The impact of age on antidepressant response: A mega-analysis of individuals with major depressive disorder. (March 2023)

• Record Type: Journal Article
• Authors: Strawn, Jeffrey R.; Mills, Jeffrey A.; Suresh, Vikram; Mayes, Taryn; Gentry, Melanie T.; Trivedi, Madhukar; Croarkin, Paul E.
• Is Part Of: Journal of psychiatric research. Volume 159(2023)
• Page Start: 266
• Page End: 273
• Publication Date: 2023-03
• Subjects: Depression -- Major depressive disorder -- Selective serotonin reuptake inhibitor (SSRI) -- Clinical trial; Psychiatry -- Periodicals; Mental Disorders -- Periodicals; Maladies mentales -- Périodiques; Psychiatry; Electronic journals; Periodicals; 616.89005
• DOI: 10.1016/j.jpsychires.2023.01.043
• Languages: English
• ISSNs: 0022-3956

Abstract

Abstract: Introduction: Understanding how age affects antidepressant response in patients with major depressive disorder has been complicated by small and heterogeneous studies. Yet, understanding how age—across the lifespan—contributes to variation in response could inform treatment selection across the lifespan. This study sought to identify how age impacts antidepressant response using participant-level data from large, NIH-sponsored trials in individuals with MDD aged 12–74 years. Materials and methods: Participant-level data were abstracted from three NIH-sponsored trials of pharmacotherapy (Treatment of SSRI-Resistant Depression in Adolescents (TORDIA) Study, Treatment of Adolescent Depression Study (TADS), and the Combining Medications to Enhance Depression Outcomes Study (COMED)) in patients with MDD. Bayesian Hierarchical Models (BHMs) of individual treatment trajectories were developed using Hamiltonian Monte Carlo No U-Turn Sampling. The individual trajectory of improvement in depressive symptoms (Clinical Global Impression-Severity [CGI-S] and CGI-S equivalent from COMED) was modeled across studies and across individuals with logarithmic trend "random effects" coefficients BHMs. Age and sex (and their interaction) were examined categorically across patients. Results: Study participants ( N = 907) were 29.7 ± 17 years of age, 66.3% women, and had a mean baseline CGI-S score of 4.6 ± 0.9. Patients ≤21 years and those >55 years had slower and less response to pharmacotherapy compared to those aged 21–35. Additionally, women improved more than men, and this effect did not differ across ages. Discussion: The patient's age should be considered in predicting antidepressant response, particularly in older and younger individuals who may benefit from other interventions to enhance treatment response. Highlights: Few studies have examined the impact of age on treatment response in MDD. Age significantly affects medication response in MDD. Antidepressant treatment response is less robust in younger and older patients.