BACKGROUND: Heterogeneity in overall response and outcomes to pharmacological treatment has been reported in several depression studies but with few sources that integrate these results. The goal of this study was to review the literature and attempt to identify nongenetic factors potentially predictive of overall response to depression treatments. METHODS: A comprehensive review of the literature from the last 10 years was performed using three key databases (PubMed, EMBASE, and Cochrane). All relevant studies that met the inclusion criteria were selected and scored for their levels of evidence using the NICE scoring method. A subjective assessment of the strength of evidence for each factor was performed using predefined criteria. RESULTS: Our broad search yielded 76 articles relevant to treatment heterogeneity. Sociodemographic factors, disease characteristics, and comorbidities were the most heavily researched areas. Some of the factors associated with more favorable overall response include being married, other social support, and low levels of baseline depressive symptoms. Evidence relating to baseline disease severity as a factor predictive of antidepressant response was particularly convincing among the factors reviewed. The presence of comorbid anxiety and pain contributed to worse antidepressant treatment outcomes. CONCLUSIONS: Several factors either predictive of or associated with overall response to antidepressant treatment have been identified. Inclusion of factors predictive of response in the design of future trials may help tailor treatments to depression patients presenting to the average clinical practice, resulting in improved outcomes.
BACKGROUND: Heterogeneity in overall response and outcomes to pharmacological treatment has been reported in several depression studies but with few sources that integrate these results. The goal of this study was to review the literature and attempt to identify nongenetic factors potentially predictive of overall response to depression treatments. METHODS: A comprehensive review of the literature from the last 10 years was performed using three key databases (PubMed, EMBASE, and Cochrane). All relevant studies that met the inclusion criteria were selected and scored for their levels of evidence using the NICE scoring method. A subjective assessment of the strength of evidence for each factor was performed using predefined criteria. RESULTS: Our broad search yielded 76 articles relevant to treatment heterogeneity. Sociodemographic factors, disease characteristics, and comorbidities were the most heavily researched areas. Some of the factors associated with more favorable overall response include being married, other social support, and low levels of baseline depressive symptoms. Evidence relating to baseline disease severity as a factor predictive of antidepressant response was particularly convincing among the factors reviewed. The presence of comorbid anxiety and pain contributed to worse antidepressant treatment outcomes. CONCLUSIONS: Several factors either predictive of or associated with overall response to antidepressant treatment have been identified. Inclusion of factors predictive of response in the design of future trials may help tailor treatments to depressionpatients presenting to the average clinical practice, resulting in improved outcomes.
Authors: Kathleen M Grubbs; Ann M Cheney; John C Fortney; Carrie Edlund; Xiaotong Han; Patricia Dubbert; Cathy D Sherbourne; Michelle G Craske; Murray B Stein; Peter P Roy-Byrne; J Greer Sullivan Journal: Psychiatr Serv Date: 2014-12-15 Impact factor: 3.084
Authors: Jutta M Joesch; Daniela Golinelli; Cathy D Sherbourne; Greer Sullivan; Murray B Stein; Michelle G Craske; Peter P Roy-Byrne Journal: Depress Anxiety Date: 2013-06-25 Impact factor: 6.505
Authors: Rebecca C Rossom; Leif I Solberg; Gabriela Vazquez-Benitez; Robin R Whitebird; A Lauren Crain; Arne Beck; Jürgen Unützer Journal: Psychiatr Serv Date: 2016-07-15 Impact factor: 3.084
Authors: Halina J Dour; Joshua F Wiley; Peter Roy-Byrne; Murray B Stein; Greer Sullivan; Cathy D Sherbourne; Alexander Bystritsky; Raphael D Rose; Michelle G Craske Journal: Depress Anxiety Date: 2013-12-12 Impact factor: 6.505
Authors: Vanessa Panaite; Nicholas W Bowersox; Kara Zivin; Dara Ganoczy; Hyungjin Myra Kim; Paul N Pfeiffer Journal: Health Serv Res Date: 2019-03-04 Impact factor: 3.402
Authors: Wei Duan-Porter; Karen M Goldstein; Jennifer R McDuffie; Jaime M Hughes; Megan E B Clowse; Ruth S Klap; Varsha Masilamani; Nancy M Allen LaPointe; Avishek Nagi; Jennifer M Gierisch; John W Williams Journal: Ann Intern Med Date: 2016-04-26 Impact factor: 25.391