Markov modelling of treatment response in a 30-year cohort study of newly diagnosed epilepsy

Author:

Simpson Hugh D1,Foster Emma12,Ademi Zanfina23,Lawn Nicholas4,Brodie Martin J5,Chen Zhibin236,Kwan Patrick1236

Affiliation:

1. Department of Neurology, Alfred Hospital, Melbourne VIC 3004, Australia

2. Department of Neuroscience, Central Clinical School, Monash University, Melbourne VIC 3800, Australia

3. School of Public Health & Preventative Medicine, Monash University, Melbourne VIC 3800, Australia

4. Western Australia Adult Epilepsy Service, Sir Charles Gairdner Hospital, Perth WA 6009, Australia

5. University of Glasgow, Glasgow G12 8QQ, Scotland, UK

6. Department of Medicine, Royal Melbourne Hospital, The University of Melbourne, Parkville VIC 3050, Australia

Abstract

Abstract People with epilepsy have variable and dynamic trajectories in response to antiseizure medications. Accurately modelling long-term treatment response will aid prognostication at the individual level and health resource planning at the societal level. Unfortunately, a robust model is lacking. We aimed to develop a Markov model to predict the probability of future seizure-freedom based on current seizure state and number of antiseizure medication regimens trialled. We included 1,795 people with newly diagnosed epilepsy who attended a specialist clinic in Glasgow, Scotland, between July 1982 and October 2012. They were followed up until October 2014 or death. We developed a simple Markov model, based on current seizure state only, and a more detailed model, based on both current seizure state and number of antiseizure medication regimens trialled. Sensitivity analyses were performed for the regimen-based states model to examine the effect of regimen changes due to adverse effects. The model was externally validated in a separate cohort of 455 newly diagnosis epilepsy patients seen in Perth, Australia, between May 1999 and May 2016. Our models suggested that once seizure-freedom was achieved, it was likely to persist, regardless of the number of antiseizure medications trialled to reach that point. The likelihood of achieving long-term seizure-freedom was highest with the first antiseizure medication regimen, at approximately 50%. The chance of achieving seizure-freedom fell with subsequent regimens. Fluctuations between seizure-free and not seizure-free states were highest earlier on, but decreased with chronicity of epilepsy. Seizure-freedom/recurrence risk tables were constructed with these probability data, similar to cardiovascular risk tables. Sensitivity analyses showed that the general trends and conclusions from the base model were maintained despite perturbing the model and input data with regimen changes due to adverse effects. Quantitative comparison with the external validation cohort showed excellent consistency at year 1, good at year 3 and moderate at year 5. Quantitative models, as used in this study, can provide pertinent clinical insights that are not apparent from simple statistical analysis alone. Attaining seizure freedom at any time in a patient’s epilepsy journey will confer durable benefit. Seizure-freedom risk tables may be used to individualise the prediction of future seizure control trajectory.

Publisher

Oxford University Press (OUP)

Subject

Clinical Neurology

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