Clinical Perspective on Core Outcome Sets in Type 1 Diabetes Trials: A Web-Based Survey Study

Background: Type 1 diabetes (T1DM) affects nearly 1.9 million individuals in the United States, necessitating daily interventions with an annual cost exceeding $16 billion. Managing T1DM is complex, requiring personalized regimens based on clinical trial findings. Challenges arise from inconsistent outcome measurements across medical domains, prompting a solution:the use of a core outcome set (COS) to standardize measurements and reporting, thus reducing bias. In this cross-sectional study we employ a web-based survey to explore how current COS are understood and applied in T1DM trials. The primary objective is to gather insights from those conducting trials, assessing the current state of COS adoption, and identifying potential areas for improvement. The findings aim to clarify awareness, attitudes, and practices related to the current COS in T1DM research, providing insights for future strategies to enhance COS usage and improve the quality and comparability of T1DM trial outcomes.

Methods: In a previous study, we assembled a sample of trials to assess the adoption of the COS for T1D. For this survey, eligible participants are clinical trialists who have been involved in the design, implementation, or analysis of T1D trials within the last five years. The survey is designed to be comprehensive, comprising a set of 20 questions. Participants will provide informed consent, and their responses will be kept confidential and anonymous. The participants' familiarity with the COS will influence the progression of their survey. We will create and distribute the surveys to trialists using REDCap (Research Electronic Data Capture), a secure web-based application designed for research data collection. Data analysis may involve both descriptive and inferential statistics, and qualitative data will be gathered through open-ended questions.

Results: The data is presently in the process of being collected, encompassing descriptive statistics, inferential statistics, and qualitative data. Patient demographics and responses to closed-ended questions will be summarized through descriptive statistics. Inferential statistics, such as chi-square tests and t-tests, will be employed to identify relationships between variables or differences among subgroups. Additionally, qualitative data will be obtained from responses to open-ended questions and subjected to thematic analysis to identify recurring themes and patterns.

Conclusion: Upon the culmination of this project, our data will provide valuable insights into the utilization and awareness of the core outcome set (COS) among clinical trialists in the realm of Type 1 Diabetes (T1D). The findings from this study could establish a basis for future initiatives and interventions geared towards enhancing the incorporation of COS among clinical trialists involved in T1D research. These outcomes may contribute to the standardization of clinical COS reporting, ultimately leading to improved patient outcomes within the context of T1D.