diff --git a/Latex/Paper/Main.tex b/Latex/Paper/Main.tex index f7e11dd..3396449 100644 --- a/Latex/Paper/Main.tex +++ b/Latex/Paper/Main.tex @@ -24,7 +24,8 @@ \titlespacing*{\paragraph} {0pt}{3.25ex plus 1ex minus .2ex}{1.5ex plus .2ex} -\title{The effects of market conditions on enrollment and completion of clinical trials\\ \small{Preliminary Draft}} +\title{The effects of market conditions and enrollment on the +completion of clinical trials\\ \small{Preliminary Draft}} \author{William King} \usepackage{multirow} diff --git a/Latex/Paper/sections/03_CausalIdentification.tex b/Latex/Paper/sections/03_CausalIdentification.tex index 3d8d9a2..eb8af10 100644 --- a/Latex/Paper/sections/03_CausalIdentification.tex +++ b/Latex/Paper/sections/03_CausalIdentification.tex @@ -2,29 +2,60 @@ \graphicspath{{\subfix{Assets/img/}}} \begin{document} +% Introduce clinicaltrials.gov +% - Describe different statuses +% - status flowchart +% Introduce causal model +% - Diagram +% - List each node and what they influence (and why) +% Begin Discussing Data +% - Where did I get data for each node? -Because running experiments on companies running clinical trials is not going -to happen anytime soon, causal identification will depend on creating a -structural causal model. -In \cref{Fig:CausalModel} I diagram the directed acyclic graph that describes -the data generating model. -The proposed data generating model consists of a decision maker, the study -sponsor, who must decide whether to let a trial run to completion or terminate +Because running randomized experiments on companies running clinical trials +is unlikely to to happen anytime soon, +causal identification will depend on observational methods. +I use the do-calculus approach developed by Judea Pearl +\cite{pearl_CausalityModels_2009} +to describe what affects the success of a Phase III clinical trial. +I then use that model to derive the econometric model capable of estimating +the effect of extending the recruiting period or of having an additional +competing drug. + + + +% In \cref{Fig:CausalModel} I diagram the directed acyclic graph that describes +% the data generating model. +The proposed data generating model consists of a decision maker +-- the study sponsor -- +who must decide whether to let a trial run to completion or terminate the trial early. -While receiving updates regarding the status of the trial, they ask questions -such as: +While receiving updates regarding the status of the trial, they try to +answer questions such as: \begin{itemize} \item Do I need to terminate the trial due to safety incidents? - \item Does it appear that the drug is effective enough to achieve our - goals, justifying continuing the trial? + \item Does it appear that the drug is effective? \item Are we recruiting enough participants to achive the statistical results we need? - \item Does the current market conditions and expectations about returns on + \item Does the current market conditions and expectations about + returns on investment justify the expenditures we are making? \end{itemize} -When appropriate, the study sponsor terminates the trial. -If there are not enough issues to terminate the trial, it continues until it -is completed. +Althought I treat this as a single agent, in reality, there are multiple +stakeholders involved in chosing whether the trial should continue, including +those running the trial (which may be a separate firm), +the company developing the drug, additional rightsholders, +or funding organizations. + +% When appropriate, the study sponsor terminates the trial. +% If there are not enough issues to terminate the trial, it continues until it +% is completed. + +In the United States, clinical trials are required by law to be registered on +\url{ClinicalTrials.gov}, where they are made available to the public. +Trials must be registered + +% + While conducting a trial, the safety and efficacy of a drug are driven by fundamental pharmacokinetic properties of the compounds. @@ -36,19 +67,25 @@ Of course, these decisions are both affected by the specific condition being treated due to differences in the severity of the symptoms. When a trial has been started, it comes time to recruit participancts. -Participants frequently depend on the advice of their physician when deciding +The enrollment of participants in a trial depends on a few factors. +Participants usually depend on the advice of their physician when deciding to join a trial or not. As these physicians have a duty to seek their patients best interest; they, along with their patients will evaluate if the previously observed safety and efficacy -results justify joining the trial over using current standard treatments. -Thus the current market conditions may affect the rate at which participants -enroll in the trial. +results justify joining the trial in contrast to using the current standard +of care. +Thus enrollment rates are influenced by the treatments currently on the market. +Recruitment can also be hindered if disease has a low impact +-- in which participants might have little incentive to join -- +or if there are few people who have the disease. +The overall impact of the disease also influences whether or not there are +already drugs on the market to treat that disease. -The enrollment of participants in a trial depends on a few other factors. The condition or disease of interest and how it progresses will determine how long recruitiment will be held open versus just an observation of treatment arms. Aditionally, a trial that has already reached a high enough enrollment will often -close recruitment by switching to an "Active, not recruiting" stage to manage costs. +close recruitment. +Both of these are reported as "Active, not recruting" to ClinicalTrials.gov. Finally, enrolling participants depends on how difficult it is to find people who suffer from the condition of interest.