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Letter to the Editor

Mr Jakubovski and Dr Bloch Reply

Ewgeni Jakubovski, MA; and Michael H. Bloch, MD, MS

Published: March 25, 2015

See Letter by Jain et al and Article by Jakubovski and Bloch

Mr Jakubovski and Dr Bloch Reply

To the Editor: We thank Dr Jain and colleagues for their interest in our recent article.1 The article written by Jain et al2 represents excellent complementary reading to our article. Although published prior to our article, their article was not MeSH indexed by the National Library of Medicine until February 22, 2014, long after our article was slated for publication. Unfortunately, this delay prevented our having the opportunity to comment on their work in our publication. We thank Jain et al and JCP for giving us the opportunity here to comment on the similarities and differences between our findings and their work.

We agree with Jain and colleagues that the likely sources of differences in results between the articles are (1) the inclusion of different baseline predictor variables between studies, (2) the restriction of our sample to those who actually completed 8 weeks of citalopram treatment, and (3) different definitions of remission between the studies. We do not wish to debate Dr Jain’s group regarding whose methodology is better, and we agree with them that their analysis of the data is also methodologically sound. Although Jain et al and our group made different choices regarding whether to examine for predictors of outcome in those who actually completed the treatment versus those who received citalopram treatment, these are both worthwhile questions for exploration.

We also welcome the opportunity to clear up any confusion regarding the relative importance of socioeconomic predictors and traditional clinical predictors in predicting selective serotonin reuptake inhibitor treatment outcome in major depressive disorder. In our article, we wrote, “Socioeconomic measures, such as income, employment status, and education, were the best predictors of treatment response and more discriminative than clinical attributes, such as past medication response, severity and duration of depression, comorbid psychiatric diagnoses, and substance use.”1(p742) This finding is consistent across both our results (most discriminant predictor for response was income and for remission was employment status) and Jain and colleagues’ 2 secondary analysis of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) data, in which income (remission) and education level (response) were the most discriminative predictors of citalopram outcomes.

We also wrote in our discussion, “Our analysis suggests, perhaps surprisingly, that these [socioeconomic] variables are likely to be more informative than routine clinical variables such as past medication response, duration and severity of illness, and comorbid psychiatric illnesses. Nonetheless, the ROC analysis also demonstrates on several occasions that the combination of a poor socioeconomic situation and poor clinical factors appears particularly pernicious.”1(p746) Jain and colleagues’ results add to our findings by suggesting that additional clinical variables that focus on individual depressive symptoms—particularly anxious depression, and possibly insomnia and significant aches and pains—may have better predictive value than other traditional clinical measures that we utilized. That being said, the predictive value of these symptoms is still less discriminate in their analysis than the socioeconomic measures and appears particularly powerful when used in combination with socioeconomic factors.

In conclusion, we thank Jain and colleagues and JCP for the opportunity to comment on their important work in relation to ours. Although there are clearly specific differences in the results between the 2 studies, which are well outlined in the letter by Jain et al and in the second paragraph of our response, the gestalt findings from the dataset are remarkably similar: (1) socioeconomic predictors (income, education, and employment status) were the most discriminative predictors of outcome, and (2) their predictive power was enhanced with traditional clinical predictors. There appears to be a particularly pernicious interaction between poor socioeconomic status and poor clinical factors. We would point readers to both articles on this topic, as we believe they are much more complementary than contradictory. Likewise, we encourage other investigators to study the STAR*D trial database to answer further important questions in depression treatment and research. The National Institute of Mental Health limited-access datasets represent a tremendously underutilized and important clinical research tool that was generously made publicly available to scientific investigators by the US government and individual trial investigators. We hope that our investigation, as well that of Jain and coworkers, represents the tip of the iceberg in terms of these efforts.


1. Jakubovski E, Bloch MH. Prognostic subgroups for citalopram response in the STAR*D trial. J Clin Psychiatry. 2014;75(7):738-747. PubMed doi:10.4088/JCP.13m08727

2. Jain FA, Hunter AM, Brooks JO 3rd, et al. Predictive socioeconomic and clinical profiles of antidepressant response and remission. Depress Anxiety. 2013;30(7):624-630. PubMed doi:10.1002/da.22045

Ewgeni Jakubovski, MA

Michael H. Bloch, MD, MS

Author affiliations: Connecticut Mental Health Center (Mr Jakubovski); Child Study Center, Yale University (both authors); and Department of Psychiatry, Yale University (Dr Bloch), New Haven, Connecticut.

Potential conflicts of interest: None reported.

Funding/support: The authors acknowledge the support of the National Institutes of Health (NIH) 1K23MH091240 (Dr Bloch); the APIRE/Eli Lilly Psychiatric Research Fellowship (Dr Bloch); the Rembrandt Foundation and UL1 RR024139 from the National Center for Research Resources, a component of the NIH; and NIH Roadmap for Medical Research (Dr Bloch).

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