Phenotyping Acute Pain for Discovery Research and Directed Therapeutics
| Status: | Withdrawn |
|---|---|
| Conditions: | Post-Surgical Pain |
| Therapuetic Areas: | Musculoskeletal |
| Healthy: | No |
| Age Range: | 18 - Any |
| Updated: | 2/24/2018 |
| Start Date: | February 21, 2018 |
| End Date: | February 21, 2018 |
The goal of the current study is to combine existing and new tools for quantifying patient
self-report to characterize changes in acute pain. The ability to quantitatively measure
self-report provides behavioral pain phenotypes that can serve as the basis for clustering
patients into sub-groups based on their self-report of their symptoms, eliminating observer
based perceptions of patients' pain.
self-report to characterize changes in acute pain. The ability to quantitatively measure
self-report provides behavioral pain phenotypes that can serve as the basis for clustering
patients into sub-groups based on their self-report of their symptoms, eliminating observer
based perceptions of patients' pain.
Pain is a therapeutic challenge as well as a public health problem that is estimated to
affect over 116 million American adults [1]; reduces quality of life; and is estimated to
cost up to $635 billion annually. Growing recognition of the need for evidence-based,
individual-centered treatment strategies raises expectations that health care will be
improved by matching proven effective treatments with knowledge of patients' unique
characteristics to optimize efficacy and safety. Essential to the goal of matching treatments
to patients to enhance analgesic drug development and therapy is identification of
intermediate phenotypes that capture the mechanistic complexity, genetic expression and
epigenetic changes of hundreds of ongoing processes and mediators that influence treatment
efficacy and safety and may form the basis for differential responses to drug therapy. The
ability to identify functional variants in the genomic responses to pain and therapeutics at
the sub-group and patient levels, however, has been limited to date by lack of thorough
phenotyping for patients with pain.
The need for a more comprehensive understanding of human phenotypes has spawned a new method
of phenotyping studies referred to as "deep phenotyping." Deep phenotyping for
pharmacogenomic studies requires both breath and depth to better interpret the complexities
of genomic variations that may underlie individual differences in pain report. One approach
to address this complexity is to use quantitative testing of clinical features to identify
more homogeneous subsets within a group of patients with a given diagnosis or characteristic.
Variations in quantitative measures may identify intermediate phenotypes that are genetically
less complex yet have potentially stronger signals closer to the site of gene action. In
pain, quantitative testing is often termed "quantitative sensory testing", or QST.
Exclusion
1. Current or history of mental disorder or substance abuse
2. Allergy to aspirin, NSAIDS, or sulfonamide
3. Pregnant and/or nursing
4. History of peptic ulcers and/or GI bleeding
5. Concurrent use of agents which may obscure pain report, e.g., alcohol, opioids,
benzodiazepines, and depressants, etc
6. Chronic use of medications confounding assessment of the inflammatory response or
analgesia, e.g., antihistamines, NSAIDS, steroids, antidepressants
7. Concurrent or history of chronic diseases, e.g., diabetes, rheumatoid arthritis, liver
disease, cancer, hypertension or obesity (body mass index >35)
8. Expectation of excessive surgical difficulty, resulting in a difficulty score of 5 for
any tooth (determined from panoramic radiograph)
9. Subjects with extreme anxiety and who are candidates for general anesthesia or conscious
sedation
affect over 116 million American adults [1]; reduces quality of life; and is estimated to
cost up to $635 billion annually. Growing recognition of the need for evidence-based,
individual-centered treatment strategies raises expectations that health care will be
improved by matching proven effective treatments with knowledge of patients' unique
characteristics to optimize efficacy and safety. Essential to the goal of matching treatments
to patients to enhance analgesic drug development and therapy is identification of
intermediate phenotypes that capture the mechanistic complexity, genetic expression and
epigenetic changes of hundreds of ongoing processes and mediators that influence treatment
efficacy and safety and may form the basis for differential responses to drug therapy. The
ability to identify functional variants in the genomic responses to pain and therapeutics at
the sub-group and patient levels, however, has been limited to date by lack of thorough
phenotyping for patients with pain.
The need for a more comprehensive understanding of human phenotypes has spawned a new method
of phenotyping studies referred to as "deep phenotyping." Deep phenotyping for
pharmacogenomic studies requires both breath and depth to better interpret the complexities
of genomic variations that may underlie individual differences in pain report. One approach
to address this complexity is to use quantitative testing of clinical features to identify
more homogeneous subsets within a group of patients with a given diagnosis or characteristic.
Variations in quantitative measures may identify intermediate phenotypes that are genetically
less complex yet have potentially stronger signals closer to the site of gene action. In
pain, quantitative testing is often termed "quantitative sensory testing", or QST.
Exclusion
1. Current or history of mental disorder or substance abuse
2. Allergy to aspirin, NSAIDS, or sulfonamide
3. Pregnant and/or nursing
4. History of peptic ulcers and/or GI bleeding
5. Concurrent use of agents which may obscure pain report, e.g., alcohol, opioids,
benzodiazepines, and depressants, etc
6. Chronic use of medications confounding assessment of the inflammatory response or
analgesia, e.g., antihistamines, NSAIDS, steroids, antidepressants
7. Concurrent or history of chronic diseases, e.g., diabetes, rheumatoid arthritis, liver
disease, cancer, hypertension or obesity (body mass index >35)
8. Expectation of excessive surgical difficulty, resulting in a difficulty score of 5 for
any tooth (determined from panoramic radiograph)
9. Subjects with extreme anxiety and who are candidates for general anesthesia or conscious
sedation
Inclusion Criteria:
1. Male and female patients aged 18 and older willing to undergo clinically indicated
non-emergent oral surgery for the removal of impacted third molars with local
anesthesia
2. Indicated for the removal of third molars, at least a minimum of one partial-bony
impacted third molar, with a total difficulty score total of not less than 4*
3. Communicate in spoken and written English
4. Willing to undergo research observation for 4 hours postoperatively and 48 hour follow
up visit
5. In good health with an ASA status of 1 or 2 by self report and review of medical
history
6. Self-report of moderate or severe pain on a categorical scale with a minimum of 4 out
of 10 on the numerical rating scale following the offset of local anesthesia
- 1=erupted, 2=soft tissue impaction, 3=partial bony impaction, 4=full bony
impaction, 5 = unusual surgical difficulty
Exclusion Criteria:
1. Current or history of mental disorder or substance abuse
2. Allergy to aspirin, NSAIDS, or sulfonamide
3. Pregnant and/or nursing
4. History of peptic ulcers and/or GI bleeding
5. Concurrent use of agents which may obscure pain report, e.g., alcohol, opioids,
benzodiazepines, and depressants, etc
6. Chronic use of medications confounding assessment of the inflammatory response or
analgesia, e.g., antihistamines, NSAIDS, steroids, antidepressants
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