KEY HIGHLIGHTS
- Frontier Science Scotland (FSS) was commissioned to carry out statistical analyses and reporting
- A low event rate led to protocol amendment and a change to the study design
- We worked on Analysis Data Model (ADaM) datasets as well as tables, figures and listings (TFLs) while essential documentation was still in draft
- High-quality datasets and outputs were achieved thanks to accurate management and tracking of study team’s changes by FSS
THE SITUATION
Beginning as an open-label randomised control trial on children with pulmonary hypertension, the aim of this study was to find out if the investigational product (IP) delayed disease progression compared with existing Standard of Care (SoC) treatments.
Children aged 2-18 were randomly selected from multiple centres in multiple countries and assigned to either the investigational product or SoC arm of the study. Enrolment in the study started in October 2017, and is ongoing as of January 2023.
THE CHALLENGE
We were commissioned to carry out statistical analyses and reporting. As this study was set up to be an event-driven study, we worked to a predicted Interim Analysis deadline in the protocol. However, the event rate was much lower than initially predicted, meaning the predicted timelines for an Interim Analysis were no longer feasible.
The low event rate prompted a protocol amendment, and the study design was updated to a single-arm extension. Consequently, all other documentation – namely the Statistical Analysis Plan (SAP) and the Data Analysis Plan (DAP) – was on hold while essential documentation was in draft, which risked holding up dry-run preparations.
OUR SOLUTION
The FSS biostatistics team mapped out a custom-fit, agile approach to ensure delivery of ADaM datasets and TFLs to the sponsor. The team found an iterative approach to tackle change management while essential trial documentation was still being developed and updated.
Create CDISC-compliant dataset structures
Our biostatistics expertise and two decades of experience helped to determine the need to create ADaM dataset structures which adhered to Clinical Data Interchange Standards Consortium (CDISC) standards. For these ADaM datasets, finalised documentation was less critical.
Utilise other sources of information until Protocol Amendment approved
Where ADaM datasets heavily relied on derivations from essential documentation, we used the data analysis plan (DAP). We split the DAP into sections that had a common theme, and updated these based on the draft Protocol Amendment. These sections were reviewed internally and externally and were used to update the ADaM specifications. This meant some sections could be progressed more quickly once the protocol amendment was approved and relevant information was obtained.
Manage and track all iterations
To ensure high-quality datasets and outputs, our team accurately managed and tracked all changes and iterations.
THE OUTCOME
Using this custom-fit agile approach, we delivered the dry-run reports to the sponsor on time while maintaining quality in the deliverables.
