
Abstract
Clinical trials often judge the efficacy of a new treatment by comparing the survival patterns of patients who are randomly assigned to undergo the new or a standard/placebo treatment. Usually, the entire groups are analyzed, although certain subgroups of patients may react differently to the new treatment than others. Some patients taking the new treatment might benefit from it (the positive responders) while others may be harmed by it (the negative responders). We applied a newly developed responder identification method (Kehl&Ulm, 2003) on the doubleblinded placebo controlled European Myocardial Infarction Amiodarone Trial (EMIAT). The method, which is based on bump hunting, proceeds to find the so called predictive factors, which describe positive and negative trends in survival in special subgroups of patients, solely due to Amiodarone. Factors found to be predictive were: age, previous infarction, beta-blocker treatment, onset, NYHA classification, and sex. Negative responders to Amiodarone, i.e. patients taking Amiodarone who survived shorter than a similar group under placebo, were patients who were older than 65 years, have had a previous infarction, and were not on beta-blockers. Positive responders to Amiodarone, (longer survival time), were male patients who were not negative responders, had NYHA classification greater than or equal to two, and onset greater than one. Further studies are needed to investigate this hypothesis.
Item Type: | Paper |
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Faculties: | Mathematics, Computer Science and Statistics > Statistics > Collaborative Research Center 386 Special Research Fields > Special Research Field 386 |
Subjects: | 500 Science > 510 Mathematics |
URN: | urn:nbn:de:bvb:19-epub-1741-1 |
Language: | English |
Item ID: | 1741 |
Date Deposited: | 10. Apr 2007 |
Last Modified: | 04. Nov 2020, 12:45 |