Monday, June 21, 2021

Sudden unexpected death in epilepsy. A personalized prediction tool

Ashwani Jha, Cheongeun Oh, Dale Hesdorffer, Beate Diehl, Sasha Devore, Martin J. Brodie, Torbjörn Tomson, Josemir W. Sander, Thaddeus S. Walczak, Orrin Devinsky. Sudden Unexpected Death in Epilepsy. A Personalized Prediction Tool. Neurology May 2021, 96 (21) e2627-e2638; DOI: 10.1212/WNL.0000000000011849


Objective To develop and validate a tool for individualized prediction of sudden unexpected death in epilepsy (SUDEP) risk, we reanalyzed data from 1 cohort and 3 case–control studies undertaken from 1980 through 2005.

Methods We entered 1,273 epilepsy cases (287 SUDEP, 986 controls) and 22 clinical predictor variables into a Bayesian logistic regression model.

Results Cross-validated individualized model predictions were superior to baseline models developed from only average population risk or from generalized tonic-clonic seizure frequency (pairwise difference in leave-one-subject-out expected log posterior density = 35.9, SEM ± 12.5, and 22.9, SEM ± 11.0, respectively). The mean cross-validated (95% bootstrap confidence interval) area under the receiver operating curve was 0.71 (0.68–0.74) for our model vs 0.38 (0.33–0.42) and 0.63 (0.59–0.67) for the baseline average and generalized tonic-clonic seizure frequency models, respectively. Model performance was weaker when applied to nonrepresented populations. Prognostic factors included generalized tonic-clonic and focal-onset seizure frequency, alcohol excess, younger age at epilepsy onset, and family history of epilepsy. Antiseizure medication adherence was associated with lower risk.

Conclusions Even when generalized to unseen data, model predictions are more accurate than population-based estimates of SUDEP. Our tool can enable risk-based stratification for biomarker discovery and interventional trials. With further validation in unrepresented populations, it may be suitable for routine individualized clinical decision-making. Clinicians should consider assessment of multiple risk factors, and not focus only on the frequency of  convulsions. ________________________________________________________________________

From the manuscript:

Why do some people experience SUDEP after their second seizure while others survive thousands of convulsive seizures? Ongoing convulsions are a major prognostic factor6,7 but adjusted analyses are less consistent as to whether early age at epilepsy onset, long epilepsy duration, symptomatic etiology, nocturnal convulsions, and a high number or nonadherence of antiseizure medications are independently predictive.8,9 We cannot, however, accurately predict individualized SUDEP risk...

We found that an increased frequency of convulsions (including GTCS and focal to bilateral tonic-clonic seizures) and nongeneralizing focal-onset seizures conferred a higher risk of SUDEP. This is a departure from previous reports that estimate a higher average relative risk from GTCS frequency8,9 and have found no significant association between focal-onset seizures and SUDEP.7,9 These differences could be explained by variation in the data themselves or the strategies used for analysis. No significant relation was found between focal-onset seizures and SUDEP from analyses not only in the most recent and homogeneously ascertained data9 but also in one of our source studies.7 In fact, stratified relative risk from convulsions was higher in a previous analysis of the same combined source data as ours,8 suggesting that differences in data can only partially explain the conflicting results. An alternative reason is that, uniquely, our analysis aimed to provide individualized predictions, whereas others aimed to infer average effects over a population. Subsequently, we include as many data features as possible in the same single model (22 clinical factors), rather than seeking to interpret the output of multiple smaller models. We also removed arbitrary seizure frequency cutoffs (e.g., <3 per year) to improve individualization and interstudy comparability but assumed a monotonic relation between seizure frequency and outcome. We sought to identify prognostic rather than causal risk factors and within these constraints convulsion frequency was not the only predictor of SUDEP risk,10 and indeed performs poorly if used as the sole predictive factor. The novel finding that nongeneralizing focal-onset seizure frequency is prognostic conflicts with other major analyses9 and requires further investigation as it has potentially wide-ranging implications for clinical practice. Whether nongeneralized focal seizures can directly cause SUDEP or may be proxies for breakthrough tonic-clonic seizure risk in individuals who were previously free of convulsions also remains uncertain. Lastly, some predictors were variably clinically defined and so our interpretations must be made with caution. Even so, medication adherence was associated with reduced risk, while alcohol/drug abuse was associated with increased risk. This highlights 2 modifiable behaviors that, if causal, could reduce risk if addressed.

The independent associations between various treatments and SUDEP risk also require further explanation. Whereas our results support prior studies that have found a protective role for epilepsy surgery, almost all antiseizure medications are independently associated with slightly increased SUDEP risk. This needs to be interpreted cautiously since adjusted ORs represent the effect of adding antiseizure medications without any benefit on seizure control—a situation that may either represent increased risk due to the medication or increased risk due to selection of those with treatment resistance. Excluding vigabatrin, which is rarely used and probably falls into the second category, lamotrigine, benzodiazepines, and carbamazepine were associated with increased SUDEP risk compared to other medications, but interventional trials would be needed to determine whether this association is causal or not. Similarly, although cardiac and respiratory comorbidity is associated with reduced risk, this observation may be confounded by a competing risk (these individuals are more likely to die from a non-epilepsy-related cause) or by increased prevalence of coexistent pathologic findings associated with SUDEP misclassification (e.g., 40% left anterior descending coronary artery occlusion).

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