Background

One of the top Contract Research Organizations (CRO) in Asia was tasked with managing a multi-centre, double-blind Phase 2 clinical trial for a novel therapeutic drug aimed at treating patients with sleep onset latency. The trial spanned 24 sites and targeted to recruit 120 participants.

The CRO intended to use cubeRBQM to evaluate site performance and monitor sites closely. They wanted to prevent high numbers of queries or data input delays, as they could result in additional data management work and delays in data analysis.

66% screening failure

However, the recruitment phase faced significant challenges due to an extremely high screening failure rate. It slowed down patient enrolment and jeopardized the study timeline. The trial team turned to cubeRBQM to identify the root cause of those screening failures, mitigate their impact and accelerate recruitment.

The trial team were under pressure to address the following problems:

Access to reliable data

To make an informed decision on how to reduce the screening failure rate, the CRO and sponsor needed to review accurate data from all trial sites as quickly as possible.

Identify trends

The monitoring team were especially interested in analysing events and data points that were similar across recruiting sites. They were hoping to identify trends that could be addressed across multiple sites.

Measure data quality

The study team were also concerned with the risk of high dropout rate. The use of ePRO data capture was identified as a potential negative impact on patient retention.

Solution: cubeRBQM

The CRO had opted to implement cubeRBQM as a way of monitoring the study more efficiently. Given its multi-centre nature, they knew they would benefit from a system that could provide real-time data across all sites.

The CRO’s team was able to quickly act upon the high screening failure rate, leveraging the following key features from cubeRBQM:

Real-time data monitoring

The platform provided continuous real-time feed from all sites, allowing the CRO to monitor screening results as they occurred. cubeRBQM was integrated with cubeCDMS, cubePRO and cubeDDC, providing vast amount of data to analyse and base their decisions on.

Risk identification and mitigation

The system allowed the team to identify patterns and underlying issues contributing to the screening failures. They could pinpoint specific inclusion and exclusion criteria that were contributing to the high screening failure rate. By comparing data across sites, the platform helped the CRO identify whether these issues were site-specific or systemic.

Data quality review

The CRO was able to extract reports that showed the quality of the ePRO data entered by patients. It reassured the sponsor that direct data capture from patients was not an issue.

RESULTS

Inclusion criteria

The data revealed that a significant number of screening failures occurred due to an overly stringent inclusion criterium. The real-time data allowed the team to monitor this trend, which had not been anticipated during the trial design phase.

Demographics influence

The system's ability to filter and segment data by demographics allowed the CRO to conduct an in-depth analysis, providing relevant information to the sponsor during their regular meetings. The analysis showed that screening failures were similar across all demographic groups.

The improved data accuracy and real-time monitoring provided by cubeRBQM allowed the CRO and sponsor to make informed decisions quickly.

The study ultimately achieved its target enrolment of 120 participants, and the CRO’s proactive risk management approach, facilitated by cubeRBQM, was credited with preserving the trial’s integrity and timelines.