Rescue Studies: Salvaging Clinical Trials Through Expert Data Management

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?

What is a Rescue Study in Clinical Data Management?

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.

Here are several factors that can contribute to studies reaching this critical state:

• Questionable database build quality:
  If the data collected in the EDC is unreliable or incomplete, it can compromise the validity of the results and limit the ability to draw accurate conclusions.
• Technical Failures:
  Technical issues with data collection tools, electronic health records, or data management systems can result in data loss or corruption or poor maintenance or major limitations, demanding rescue measures.
• Data Quality Issues:
  Poor data quality due to errors, inaccuracies, or inconsistencies in data collection and management can lead to the need for a rescue study.
• Operational Challenges:
  Issues related to site performance, patient recruitment, data monitoring, or data entry can disrupt the smooth progression of a clinical trial.

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.

Responsibilities and Risks in Rescue studies:

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:

• Time Restrictions:
  Time is of the essence in rescue studies. Delays in initiating and completing the rescue process can further degrade data quality and impact study timelines.
• Resource Intensiveness:
  Rescue studies may require significant resources in terms of personnel, time, and budget. Allocating these resources while managing ongoing trials can strain an organization.
• Regulatory Compliance:
  Ensuring that all rescue study activities comply with regulatory guidelines is essential. Non-compliance can lead to regulatory issues and impact the validity of the rescue effort.
• Documentation and Reporting:
  Proper documentation of all actions taken during the rescue study is essential. This documentation is critical for regulatory compliance and transparency.
• Quality Control:
  Rigorous quality control processes are put in place to ensure that the data is accurate and reliable after rescue efforts. This may involve independent data review and validation.
• Validation and Auditing:
  Independent validation and auditing of the rescue study process may be conducted to ensure the integrity of the data.
• Effective Communications:
  Maintaining transparent and effective communication among all stakeholders, including sponsors, investigators, and regulatory authorities, can be challenging but vital for a successful rescue study.
• Study Bias:
  There is a risk of introducing bias during the rescue study, especially when decisions about data handling and cleaning are subjective. Careful documentation and validation can mitigate this risk.
• Impact on Trial Outcomes:
  Depending on the severity of data issues and the success of the rescue effort, the final trial outcomes may still be compromised or less reliable than initially expected.
• Costs:
  Due to the resource-intensive nature of rescue studies, there is a risk of exceeding the allocated budget, which can have financial implications for both the Sponsor and CRO end.

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.