Placebo response is a bane of clinical trials but it can be very helpful in practice. A team of American and Canadian researchers used AI to help identify predictors of the placebo response. The results were recently published in Pain, under the title, Predicting placebo analgesia in patients with chronic pain using natural language processing: a preliminary validation study.
Since they used AI for their study, I thought it would be fitting to use ChatGPT to edit their abstract for the lay public.
Patients with chronic pain often experience significant pain relief from placebos (inert pills), and this effect can last for days or even weeks. However, it’s still unclear whether we can reliably predict who will respond to placebo and how to do so. Previous research has shown that people who respond well to placebos tend to talk about their pain and their life in a certain way. In this study, the researchers looked at whether these language patterns can predict who will respond to a placebo before they even receive the treatment, and whether we can distinguish between people who will respond to a placebo versus a real drug.
To do this, they analyzed language patterns from patients with chronic back pain who received a placebo in one study and used this information to build a language model that could predict who would respond to a placebo in a separate study. They found that this language model was able to predict, before treatment, which patients would respond well to a placebo in the second study. These patients reported an average of 30% pain relief from the placebo, while those predicted to be non-responders only experienced a 3% reduction in pain. However, the model was not able to predict who would respond to a real pain medication or who would recover without treatment, suggesting that it specifically predicts response to placebos.
Overall, this study suggests that we may be able to use language patterns to predict who will respond to placebos, which could help researchers design better clinical trials and improve patient care.
