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Trials. 2007 Mar 29;8:12.

Importance of competing risks in the analysis of anti-epileptic drug failure.

Author information

1
Centre for Medical Statistics and Health Evaluation, University of Liverpool, Liverpool, UK. prw@liv.ac.uk

Abstract

BACKGROUND:

Retention time (time to treatment failure) is a commonly used outcome in antiepileptic drug (AED) studies.

METHODS:

Two datasets are used to demonstrate the issues in a competing risks analysis of AEDs. First, data collection and follow-up considerations are discussed with reference to information from 15 monotherapy trials. Recommendations for improved data collection and cumulative incidence analysis are then illustrated using the SANAD trial dataset. The results are compared to the more common approach using standard survival analysis methods.

RESULTS:

A non-significant difference in overall treatment failure time between gabapentin and topiramate (logrank test statistic = 0.01, 1 degree of freedom, p-value = 0.91) masked highly significant differences in opposite directions with gabapentin resulting in fewer withdrawals due to side effects (Gray's test statistic = 11.60, 1 degree of freedom, p = 0.0007) but more due to poor seizure control (Gray's test statistic = 14.47, 1 degree of freedom, p-value = 0.0001). The significant difference in overall treatment failure time between lamotrigine and carbamazepine (logrank test statistic = 5.6, 1 degree of freedom, p-value = 0.018) was due entirely to a significant benefit of lamotrigine in terms of side effects (Gray's test statistic = 10.27, 1 degree of freedom, p = 0.001).

CONCLUSION:

Treatment failure time can be measured reliably but care is needed to collect sufficient information on reasons for drug withdrawal to allow a competing risks analysis. Important differences between the profiles of AEDs may be missed unless appropriate statistical methods are used to fully investigate treatment failure time. Cumulative incidence analysis allows comparison of the probability of failure between two AEDs and is likely to be a more powerful approach than logrank analysis for most comparisons of standard and new anti-epileptic drugs.

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