claude_rewrite
will king 2 years ago
commit 510ad55d49

@ -52,10 +52,10 @@
\subfile{sections/10_CausalStory} \subfile{sections/10_CausalStory}
\subfile{sections/02_data} \subfile{sections/02_data}
%--------------------------------------------------------------- % %---------------------------------------------------------------
\section{Causal Identification}\label{SEC:CausalIdentification} % \section{Causal Identification}\label{SEC:CausalIdentification}
%--------------------------------------------------------------- % %---------------------------------------------------------------
\subfile{sections/03_CausalIdentification} % \subfile{sections/03_CausalIdentification}
%--------------------------------------------------------------- %---------------------------------------------------------------
\section{Econometric Model}\label{SEC:EconometricModel} \section{Econometric Model}\label{SEC:EconometricModel}

@ -62,7 +62,7 @@ investment directly, causing a trial to terminate early if the return is
not high enough. not high enough.
\begin{figure}[H] %use [H] to fix the figure here. \begin{figure}[H] %use [H] to fix the figure here.
\includegraphics[width=\textwidth]{../assets/img/dagitty-model.jpg} \scalebox{0.6}{\tikzfig{../assets/tikzit/CausalGraph2}}
\caption{Causal Model} \caption{Causal Model}
\label{Fig:CausalModel} \label{Fig:CausalModel}
\end{figure} \end{figure}

@ -47,8 +47,8 @@ The betas are distributed
\end{align} \end{align}
With hyperparameters With hyperparameters
\begin{align} \begin{align}
\mu_k \sim \text{Normal}(0,1) \\ \mu_k \sim \text{Normal}(0,0.05) \\
\sigma_k \sim \text{Gamma}(2,1) \sigma_k \sim \text{Gamma}(4,20)
\end{align} \end{align}

@ -19,97 +19,101 @@ written or requires reparameterization.
%TODO: and info about how I learned about these diagnostics %TODO: and info about how I learned about these diagnostics
\subsubsection{Diagnostics} % \subsubsection{Diagnostics}
%Examine trank plots % %Examine trank plots
To identify which parameters were problematic, I first looked at trace rank % To identify which parameters were problematic, I first looked at trace rank
histograms. % histograms.
Under idea circumstances, each line (representing a chain) should exchange % Under idea circumstances, each line (representing a chain) should exchange
places with the other lines frequently. % places with the other lines frequently.
In both \cref{fig:mu_trank} and \cref{fig:sigma_trank}, most parameters seem % In both \cref{fig:mu_trank} and \cref{fig:sigma_trank}, most parameters seem
to mix well but there are a couple of exceptions. % to mix well but there are a couple of exceptions.
This warrants further investigation. % This warrants further investigation.
%
% \begin{figure}[H]
% \includegraphics[width=\textwidth]{../assets/img/mu_trank.png}
% \caption{Trace Rank Histogram: Mu values}
% \label{fig:mu_trank}
% \end{figure}
%
% \begin{figure}[H]
% \includegraphics[width=\textwidth]{../assets/img/sigma_trank.png}
% \caption{Trace Rank Histogram: Sigma values}
% \label{fig:sigma_trank}
% \end{figure}
%
% %Take a look at batman and points for mu
% In the case of the Mu values, a parallel coordinates plot
% doesn't seem to indicate any parameters as likely candidates
% for causing the issues with divergent transitions.
% \begin{figure}[H]
% \includegraphics[width=\textwidth]{../assets/img/mu_batman.png}
% \caption{Parallel Coordinate Plot: Mu values}
% \label{fig:mu_batman}
% \end{figure}
% Note that at each parameter, there is some level of dispersion between
% values that diverged.
%
% On the other hand, in the parallel coordinates plot for sigma values,
% it appears that most divergent transitions occur with values of
% sigma[1], sigma[3], sigma[6], and sigma[7] close to zero.
% \begin{figure}[H]
% \includegraphics[width=\textwidth]{../assets/img/sigma_batman.png}
% \caption{Parallel Coordinate Plot: Sigma values}
% \label{fig:sigma_batman}
% \end{figure}
% Overall this suggests that there is an issue with the specification
% of the covariance structures of the hyperparameters.
%
% Additional evidence that the covariance structure is incorrect comes from
% plotting pairs of parameter values and examining the chains with divergent
% transitions.
%
% \begin{figure}[H]
% \includegraphics[width=\textwidth]{../assets/img/sigma_pairs_5-9.png}
% \caption{Parameter Pairs plots: Sigma[5] through Sigma[9]}
% \label{fig:sigma_pairs_5-9.png}
% \end{figure}
% From this we can see that divergent pairs are highly correlated with the cases
% where sigma[6] or sigma[7] are equal to zero.
% This has an impact on the shape of both of those estimated parameters, causing
% both to be bimodal.
\begin{figure}[H]
\includegraphics[width=\textwidth]{../assets/img/mu_trank.png}
\caption{Trace Rank Histogram: Mu values}
\label{fig:mu_trank}
\end{figure}
\begin{figure}[H] \subsection{Interpretation}
\includegraphics[width=\textwidth]{../assets/img/sigma_trank.png}
\caption{Trace Rank Histogram: Sigma values}
\label{fig:sigma_trank}
\end{figure}
%Take a look at batman and points for mu The key results so far are related to the distribution of differences in $p$.
In the case of the Mu values, a parallel coordinates plot
doesn't seem to indicate any parameters as likely candidates In figure \ref{fig:pred_dist_dif_delay} we see that there while most trials do not see any increased risk
for causing the issues with divergent transitions. from a delay in closing enrollment, there is a small group that does experience this.
\begin{figure}[H]
\includegraphics[width=\textwidth]{../assets/img/mu_batman.png}
\caption{Parallel Coordinate Plot: Mu values}
\label{fig:mu_batman}
\end{figure}
Note that at each parameter, there is some level of dispersion between
values that diverged.
On the other hand, in the parallel coordinates plot for sigma values,
it appears that most divergent transitions occur with values of
sigma[1], sigma[3], sigma[6], and sigma[7] close to zero.
\begin{figure}[H] \begin{figure}[H]
\includegraphics[width=\textwidth]{../assets/img/sigma_batman.png} \includegraphics[width=\textwidth]{../assets/img/current/pred_dist_diff-delay}
\caption{Parallel Coordinate Plot: Sigma values} \caption{}
\label{fig:sigma_batman} \label{fig:pred_dist_diff_delay}
\end{figure} \end{figure}
Overall this suggests that there is an issue with the specification
of the covariance structures of the hyperparameters.
Additional evidence that the covariance structure is incorrect comes from
plotting pairs of parameter values and examining the chains with divergent
transitions.
Figure \ref{fig:pred_dist_dif_delay2} shows how this varies across disease categories
\begin{figure}[H] \begin{figure}[H]
\includegraphics[width=\textwidth]{../assets/img/sigma_pairs_5-9.png} \includegraphics[width=\textwidth]{../assets/img/current/pred_dist_diff-delay-group}
\caption{Parameter Pairs plots: Sigma[5] through Sigma[9]} \caption{}
\label{fig:sigma_pairs_5-9.png} \label{fig:pred_dist_dif_delay2}
\end{figure} \end{figure}
From this we can see that divergent pairs are highly correlated with the cases
where sigma[6] or sigma[7] are equal to zero.
This has an impact on the shape of both of those estimated parameters, causing
both to be bimodal.
\subsection{Interpretation}
Ignoring the diagnosed issues with the model, we do see some interesting
preliminary results.
%in mu, mu[5] shifted strongly
In \cref{fig:mu_posterior} we see that mu[5], the parameter corresponding
to enrollment appears to be strongly negative.
This is consistent with the idea that enrollment close to planned enrollment
decreases the probability of terminating the trial.
In \cref{fig:sigma_posterior}, sigma[2] (corresponding to the number of brands
selling the drug of interest) has a large variance covers some relatively
high values.
This suggests that the impact of how frequently the drug is sold varies greatly
across different ICD-10 categories of disease.
We can also examine the direct effect from adding a single generic competitior drug.
\begin{figure}[H] \begin{figure}[H]
\includegraphics[width=\textwidth]{../assets/img/mu_posterior.png} \includegraphics[width=\textwidth]{../assets/img/current/pred_dist_diff-generic}
\caption{Posterior Parameter Estimates: Mu} \caption{}
\label{fig:mu_posterior} \label{fig:pred_dist_diff_generic}
\end{figure} \end{figure}
% Sigma[2] suggests there is a high variance in the impact that the number of drugs on the market has. Figure \ref{fig:pred_dist_dif_generic2} shows how this varies across disease categories
\begin{figure}[H] \begin{figure}[H]
\includegraphics[width=\textwidth]{../assets/img/sigma_posterior.png} \includegraphics[width=\textwidth]{../assets/img/current/pred_dist_diff-generic-group}
\caption{Posterior Hyperparameter Estimates: Sigma} \caption{}
\label{fig:sigma_posterior} \label{fig:pred_dist_dif_generic2}
\end{figure} \end{figure}
Due to the deficiencies in the data and model, this is the limit of the
analysis I will perform at this time.
\end{document} \end{document}

@ -62,7 +62,7 @@ investment directly, causing a trial to terminate early if the return is
not high enough. not high enough.
\begin{figure}[H] %use [H] to fix the figure here. \begin{figure}[H] %use [H] to fix the figure here.
\includegraphics[width=\textwidth]{../assets/img/dagitty-model.jpg} \scalebox{0.6}{\tikzfig{../assets/tikzit/CausalGraph2}}
\caption{Causal Model} \caption{Causal Model}
\label{Fig:CausalModel} \label{Fig:CausalModel}
\end{figure} \end{figure}

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@ -27,6 +27,7 @@
\input{../assets/preambles/BibPreamble.tex} \input{../assets/preambles/BibPreamble.tex}
\input{../assets/preambles/GeneralPreamble.tex} \input{../assets/preambles/GeneralPreamble.tex}
\addbibresource{/home/will/research/ClinicalTrialsPaper/Latex/assets/preambles/References.bib}
%---------------------------------------------------------------------------------------- %----------------------------------------------------------------------------------------
% TITLE PAGE % TITLE PAGE
@ -445,19 +446,20 @@ Washington State University \\ % Your institution for the title page
Thus the required adjustment set depends on the effects of interest. Thus the required adjustment set depends on the effects of interest.
For the total effect these are controls for: For the total effect:
\begin{itemize} \begin{itemize}
\item Proceed with Phase III \item Proceed with Phase III
\item Condition \item Condition
\item Population \item Population
\end{itemize} \end{itemize}
For the direct effect these are controls for: For the direct effect:
\begin{itemize} \begin{itemize}
\item Proceed with Phase III \item Proceed with Phase III
\item Condition \item Condition
\item Population (optional) \item Population (optional)
\item Enrollment \item Enrollment Status
\item Elapsed Duration
\end{itemize} \end{itemize}
\end{frame} \end{frame}
@ -736,24 +738,53 @@ Washington State University \\ % Your institution for the title page
\begin{frame} \begin{frame}
\frametitle{Total Effects Model} \frametitle{Total Effects Model}
%TODO: describe X\beta %TODO: describe X\beta
\begin{itemize}
\item asinh(brands with identical ingredients)
\item asinh(brands in USP-DC category)
\item asinh(high sdi DALY estimate)
\item asinh(high-medium sdi DALY estimate)
\item asinh(medium sdi DALY estimate)
\item asinh(low-medium sdi DALY estimate)
\item asinh(low sdi DALY estimate)
\end{itemize}
Units of observation: Snapshots
\end{frame} \end{frame}
%------------------------------- %-------------------------------
\begin{frame} \begin{frame}
\frametitle{Direct Effects Model} \frametitle{Direct Effects Model}
%TODO: describe X\beta %TODO: describe X\beta
\begin{itemize}
\item elapsed duration
\item enrollment status
\item asinh(brands with identical ingredients)
\item asinh(brands in USP-DC category)
\item asinh(high sdi DALY estimate)
\item asinh(high-medium sdi DALY estimate)
\item asinh(medium sdi DALY estimate)
\item asinh(low-medium sdi DALY estimate)
\item asinh(low sdi DALY estimate)
\end{itemize}
Units of Observation: Snapshot
\end{frame} \end{frame}
%------------------------------- %-------------------------------
\begin{frame} \begin{frame}
\frametitle{Analysis} \frametitle{Analysis}
Review: For each effect, we will look at:
\begin{itemize} \begin{itemize}
\item Hyperparameters \item Distribution of Parameters of Interest
\item Parameters of Interest
\item Distrbution of Predicted Differences (Hypothetical Causal Intervention) \item Distrbution of Predicted Differences (Hypothetical Causal Intervention)
\end{itemize} \end{itemize}
\vspace{12pt}
The interventions are:
\begin{itemize}
\item Adding a single brand to the generic market competitors
\item Adding a single brand to the USP DC market competitors
\end{itemize}
\end{frame} \end{frame}
%------------------------------- %-------------------------------
\begin{frame} \begin{frame}
@ -767,29 +798,30 @@ Washington State University \\ % Your institution for the title page
%-------------------------------- %--------------------------------
%------------------------------- %-------------------------------
\begin{frame} \begin{frame}
\frametitle{Priors - Mu} \frametitle{Data Summaries}
\begin{figure} \begin{figure}
% \includegraphics[height=0.8\textheight]{../assets/img/Images/} \includegraphics[height=0.8\textheight]{/home/will/research/ClinicalTrialsPaper/Latex/Presentation/Images/HistTrialDurations_Faceted.png}
\label{FIG:Prior:Mu}
\caption{Prior - Mu}
\end{figure} \end{figure}
\end{frame} \end{frame}
%------------------------------- %-------------------------------
\begin{frame} \begin{frame}
\frametitle{Priors - Sigma} \frametitle{Data Summaries}
\begin{figure} \begin{figure}
% \includegraphics[height=0.8\textheight]{../assets/img/Images/} \includegraphics[height=0.8\textheight]{/home/will/research/ClinicalTrialsPaper/Latex/Presentation/Images/HistSnapshots.png}
\label{FIG:Prior:Sigma}
\caption{Prior - Sigma}
\end{figure} \end{figure}
\end{frame} \end{frame}
%------------------------------- %-------------------------------
\begin{frame} \begin{frame}
\frametitle{Priors - $p$} \frametitle{Data Summaries}
\begin{figure} \begin{figure}
% \includegraphics[height=0.8\textheight]{../assets/img/Images/} \includegraphics[height=0.8\textheight]{/home/will/research/ClinicalTrialsPaper/Latex/Presentation/Images/SnapshotsVsDurationVsTermination.png}
\label{FIG:Prior:p} \end{figure}
\caption{Prior - $p$} \end{frame}
%-------------------------------
\begin{frame}
\frametitle{Data Summaries}
\begin{figure}
\includegraphics[height=0.8\textheight]{/home/will/research/ClinicalTrialsPaper/Latex/Presentation/Images/CategoryCounts.png}
\end{figure} \end{figure}
\end{frame} \end{frame}
%-------------------------------- %--------------------------------
@ -803,29 +835,96 @@ Washington State University \\ % Your institution for the title page
% - Distributions % - Distributions
% - Review Posterior Prediction for interventions % - Review Posterior Prediction for interventions
%-------------------------------- %--------------------------------
%%-------------------------------
%\begin{frame}
% \frametitle{Priors - Mu}
% \begin{figure}
%% \includegraphics[height=0.8\textheight]{../assets/img/Images/}
% \label{FIG:Prior:Mu}
% \caption{Prior - Mu}
% \end{figure}
%\end{frame}
%%-------------------------------
%\begin{frame}
% \frametitle{Priors - Sigma}
% \begin{figure}
%% \includegraphics[height=0.8\textheight]{../assets/img/Images/}
% \label{FIG:Prior:Sigma}
% \caption{Prior - Sigma}
% \end{figure}
%\end{frame}
%------------------------------- %-------------------------------
\begin{frame} \begin{frame}
\frametitle{Results} \frametitle{Priors - $p$}
Because Bayesian estimation is typically done numerically, we will first \begin{figure}
validate convergence. \includegraphics[height=0.8\textheight]{/home/will/research/ClinicalTrialsPaper/Latex/Presentation/Images/TotalEffects/prior_p.png}
\label{FIG:Prior:p}
Then we will take a look at preliminary results. \caption{Prior prediction - $p$}
\end{figure}
Sampling details \end{frame}
%-------------------------------
%TODO: Update \begin{frame}
\begin{itemize} \frametitle{Posteriors - $\beta$ Competing Brands}
\item 4 chains \begin{figure}
\item 2,500 warm-up, 2,500 sampling runs \includegraphics[height=0.8\textheight]{/home/will/research/ClinicalTrialsPaper/Latex/Presentation/Images/TotalEffects/Parameters/1&2_generics_and_uspdc.png}
\item seed = 11021585 \label{FIG:Posterior:beta-brands-total}
\end{itemize} \end{figure}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Predictive Posteriors - $p$ - no intervention}
\begin{figure}
\includegraphics[height=0.8\textheight]{/home/will/research/ClinicalTrialsPaper/Latex/Presentation/Images/TotalEffects/posterior_p.png}
\label{FIG:Prior:p}
\caption{Posterior prediction - $p$}
\end{figure}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Posteriors - $p$ with intervention (generics)}
\begin{figure}
\includegraphics[height=0.8\textheight]{/home/will/research/ClinicalTrialsPaper/Latex/Presentation/Images/TotalEffects/default_p_generic_intervention_interv.png}
\label{FIG:Prior:p-intervention_total}
\end{figure}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Distribution of Differences - Generics Intervention}
\begin{figure}
\includegraphics[height=0.8\textheight]{/home/will/research/ClinicalTrialsPaper/Latex/Presentation/Images/TotalEffects/default_p_generic_intervention_distdiff.png}
\label{FIG:Prior:p-intervention_total}
\end{figure}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Distribution of Differences - Generics Intervention | By group}
\begin{figure}
\includegraphics[height=0.8\textheight]{/home/will/research/ClinicalTrialsPaper/Latex/Presentation/Images/TotalEffects/p_generic_intervention_histdiff_by_group.png}
\label{FIG:Prior:p-intervention_total}
\end{figure}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Posteriors - $p$ with intervention (USP DC)}
\begin{figure}
% \includegraphics[height=0.8\textheight]{../assets/img/Images/}
\includegraphics[height=0.8\textheight]{/home/will/research/ClinicalTrialsPaper/Latex/Presentation/Images/TotalEffects/p_uspdc_intervention_distdiff_styled.png}
\label{FIG:Prior:p-intervention_total}
\end{figure}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Posteriors - $p$ with intervention (USP DC) by group}
\begin{figure}
\includegraphics[height=0.8\textheight]{/home/will/research/ClinicalTrialsPaper/Latex/Presentation/Images/TotalEffects/p_uspdc_intervention_distdiff_by_group.png}
\label{FIG:Prior:p-intervention_total}
\end{figure}
\end{frame} \end{frame}
%------------------------------- %-------------------------------
\begin{frame} \begin{frame}
\frametitle{Questions?} \frametitle{Questions?}
\end{frame} \end{frame}
%-------------------------------
%-------------------------------- %--------------------------------
\subsubsection{Direct Effects} \subsubsection{Direct Effects}
% - Review Parameter Values % - Review Parameter Values
@ -839,14 +938,62 @@ Washington State University \\ % Your institution for the title page
%-------------------------------- %--------------------------------
%------------------------------- %-------------------------------
\begin{frame} \begin{frame}
\frametitle{Convergence} \frametitle{Posteriors - $\beta$ Competing Brands}
Sampling details \begin{figure}
%TODO: UPDATE \includegraphics[height=0.8\textheight]{/home/will/research/ClinicalTrialsPaper/Latex/Presentation/Images/DirectEffects/Parameters/2+3_generic_and_uspdc.png}
\begin{itemize} \label{FIG:Posterior:beta-brands-total}
\item 6 chains \caption{Posterior prediction - $\beta$}
\item 2,500 warm-up, 2,500 sampling runs \end{figure}
\item seed = 11021585 \end{frame}
\end{itemize} %-------------------------------
\begin{frame}
\frametitle{Predictive Posteriors - $p$ - no intervention}
\begin{figure}
\includegraphics[height=0.8\textheight]{/home/will/research/ClinicalTrialsPaper/Latex/Presentation/Images/DirectEffects/posterior_p.png}
\label{FIG:Prior:p}
\caption{Posterior prediction - $p$}
\end{figure}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Posteriors - $p$ with intervention (generics)}
\begin{figure}
\includegraphics[height=0.8\textheight]{/home/will/research/ClinicalTrialsPaper/Latex/Presentation/Images/DirectEffects/default_p_generic_intervention_interv.png}
\label{FIG:Prior:p-intervention_total}
\end{figure}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Distribution of Differences - Generics Intervention}
\begin{figure}
\includegraphics[height=0.8\textheight]{/home/will/research/ClinicalTrialsPaper/Latex/Presentation/Images/DirectEffects/default_p_generic_intervention_distdiff.png}
\label{FIG:Prior:p-intervention_total}
\end{figure}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Distribution of Differences - Generics Intervention | By group}
\begin{figure}
\includegraphics[height=0.8\textheight]{/home/will/research/ClinicalTrialsPaper/Latex/Presentation/Images/DirectEffects/p_generic_intervention_histdiff_by_group.png}
\label{FIG:Prior:p-intervention_total}
\end{figure}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Posteriors - $p$ with intervention (USP DC)}
\begin{figure}
% \includegraphics[height=0.8\textheight]{../assets/img/Images/}
\includegraphics[height=0.8\textheight]{/home/will/research/ClinicalTrialsPaper/Latex/Presentation/Images/DirectEffects/p_uspdc_intervention_distdiff_styled.png}
\label{FIG:Prior:p-intervention_total}
\end{figure}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Posteriors - $p$ with intervention (USP DC) by group}
\begin{figure}
\includegraphics[height=0.8\textheight]{/home/will/research/ClinicalTrialsPaper/Latex/Presentation/Images/DirectEffects/p_uspdc_intervention_histdiff_by_group.png}
\label{FIG:Prior:p-intervention_total}
\end{figure}
\end{frame} \end{frame}
%------------------------------- %-------------------------------
\begin{frame} \begin{frame}
@ -865,13 +1012,27 @@ Washington State University \\ % Your institution for the title page
\begin{enumerate} \begin{enumerate}
\item Match more trials to ICD-10 codes and Formularies \item Match more trials to ICD-10 codes and Formularies
\item Add more formularies \item Add more formularies
\item Remove disease categories that don't exist in the data from the priors \item Remove disease categories that don't exist in the data.
\item Imputing Enrollment \item Imputing Enrollment
\item Add covariance terms to $\beta$.
\end{enumerate} \end{enumerate}
Suggestions?
\end{frame} \end{frame}
%------------------------------- %-------------------------------
\begin{frame} \begin{frame}
\frametitle{Summary} \frametitle{Summary}
Results Summary
\begin{enumerate}
\item A trial's response to adding a competitor drug depends on:
\begin{itemize}
\item Whether the drug is a generic or not
\item The disease category that applies to the trial
\end{itemize}
The effects suggest that the enrollment pathway had a strong regulating effect.
\item
\end{enumerate}
\end{frame} \end{frame}
%------------------------------- %-------------------------------
\begin{frame} \begin{frame}
@ -885,75 +1046,49 @@ Washington State University \\ % Your institution for the title page
%------------------------------------------------------------------------------------- %-------------------------------------------------------------------------------------
%---------------------------------- %----------------------------------
%%%%%%%%%%%%%%%%%%%% Convergence Tests %%%%%%%%%%%%%%%%%%%% Convergence Tests
\subsection{Convergence} %\subsection{Convergence}
%---------------------------------- %----------------------------------
%------------------------------- %-------------------------------
\begin{frame}
\frametitle{Warnings}
%TODO: UPDATE
\begin{itemize}
\item There were no diverging transitions.
\item There were 15,000 transitions that exceeded max treedepth.
Sampling efficiency is poor.
\item All chains had low Bayesian Fraction of Missing Information.
Some areas of the distribution were poorly explored.
\item R-hat = $1.23$, ideal is around 1, chains did not mix well.
\item Bulk and Tail Effective Sample sizes were low,
suggesting mean and variance/quantile estimates will be unreliable.
\end{itemize}
\cite{mc-stan}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Convergence: Mu}
\begin{figure}
%TODO: UPDATE
%\includegraphics[height=0.9\textheight]{../assets/img/2023-04-11_mu_points.png}
\label{FIG:caption}
\caption{Hyperparameter Points Plots: Mu}
\end{figure}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Convergence: Sigma}
\begin{figure}
%TODO: UPDATE
%\includegraphics[height=0.9\textheight]{../assets/img/2023-04-11_mu_points.png}
\label{FIG:caption}
\caption{Hyperparameter Points Plots: Sigma}
\end{figure}
\end{frame}
%-------------------------------
\begin{frame}[allowframebreaks]
\frametitle{Bibliography}
\printbibliography
\end{frame}
%-------------------------------
\end{document}
%=========================================
%\begin{frame} %\begin{frame}
% \frametitle{MarginalRevenue} % \frametitle{Warnings}
% %TODO: UPDATE
%
% \begin{itemize}
% \item There were no diverging transitions.
% \item There were 15,000 transitions that exceeded max treedepth.
% Sampling efficiency is poor.
% \item All chains had low Bayesian Fraction of Missing Information.
% Some areas of the distribution were poorly explored.
% \item R-hat = $1.23$, ideal is around 1, chains did not mix well.
% \item Bulk and Tail Effective Sample sizes were low,
% suggesting mean and variance/quantile estimates will be unreliable.
% \end{itemize}
% \cite{mc-stan}
%\end{frame}
%%-------------------------------
%\begin{frame}
% \frametitle{Convergence: Mu}
% \begin{figure} % \begin{figure}
% \tikzfig{../Assets/owned/ch8_MarginalRevenue} % %TODO: UPDATE
% \includegraphics[height=\textheight]{../Assets/copyrighted/KrugmanObsterfeldMeliz_fig8-7.jpg} % %\includegraphics[height=0.9\textheight]{../assets/img/2023-04-11_mu_points.png}
% \label{FIG:costs} % \label{FIG:caption}
% \caption{Average Cost Curve as firms enter.} % \caption{Hyperparameter Points Plots: Mu}
% \end{figure} % \end{figure}
%\end{frame} %\end{frame}
%------------------------------- %%-------------------------------
%\begin{frame} %\begin{frame}
% \frametitle{Columns} % \frametitle{Convergence: Sigma}
% \begin{columns}
% \begin{column}{0.5\textwidth}
% \end{column}
% \begin{column}{0.5\textwidth}
% \begin{figure} % \begin{figure}
% \tikzfig{../Assets/owned/ch7_EstablishedAdvantageExample2} % %TODO: UPDATE
% \label{FIG:costs} % %\includegraphics[height=0.9\textheight]{../assets/img/2023-04-11_mu_points.png}
% \caption{Setting the Stage} % \label{FIG:caption}
% \caption{Hyperparameter Points Plots: Sigma}
% \end{figure} % \end{figure}
% \end{column}
% \end{columns}
%\end{frame} %\end{frame}
% %--------------------------------------------------------------- %%-------------------------------
\begin{frame}[allowframebreaks]
\frametitle{Bibliography}
\printbibliography
\end{frame}
%-------------------------------
\end{document}

@ -1,573 +0,0 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Beamer Presentation
% LaTeX Template
% Version 1.0 (10/11/12)
%
% This template has been downloaded from:
% http://www.LaTeXTemplates.com
%
% License:
% CC BY-NC-SA 3.0 (http://creativecommons.org/licenses/by-nc-sa/3.0/)
%
% Changed theme to WSU by William King
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%----------------------------------------------------------------------------------------
% PACKAGES AND THEMES
%----------------------------------------------------------------------------------------
\documentclass[xcolor=dvipsnames,aspectratio=169]{beamer}
%Import Preamble bits
\input{../assets/preambles/FormattingPreamble.tex}
\input{../assets/preambles/TikzitPreamble.tex}
\input{../assets/preambles/MathPreamble.tex}
\input{../assets/preambles/BibPreamble.tex}
\input{../assets/preambles/GeneralPreamble.tex}
%----------------------------------------------------------------------------------------
% TITLE PAGE
%----------------------------------------------------------------------------------------
\title[Clinical Trials]{The Effects of Market Conditions on Recruitment and Completion of Clinical Trials}
\author{Will King} % Your name
\institute[WSU] % Your institution as it will appear on the bottom of every slide, may be shorthand to save space
{
Washington State University \\ % Your institution for the title page
\medskip
\textit{william.f.king@wsu.edu} % Your email address
}
\date{\today} % Date, can be changed to a custom date
\begin{document}
\begin{frame}
\titlepage % Print the title page as the first slide
\end{frame}
%----------------------------------
\begin{frame} %Allow frame breaks
\frametitle{Clincial Trials} % Table of contents slide, comment this out to remove it
% - Intro and hook (Clinical Trials are key part of pharmacological pipeline)
Pharmaceuticals are a frequently discussed aspect of health care cost managment.
Their development is dictated by scientific and regulatory hurdles
including passing clinical trials
(\cite{noauthor_fda_nodate}),
while their market is characterized by strategic competition and ambiguous
patent protection
(\cite{van_der_gronde_addressing_2017}).
\vspace{12pt}
This research investigates the pathways by which market conditions
affect clinical trial completion.
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{This research}
\textbf{Questions:}
\begin{enumerate}
\item Does the existence of alternative drugs on the market make it
harder for clinical trials to complete successfully?
\item How much of this is occurs due to increased recruitment difficulty?
\end{enumerate}
\end{frame}
%--------------------------------
\begin{frame}
\frametitle{Thanks} % Table of contents slide, comment this out to remove it
Thanks to Chris Adams and Rebecca Sachs of the Congressional Budget Office.
\end{frame}
%--------------------------------
\begin{frame}[allowframebreaks] %Allow frame breaks
\frametitle{Overview} % Table of contents slide, comment this out to remove it
\tableofcontents
% - Intro and hook
% - Literature review
% - Causal Identification
% - Data
% - Econometric model
% - Results
% - Improvements
\end{frame}
%-------------------------------------------------------------------------------------
%%%%%%%%%%%%%%%%%%%% Lit Review %%%%%%%%%%%%%%%%%%%%%%%%
\section{Lit Review}
% First slide:
%-------------------------------------------------------------------------------------
%-------------------------------
\begin{frame}
\frametitle{Literature Highlights}
\begin{itemize}
\item \cite{van_der_gronde_addressing_2017}:
High level synthesis of overall discussion regarding drug costs.
Both academic and non-academic sources.
\item \cite{hwang_failure_2016}:
Answered the question "Why do late-stage (phase III) trials fail?"
Found that efficacy, safety, and competition reasons accounted for
57\%, 17\%, and 22\% respectively.
\item \cite{abrantes-metz_pharmaceutical_2004}:
Described how drugs progress through the 3 phases of clinical trials
and correllations between various trial characteristics and the
clinical trial failures.
\item \cite{khmelnitskaya_competition_2021}:
Modeled clinical trial lifecycle of drugs, found method to separate
scientific from competitive reasons for failure to progress to the
next phase.
% \item \cite{}:
\end{itemize}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{This research, in context}
In contrast to previous work looking at multiple phases of trials,
I seek to figure out what causes individual trials to fail.
\vspace{12pt}
Instead of focusing on the drug development pipeline, I attempt to
investigate the population of drug-based, phase III trials.
\end{frame}
%-------------------------------
\begin{frame} %Allow frame breaks
\frametitle{Why this approach?} % Table of contents slide, comment this out to remove it
\begin{figure}
\includegraphics[height=0.8\textheight]{../assets/img/methodology_trial.png}
\label{FIG:xkcd2726}
\caption{``If you think THAT'S unethical, you should see the stuff we approved via our Placebo IRB.''
- \url{https://xkcd.com/2726}
}
\end{figure}
\end{frame}
%-------------------------------------------------------------------------------------
%%%%%%%%%%%%%%%%%%%% Causal Identification / DGP%%%%%%%%%%%%%%%%%%%%%%%%
\section{Causal Model}
% Data Generating process
% - Agents and their decisions
% - Factors that influence each decision
% -
% -
%-------------------------------------------------------------------------------------
%-------------------------------
\begin{frame}
\frametitle{Data Generating Process}
% study sponsors
Study Sponsors Decide to start a Phase 3 trial and whether to terminate it.
\\
They ask themselves:
\begin{itemize}
\item Do safety incidents require terminating a trial?
\item Do efficacy results indicate the trial is worth continuing?
\item Is recruiting sufficient to achieve our results and contain costs?
\item Do expectations about future returns justify our expenditures?
\end{itemize}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Data Generating Process}
% participants
Participants decide to enroll (and disenroll) themselves in a trial based
\begin{itemize}
\item Disease severity
\item Relative safety/efficacy compared to other treatments
\end{itemize}
Study sponsors plan their enrollment considering
\begin{itemize}
\item Total population affected
\item Likely participant response rates
\end{itemize}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Data Generating Process}
% Trial Snapshots and dependencies.
During a trial, the study sponsor reports snapshots of their trial.
This includes updates to:
\begin{itemize}
\item enrollment (actual or anticipated)
\item current recruitment status (Recruiting, Active not recruiting, etc)
\item study sponsor
\item planned completion dates
\item elapsed duration
\end{itemize}
Note that final enrollment and the final status (Completed or Terminated)
of the trial are jointly determined.
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Causal Diagram: Key Pathways}
% Estimating Direct vs Total Effects
\begin{figure}
\resizebox{!}{0.5\textheight}{
\tikzfig{../assets/tikzit/CausalGraph}
}
\label{FIG:CausalDiagram}
\caption{Causal Diagram highlighting direct and total pathways}
\end{figure}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Causal Diagram: Backdoor Crieterion}
\small
\begin{block}{$d$-separation}
A set $S$ of nodes blocks a path $p$ if either
\begin{enumerate}
\item $p$ contains at least one arrow-emitting node in $S$
\item $p$ contains at least one collision node $c$ that is outside $S$
and has no descendants in $S$.
\end{enumerate}
If $S$ blocks all paths from X to Y, then it is said to ``$d$-separate''
$X$ and $Y$, and then $X \perp Y | S$.
\end{block}
\begin{block}{Back-Door Criterion}
A set $S$ of covariates is admisible as controls on the
causal relationship $X \rightarrow Y$ if:
\begin{enumerate}
\item No element of $S$ is a decendant of $X$
\item The elements of $S$ d-separate all paths from $X$ to $Y$ that include
parents of $X$.
\end{enumerate}
\end{block}
\cite{pearl_causality_2000}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Causal Diagram}
Key takeaways
\begin{itemize}
\item Measuring enrollment prior to trial completion is necessary for causal identification.
\item The backdoor criterion gives us the following adjustment sets:
\begin{itemize}
\item Total Effect for Market on Termination; Population, Condition, Phase III
\item Direct Effects for Enrollment, Market on Termination; Population, Condition Phase III,
Elapsed Duration, Planned Enrollment
\end{itemize}
\item Enrollment requires imputation
\end{itemize}
\end{frame}
%-------------------------------------------------------------------------------------
%%%%%%%%%%%%%%%%%%%% Data %%%%%%%%%%%%%%%%%%%%%%%%
\section{Data}
%-------------------------------------------------------------------------------------
%----------------------------------
%%%%%%%%%%%%%%%%%%%% Sources
\subsection{Sources}
%----------------------------------
%-------------------------------
\begin{frame} %Allow frame breaks
\frametitle{Data Sources}
\begin{itemize}
\item ClinicalTrials.gov - AACT \& custom scripts
\begin{itemize}
\item Select trials of interest
\item Trial details:
\begin{itemize}
\item conditions
\item final status
\item drugs/interventions
\end{itemize}
\item Trial snapshots:
\begin{itemize}
\item enrollment (anticipated, planned, or actual)
\item elapsed duration
\item current status
\end{itemize}
\end{itemize}
\item Medical Subject Headings (MeSH) Thesaurus
\begin{itemize}
\item A standardized nomenclature used to classify interventions
and conditions in the clinical trials database.
\end{itemize}
\end{itemize}
\end{frame}
%-------------------------------
\begin{frame} %Allow frame breaks
\frametitle{Data Sources}
\begin{itemize}
\item NSDE Files (New drug code Structured product labels Data Element)
\begin{itemize}
\item Contains information about when a given drug was on the market.
\end{itemize}
\item RxNorm
\begin{itemize}
\item Links pharmaceuticals between MeSH standardized terms and
NSDE files.
\end{itemize}
\item Global Disease Burden Survey (2019)
\begin{itemize}
\item Estimates of DALYs for categories of disease
\item Links of Categories to ICD-10 Codes
\end{itemize}
\item ICD-10 (2019)
\begin{itemize}
\item WHO version
\item CMS version (Clinical Managment)
\item Used to group disease conditions in hierarchal model
\end{itemize}
\item Unified Medical Language System Thesaurus
\begin{itemize}
\item Used to link MeSH standardized terms and ICD-10 conditions
\item Manual matching process
\end{itemize}
\end{itemize}
\end{frame}
%----------------------------------
%%%%%%%%%%%%%%%%%%%% Integration
\subsection{Integration}
%----------------------------------
%-------------------------------
\begin{frame}
\frametitle{Data Summaries}
%put summaries now
\begin{itemize}
\item Number of Phase III, FDA monitored Drug Trials: 1,981
\item Number of Trials matched to ICD-10: 186
\item Number of Trials matched to ICD-10 with population measures: 67
(51 completed, 16 terminated)
\item Number of Snapshots: 616
\end{itemize}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Data used}
The following data points were used.
\begin{itemize}
\item elapsed duration
\item asinh(number of brands)
\item asinh(high sdi DALY estimate)
\item asinh(high-medium sdi DALY estimate)
\item asinh(medium sdi DALY estimate)
\item asinh(low-medium sdi DALY estimate)
\item asinh(low sdi DALY estimate)
\end{itemize}
The asinh operator was used because it parallells $\text{ln}(x)$ for
large values of $x$ but also handles $\text{asinh}(0)=0$.
\end{frame}
%----------------------------------
\begin{frame}
\frametitle{Summaries: Trial Durations}
\begin{figure}
\includegraphics[height=0.8\textheight]{../assets/img/2023-04-12_durations_hist.png}
\label{FIG:durations}
\caption{Trial Durations (days)}
\end{figure}
\end{frame}
%----------------------------------
\begin{frame}
\frametitle{Summaries: snapshots}
\begin{figure}
\includegraphics[height=0.8\textheight]{../assets/img/2023-04-12_snapshots_hist.png}
\label{FIG:snapshots}
\caption{Number of Snapshots per matched trial}
\end{figure}
\end{frame}
%----------------------------------
\begin{frame}
\frametitle{Summaries: snapshots}
\begin{figure}
\includegraphics[height=0.8\textheight]{../assets/img/2023-04-12_status_duration_snapshots_points.png}
\label{FIG:snapshot_duration_scatter}
\caption{Scatterplot of snapshot count and durations}
\end{figure}
\end{frame}
%-------------------------------------------------------------------------------------
%%%%%%%%%%%%%%%%%%%% Econometric Model %%%%%%%%%%%%%%%%%%%%%%%%
\section{Econometric model}
%-------------------------------------------------------------------------------------
%-------------------------------
\begin{frame}
\frametitle{Econometric Model}
Estimating the total effect of brands on market
\begin{align}
y_n &\sim \text{Bernoulli}(p_n) \\
p_n &= \text{logisticfn}(x_n * \beta(d_n)) \\
\beta_k(d) &\sim \text{Normal}(\mu_k, \sigma_k) \\
\mu_k &\sim \text{Normal}(0,1) \\
\sigma_k &\sim \text{Gamma}(2,1)
\end{align}
$k$ indexes parameters and $d_n$ represets the ICD-10 group the trial corresponds to.
\end{frame}
%-------------------------------------------------------------------------------------
%%%%%%%%%%%%%%%%%%%% Results %%%%%%%%%%%%%%%%%%%%%%%%
\section{Results}
%-------------------------------------------------------------------------------------
%-------------------------------
\begin{frame}
\frametitle{Results}
Because bayesian estimation is typically done numerically, we will first
validate convergence.
Then we will take a look at preliminary results.
Sampling details
\begin{itemize}
\item 6 chains
\item 2,500 warmup, 2,500 sampling runs
\item seed = 11021585
\end{itemize}
\end{frame}
%----------------------------------
%%%%%%%%%%%%%%%%%%%% Convergence Tests
\subsection{Convergence}
%----------------------------------
%-------------------------------
\begin{frame}
\frametitle{Warnings}
\begin{itemize}
\item There were no diverging transitions.
\item There were 15,000 transitions that exceeded max treedepth.
Sampling efficiency is poor.
\item All chains had low Bayesian Fraction of Missing Information.
Some areas of the distribution were poorly explored.
\item R-hat = $1.23$, ideal is around 1, chains did not mix well.
\item Bulk and Tail Effective Sample sizes were low,
suggesting mean and variance/quantile estimates will be unreliable.
\end{itemize}
\cite{mc-stan}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Convergence: Mu}
\begin{figure}
\includegraphics[height=0.9\textheight]{../assets/img/2023-04-11_mu_points.png}
\label{FIG:caption}
\caption{Hyperparameter Points Plots: Mu}
\end{figure}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Convergence: Sigma}
\begin{figure}
\includegraphics[height=0.8\textheight]{../assets/img/2023-04-11_sigma_points.png}
\label{FIG:caption}
\caption{Hyperparameter Points Plots: Sigma}
\end{figure}
\end{frame}
%----------------------------------
%%%%%%%%%%%%%%%%%%%% Preliminary Results
\subsection{Preliminary Results}
%----------------------------------
%-------------------------------
\begin{frame}
\frametitle{Preliminary Results: Mu}
\begin{columns}
\begin{column}{0.3\textwidth}
\begin{enumerate}
\item elapsed duration
\item asinh(n\_brands)
\item asinh(high sdi)
\item asinh(high-medium sdi)
\item asinh(medium sdi)
\item asinh(low-medium sdi)
\item asinh(low sdi)
\end{enumerate}
\end{column}
\begin{column}{0.7\textwidth}
\begin{figure}
\includegraphics[height=0.8\textheight]{../assets/img/2023-04-11_mu_dist.png}
\label{FIG:caption}
\caption{Hyperparameter Distribution: Mu}
\end{figure}
\end{column}
\end{columns}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Preliminary Results: Sigma}
\begin{figure}
\includegraphics[height=0.8\textheight]{../assets/img/2023-04-11_sigma_dist.png}
\label{FIG:caption}
\caption{Hyperparameter Distribution: Sigma}
\end{figure}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Interpretation}
All of the following interpretations are done in the context of insufficient data
\begin{enumerate}
\item Elapsed Duration (Mu[1]): Trending Negative, reduced probability of termination.
\item Number of Brands(Mu[2]): Trending Positive, increased probability of termination.
\item Population Measures (Mu[3]-Mu[7])
\begin{enumerate}
\item What is most surprising is that these are both positive and negative.
Probably need more data.
\end{enumerate}
\item It is surprising to see the wide distribution in sigma values.
\end{enumerate}
\end{frame}
%-------------------------------------------------------------------------------------
%%%%%%%%%%%%%%%%%%%% Improvements %%%%%%%%%%%%%%%%%%%%%%%%
\section{Improvements}
%-------------------------------------------------------------------------------------
%-------------------------------
\begin{frame}
\frametitle{Proposed improvements}
\begin{enumerate}
\item Match more trials to ICD-10 codes
\item Improve Measures of Market Conditions
\item Adjust Covariance Structure
\item Find Reasonable Priors
\item Remove disease categories that don't exist in the data from the priors
\item Imputing Enrollment
\item Improve Population Estimates
\end{enumerate}
\end{frame}
%-------------------------------
\begin{frame}
\frametitle{Questions?}
\center{\huge{Questions?}}
\end{frame}
%-------------------------------
\begin{frame}[allowframebreaks]
\frametitle{Bibliography}
\printbibliography
\end{frame}
%-------------------------------
\end{document}
%=========================================
%\begin{frame}
% \frametitle{MarginalRevenue}
% \begin{figure}
% \tikzfig{../Assets/owned/ch8_MarginalRevenue}
% \includegraphics[height=\textheight]{../Assets/copyrighted/KrugmanObsterfeldMeliz_fig8-7.jpg}
% \label{FIG:costs}
% \caption{Average Cost Curve as firms enter.}
% \end{figure}
%\end{frame}
%-------------------------------
%\begin{frame}
% \frametitle{Columns}
% \begin{columns}
% \begin{column}{0.5\textwidth}
% \end{column}
% \begin{column}{0.5\textwidth}
% \begin{figure}
% \tikzfig{../Assets/owned/ch7_EstablishedAdvantageExample2}
% \label{FIG:costs}
% \caption{Setting the Stage}
% \end{figure}
% \end{column}
% \end{columns}
%\end{frame}
% %---------------------------------------------------------------

@ -0,0 +1,76 @@
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