OARSI 2022

Insights to Help You Design Better OA Clinical Trials

If you’re designing clinical trials in OA, you probably have questions about the placebo response – and Cognivia has answers.
The placebo response has been estimated to comprise more than 60% of the measured treatment effect in chronic pain (Hauser, et al., Pain 2011), making it difficult to demonstrate true drug efficacy. Through the research conducted at Cognivia, we’ve accumulated insights on the placebo response that also impact clinical trial design. We’d love to share our data to help you address the placebo response, design successful clinical trials, and get OA patients the treatment and relief they need.

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Members of our team will be attending OARSI 2022, World Congress on Osteoarthritis, from April 6 to 10 in Berlin, Germany. Let’s meet to discuss how we can bring more insights to your OA clinical trial.

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Top Issues in OA Clinical Trial Design

How can the Placebo Response Be Better Managed in OA Clinical Trials?

Placebell is Cognivia’s AI-based method to predict and account for individual patients’ placebo responsiveness in clinical trials. By combining baseline patient data and psychology with a predictive algorithm trained in chronic pain, Placebell defines patient placebo responsiveness as a score that can be used as a covariate in the statistical analysis. This low-risk approach improves the ability to detect statistically significant differences between drug treatment and placebo – and it’s proven in OA, too. Explore the data below to see how Placebell has worked in sponsored OA clinical trials.


Leveraging Historical Data to Optimize the Number of Covariates and Explained Variance in Analysis of RCT


Improving Precision of Treatment Effect Estimation in OA


Prediction of Placebo Response in OA


Proven Performance of Novel Technology to Predict Placebo Response in OA Clinical Trials

Interesting data, right?

Let’s talk about it at OARSI 2022.

Is Pain Reporting Training Enough to Manage the Placebo Response?

The assessment of pain is, by nature, subjective – and the risk is high that patients will evaluate it inconsistently. Reducing this inconsistency could help OA clinical trials better understand the placebo and treatment responses.  While this approach is routinely taken, is it enough to reduce OA clinical trial failure?


Impact of Excluding Highly Variable Pain Subjects on the Treatment Estimation


Minimizing Evaluation Error in OA Pain


Can Daily Self-Assessment Induce a Learning Effect?

Should Placebo Responders Be Excluded from RCTs?

One strategy to contend with the placebo response problem in OA trials is to identify potential high placebo responders – for example, using placebo lead-in periods – and exclude them from randomized clinical trials (RCTs). This makes good sense on the surface, but is will it actually benefit your trial?


Should Strong Placebo Responders be Excluded from Clinical Trials?

Scientific Poster

Cost/Benefit Ratio of Enrichment Screening vs. Covariate Adjustment


The Case Against Excluding Placebo Responders

We hope you find these data useful

and we look forward to discussing more insights with you at OARSI 2022