4.4.1 Quantitative Sensory Testing
Quantitative sensory testing (QST) of pain refers to a series of standardized techniques to quantify sensory experiences through various pain inducing assays. QST-induced nociceptive stimuli can include heat, cold, mechanical, or pressure149. Through controlled and calibrated administration of nociceptive stimuli, QST aims to reliably quantify pain and detect abnormalities in pain processing systems. Commonly used QST measures include single-point or static paradigms to a single stimulus, such as threshold (the weakest stimulus sufficient to cause pain) and tolerance (the maximum stimulus tolerated before pain becomes unbearable)149.
In addition, multiple point or dynamic paradigms can measure central nervous system pain processing, by applying a supra-threshold pain stimuli and closely assessing the pain responses over a defined period of time150. Examples of dynamic QST include temporal summation and conditioned pain modulation. Temporal summation involves increased pain perception to repetitive noxious stimuli and reflects augmented spinal cord facilitation, while conditioned pain modulation refers to decreased pain from one stimulus due to a second simultaneous painful stimulus, reflecting descending inhibition151. By quantifying these processes, the QST can identify abnormalities in ascending and descending pain pathways. A full QST profile (e.g., batteries containing various modalities of sensory inputs) can typically be completed within an hour and brief (20-minute) batteries have been developed149.
Results from a study by Prosser and colleagues show that patients with a history of OUD had higher heat and pain thresholds compared to healthy controls, indicating reduced sensitivity to noxious stimuli152. These abnormal heat and pain perceptions persisted even after remission from opioids, which suggests that there may exist subgroups of individuals whose endophenotypes (e.g., aberrant pain modulatory systems) are associated with OUD152. Other studies have attempted to correlate QST’s detection of hyperalgesia with genetic risks for the development of OUD, further verifying QST’s clinical relevance153-155. Collectively, these studies support the notion that QST can help us gain insights into the multifaceted nature of pain.
Edwards and colleagues demonstrated that QST may be a predictive tool for identifying patients at high risk for OUD or those with OUD at risk for a worsening prognosis. A total of 91 participants were chronically prescribed at least 50 mg daily morphine milligram equivalents (MME) of non-specified full agonist opioids. Although rates of formally diagnosed OUD were not described in the study, several participants presented with opioid craving and tolerance, and some had already started non-medical opioid use, potentially qualifying for at least mild OUD. In this longitudinal study, participants classified as high-risk for non-medical opioid use exhibited increased pain sensitivity and decreased pain threshold and tolerance across multiple pain modalities, regardless of whether or not they already used opioids non-medically156. The high-risk group patients also presented with higher rates of hyperalgesia.
Echoing Edwards’ findings, Compton and collaborators157 identified differences in QST responses between patients with chronic pain who developed OUD after starting prescribed opioid therapy (n=20) and those who did not (n=20). In this cross-sectional study, they demonstrated worsened temporal summation results and increased pain sensitization among those patients who developed OUD. These results indicate that QST can identify pain phenotypes associated with a higher risk for the development of OUD.
Although QST has the potential to become a practical clinical tool for measuring pain responses in patients with OUD, it is not yet widely clinically available. Much of the existing research with QST and abnormal pain profiles provides strong associations with a risk of OUD, but there is little mechanistic understanding of these associations149. There are also several documented instances of interpersonal and intrapersonal variables that affect QST responses, such as age, gender, diet, mood, sleep, etc.149 Further research into characterizing and understanding how QST is related to these variables is necessary before it can be implemented as a widely available clinical tool.