When a clinical trial faces data quality challenges, every day counts. Rescue studies have become an increasingly critical component in preserving valuable research and protecting investments in medical device development. But what exactly constitutes a rescue study, and why are they essential in modern clinical data management?
A ‘rescue study’ is a clinical trial that has previously been conducted by a vendor or sponsor that is being contracted with a different vendor. The reasons for the change may be based on issues negatively affecting timelines, costs, quality, resources, or changes with study design and reporting requirements.
In clinical data management, rescue studies refer to efforts undertaken to salvage or rectify data quality and integrity issues that have arisen during the course of a clinical trial due to, among other factors, poor build design, not adhering to the protocol, and poor study management and communications.
The objective of a rescue study is to correct the problems in the original trial and ensure that the results are valid, reliable, and can be used to support further clinical development. This might include rebuilding the database, cleaning the data, revalidating the data, and sometimes even re-enrolling participants if necessary.
Each of these factors poses unique challenges, and a rescue study is initiated to address the specific issues identified in a given clinical trial. Timely recognition of these challenges and a well-planned rescue strategy are essential to salvage the trial’s integrity and maintain the scientific validity of the research.
Identify the problem:
The first activity in a rescue study is to identify the root causes of the study data problems. Each study is unique, and a rescue plan should be tailored to fit the needs of the study.
Kick-off meeting with sponsor:
Communications with the sponsor regarding their insight and concerns is a first step in the transition process in developing the scope of work and budget documents.
Request key documents:
Documents such as protocol(s), data management plan, Case Report Forms (eCRFs, aCRFs) and other related documents and data sources should be received/reviewed.
Gap analysis:
A gap analysis is generated based on review of documents and data sources, such as:
Protocol Adherence:
Ensuring that the study protocol was followed correctly is crucial. Any deviations from the protocol need to be documented and addressed appropriately.
Database Design Assessment:
Assessment of the database design of the clinical study by reviewing the eCRF against the protocol, Edit Check specification, and any inconsistencies in the folder structure and investigate on any issues due to the EDC tool limitation.
Data Assessment:
Assessment of the extent and nature of data issues by reviewing data discrepancies, missing data, or any inconsistencies in data collection. With a gap analysis, a transition plan, budget, and timelines become clearer and discussions with sponsor can advance to possible solutions.
Identify the solution:
Approach to database transfer: Are needs best met by:
Building a new database with a new EDC tool?
Transferring the database URL to the new CRO?
Or an approach that would leave the database with the original vendor and limit the incoming CRO’s tasks to data cleaning and query management.
New Database
Creating a new database can be accomplished by a programmatic remapping or a manual re-entry of the data into a new database, a decision that is influenced by the amount of data to be transferred and extent of changes needed to the database. This approach may be time and cost intensive. This approach would be used when database design problems are evident along with other issues of data integrity.
Transferring the database URL
The transfer of an existing URL to a new vendor is a more common approach than creating a new database. The new vendor assumes responsibility for the administrative tasks for maintenance, revisions, updates, and database lock. This approach may take some coordination with the original holder of the URL if there are multiple studies on the URL but could be used when problems are not limited to data cleaning and query management.
Data Cleaning/Query management under existing vendor
The least time intensive approach is to leave the database with the original vendor with the new vendor responsible for activities of data cleaning and query management. This approach would be used when the problems are primarily with data cleaning.
Rescue studies in clinical data management, while essential for retrieving compromised trial data, come with their own set of risks and challenges. Here are some common risks and key aspects of responsibilities associated with rescue studies:
To mitigate these risks, careful planning, experienced personnel, adherence to regulatory guidelines, and clear documentation are essential. Organizations should also consider risk assessment and mitigation strategies specific to their rescue study scenarios to minimize the impact of these challenges on the overall integrity of the clinical trial data.
Conclusion:
In summary, experience in rescue studies within clinical data management requires a thorough knowledge of clinical trial processes, data quality issues, and regulatory requirements. Professionals in this field play a crucial role in salvaging and restoring the integrity of clinical trial data, ultimately ensuring that the trial results are reliable and meaningful for further analysis and decision-making. With a solid background in clinical data management and a proven track record of successfully conducting rescue studies, we are well-suited to be a partner for rescue studies and here to help.
Get in touch with a member of the Veranex team. Our global team includes experts proficient in all phases and disciplines of medical device innovation including clinical data services. We can help at any time, in any phase including salvage studies with a 30,000 foot view of your environment, needs and potential.