#Clinical Trials #Belgium #Cognivia #pain measurement #Mont-Saint-Guibert

Introduction

Measuring subjective outcomes such as pain, mood, and fatigue in clinical research has long posed challenges due to their inherent variability and the dependence on individual patient experiences. However, a groundbreaking study released in The Journal of Pain by Cognivia has introduced a novel methodology that aims to enhance the accuracy of these measurements during clinical trials. This shift is expected to improve data quality and foster better-informed decisions in medical research.

The Study

Cognivia's study tackles the issue of high variability in trial outcomes, demonstrating a new approach to covariate adjustment that improves how outcomes like pain are analyzed. This newly published research showcases a straightforward method for performing such adjustments, which is critical for addressing the inconsistencies often found in subjective outcomes. To ensure robustness, the findings were backed by data collected from a real-world Phase III trial focused on acute lumbar pain.

Key to their findings was the use of composite baseline covariates, which are patient-specific indicators that facilitate compliance with the guidance from the FDA. By selecting and constructing these prognostic covariates based on individual patient factors, the researchers achieved considerable precision improvements in the trial's results. Notably, when researchers incorporated composite psychological predictors from Cognivia's proprietary Placebell platform, they observed an impressive enhancement in results—up to 23.4% in accuracy.

Implications for Clinical Trials

Dominique Demolle, PhD and CEO of Cognivia, stated, "Trials too often fail, not because therapies are ineffective, but because the signals get lost in noise." This assertion underscores the significance of pinpointing methodological noise that obscures clinical trial outcomes. Through the implementation of covariate adjustment, Cognivia offers an actionable pathway to minimize these discrepancies without the need for increased patient recruitment, extended timelines, or additional costs.

Covariate adjustment works by accounting for differences in patient characteristics, such as psychological traits and baseline health status, thereby refining the overall outcome measurements—be it pain, mood, or fatigue. While the FDA supports this methodological approach, it remains surprisingly underutilized in the industry. Cognivia sets itself apart as the pioneer in providing a practical roadmap for its application in real-world settings, demonstrating effectiveness across a spectrum of studies.

Quotes from Experts

Samuel Branders, Cognivia's Director of Data Science and co-author on the study, emphasized, "This approach is a game changer for trials with subjective endpoints displaying a high variability. It helps produce clearer, more trustworthy results and maximizes the efficient use of patient resources by enhancing precision without inflating sample size."

Conclusion

The study, titled From Theory to Practice: Simple Rules for Improving Clinical Trial Confidence with Covariate Adjustment, was featured in the September 2025 edition of The Journal of Pain. The authors, including prominent figures like Arthur Ooghe, Alvaro Pereira, and Luana Colloca, established a compelling case for adopting these strategies in clinical research. The implications of this study extend not only to pain-related trials but also to any area of medical research characterized by subjective or variable outcomes, paving the way for more reliable therapeutic evaluations across various health sectors. By harnessing innovative techniques that quantify the psychological aspects of patient experiences, Cognivia aims to revolutionize the standards of clinical trial success and overall healthcare outcomes.