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Comparative analysis of the safety and tolerability of eslicarbazepine acetate in older (≥60 years) and younger (18–59 years) adults

2020· article· en· W3091931967 on OpenAlexaff
Eva Andermann, William E. Rosenfeld, Patricia Penovich, Joanne Rogin, Fernando Cendes, Mar Carreño, R. Eugene Ramsay, Elinor Ben‐Menachem, Helena Gama, Francisco Rocha, Patrı́cio Soares-da-Silva, Robert Tosiello, David Blum, Todd Grinnell

Bibliographic record

VenueEpilepsy Research · 2020
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersSunovion
KeywordsTolerabilityEpilepsyMedicinePediatricsPsychologyInternal medicineAdverse effectPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate the safety and tolerability of eslicarbazepine acetate (ESL), a once-daily oral anti-seizure drug (ASD), in older and younger adult patient populations. METHODS: Two post-hoc pooled data analyses were performed: one from three Phase III studies in patients with focal (partial-onset) seizures who were taking 1-3 concomitant ASDs; the other from five Phase II studies in patients from non-epilepsy populations not taking other ASDs chronically and/or at a clinically-effective anti-seizure dose. The frequencies of treatment-emergent adverse events (TEAEs) were calculated for the older (≥60 years) and younger (18-59 years) adults separately. RESULTS: In the focal seizures study pool, 4.1 % of patients (58/1431) were aged ≥60 years. The overall frequency of TEAEs was 77.5 % in older ESL-treated patients and 72.6 % in younger ESL-treated patients (p = 0.495). For patients who received placebo, the overall frequency of TEAEs was 50.0 % in the older adults and 57.5 % in the younger adults (p = 0.531). The overall placebo-adjusted frequency of TEAEs was 27.5 % in older adults and 15.1 % in younger adults. The placebo-adjusted frequencies of the TEAEs dizziness, somnolence, headache, nausea, diplopia, blurred vision, and ataxia were ≥5 % higher, and frequencies of vomiting and vertigo were ≥2 % higher in older than younger adults. The overall frequency of TEAEs leading to discontinuation was 15.0 % in older ESL-treated patients and 17.6 % in younger ESL-treated patients (p = 0.647); the frequency increased with increasing ESL dose. For patients who received placebo, the overall frequency of TEAEs leading to discontinuation was 5.6 % in older adults and 6.6 % in younger adults (p = 0.847). In the non-epilepsy study pool, 30.2 % of patients (515/1705) were aged ≥60 years. The overall frequency of TEAEs was 56.9 % in older ESL-treated patients and 58.8 % in younger ESL-treated patients. The placebo-adjusted frequencies were 14.9 % in older and 15.1 % in younger ESL-treated patients. The placebo-adjusted frequencies of the TEAEs nausea, vomiting, fatigue, and vertigo were ≥2 % higher in older adults, whereas somnolence was ≥2 % higher in younger adults. The overall frequency of TEAEs leading to discontinuation was 18.3 % in older ESL-treated patients and 12.1 % in younger ESL-treated patients (p = 0.003); frequencies were not related to ESL dose. For patients who received placebo, the overall frequency of TEAEs leading to discontinuation was 8.0 % in older adults and 5.6 % in younger adults (p = 0.407). CONCLUSION: Analyses of adverse event data support the safety and tolerability of ESL in adults aged ≥60 years. In the limited number of older patients with focal seizures taking ESL plus concomitant ASDs (n = 40), the frequency of TEAEs was generally higher than in younger adults. However, in the non-epilepsy patient group (in which the number of older patients was ten times larger; 427 patients taking ESL without concomitant ASDs), no marked age-related TEAE differences were observed, suggesting that increased ASD load associated with adjunctive therapy may complicate treatment selection in older patients, due to risk of increased adverse events. As is common practice for all ASDs, balancing clinical response and tolerability is needed in this vulnerable group of patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.423

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.073
GPT teacher head0.387
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations5
Published2020
Admission routes1
Has abstractyes

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