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. 2023 Jan;29(1):107-118.
doi: 10.1177/13524585221122207. Epub 2022 Oct 27.

Polypharmacy and multiple sclerosis: A population-based study

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Polypharmacy and multiple sclerosis: A population-based study

Anibal Chertcoff et al. Mult Scler. 2023 Jan.

Abstract

Background: Little is known about polypharmacy and multiple sclerosis (MS).

Objectives: To estimate polypharmacy prevalence in a population-based MS cohort and compare persons with/without polypharmacy.

Methods: Using administrative and pharmacy data from Canada, we estimated polypharmacy prevalence (⩾5 concurrent medications for >30 consecutive days) in MS individuals in 2017. We compared the characteristics of persons with/without polypharmacy and described the number of polypharmacy days, the most common medication classes contributing to polypharmacy and hyper-polypharmacy prevalence (⩾10 medications).

Results: Of 14,227 included individuals (75% women), mean age = 55.4 (standard deviation (SD): 13.2) years; 28% (n = 3995) met criteria for polypharmacy (median polypharmacy days = 273 (interquartile range (IQR): 120-345)). Odds of polypharmacy were higher for women (adjusted odds ratio (aOR) = 1.14; 95% confidence intervals (CI):1.04-1.25), older individuals (aORs 50-64 years = 2.04; 95% CI:1.84-2.26; ⩾65 years = 3.26; 95% CI: 2.92-3.63 vs. <50 years), those with more comorbidities (e.g. ⩾3 vs. none, aOR = 6.03; 95% CI: 5.05-7.22) and lower socioeconomic status (SES) (e.g. most (SES-Q1) vs. least deprived (SES-Q5) aOR = 1.64; 95% CI: 1.44-1.86). Medication classes most commonly contributing to polypharmacy were as follows: antidepressants (66% of polypharmacy days), antiepileptics (47%), and peptic ulcer drugs (41%). Antidepressants were most frequently co-prescribed with antiepileptics (34% of polypharmacy days) and peptic ulcer drugs (27%). Five percent of persons (716/14,227) experienced hyper-polypharmacy.

Conclusion: More than one in four MS persons met criteria for polypharmacy. The odds of polypharmacy were higher for women, older persons, and those with more comorbidities, but lower SES.

Keywords: MS; pharmacoepidemiology; polypharmacy; population-based data; prescription medication use.

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Conflict of interest statement

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: A.C. receives funding from the MS Society of Canada’s endMS Postdoctoral Fellowship and the Michael Smith Foundation for Health Research Trainee Award. H.S.N. has received funding from the Multiple Sclerosis Society of Canada’s endMS Postdoctoral Fellowship, and the Michael Smith Foundation for Health Research Trainee Award. F.Z. and Y.Z. have no disclosures. H.T. has, in the last 5 years, received research support from the Canada Research Chair Program, the National Multiple Sclerosis Society, the Canadian Institutes of Health Research, the Multiple Sclerosis Society of Canada, and the Multiple Sclerosis Scientific Research Foundation. In addition, in the last 5 years, has had travel expenses or registration fees prepaid or reimbursed to present at CME conferences from the Consortium of MS Centers (2018), National MS Society (2016, 2018), ECTRIMS/ACTRIMS (2015, 2016, 2017, 2018, 2019, 2020, 2021, and 2022), American Academy of Neurology (2015, 2016, and 2019). Speaker honoraria are either declined or donated to an MS charity or to an unrestricted grant for use by HT’s research group.

Figures

Figure 1.
Figure 1.
Illustrative example of an individual meeting the definition of polypharmacy: concurrent exposure to at least five different medications for more than 30 consecutive days. *Medications A-E, represent five individual, unique medications (WHO’s ATC classification system, fifth level). The definition of polypharmacy was met as concurrent exposure to ⩾5 medications occurred between Day 10 and Day 50. The total number of polypharmacy days was 41. Using Medication E as an example to illustrate how overlapping prescription fills for the same drug were handled: on Day 40, another prescription was filled (dotted vertical line) before the previous supply of this medication was potentially exhausted. Thus, the last day of exposure for this medication was estimated based on the days of drug supplied at Day 40 (i.e. at the last prescription fill).
Figure 2.
Figure 2.
Flowchart of individuals with MS included in the study. MS: Multiple sclerosis; DMD: disease-modifying drug; BC: British Columbia.
Figure 3.
Figure 3.
Association between the characteristics of the MS population at study entry and the presence of polypharmacy (⩾5 concurrent medications for >30 days) in 2017. Cl: Confidence interval. Results were obtained from a logistic regression model. aORs represent the odds of polypharmacy accounting for the other characteristics shown in the Figure at study entry. SES quintiles were derived from each individual’s postal code linked to their neighborhood-level income. Comorbidity score was measured by using the Charlson Comorbidity Index (excluding hemiplegia/paraplegia) during the year before study entry.
Figure 4.
Figure 4.
Heatmap depicting the most frequent combinations of medication classes co-prescribed in the MS population exposed to polypharmacy (reported as the percentage (%) of the total number of polypharmacy days in 2017). GERD: Gastro-esophageal reflux disease; ACE: angiotensin-converting enzyme. Note for the interested reader: a post hoc descriptive analysis for individuals filling simultaneous prescriptions for antidepressants and antiepileptics (vs. those not) was performed, focusing on additional pain-related medications used (opioids and centrally acting muscle relaxants). More than half (52.1%; 788/1513) of the antidepressant/antiepileptic co-users (vs. 38.0%; 942/2482 of the non-co-users) also filled prescriptions for opioids, representing 28.2% (112,255/398,531) and 20.0% (107,141/536,833) of their polypharmacy days, respectively. In addition, 41.2% (624/1513) of antidepressant/antiepileptic co-users (vs. 29.4%; 730/2482 of the non-co-users) filled a prescription for a centrally acting muscle relaxant, representing 31.2% (124,191/398,531) and 24.3% (130,686/536,833) of their polypharmacy days, respectively.

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