Shiny Application for expertsurv
R packages have many advantages, primarily allowing for easy sharing and documentation of code and ensuring code follows standardised conventions. Although R packages are more user friendly than a collection of functions, they still require the user to have a working knowledge of R something which most experts will not have.
As noted by (Mikkola et al. 2023), there is a need for tools which can embed the elicitation of expert opinion within the statistical workflow. One such tool is Shiny, an open-source R package that provides an elegant and powerful web framework for building web applications using R. Shiny can turn analyses conducted by R into interactive web applications without requiring HTML, CSS, or JavaScript knowledge (Chang et al. 2023).
Learning how to interact with a webpage should be a much simpler task for experts and health economists not familiar with R. Furthermore, we can leverage R Markdown to create reproducible reports of the relevant outputs of the \(\texttt{expertsurv}\) package in formats such as PDF, HTML and Word.
The tutorial below provides an overview of the steps required to elicit expert opinion on the survival at a timepoint of 20 months and incorporate these beliefs with survival data. To begin we simply run the following function \(\texttt{elicit_surv}()\) which will open up a webpage.
In Figure 1 we have the following steps to upload the data:
- Upload an excel file containing the survival data
- Select the columns referring to the time, status and arm (if jointly modelling treatment and comparator)
- Set the limit of the for the survival plot (ensuring that Choose opinion type as ‘’Survival at timepoint(s)’’
- We assume that there are two experts who we will provide expert opinion
- Once the above parameters are defined select the ‘’Plot/Update Survival Curves and Expert Opinions’’
Figure 1: Upload data and generate Kaplan-Meier plot
In Figure 2 we have the following steps to elicit the expert’s opinions:
- We set the timepoint at which we elicit expert opinion to 20 months.
- Experts will be asked for their beliefs on the median survival at 20 months, the lower \(2.5\%\) and upper \(97.5\%\) probabilities of the population survival.
Once these steps are complete, we click the ‘’Plot/Update Survival Curves and Expert Opinions’’ button.
Figure 2: Expert beliefs about survival at 20 months
In Figure 2 we have the following steps to run the analysis:
- Several other advanced options relating to the expert opinion are available in the checkbox; these include specifying the most likely value (MLV), the choice of pooling expert opinion (linear or logarithmic pooling - default linear pooling) and the parametric distribution to fit to each individual opinion (default is best fitting).
- We can select which treatment arm relates to the expert’s belief (i.e. treatment or comparator).
- Selecting Run Analysis will conduct the analysis; and it should be noted that the Bayesian analysis can take a considerable amount of time.
- Once the analysis is complete we can download the \(\texttt{expertsurv}\) object which can be loaded an R session later.
- We can also download the results as a report in one of three formats (HTML, PDF or Word) as shown in Figure 4.
Figure 3: Running statistical analysis
Figure 4: Results generated from the Markdown file