Primary Efficacy Endpoint in Clinical Trials of Antiepileptic Drugs: Change or Percentage Change
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Primary Efficacy Endpoint in Clinical Trials of Antiepileptic Drugs: Change or Percentage Change Ohidul Siddiqui and Norman Hershkowitz Drug Information Journal 2010 44: 343 DOI: 10.1177/009286151004400316 The online version of this article can be found at: http://dij.sagepub.com/content/44/3/343
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STATISTICS
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Primary Efficacy Endpoint in Clinical Trials of Antiepileptic Drugs: Change or Percentage Change
Ohidul Siddiqui, PhD Division of Biometrics-l. Office of Biostatistics, Center for Drug Evaluation and Research, US Food and Drug Administration Norman Hersbkowitr, MD Division of Neurology Products, Office of New Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration
Key Words AED trials; Parametric tests; Nonparametric tests; Change from baseline Correspondence Address Ohidul Siddiqui, Food and Drug Administration, 10903 New Hampshire Ave.. Rm 4606, Bldg. 21, Silver Spring, M D 20993 (email: ohidul.siddiqui@fda. hhs.gov).
The views expressed in this adicle d o not reflect any position ofthe US Food and Drug Administration.
In randomized dinical trials of antiepileptic drugs (AEDS), the s e i m jkjuency per x days during baseline and treatment phase pm'als are recded to evaluate ficacy of a drug. The seizure jkpency data are often nonnormal, and hence an approyniate mathematical tmnsformation is necessaryfora statisticalanalysis. The most commonly used trunsfnmations in AED development research are (a) log-trunsformation of the seizure jkpency data, and (b) calculation of percentage change 0 f i m baseline in seizure jkjuenq Ihe log-tmnsformed postbasdine seizure frequency data are analyzed using a parametric ANCOVA model
INTRODUCTION In randomized clinical trials, seizure frequency per x days at the end of a randomized study period (postbaseline) is compared to the seizure frequency per x days at baseline to determine the effectiveness of antiepileptic drugs (AEDs). The seizure frequency data are often highly skewed with a long right tail, and difficult to analyze without making any transformation of the data. One of the commonly used transformations is the calculation of percentage of patients whose seizure frequency is decreased by a certain percentage (eg, 25%, SO%, or 75%) at a given time interval (x days) of a postbaseline period from the rates for x days at baseline, and make a statistical comparison of the percentages across treatment groups. An arbitrary dichotomization of the change in seizure freq
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