Background & Aims
Despite decades of research on chronic pain (CP) treatment, its management remains suboptimal [1, 2]. Notably, the importance of finding solutions for optimal medication use has been emphasized [3]. In fact, the use of medication is frequent among individuals living with CP (>70% use ?5 medications [4]). Several pain medications are often combined and work through diverse mechanisms but polypharmacy may carry adverse effects [5, 6]. Hence, quantifying the risks associated with medication use is helpful for enhancing patient safety, informing decisions, and raising awareness for responsible medication use. However, quantifying these risks is challenging, as the risk may change over time and according to patient characteristics. As sex disparities in pain medication use and adverse effects prevalence has been demonstrated [7, 8], this study aimed to explore sex differences in risk trajectories associated with medication use for chronic pain using trajectory modelling techniques.
Methods
This retrospective cohort study was conducted using the TorSaDE Cohort (n=102,148), which links data from Quebec health administrative databases and the Canadian Community Health Survey [9]. The cohort includes survey respondents from the province of Quebec who participated in at least one of the 2007-2016 cycles. Health administrative databases include health care services claims, hospitalizations, diagnoses, and health insurance registration information for all Quebec residents. 8,760 adults reporting CP and covered by the public drug insurance in the two years post survey completion were selected. During those two years, the monthly risk associated with medication use was calculated using the Medication Quantification Scale 4.0 [10]. This score is obtained by assigning risk weights to each pain medication used by patients. Growth Mixture Modeling [11] was applied to identify subgroups of individuals with similar patterns of risk over time (risk trajectories) among females and males.
Results
Among females and males respectively, the mean age was 64.6±14.6 vs. 61.8±15.0, and 27.3% vs. 19.5% used ?10 medications in the first 90-day of study period. Similar patterns (shape and number) were found for females and males respectively: 1) low-stable risk over time (n=1,798; 31.6% vs. n=1,185; 38.5%), 2) moderate-stable risk (n=3,035; 53.4% vs. n=1,444; 44.9%), 3) moderate risk with a marked increase over time (n=429; 7.6% vs. n=223; 7.3%), 4) high risk with a marked decrease over time (n=422; 7.4% vs. n=224; 7.3%). In females, the “moderate-risk-increasing” group showed the highest proportion of persons with moderate/severe pain intensity and the “high-risk-decreasing” group was the one with the highest proportion of persons using ?10 medications, with some/most activities prevented by pain, with fair/poor perceived general health, and highest Charlson comorbidity index mean score. In males, different profiles were found in those trajectory groups.
Conclusions
Our study is timely in the context of IASP’s Global Year about Sex and Gender Disparities in Pain. We showed four risk trajectories (subgroups) associated with medication use for CP among females and males, in a broad community sample of individuals residing in Quebec, Canada. Although the same number of groups and similar patterns of risks were observed among females and males, groups’ sociodemographic and health profiles for a same type of trajectory were not necessarily the same. This suggests the importance of considering sex- and gender-differences when studying disparities and inequities associated with medication use for CP to effectively prevent them. Our next step will be to explore how gender-related variables (e.g. employment status, income, household responsibilities, etc.) intersect with sex to affect risk trajectories to better understand biological vs. modifiable social factors.
References
1.Campbell, F., M. Hudspith, and M. Choinière, La douleur chronique au Canada: jeter les bases d’un programme d’action. Rapport du groupe de travail canadien sur la douleur, 2019.
2.Lacasse, A., M. Choinière, and J.-A. Connelly, Knowledge, beliefs, and attitudes of the Quebec population toward chronic pain: Where are we now? Canadian Journal of Pain, 2017. 1(1): p. 151-160.
3.El-Gabalawy, R., et al., A longitudinal examination of anxiety disorders and physical health conditions in a nationally representative sample of U.S. older adults. Exp Gerontol, 2014. 60: p. 46-56.
4.Zahlan, G., et al., Polypharmacy and Excessive Polypharmacy Among Persons Living with Chronic Pain: A Cross-Sectional Study on the Prevalence and Associated Factors. Journal of Pain Research, 2023: p. 3085-3100.
5.Sirois, C., et al., Polypharmacy definitions for multimorbid older adults need stronger foundations to guide research, clinical practice and public health. Pharmacy, 2019. 7(3): p. 126.
6.Pazan, F. and M. Wehling, Polypharmacy in older adults: a narrative review of definitions, epidemiology and consequences. European geriatric medicine, 2021. 12: p. 443-452.
7.Nguena Nguefack, H.L., et al., Gender Differences in Medication Adverse Effects Experienced by People Living With Chronic Pain. Frontiers in Pain Research, 2022. 3.
8.Hopkins, R.E., et al., Use of pharmacological and nonpharmacological treatments for chronic noncancer pain among people using opioids: a longitudinal cohort study. PAIN, 2022. 163(6): p. 1049-1059.
9.Vanasse, A., et al., Cohort profile: the care trajectories—enriched data (TorSaDE) cohort. International journal of epidemiology, 2021. 50(4): p. 1066-1066h.
10.De Clifford-Faugère, G., et al., The Medication Quantification Scale 4.0: An Updated Index Based on Prescribers’ Perceptions of the Risk Associated With Chronic Pain Medications. The Journal of Pain, 2023.
11.Muthén, B., Latent variable analysis: Growth mixture modeling and related techniques for longitudinal data., in Handbook of quantitative methodology for the social sciences, D. Kaplan, Editor. 2004, CA: Sage: Newbury Park. p. 345-368.
Presenting Author
Hermine Lore Nguena Nguefack
Poster Authors
Hermine Lore Nguena Nguefack
MSc
Université du Québec en Abitibi-Témiscamingue (UQAT)
Lead Author
Nancy Ménard
Université du Québec en Abitibi-Témiscamingue
Lead Author
Sylvie Beaudoin
Université du Québec en Abitibi-Témiscamingue
Lead Author
Gabrielle Pagé
University of Montreal
Lead Author
Line Guénette
D.Pharm
Université Laval
Lead Author
Catherine Hudon
PhD
Centre de recherche du Centre hospitalier universitaire de Sherbrooke (CRCHUS)
Lead Author
Oumar Mallé Samb
PhD
Université du Québec en Abitibi-Témiscamingue
Lead Author
Anaïs Lacasse
PhD
Université du Québec en Abitibi-Témiscamingue
Lead Author
Topics
- Gender/Sex Differences