Accrual Index: A Real-Time Measure of the Timeliness of Clinical Study Enrollment

Using Bayesian hierarchical modeling for performance evaluation of clinical trial accrual for a cancer center

Introduction

Slow patient accrual in cancer clinical trials is always a concern. In 2021, the University of Kansas Comprehensive Cancer Center (KUCC), an NCI-designated comprehensive cancer center, implemented the Curated Cancer Clinical Outcomes Database (C3OD) to perform trial feasibility analyses using real-time electronic medical record data. In this study, we proposed a Bayesian hierarchical model to evaluate annual cancer clinical trial accrual performance.

Methods

The Bayesian hierarchical model uses Poisson models to describe the accrual performance of individual cancer clinical trials and a hierarchical component to describe the variation in performance across studies. Additionally, this model evaluates the impacts of the C3OD and the COVID-19 pandemic using posterior probabilities across evaluation years. The performance metric is the ratio of the observed accrual rate to the target accrual rate.

Results

Posterior medians of the annual accrual performance at the KUCC from 2018 to 2023 are 0.233, 0.246, 0.197, 0.150, 0.254, and 0.340. The COVID-19 pandemic partly explains the drop in performance in 2020 and 2021. The posterior probability that annual accrual performance is better with C3OD in 2023 than pre-pandemic (2019) is 0.935.

Conclusions

This study comprehensively evaluates the annual performance of clinical trial accrual at the KUCC, revealing a negative impact of COVID-19 and an ongoing positive impact of C3OD implementation. Two sensitivity analyses further validate the robustness of our model. Evaluating annual accrual performance across clinical trials is essential for a cancer center. The performance evaluation tools described in this paper are highly recommended for monitoring clinical trial accrual.

Building an infrastructure to support the development, conduct, and reporting of informative clinical studies: The Rockefeller University experience

Introduction

Clinical trials are a vital component of translational science, providing crucial information on the efficacy and safety of new interventions and forming the basis for regulatory approval and/or clinical adoption. At the same time, they are complex to design, conduct, monitor, and report successfully. Concerns over the last two decades about the quality of the design and the lack of completion and reporting of clinical trials, characterized as a lack of "informativeness," highlighted by the experience during the COVID-19 pandemic, have led to several initiatives to address the serious shortcomings of the United States clinical research enterprise.

Methods and Results

Against this background, we detail the policies, procedures, and programs that we have developed in The Rockefeller University Center for Clinical and Translational Science (CCTS), supported by a Clinical and Translational Science Award (CTSA) program grant since 2006, to support the development, conduct, and reporting of informative clinical studies.

Conclusions

We have focused on building a data-driven infrastructure to both assist individual investigators and bring translational science to each element of the clinical investigation process, with the goal of both generating new knowledge and accelerating the uptake of that knowledge into practice.

Pilot test of an accrual Common Metric for the NIH Clinical and Translational Science Awards (CTSA) Consortium: Metric feasibility and data quality

Failure to accrue participants into clinical trials incurs economic costs, wastes resources, jeopardizes answering research questions meaningfully, and delays translating research discoveries into improved health. This paper reports the results of a pilot test of the Median Accrual Ratio (MAR) metric developed as a part of the Common Metrics Initiative of the NIH's National Center for Advancing Translational Science (NCATS) Clinical and Translational Science Award (CTSA) Consortium. Using the metric is intended to enhance the ability of the CTSA Consortium and its "hubs" to increase subject accrual into trials within expected timeframes. The pilot test was undertaken at Tufts Clinical and Translational Science Institute (CTSI) with eight CTSA Consortium hubs. We describe the pilot test methods, and results regarding feasibility of collecting metric data and the quality of data that was collected. Participating hubs welcomed the opportunity to assess accrual efforts, but experienced challenges in collecting accrual metric data due to insufficient infrastructure and inconsistent implementation of electronic data systems and lack of uniform data definitions. Also, the metric could not be constructed for all trial designs, particularly those using competitive enrollment strategies. We offer recommendations to address the identified challenges to facilitate progress to broad accrual metric data collection and use.

CTSA recruitment resources: An inventory of what CTSA hubs are currently offering

Introduction:

In order to tackle the challenge of efficiently meeting clinical research accrual goals, many Clinical and Translational Science Award (CTSA) recipients have developed recruitment support mechanisms and resources to help investigators successfully recruit study participants. Disseminating recruitment best practices and developing collaborations between institutions can help strengthen recruitment capabilities and methodologies currently utilized by researchers.

Methods:

To discover what recruitment resources and mechanisms CTSAs are using, the CTSA Recruitment and Retention working group developed an electronic survey, which was distributed to CTSAs between May and July 2019. The survey contained over 50 multiple choice and short answer questions, with 40 of the 64 CTSA institutions completing the survey. Institutions reported on registries, feasibility assessment tools, clinical trial listings, experience recruiting special populations, program operations and evaluation, workforce education, social media use, and other recruitment resources.

Results:

All respondents currently utilize some form of a volunteer registry; over 80% of the CTSAs provide investigators with recruitment consultations, feasibility assessments, study listings, and electronic health record (EHR) utilization; 73% assist with study materials; 47% offer social media assistance. Many institutions reported success in recruiting patients and healthy volunteers, but difficulty in recruiting special populations such as non-English-speaking persons and rural populations. Additional recruitment tools included use of the EHR to facilitate recruitment, use of registries, and use of social media to engage participants.

Conclusions:

Areas of opportunity or growth include the development of innovative solutions in the areas of social media advertising, identification of participants from special populations, and research volunteer engagement.

A survey of practices for the use of electronic health records to support research recruitment

Electronic health records (EHRs) provide great promise for identifying cohorts and enhancing research recruitment. Such approaches are sorely needed, but there are few descriptions in the literature of prevailing practices to guide their use. A multidisciplinary workgroup was formed to examine current practices in the use of EHRs in recruitment and to propose future directions. The group surveyed consortium members regarding current practices. Over 98% of the Clinical and Translational Science Award Consortium responded to the survey. Brokered and self-service data warehouse access are in early or full operation at 94% and 92% of institutions, respectively, whereas, EHR alerts to providers and to research teams are at 45% and 48%, respectively, and use of patient portals for research is at 20%. However, these percentages increase significantly to 88% and above if planning and exploratory work were considered cumulatively. For most approaches, implementation reflected perceived demand. Regulatory and workflow processes were similarly varied, and many respondents described substantive restrictions arising from logistical constraints and limitations on collaboration and data sharing. Survey results reflect wide variation in implementation and approach, and point to strong need for comparative research and development of best practices to protect patients and facilitate interinstitutional collaboration and multisite research.