Background & Aims
Persistent pain after injury or surgery places a significant burden on the individual, their family, and society [4]. We previously identified a subgroup of people at risk for ongoing pain after surgery and exercised induced injury, characterized by both genetic AND psychological factors [1,3]. In a pre-clinical trial, we did not find benefit for the primary outcome of pain recovery for treatments matched to genetic and psychological factors. However, pain sensitivity measures were not analyzed as part of the primary analyses. Measures of pain sensitivity have potential relevance for patient care based on value in predicting future pain after surgery and responses to treatment [2,5]. Here, we report on a planned secondary analysis examining the effect of the personalized interventions on pain sensitivity outcomes. We hypothesized that individuals receiving the matched interventions would report greater improvement in pain sensitivity compared to unmatched interventions.
Methods
Healthy individuals with the COMT AA genotype and Pain Catastrophizing Scale scores of 5 or higher were enrolled [1,3]. Consented individuals were screened. Those eligible received exercise-induced muscle injury on day 1, followed by four days of a randomly assigned treatment: general education and placebo, personalized psychologic and placebo, general education and propranolol, or personalized psychologic and propranolol. Pain sensitivity outcomes using quantitative sensory testing (QST) included pressure pain thresholds at local and remote sites, suprathreshold heat rating, temporal summation of second pain, and conditioned pain modulation efficiency. QST outcomes were compared using a mixed effect model to examine difference among groups, adjusted for age, sex and race. Additionally, propranolol and psychologic education were compared. Interaction terms were examined to guide future work. To adjust for multiple testing of between group differences, a graphical approach was used.
Results
No main effects for group assignment were noted (p>0.05), when considered as 4 groups or between the propranolol and placebo or between the personalized psychologic and general education. For PPT, interactions across sex and time, and race and time were noted in which thresholds in white participants became greater at the shoulder than non-white participants, and females became more sensitive to PPT over time compared to men. Interactions between sex and group and race and group were retained in the models for temporal summation measures. The responses to the interventions differed such that females assigned to propranolol and general education had greater temporal summation than females receiving placebo with personalized psychologic interventions. In addition, White participants assigned to propranolol and general education had elevated temporal summation compared to white participants in other groups and non-white participants. This finding was consistent for suprathreshold ratings.
Conclusions
Results indicated no change in pain sensitivity after receiving treatment matched to genetic and psychologic characteristics of the high-risk subgroup when compared to unmatched treatment. These findings largely align with findings from the primary trial primary outcome of pain recovery. Exploratory analysis of interactions among ethnic/racial and gender identities by treatment groups showed the potential for differential effects. Significant interactions terms across QST modalities (e.g., race and treatment group, sex and treatment group) suggest analysis of higher order interactions/intersectionality could be of great interest for testing efficacy of personalized interventions in future trials. These findings are meant to be hypothesis generating as future work in this area would require much larger samples of participants across the intersection of genetic haplotypes and racial and gender identities to make stronger clinical conclusions.
References
1. Borsa PA, Parr JJ, Wallace MR, et al. Genetic and psychological factors interact to predict physical impairment phenotypes following exercise-induced shoulder injury. J Pain Res. 2018;11:2497-2508. doi:10.2147/JPR.S171498
2. Edwards RR, Haythornthwaite JA, Tella P, Max MB, Raja S. Basal heat pain thresholds predict opioid analgesia in patients with postherpetic neuralgia. Anesthesiology. 2006;104(6):1243-1248. doi:10.1097/00000542-200606000-00020
3. George SZ, Parr JJ, Wallace MR, et al. Inflammatory genes and psychological factors predict induced shoulder pain phenotype. Med Sci Sports Exerc. 2014;46(10):1871-1881. doi:10.1249/MSS.0000000000000328
4. Vos T, Flaxman AD, Naghavi M, et al. Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380(9859):2163-2196. doi:10.1016/S0140-6736(12)61729-2
5. Yarnitsky D, Granot M, Nahman-Averbuch H, Khamaisi M, Granovsky Y. Conditioned pain modulation predicts duloxetine efficacy in painful diabetic neuropathy. Pain. 2012;153(6):1193-1198. doi:10.1016/j.pain.2012.02.021
Presenting Author
Mark D Bishop
Poster Authors
Mark Bishop
PhD
University of Florida
Lead Author
Corey Simon
PT
Department of Orthopaedic Surgery, Duke University, North Carolina, USA
Lead Author
Yunan Huo
PhD
Gilead Sciences, Inc., Los Angeles, USA
Lead Author
Samuel S Wu
PhD
Department of Biostatistics, University of Florida, Florida, USA
Lead Author
Steven George
Duke University
Lead Author
Topics
- Treatment/Management: Pharmacology: Non-opioid