This repository contains materials for a hands on example for the Effective Visual Communication Webinar.
- Purpose_Worksheet.docx is a partially completed Purpose Worksheet setting up the purpose for the visualization exercise.
- Missed_Doses_Due_to_COVID.csv is a dataset that can be used to generate visualizations for the exercise.
This example is inspired by a drug being tested in a Phase 3 study during the COVID-19 pandemic. Drug kinetics and endpoints have been altered and no longer reflect the PKPD/efficacy properties of a real drug.
Situation:
- A Phase 3 time to event trial is being conducted for Drug A during the COVID-19 pandemic.
- Drug A is administered in the clinic by a health care provider.
Complication:
- The clinical trial team has noticed a pattern of patients missing dosing visits
- Due to the COVID-19 pandemic, patients’ access to the clinic has been greatly impacted, resulting in patients missing one or more dosing visits.
- The project team is considering whether mitigation is required, and if so what action should be taken.
Question:
- What effect would 1, 2, or 3 missed doses have on the efficacy of the current trial?
- Should the trial be stopped? Should the trial management team make significant efforts to increase compliance? Or is the predicted impact of these missed doses negligible?
The Purpose Worksheet is intended to help with Step 1 of Effective Visual Communication (i.e., have a clear purpose). For this exercise, we have partially completed the Purpose_Worksheet for you, based on the background information above. Review the partially completed worksheet, make any changes you wish, and complete what hasn’t been filled in.
A simulated dataset has been provided for this example: Missed_Doses_Due_to_COVID.csv. Step 2 of Effective Visual Communication involves you choosing what data to display and how, in order to support the Purpose. You may or may not use all of the information supplied in the dataset.
The dataset represents a simulated set of individual patients following placebo, continuous treatment, or 1, 2, or 3 missed doses of Drug A. The dataset contains individual drug exposure information, as well as individual time-to-event information for the primary endpoint which is a time-to-event endpoint. Below are descriptions of the variables in the dataset
- id - unique subject identifier
- TRT - treatment group, including number of missed doses (values: “Continuous Treatment”, “1 missing dose”, “2 missing doses”, “3 missing doses”, “Placebo”)
- time - time of event (years)
- status - event identifier (1 = right censored / lost to follow up, 2 = event of interest / primary endpoint)
- label - description of event (values: “censored”, “event”)
- avgAUC - average drug exposure up to the time of the event (ng/mL)
- avgAUEC - average change from baseline in PD marker up to time of event (mmol/L)
- HRR - model predicted relative change in hazard based on avgAUEC (relative to avgAUEC of 0)
Below find the first six rows of the dataset. Access the full dataset here: Missed_Doses_Due_to_COVID.csv
| id | TRT | time | status | label | avgAUC | avgAUEC | HRR |
|---|---|---|---|---|---|---|---|
| 1 | Placebo | 1.60 | 1 | censored | 0 | -0.052686 | -0.026343 |
| 2 | Placebo | 0.70 | 2 | event | 0 | -0.260150 | -0.130070 |
| 3 | Placebo | 2.90 | 1 | censored | 0 | 0.455220 | 0.227610 |
| 4 | Placebo | 1.95 | 2 | event | 0 | 0.381400 | 0.190700 |
| 5 | Placebo | 1.95 | 1 | censored | 0 | 0.278710 | 0.139360 |
| 6 | Placebo | 1.15 | 1 | censored | 0 | 0.069280 | 0.034640 |
NOTE to download a single data set locally as a csv file, click on the raw button and save the file, e.g. right-click and select "save-as". The following link describes the process in further detail.