Evidence map›Paper›PMID 30389894›Full record

Trial reportNeurology2018

Identification of patients who will not achieve seizure remission within 5 years on AEDs.

David M Hughes, Laura J Bonnett, Gabriela Czanner, Arnošt Komárek, Anthony G Marson, Marta García-Fiñana

Abstract readMulticenter StudyRandomized Controlled Trial
In one paragraph

Trial report in Neurology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Medication Beliefs and Adherence to Antiseizure Medications.Neurology research international · 2020
    Article
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

David M HughesFrom the Departments of Biostatistics (D.M.H., L.J.B., G.C., M.G.-F.) and Molecular and Clinical Pharmacology (A.G.M.), Institute of Translational Medicine, and Department of Eye and Vision Science (G.C.), Institute of Ageing & Chronic Disease, University of Liverpool, UK; and Department of Probability and Mathematical Statistics (A.K.), Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic.
Laura J BonnettFrom the Departments of Biostatistics (D.M.H., L.J.B., G.C., M.G.-F.) and Molecular and Clinical Pharmacology (A.G.M.), Institute of Translational Medicine, and Department of Eye and Vision Science (G.C.), Institute of Ageing & Chronic Disease, University of Liverpool, UK; and Department of Probability and Mathematical Statistics (A.K.), Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic.
Gabriela CzannerFrom the Departments of Biostatistics (D.M.H., L.J.B., G.C., M.G.-F.) and Molecular and Clinical Pharmacology (A.G.M.), Institute of Translational Medicine, and Department of Eye and Vision Science (G.C.), Institute of Ageing & Chronic Disease, University of Liverpool, UK; and Department of Probability and Mathematical Statistics (A.K.), Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic.
Arnošt KomárekFrom the Departments of Biostatistics (D.M.H., L.J.B., G.C., M.G.-F.) and Molecular and Clinical Pharmacology (A.G.M.), Institute of Translational Medicine, and Department of Eye and Vision Science (G.C.), Institute of Ageing & Chronic Disease, University of Liverpool, UK; and Department of Probability and Mathematical Statistics (A.K.), Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic.
Anthony G MarsonFrom the Departments of Biostatistics (D.M.H., L.J.B., G.C., M.G.-F.) and Molecular and Clinical Pharmacology (A.G.M.), Institute of Translational Medicine, and Department of Eye and Vision Science (G.C.), Institute of Ageing & Chronic Disease, University of Liverpool, UK; and Department of Probability and Mathematical Statistics (A.K.), Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic.
Marta García-FiñanaFrom the Departments of Biostatistics (D.M.H., L.J.B., G.C., M.G.-F.) and Molecular and Clinical Pharmacology (A.G.M.), Institute of Translational Medicine, and Department of Eye and Vision Science (G.C.), Institute of Ageing & Chronic Disease, University of Liverpool, UK; and Department of Probability and Mathematical Statistics (A.K.), Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic. martaf@liv.ac.uk.

Funding

Department of Health PDF-2015-08-044Medical Research Council MR/L010909/1Medical Research Council MR/R024847/1
6 · The paper itself

Abstract

objectiveTo identify people with epilepsy who will not achieve a 12-month seizure remission within 5 years of starting treatment.

methodsThe Standard and New Antiepileptic Drug (SANAD) study is the largest prospective study in patients with epilepsy to date. We applied a recently developed multivariable approach to the SANAD dataset that takes into account not only baseline covariates describing a patient's history before diagnosis but also follow-up data as predictor variables.

resultsChanges in number of seizures and treatment history were the most informative time-dependent predictors and were associated with history of neurologic insult, epilepsy type, age at start of treatment, sex, and having a first-degree relative with epilepsy. Our model classified 95% of patients. Of those classified, 95% of patients observed not to achieve remission at 5 years were correctly classified (95% confidence interval [CI] 89.5%-100%), with 51% identified by 3 years and 90% within 4 years of follow-up. Ninety-seven percent (95% CI 93.3%-98.8%) of patients observed to achieve a remission within 5 years were correctly classified. Of those predicted not to achieve remission, 76% (95% CI 58.5%-88.2%) truly did not achieve remission (positive predictive value). The predictive model achieved similar accuracy levels via external validation in 2 independent United Kingdom-based datasets.

conclusionOur approach generates up-to-date predictions of the patient's risk of not achieving seizure remission whenever new clinical information becomes available that could influence patient counseling and management decisions.

Indexed as

AdultAnticonvulsantsDrug Resistant EpilepsyFemaleHumansMaleMiddle AgedMultivariate AnalysisProspective StudiesRisk FactorsAnticonvulsants

Identifiers

PMID30389894
PMCPMC6282237

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.