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Understanding the impact of genetics could aid rational, precision drug choices. In the current study, investigators will focus on whether genetic analysis of drug processing using the Inagene platform could predict efficacy and side effect profile in patients prescribed medication for pain.
Understanding the impact of genetics could aid rational, precision drug choices. In the current study, investigators will focus on whether genetic analysis of drug processing using the Inagene platform could predict efficacy and side effect profile in patients prescribed medication for pain. In the investigator's clinic commonly employed medications included nortriptyline, duloxetine, topiramate, gabapentin, pregabalin, opioids (morphine derivatives, tramadol, tapentadol, buprenorphine patch), cesamet (a synthetic cannabinoid). To the investigator's knowledge this type of study has not been completed in this environment and/or patient population.
Research Objectives:
The main goal of this study is to determine whether genetic analysis of drug processing could help predict efficacy and side effect profiles of medications in a cohort of patients suffering from chronic pain.
In order to control for various clinical factors, patient reported outcomes will also be collected. As a standard part of any patient intake, pain diagrams, measures of pain, function, mental health status and exercise describe the conditions and relative impact will be included. Investigators will include various standardized and/or adapted versions of other questionnaires which will allow investigators to control for known confounders.
The following information will be collected at baseline
Demographics - age, gender, rank, working status, medical category
Patient Reported Outcomes at baseline (Appendix A)
The following information will be collected at follow up, defined by discontinuation of medication or continuation on medication associated with predefined measure of clinical efficacy
Clinical efficacy will be defined by achieving 5-8 on the Patient Global Impression of Change scale (PGIC). Medication selection will be done in accordance with current standard of care, patient informed consent and clinical experience. Prescription of medication will not be directed by the results of the genetics analytics. Doses will be adjusted if side effects permit and until clinical efficacy is achieved
Classification of inferred phenotypes (i.e. ultrarapid, normal, intermediate and poor metabolizer) will be consistent with the recently published guidance for allele function status. As noted, there are four possible scores for each tested medication, ranging from 1-4, which includes; 1) do not use 2) caution 3) use as directed 4) preferred. For the main analysis, the phenotypes will be grouped 1&2 (do not prescribe) and 3&4 (prescribe) and compared against whether patient responded or not to determine sensitivity and specificity of the genetic testing. Sub-analysis will determine for those that did not respond and whether this was a result of side effects or a lack of efficacy. From a functional standpoint for each recommendation the pharmacogenetics testing will classified into green (prescribe), yellow (caution), red (do no prescribe). All yellow outcomes will be reviewed to determine if the clinical information (ie dosing, smoking, and/or current medications), could allow for re-classification to a green or red recommendation for the purpose of the analysis.
The distribution of the prediction score will also be separately evaluated for medications actively taken by participants and for medications that had been discontinued. The distribution of prediction scores will be compared using ANOVA. Genetic prediction scores will be separately compared against participants reported efficacy and side effects profile using Spearman's correlation coefficient, and the respective p values will be calculated, and corrected for multiple comparison
Patient Care:
Participation in the current study will not impact patient care or impact decision making regarding medication. Each patient is simply evaluating the effects of the medications so that we can compare their experiences with the predictive abilities of genetic prediction score.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Patients with chronic pain | Patients seen in clinic agreeing to participate in trial by completing clinical questionnaires and genetic testing |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Genetic test for drug response prediction | Diagnostic Test | There is interest in whether genetic analysis of how a given drug is processed for a patient can help with rational drug choices (i.e. most efficacious, with least side effects/interactions, in the fastest time). This appears to have some early support in cardiac, psychiatric and acute pain studies. All participants enrolled in the study will provide consent and a buccal cell sample for genotyping and standard patient reported outcomes questionnaires at the beginning of the study. |
| Measure | Description | Time Frame |
|---|---|---|
| Sensitivity and Specificity of PGx testing for pain response | For the main analysis, the phenotypes will be grouped 1&2 (do not prescribe) and 3&4 (prescribe) and compared against whether patient responded or not to determine sensitivity and specificity of the genetic testing. Sub-analysis will determine for those that did not respond and whether this was a result of side effects or a lack of efficacy | up to 8 weeks post initial medication prescription |
| Measure | Description | Time Frame |
|---|---|---|
| Sensitivity and Specificity of PGx testing for side effects | For the main analysis, the phenotypes will be grouped 1&2 (do not prescribe) and 3&4 (prescribe) and compared against whether patient responded or not to determine sensitivity and specificity of the genetic testing. Sub-analysis will determine for those that did not respond and whether this was a result of side effects or a lack of efficacy |
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Inclusion Criteria:
Exclusion Criteria:
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The study population will be Canadian Forces members between the ages of 18-60 years old, suffering from chronic pain, seen within the Canadian Forces Ottawa Physical Medicine and Rehabilitation clinic (CFO-P).
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Canadian Forces Health Services Centre | Ottawa | Ontario | K1J6L4 | Canada |
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| ID | Term |
|---|---|
| D059350 | Chronic Pain |
| ID | Term |
|---|---|
| D010146 | Pain |
| D009461 | Neurologic Manifestations |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
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| ID | Term |
|---|---|
| D005820 | Genetic Testing |
| ID | Term |
|---|---|
| D019411 | Clinical Laboratory Techniques |
| D019937 | Diagnostic Techniques and Procedures |
| D003933 | Diagnosis |
| D008919 | Investigative Techniques |
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Our study will use Inagene commercial platform, a genomics-guided personalized medication management service that aims to predict how efficacious medications are and limiting potential side effects for a given patient. The platform itself uses genetic information and provides a report listing 4 possible scores for each tested medication, 1) do not use 2) caution 3) use as directed 4) preferred. This is consistent with recently published guidance for allele function status where phenotypes were sub-classified (i.e. ultrarapid, normal, intermediate and poor metabolizer
This appears to have some early support in cardiac, psychiatric and acute pain studies. In fact, the US Federal Drug Administration have made dosing recommendations to included CPY2D6 and CYP2C19 polymorphisms for certain psychotropic medications [ ]
|
| up to 8 weeks post initial medication prescription |
| D005821 | Genetic Techniques |
| D033142 | Genetic Services |
| D006296 | Health Services |
| D005159 | Health Care Facilities Workforce and Services |
| D003954 | Diagnostic Services |
| D011314 | Preventive Health Services |