A New Statistical Method to Assess Treatment Benefit/Risk in Clinical Trials, With Examples in Oncology

MessageThis Webinar is over
Date Feb 22, 2018
Time 03:00 AM EDT
Cost Free
Note: All webinars are entirely free to attend, and if a registrant is unable to make the live event we will send them the recorded archive after the webinar has completed.

The management of cancer patients in clinical practice relies to a great extent on the results of clinical trials. Although several statistical methods are currently used to test the effects of treatments in clinical trials, all of them suffer from limitations. Moreover, it is not standard practice to take into account multiple endpoints to formally assess treatment results under a single metric. Very often, a new treatment yields positive results for the primary endpoint, but not for all secondary endpoints. Not incorporating the results of these other endpoints may lead to an incomplete view of the benefit/risk ratio.

Despite the promise of precision medicine, treatment choices could be taken one step further if patient preferences were taken into account in decision-making using a formal statistical framework. This might be called a truly “personalized medicine”. The speakers in this webinar have proposed a new statistical framework, named “generalized pairwise comparisons” (GPC), which can be useful in the search for personalized treatment choices.

In this webinar, expert speakers will:
  • Review commonly used metrics to assess treatment benefit, especially considering survival endpoints
  • Describe the GPC method as a novel approach to the analysis of clinical-trial data, providing examples of recent studies in which this method has been used and has shed new light on the assessment of treatment benefit
  • Describe ongoing efforts to enhance this methodology and make it available to end-users, such as clinical trialists, physicians, and patients


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