added current presentation draft

claude_rewrite
Will King 3 years ago
parent 3b109deeff
commit 209977f4ff

@ -196,7 +196,7 @@ Washington State University \\ % Your institution for the title page
\item current status \item current status
\end{itemize} \end{itemize}
ClinicalTrials.gov also reports the ``history'' from previous ClinicalTrials.gov also reports the history from previous
updates. updates.
\end{frame} \end{frame}
@ -216,7 +216,111 @@ Washington State University \\ % Your institution for the title page
% - Introduce backdoor criterion % - Introduce backdoor criterion
%-------------------------------- %--------------------------------
%-------------------------------
\begin{frame}
\frametitle{Framing my Questions}
Two potential causes of trial termination include
\begin{enumerate}
\item Alternative (competitor) treatments exist
\begin{itemize}
\item reduces future profitability.
\item reduces incentives to enroll as participants.
\end{itemize}
\item It can be difficult to recruit patients
\begin{itemize}
\item Are there few patients?
\item Are potential participants choosing other alternatives?
\end{itemize}
\end{enumerate}
Overall this can be described graphically as:
INSERT IMAGE OF 4 NODES HERE
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Causal Identification: Backdoor Criterion}
%Discuss the two different effects: total effect, direct effects
\begin{columns}
\begin{column}{0.5\textwidth}
Total Effect of Competitors
INSERT TOTAL EFFECT GRAPH
\end{column}
\begin{column}{0.5\textwidth}
Direct Effects of Competitors and Enrollment
INSERT DIRECT EFFECT GRAPH
\end{column}
\end{columns}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Rephrasing Questions}
To rephrase my questions
\begin{enumerate}
\item How large is the total effect of increasing the number of competing drugs on completing clinical trials?
\item How large is the direct effect of increasing the number of competing drugs on completing clincial trials?
\end{enumerate}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Additional Concerns}
%Confounders
Of course, there are other confounding relationships
\begin{enumerate}
\item Population Effects
\item Fundamental Safety and Efficacy of compound/dosage/route
\end{enumerate}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Complete graph}
%introduce backdoor criterion
INSERT COMPLETE GRAPH HERE
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Causal Identification: Backdoor Criterion}
%introduce backdoor criterion
\cite{PEARLYYYY} developed a method of verifying causal identification from DAGs like the one I presented.
Of particular interest is the rule called the Backdoor criterion:
INSERT DESCRIPTION OF THE BACK DOOR CRITERION
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Sufficent Adjustment Set}
%introduce backdoor criterion
INSERT COMPLETE GRAPH HERE with adjustment set highlighted
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Sufficent Adjustment Set}
%introduce backdoor criterion
Thus the required adjustment set includes:
\begin{itemize}
\item Population Measures
\item Safety and Efficacy Measures
\item INSERT MORE
\end{itemize}
\end{frame}
%------------------------------- %-------------------------------
\begin{frame} \begin{frame}
\frametitle{Questions?} \frametitle{Questions?}
@ -236,6 +340,84 @@ Washington State University \\ % Your institution for the title page
% - Data Sizes % - Data Sizes
%-------------------------------- %--------------------------------
%-------------------------------
\begin{frame}
\frametitle{Data Sources}
%TODO: add citations
Data sources
\begin{itemize}
\item ClinicalTrials.gov
\begin{itemize}
\item AACT-CTTI
\item Scraping historical snapshots
\end{itemize}
\item ICD-10 (CMS and WHO)
\item IHME Global Burden of Disease
\item Structured Product Labels
\item USP Drug Classification
\item Drugs@FDA: RxNav / RxNorm / MeSH
\end{itemize}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Linking data}
%
The following linking process was used:
\begin{enumerate}
\item AACT trials to snapshots (internal ID)
\item AACT trials to ICD-10 (hand match)
\item ICD-10 to IHME (IHME)
\item Snapshots to drug brands (RxNorm/RxNav/MeSh, SPL)
\item AACT to USP DC alternates (RxNorm, USP DC, hand match)
\end{enumerate}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Measures of Causes and Effects}
\begin{itemize}
\item Final Status: Measured from AACT - status when trial is over.
\item Competitors on Market: Measured by the number of drugs
\begin{itemize}
\item with same active ingredients (at the time of the snapshot)
\item sharing the USP DC category and class (in 2023)
\end{itemize}
\item Enrollment: Measured by enrollment status at the snapshot level.
\end{itemize}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Adjustment set}
\begin{itemize}
\item Population Measures
\begin{itemize}
\item IHME Global Disease Burden: QUALYs, spread over 5 levels of the Social Development Index
\end{itemize}
\item Beliefs about safety \& efficacy: Restricted to Phase 3 trials.
\item Disease Type: Hierarchal parameters in model
\end{itemize}
Note the implicit conditioning on trials treating diseases with IHME data\footnote{
IHME does not track data for W61.62XD: Struck by duck, subsequent encounter
}.
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Other Details}
Other Trial Selection Criteria
\begin{itemize}
\item Interventional Study
\item Involved an FDA Regulated Drug
\item Phase 3 trial
\item Started after 2010-01-01
\item Ended before 2022-01-01
\end{itemize}
\end{frame}
%------------------------------- %-------------------------------
\begin{frame} \begin{frame}
\frametitle{Questions?} \frametitle{Questions?}

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