KNOWLEDGE / Insights / POST
October 15, 2018

There is substantial scientific literature describing the placebo response in pain, including characterizing the magnitude and duration of placebo response in randomized clinical trials, examining correlations between specific patient demographics, and understanding the contributions of psychological traits to the placebo response. A recent excellent paper titled “Brain and Psychological Determinant of Placebo Pill Response in Chronic Pain Patients”1 by Etienne Vachon-Presseau and colleagues published recently in Nature, however, provided further evidence that it possible to predict the placebo response of individual patients.


The experimental design of this study aimed to identify both neurobiological and psychological factors that (1) predict which patients are responsive to placebo treatments; and (2) are dynamically modified in response to placebo treatment. A total of 82 patients with chronic low back pain completed several psychological questionnaires and fMRI imaging sessions, and were randomized to receive placebo, no treatment or active treatment (Naproxen, 500mg) for 8 weeks. The data suggested that specific personality traits – including Openness, Not Distracting, Attention Regulation, Emotional Awareness and Self-Regulation – were correlated with the magnitude of the placebo response. Placebo responsiveness was further predicted from anatomic MRI by subcortical limbic volume asymmetry and sensorimotor cortex thickness. The authors then used a machine learning-based algorithm to predict the magnitude of the placebo response in each patient. Interestingly, the resulting model was no longer predictive of the placebo response if psychological scores were removed, highlighting the paramount importance of considering psychological traits when predicting placebo responsiveness. In general, this approach was able to explain approximately 36% of the variance in patient analgesia.


These landmark results further substantiate the approach taken by the Tools4Patient (T4P) team, who similarly set out about 4 years ago to develop a tool – named Placebell©™ – to identify placebo responsiveness in clinical trial participants. T4P scientists took a slightly different approach by limiting placebo prediction to non-pharmacodynamic measurements (i.e. not including imaging), for ease of use in randomized clinical trials. Interestingly, the Placebell©™ algorithm can explain a similar variance due to the placebo effect in peripheral neuropathic pain by incorporating results from its validated personality questionnaire with usual patient demographics and specifically-identified disease characteristics. Placebell©™ is currently available to the biotechnology, pharmaceutical, generic drug and device companies for incorporation into clinical trials.

1 Vachon-Presseau, et al. “Brain and psychological determinants of placebo pill response in chronic pain patients.” Nature Communications 9: 3397, 2018

Authors

Related content

Insights

Leveraging Historical Data For High-dimensional Regression Adjustment, A Machine Learning Approach

Samuel Branders, Ph.D., Data Mining and Statistical Research Scientist of Tools4Patient (T4P) recently presented cutting-edge research at the...

Read More
Insights

Compilation Of Frequently Asked Questions About Placebell©™

In May 2018, Tools4Patient (T4P) presented a webinar entitled “Characterization of Individual Patient Placebo Response: Impact on the...

Read More
Insights

Patient-Centricity at the Heart of Innovation

Tools4Patient was founded with the goal of developing innovative, sophisticated tools to optimize clinical trial design and data...

Read More

Understand patient differences in your next clinical trial

Increase clinical trial success rates and get new therapies to patients faster. Tell us about your clinical trial below and we'll be in touch.

"*" indicates required fields

This field is for validation purposes and should be left unchanged.