Pharmacogenetic Testing and Chronic 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

1. Demographics - age, gender, rank, working status, medical category
2. Patient Reported Outcomes at baseline (Appendix A)
3. Body Pain Diagram
4. Pain, Enjoyment and General Activity Scale (PEG)
5. Pain Disability Index
6. Hospital Anxiety and Depressions Scale (HADS)
7. Adapted Deployment Risk \& Resilience Inventory 2 Section J: Unit Support Exercise Questionnaire
8. Brief Trauma Questionnaire (BTQ)
9. Litigation Status

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

1. Medication Efficacy and Side effect Form - for each prescribed medication noted perceived efficacy, severity of side effects and general comments. This will be completed at either the time of medication discontinuation, or when no further changes to dosing is made.
2. Previous medication taken (Appendix B) - investigators will look specifically at commonly prescribed pain medications, including: nortriptyline, duloxetine, topiramate, gabapentin, pregabalin, opioids (ie morphine derivatives, tramadol, tapentadol, buprenorphine patch), Cesamet and plant based cannabis. If necessary, the patient's health record will be accessed to complete this record
3. Current medications
4. Smoking status and total starting/current dose

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.