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Record W2509532991 · doi:10.1186/s12883-016-0663-7

Comparative effectiveness of levetiracetam, valproate and carbamazepine among elderly patients with newly diagnosed epilepsy: subgroup analysis of the randomized, unblinded KOMET study

2016· article· en· W2509532991 on OpenAlexaff
Bernd Pohlmann‐Eden, Anthony G Marson, Matthias Noack‐Rink, Francisco C. Ramirez, Azita Tofighy, Konrad J. Werhahn, Imane Wild, Eugen Trinka

Bibliographic record

VenueBMC Neurology · 2016
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsDalhousie UniversityQueen Elizabeth II Health Sciences Centre
FundersUCB Pharma
KeywordsMedicineLevetiracetamCarbamazepineTolerabilityHazard ratioSubgroup analysisRandomized controlled trialLamotrigineInternal medicineEpilepsyConfidence intervalClinical endpointAnesthesiaPediatricsAdverse effectPsychiatry

Abstract

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BACKGROUND: Few clinical trials have evaluated the efficacy and tolerability of antiepileptic drugs (AEDs) as initial monotherapy for elderly patients. METHODS: This post-hoc subgroup analysis of data from an unblinded, randomized, 52-week superiority study (KOMET) compared the effectiveness of levetiracetam (LEV) with extended-release sodium valproate (VPA-ER) and controlled-release carbamazepine (CBZ-CR) as monotherapy in patients aged ≥ 60 years with newly diagnosed epilepsy. The physician chose VPA or CBZ as preferred standard treatment; patients were randomized to standard AEDs or LEV. The primary endpoint was time to treatment withdrawal. Results are exploratory, since KOMET was not powered for a subgroup analysis by age. RESULTS: Patients (n = 308) were randomized to LEV (n = 48) or VPA-ER (n = 53) in the VPE-ER stratum or to LEV (n = 104) or CBZ-CR (n = 103) in the CBZ-CR stratum. Mean age was 69.6 years, range 60.2-89.9 years (intention-to-treat population n = 307). Time to treatment withdrawal hazard ratio [HR] (95 % confidence interval [CI]) for LEV vs. standard AEDs was 0.44 (0.28-0.67); LEV vs. VPA-ER: 0.46 (0.16-1.33); LEV vs. CBZ-CR: 0.45 (0.28-0.72). Twelve-month withdrawal rates were: LEV vs. standard AEDs, 20.4 vs. 38.7 %; LEV vs. VPA-ER, 10.4 vs. 23.1 %; LEV vs. CBZ-CR, 25.0 vs. 46.6 %. Time to first seizure was similar between LEV and standard AEDs (HR: 0.92, 95 % CI: 0.63-1.35), LEV and VPA-ER (0.77, 0.38-1.56), and LEV and CBZ-CR (1.02, 0.64-1.63). Adverse events were reported by 76.2, 67.3, and 82.5 % of patients for LEV, VPA-ER, and CBZ-CR, respectively. Discontinuation rates due to AEs were 11.3, 10.2, and 35.0 % for LEV, VPA-ER, and CBZ-CR, respectively. CONCLUSIONS: Time to treatment withdrawal was longer with LEV compared with standard AEDs. This finding was driven primarly by the result in the CBZ-CR stratum, which in turn was likely due to the more favorable tolerability profile of LEV. Results of this post-hoc analysis suggest that LEV may be a suitable option for initial monotherapy for patients aged ≥ 60 years with newly diagnosed epilepsy. TRIAL REGISTRATION: ClinicalTrials.gov: NCT00175903 ; September 9, 2005.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.020
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.011
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.286
Teacher spread0.266 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
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".

Quick stats

Citations65
Published2016
Admission routes1
Has abstractyes

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