patients developed the latter two patterns (8/11 [72.2%]). Three different patterns of enhancing lesion volume were observed: in 3/10 (30%) an early (<200 days) continuous decrease, in 2/10 (20%) a marked early increase, and in 5 (50%) a marked late (≥200 days) increase. The overall linear trend in rCBV was negative in most patients (8/11 (72.2%)). CONCLUSIONS High doses to the tumor cavity result in characteristic perilesional enhancement patterns. These results will be useful for the response evaluation of patients exposed to high doses of radiotherapy in future studies, such as the multicenter randomized INTRAGO II trial (NCT02685605).
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Project description:BackgroundNon-Hispanic Black and Hispanic persons with MS (pwMS) are more likely to experience rapid disease progression and severe disability than non-Hispanic White pwMS; however, it is unknown how the initiation of high-efficacy disease-modifying therapies (DMTs) differs by race/ethnicity. This real-world study describes DMT treatment patterns in newly diagnosed pwMS in the United States (US) overall and by race/ethnicity.MethodsThis retrospective analysis used the US Optum Market Clarity claims/electronic health records database (January 2015-September 2020). pwMS who were first diagnosed in 2016 or later and initiated any DMT in the two years following diagnosis were included. Continuous enrollment in the claims data for ≥ 12 months before and ≥ 24 months after diagnosis was required. Treatment patterns 2 years after diagnosis were analyzed descriptively overall and by race/ethnicity.ResultsThe sample included 682 newly diagnosed and treated pwMS (non-Hispanic Black, n = 99; non-Hispanic White, n = 479; Hispanic, n = 35; other/unknown race/ethnicity, n = 69). The mean time from diagnosis to DMT initiation was 4.9 months in all pwMS. Glatiramer acetate and dimethyl fumarate were the most common first-line DMTs in non-Hispanic Black (28% and 20% respectively) and Hispanic pwMS (31%, 29%); however, glatiramer acetate and ocrelizumab were the most common in non-Hispanic White pwMS (33%, 18%). Use of first-line high-efficacy DMTs was limited across all race/ethnicity subgroups (11-29%), but uptake increased in non-Hispanic Black and White pwMS over the study period.ConclusionUse of high-efficacy DMTs was low across all race/ethnicity subgroups of newly diagnosed pwMS in the US, including populations at a greater risk of experiencing rapid disease progression and severe disability.
| S-EPMC10730787 | biostudies-literature
Project description:ImportanceTolerability is a key determinant of the effectiveness of epilepsy treatment. It is important to evaluate whether the overall tolerability has improved.ObjectiveTo identify factors associated with poor tolerability of antiseizure medications (ASMs) and examine temporal changes in tolerability.Design, setting, and participantsThis was a longitudinal cohort study at a specialist clinic in Glasgow, Scotland. Patients with newly diagnosed and treated epilepsy between July 1982 and October 2012 were included from 2282 eligible individuals. They were followed up until April 2016 or death. Data analysis was completed in August 2019.ExposuresAntiseizure medications.Main outcomes and measuresUnivariable and multivariable survival analyses were performed to examine associations between potential risk factors and development of intolerable adverse effects (AEs). Intolerable AE rates of the ASMs as the initial monotherapy were compared between 3 epochs (July 1982-June 1992, July 1992-June 2002, and July 2002-April 2016).ResultsOf 1795 patients, 969 (54.0%) were male, and the median (interquartile range) age was 33 (21-50) years. A total of 3241 ASMs were prescribed during the period, of which 504 (15.6%) were discontinued within 6 months owing to intolerable AEs. Children younger than 18 years had lower intolerable AE rates than adults (vs aged 18-64 years: adjusted hazard ratio [aHR], 1.58; 95% CI, 1.07-2.32; vs aged ≥65 years: aHR, 1.90; 95% CI, 1.19-3.02) while female individuals (aHR, 1.60; 95% CI, 1.30-1.96) and those who had more than 5 pretreatment seizures (aHR, 1.24; 95% CI, 1.03-1.49) were associated with having higher risk. For each ASM trial, the risk of intolerable AEs increased with the number of previous drug withdrawals due to AEs (aHR, 1.18; 95% CI, 1.09-1.28) and the number of concomitant ASMs (aHR, 1.31; 95% CI, 1.04-1.64). The proportion of second-generation ASMs prescribed as the initial monotherapy increased from 22.3% (33 of 148) in the first epoch to 68.7% (645 of 939) in the last (P < .001). Although differences in intolerable AE rates and types of AEs were found between the ASMs, there was no difference in the overall intolerable AEs rates to the initial monotherapy across the 3 epochs (first: 10.1% [15 of 148]; second: 13.8% [98 of 708]; third: 14.0% [131 of 939]; P = .41).Conclusions and relevanceIn this cohort study, the increased use of the second-generation ASMs had not improved overall treatment tolerability. Greater effort to improve tolerability in ASM development is needed.
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Project description:Neuroimaging studies have shown that juvenile myoclonic epilepsy (JME) is characterized by impaired brain networks. However, few studies have investigated the potential disruptions in rich-club organization-a core feature of the brain networks. Moreover, it is unclear how structure-function relationships dynamically change over time in JME. Here, we quantify the anatomical rich-club organization and dynamic structural and functional connectivity (SC-FC) coupling in 47 treatment-naïve newly diagnosed patients with JME and 40 matched healthy controls. Dynamic functional network efficiency and its association with SC-FC coupling were also calculated to examine the supporting of structure-function relationship to brain information transfer. The results showed that the anatomical rich-club organization was disrupted in the patient group, along with decreased connectivity strength among rich-club hub nodes. Furthermore, reduced SC-FC coupling in rich-club organization of the patients was found in two functionally independent dynamic states, that is the functional segregation state (State 1) and the strong somatomotor-cognitive control interaction state (State 5); and the latter was significantly associated with disease severity. In addition, the relationships between SC-FC coupling of hub nodes connections and functional network efficiency in State 1 were found to be absent in patients. The aberrant dynamic SC-FC coupling of rich-club organization suggests a selective influence of densely interconnected network core in patients with JME at the early phase of the disease, offering new insights and potential biomarkers into the underlying neurodevelopmental basis of behavioral and cognitive impairments observed in JME.
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