Dymaxium will be presenting three posters during ISPOR's 13th Annual Meeting in Toronto!
Poster Session I
Monday, May 5, 2008 - 9:00 AM - 8:00 PM
Cost Savings From Reduced Hiv Incidence Estimates
(Jason Flavin, Russell Becker - Dymaxium Inc, Toronto, Canada)
Objectives:
The “AIDS epidemic update” (2007) published by the United Nations (UN) and World Health Organization (WHO), reports lower estimates of incidences of persons infected with HIV globally. This study evaluates the cost savings of these lower estimates on costs associated with patients being treated by antiretroviral (ARV) drugs and opportunistic infection (OI) prophylaxis.
A Budget Impact Analysis Of Ixabepilone In Treating Metastatic Cancer Patients
(Finlay Whillans1, Lihua Zhang2, Joanne Ho1, Allen Lising1, Lora Todorova1, Patricia Corey-Lisle3, Yong Yuan2 - 1Dymaxium Inc, Toronto, Canada, 2Bristol-Myers Squibb, Plainsboro, NJ, 3Bristol-Myers Squibb, Wallingford, CT)
Objective:
To evaluate the budget impact to a health plan after introducing Ixabepilone as a treatment option for metastatic breast cancer patients who have previously failed Anthracycline and Taxane based regimen.
Poster Session II
Tuesday, May 6, 2008 - 9:00 AM - 7:00 PM
Determining The Mechanism Of Missing Data In Incomplete Datasets
(Finlay Whillans1, Jean-Eric Tarride2, Gord Blackhouse2, Rob Hopkins2, Ron Goeree2 - 1Dymaxium Inc, Toronto, Canada, 2PATH, Hamilton, Canada )
Objectives:
In any economic study involving individual level data, such as clinical trial data, the problems associated with incomplete observation are an obstacle to analysis. For this reason methods have been developed and debated to complete these datasets. A general consensus has been reached on the superiority of the more robust and computationally intensive methods, namely multiple imputations. But the necessity of such methods are driven by the mechanism of missingness; dataset with the data missing completely at random can be completed with much simpler methods. For this reason the first step in an analysis is to determine the mechanism of missingness.
