TY - JOUR
T1 - The impact of age on antidepressant response
T2 - A mega-analysis of individuals with major depressive disorder
AU - Strawn, Jeffrey R.
AU - Mills, Jeffrey A.
AU - Suresh, Vikram
AU - Mayes, Taryn
AU - Gentry, Melanie T.
AU - Trivedi, Madhukar
AU - Croarkin, Paul E.
N1 - Funding Information:
The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government. The NIMH had no role in drafting or reviewing the manuscript or collecting or analyzing the data. Dr. Croarkin was supported under R01MH113700 and R01MH124655. Dr. Strawn was supported by the Yung Family Foundation and R01HD098757, R01HD099775, the National Institutes of Health Clinical and Translational Science Award ( CTSA ) program (UL1TR001425), and PCORI . The content of this publication is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/3
Y1 - 2023/3
N2 - 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.
AB - 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.
KW - Clinical trial
KW - Depression
KW - Major depressive disorder
KW - Selective serotonin reuptake inhibitor (SSRI)
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U2 - 10.1016/j.jpsychires.2023.01.043
DO - 10.1016/j.jpsychires.2023.01.043
M3 - Article
C2 - 36774767
AN - SCOPUS:85147822218
SN - 0022-3956
VL - 159
SP - 266
EP - 273
JO - Journal of Psychiatric Research
JF - Journal of Psychiatric Research
ER -