A real-world analysis of antidepressant medications in US veterans aged 60 years and older: a comparative analysis
Publication: Journal of Comparative Effectiveness Research
Abstract
Aim: To compare the safety and efficacy of antidepressants (AD) among older adults with major depressive disorder (MDD) by assessing treatment change, augmentation and hospitalization rates. Methods: This retrospective study analyzed data from the Veterans Affairs (VA) database, including 142,138 patients aged ≥60 years diagnosed with MDD. Patients prescribed bupropion, citalopram, duloxetine, escitalopram, fluoxetine, mirtazapine, paroxetine, sertraline, or venlafaxine were included. Outcomes were treatment change, augmentation and hospitalization rates. Hazard ratios (aHRs) were calculated using sertraline as the reference. Results: Of the patients, 39.6% required augmentation, 18.1% changed antidepressant treatment and 13.3% were hospitalized. The corresponding incidence rate was 544, 124 and 122 events per 1000 person-years. Compared with sertraline, mirtazapine users had the highest AD change risk (aHR 1.34, 95% CI: 1.29–1.40), while duloxetine users had the lowest (aHR 0.87, 95% CI: 0.83–0.92). Duloxetine also had the lowest augmentation risk (aHR 0.89, 95% CI: 0.86–0.92). Mirtazapine users also had the highest risks of augmentation (aHR 1.15, 95% CI: 1.12–1.18) and hospitalization (aHR 1.14, 95% CI: 1.07–1.23). Bupropion had the lowest hospitalization risk (aHR 0.77, 95% CI: 0.71–0.84). Conclusion: Antidepressant choice significantly influences treatment outcomes in older adults with MDD. Duloxetine demonstrated the best profile with the lowest risks of AD change and augmentation, while mirtazapine posed the highest risks of all three outcomes. Personalized treatment strategies are crucial to improving outcomes in this population.
Plain language summary
What is this article about?
This article looks at how different antidepressants work for people aged 60 years or older who have major depressive disorder (MDD), a common and serious mental health condition. Older adults often experience unique challenges with depression, including side effects from medications and a higher likelihood of needing to change treatments. The study analyzed real-world data from the US Department of Veterans Affairs to better understand three key outcomes for older adults taking antidepressants:
1.
How often they change antidepressant.
2.
How often they need additional medications (augmentation).
3.
How often they are hospitalized.
What were the results?
The study found that:
•
Changing antidepressant: About 18% of patients changed their antidepressant. Duloxetine was the least likely to be changed, while mirtazapine and citalopram had the highest risks of being changed.
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Adding medications (augmentation): Nearly 40% of patients needed an additional medication. Duloxetine and bupropion were the least likely to need augmentation, while mirtazapine had the highest risk.
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Hospitalization: Only 13.3% of patients were hospitalized. Mirtazapine was associated with the highest risk of hospitalization, while bupropion had the lowest.
What do the results of the study mean?
The study highlights that not all antidepressants work the same for older adults. Some medications are more likely to require changes or additional treatments, and some are linked to higher risks of hospitalization. This information can help doctors make better decisions when prescribing antidepressants to older patients, balancing the potential benefits with the risks of side effects or complications. Importantly, the study does not recommend one antidepressant over another but aims to provide a clearer understanding to guide treatment choices. This summary is intended to make the study more accessible to patients, caregivers and advocates who want to understand how depression treatments work in older adults.
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References
Papers of special note have been highlighted as: • of interest; •• of considerable interest
1.
Jorm AF, Patten SB, Brugha TS, Mojtabai R. Has increased provision of treatment reduced the prevalence of common mental disorders? Review of the evidence from four countries. World Psychiatry 16(1), 90–99 (2017).
2.
Andrews G. Reducing the burden of depression. Can. J. Psychiatry 53(7), 420–427 (2008).
3.
Herrman H, Kieling C, McGorry P et al. Reducing the global burden of depression: a Lancet–World Psychiatric Association Commission. Lancet 394(10193), 1553–1554 (2019).
4.
Health NIoM. Major Depression 2023 [cited 2024]. Available from: https://www.samhsa.gov/data/report/2021-nsduh-annual-national-report
5.
Greenberg P, Chitnis A, Louie D et al. The economic burden of adults with major depressive disorder in the United States (2019). Adv. Ther. 40(10), 4460–4479 (2023).
• Highlights the significant economic burden of major depressive disorder (MDD) in the USA, emphasizing the importance of improving treatment outcomes to reduce healthcare costs.
6.
Administration USFD. Depression medicines: From the FDA Office of Women's Health 2019 [cited 2024]. Available from: https://www.fda.gov/consumers/womens-health-topics/depression-medicines
7.
Henssler J, Kurschus M, Franklin J et al. Long-term acute-phase treatment with antidepressants, 8 weeks and beyond: a systematic review and meta-analysis of randomized, placebo-controlled trials. J. Clin. Psychiatry 79(1), 15r10545 (2018).
•• Provides evidence for the long-term effectiveness of antidepressants, underscoring their role in managing chronic depression and preventing relapse.
8.
Kishi T, Ikuta T, Sakuma K et al. Antidepressants for the treatment of adults with major depressive disorder in the maintenance phase: a systematic review and network meta-analysis. Mol. Psychiatry 28(1), 402–409 (2023).
9.
Undurraga J, Baldessarini RJ. Randomized, placebo-controlled trials of antidepressants for acute major depression: thirty-year meta-analytic review. Neuropsychopharmacology 37(4), 851–864 (2012).
10.
Cipriani A, Furukawa TA, Salanti G et al. Comparative efficacy and acceptability of 21 antidepressant drugs for the acute treatment of adults with major depressive disorder: a systematic review and network meta-analysis. Lancet 391(10128), 1357–1366 (2018).
•• Offers a comprehensive comparison of antidepressant drugs, crucial for understanding variations in effectiveness and tolerability among treatment options.
11. .
Caplan Z. U.S. older population grew from 2010 to 2020 at fastest rate since 1880 to 1890. Census Bureau Available from: https://www.census.gov/library/stories/2023/05/2020-census-united-states-older-population-grew.html
12.
Fried EI, Flake JK, Robinaugh DJ. Revisiting the theoretical and methodological foundations of depression measurement. Nat. Rev. Psychol. 1(6), 358–368 (2022).
13.
Gutsmiedl K, Krause M, Bighelli I et al. How well do elderly patients with major depressive disorder respond to antidepressants: a systematic review and single-group meta-analysis. BMC Psychiatry 20(1), 102 (2020).
• Examines the efficacy of antidepressants specifically in elderly populations, providing a valuable context for the study's target demographic.
14.
Jakobsen JC, Gluud C, Kirsch I. Should antidepressants be used for major depressive disorder? BMJ Evid. Based Med. 25(4), 130 (2020).
• Critically assesses the risks and benefits of antidepressants, providing a balanced perspective on their use in managing MDD.
15.
Rush AJ, Sackeim HA, Conway CR et al. Clinical research challenges posed by difficult-to-treat depression. Psychol. Med. 52(3), 419–432 (2022).
16.
Umbricht D, Niggli M, Sanwald-Ducray P et al. Randomized, double-blind, placebo-controlled trial of the mGlu2/3 negative allosteric modulator decoglurant in partially refractory major depressive disorder. J. Clin. Psychiatry 81(4), 18m12470 (2020).
17.
Cheon EJ, Bearden CE, Sun D et al. Cross disorder comparisons of brain structure in schizophrenia, bipolar disorder, major depressive disorder, and 22q11.2 deletion syndrome: a review of ENIGMA findings. Psychiatry Clin. Neurosci. 76(5), 140–161 (2022).
18.
Mandal PK, Gaur S, Roy RG et al. Schizophrenia, bipolar and major depressive disorders: overview of clinical features, neurotransmitter alterations, pharmacological interventions, and impact of oxidative stress in the disease process. ACS Chem. Neurosci. 13(19), 2784–2802 (2022).
19.
Hsu CW, Tseng WT, Wang LJ et al. Comparative effectiveness of antidepressants on geriatric depression: real-world evidence from a population-based study. J. Affect. Disord. 296, 609–615 (2022).
•• Directly aligns with the study's focus, offering real-world insights into the effectiveness of antidepressants in older adults and informing clinical decisions.
20.
UpToDate. Depression in adults: antidepressant doses 2024 [cited 2024]. Available from: https://www.uptodate.com/contents/image?imageKey=PC%2F53818
21.
Sheffler ZM, Patel P, Abdijadid S. Antidepressants. StatPearls, Treasure Island (FL) (2024)).
22.
Moussavi S, Chatterji S, Verdes E et al. Depression, chronic diseases, and decrements in health: results from the World Health Surveys. Lancet 370(9590), 851–858 (2007).
23.
Rovner BW, German PS, Brant LJ et al. Depression and mortality. JAMA 265(8), 993–996 (1991).
24.
Ayerbe L, Ayis S, Crichton SL et al. Explanatory factors for the increased mortality of stroke patients with depression. Neurology 83(22), 2007–2012 (2014).
25.
Chiu CC, Liu HC, Li WH et al. Incidence, risk, and protective factors for suicide mortality among patients with major depressive disorder. Asian J. Psychiatry 80, 103399 (2023).
26.
Zhang Z, Jackson SL, Gillespie C et al. Depressive symptoms and mortality among US adults. JAMA Netw. Open 6(10), e2337011 (2023).
27.
Giovannini S, Onder G, van der Roest HG et al. Use of antidepressant medications among older adults in European long-term care facilities: a cross-sectional analysis from the SHELTER study. BMC Geriatr. 20(1), 310 (2020).
28.
Pradier MF, McCoy TH Jr, Hughes M et al. Predicting treatment dropout after antidepressant initiation. Transl. Psychiatry 10(1), 60 (2020).
29.
Nigatu YT, Bultmann U, Reijneveld SA. The prospective association between obesity and major depression in the general population: does single or recurrent episode matter? BMC Public Health 15, 350 (2015).
30.
Pickering RP, Goldstein RB, Hasin DS et al. Temporal relationships between overweight and obesity and DSM-IV substance use, mood, and anxiety disorders: results from a prospective study, the National Epidemiologic Survey on Alcohol and Related Conditions. J. Clin. Psychiatry 72(11), 1494–1502 (2011).
31.
Ul-Haq Z, Smith DJ, Nicholl BI et al. Gender differences in the association between adiposity and probable major depression: a cross-sectional study of 140,564 UK Biobank participants. BMC Psychiatry 14, 153 (2014).
32.
Godin O, Elbejjani M, Kaufman JS. Body mass index, blood pressure, and risk of depression in the elderly: a marginal structural model. Am. J. Epidemiol. 176(3), 204–213 (2012).
33.
Ishtiak-Ahmed K, Musliner KL, Christensen KS et al. Real-world evidence on clinical outcomes of commonly used antidepressants in older adults initiating antidepressants for depression: a nationwide cohort study in Denmark. Am. J. Psychiatry 181(1), 47–56 (2024).
34. .
Glenmullen J. The antidepressant solution: a step-by-step guide to safely overcoming antidepressant withdrawal, dependence, and “addiction. Free Press, NY, USA (2006).
35. .
Publishing HH. Going off antidepressants: coming off your medication can cause antidepressant withdrawal – and could set you up for a relapse of depression. Harvard Medical School (2022). Available from: https://www.health.harvard.edu/diseases-and-conditions/going-off-antidepressants
36.
Thunander Sundbom L, Bingefors K, Hedborg K et al. Are men under-treated and women over-treated with antidepressants? Findings from a cross-sectional survey in Sweden. B. J. Psych Bull. 41(3), 145–150 (2017).
37.
McGregor B, Li C, Baltrus P et al. Racial and ethnic disparities in treatment and treatment type for depression in a national sample of Medicaid recipients. Psychiatr. Serv. 71(7), 663–669 (2020).
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© 2025 The authors. This work is licensed under the Attribution-NonCommercial-NoDerivatives 4.0 Unported License
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Received: 26 September 2024
Accepted: 16 December 2024
Published online: 21 January 2025
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A real-world analysis of antidepressant medications in US veterans aged 60 years and older: a comparative analysis. (2025) Journal of Comparative Effectiveness Research. DOI: 10.57264/cer-2024-0187
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Citing Literature
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- Oscar Fraile-Martinez, Cielo Garcia-Montero, Miguel Angel Alvarez-Mon, Miguel A. Ortega, Melchor Alvarez-Mon, Javier Quintero, Delving into the Perception, Use, and Context of Duloxetine in Clinical Practice: An Analysis Based on the Experience of Healthcare Professionals, Brain Sciences, 10.3390/brainsci15070757, 15, 7, (757), (2025).