<pre><FONT COLOR = BLACK>
<B>Estimating the causal effect of time-dependent antidepressant usage on survival
 </B>
   Lead Investigator:    Ran Duan
   Institution      :    Department of Biostatistics,University of Kentucky
   E-Mail           :    ran.duan@uky.edu
   Proposal ID      :    933
</FONT>
<BR>
   Proposal Description:
   <textarea name="description" rows="12" cols="85" wrap="virtual" readonly>The primary goal of this study is to estimate the causal effect of                time-dependent antidepressant usage on survival of MCI patients using marginal    structural models as a tool of correcting biased estimate using conventional      modeling techniques. The hypothesis is that marginal structural models would      generate less biased estimates in comparison to conventional modeling             techniques.                                                                       We propose to perform a retrospective cohort study among MCI patients using the   Uniform Data Set. Survival time from first diagnosis of MCI would be the          primary outcome of interest. Longitudinal antidepressant usage would be the       primary exposure of interest. Other covariates of interest include age in         years, sex, race, education in years, smoking in years, alcohol consumption,      health conditions and medications that may influence the patients??? survival,    global CDR, GDS score and MMSE score.                                             Findings from this study may help inform the causal effect of long-term           antidepressant usage on survival of MCI patients. </textarea>