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.