Beschreibung
Considerable attention has been given particularly to the practice of surrogate endpoints in AIDS clinical trials. A successful surrogate endpoint should be able to decrease the follow-up trial time and in some cases to decrease the number of patients required to find out a specific treatment impact. An extensively used criterion for assessing whether such measures are reliable as surrogate endpoints requires that the presumed surrogate fully captures the effect accumulated over all mechanisms of action (the net impact) of the treatment on the clinical endpoint. CD4 and viral loads are used in a majority of AIDS clinical trials as surrogate endpoints for evaluating the effectiveness of newly available drugs. However, no surrogate endpoint has yet been shown to be suitable in forecasting the effectiveness of anti-HIV treatments. As a solution, the current study is intended on developing a surrogate endpoint for AIDS based on a combination of variables.
Autorenporträt
Chamindi Kavindya Samarasekara is a B. Sc (Hons) Statistics with Computer Science graduate of University of Colombo. Currently she is working as a Lecturer (Probationary) at Department of Information and Communication Technology, Faculty of Technology, University of Colombo. Her research interests are Machine Learning and Artificial Intelligence.
Herstellerkennzeichnung:
OmniScriptum SRL
Str. Armeneasca 28/1, office 1
2012 Chisinau
MD
E-Mail: info@omniscriptum.com
