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Predicting relapse with individual residual symptoms in major depressive disorder: a reanalysis of the STAR*D data

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Abstract

Background

Residual symptoms are detrimental to prognosis in major depressive disorder (MDD); however, little is known about the contribution of each residual symptom in predicting outcomes. The objective of this analysis was to identify which individual symptoms, based on self-report and clinician interview, could predict subsequent relapse.

Methods

The data of 1133 outpatients with nonpsychotic MDD who entered a 12-month naturalistic follow-up phase after achieving remission with level 1 treatment (i.e., citalopram for up to 14 weeks) and had at least one post-baseline contact in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial were analyzed. Specific residual symptoms in the 16-item Quick Inventory of Depressive Symptomatology, self-report (QIDS-SR16) and clinician rating (QIDS-C16), at the follow-up entry that predicted relapse were identified, using a Cox proportional hazards model.

Results

The following three QIDS-SR16 symptoms were significantly associated with subsequent relapse: restlessness (HR = 1.197, p = 0.018), hypersomnia (HR = 1.190, p = 0.009), and weight change (HR = 1.127, p = 0.041). On the other hand, the following three symptoms in the QIDS-C16 at the follow-up entry were significantly associated with relapse in the follow-up phase: restlessness (HR = 1.328, p = 0.001), sleep onset insomnia (HR = 1.129, p = 0.047), and weight change (HR = 1.125, p = 0.045).

Limitations

The original trial was not designed to evaluate the issue addressed herein. Individual symptoms may be associated with each other and functional status was not addressed.

Conclusions

Some residual symptoms, including restlessness, insomnia, and weight change, may help better identify patients with MDD vulnerable to relapse. Contribution of individual residual symptoms to subsequent relapse was similar between self-report and clinician-rated symptoms.

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Acknowledgments

Data used in the preparation of this article were obtained from the limited access datasets distributed from the NIH-supported Sequenced Treatment Alternatives to Relieve Depression (STAR*D). STAR*D focused on nonpsychotic major depressive disorder in adults seen in outpatient settings. The primary purpose of this research study was to determine which treatments work best if the first treatment with medication does not produce an acceptable response. The study was supported by NIMH Contract # N01MH90003 to the University of Texas Southwestern Medical Center. The ClinicalTrials.gov identifier is NCT00021528. The version of the dataset used was 2.

Contribution of authors

Hitoshi Sakurai: study design, study analysis, interpretation of data, and article draft

Takefumi Suzuki: interpretation of data and article draft

Kimio Yoshimura: study analysis

Masaru Mimura: article revision

Hiroyuki Uchida: study design, study analysis, interpretation of data, and article draft

Author information

Authors and Affiliations

  1. Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan

    Hitoshi Sakurai, Takefumi Suzuki, Kimio Yoshimura, Masaru Mimura & Hiroyuki Uchida

  2. Department of Health Policy and Management, Keio University School of Medicine, Tokyo, Japan

    Kimio Yoshimura

  3. Geriatric Mental Health Program, Centre for Addiction and Mental Health, Toronto, ON, Canada

    Hiroyuki Uchida

Authors
  1. Hitoshi Sakurai
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Corresponding author

Correspondence to Hitoshi Sakurai.

Ethics declarations

Following a complete description of the study, participants provided written informed consent at the study enrollment in the original studies. Because of the completely anonymous nature of this analysis and an absence of direct human involvement, no ethical approval was sought for the present analysis.

Disclaimer

This manuscript reflects the views of the authors and may not reflect the opinions or views of the STAR*D Study Investigators or the NIH.

Role of funding

No funding support for the present analysis of the data from STAR*D.

The funding source for STAR*D had no role in any content of the present work.

Disclosures

Dr. Sakurai has received manuscript or speaker’s honoraria from Dainippon Sumitomo, Eli Lilly, Meiji-Seika Pharma, Otsuka Pharmaceutical, Tanabe Mitsubishi Pharma, and Yoshitomi Yakuhin within the past 3 years. Dr. Suzuki has received manuscript or speaker’s honoraria from Astellas, Dainippon Sumitomo, Eli Lilly, Elsevier Japan, Janssen, Meiji Seika, Novartis, Otsuka, and Weily Japan within the past 3 years. Dr. Yoshimura has nothing to declare. Dr. Mimura has received grants and/or speaker’s honoraria from Asahi Kasei Pharma, Astellas Pharmaceutical, Daiichi Sankyo, Dainippon-Sumitomo Pharma, Eisai, Eli Lilly, GlaxoSmithKline, Janssen Pharmaceutical, Meiji-Seika Pharma, Mochida Pharmaceutical, MSD, Novartis Pharma, Otsuka Pharmaceutical, Pfizer, Shionogi, Takeda, Tanabe Mitsubishi Pharma, and Yoshitomi Yakuhin within the past 3 years. Dr. Uchida has received grants from Astellas Pharmaceutical, Eisai, Otsuka Pharmaceutical, Shionogi, Dainippon-Sumitomo Pharma, Eli Lilly, Mochida Pharmaceutical, Meiji-Seika Pharma, and Yoshitomi Yakuhin and speaker’s honoraria from Otsuka Pharmaceutical, Eli Lilly, Shionogi, Pfizer, Yoshitomi Yakuhin, Dainippon-Sumitomo Pharma, Meiji-Seika Pharma, MSD, and Janssen Pharmaceutical within the past 3 years.

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Sakurai, H., Suzuki, T., Yoshimura, K. et al. Predicting relapse with individual residual symptoms in major depressive disorder: a reanalysis of the STAR*D data. Psychopharmacology 234, 2453–2461 (2017). https://doi.org/10.1007/s00213-017-4634-5

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  • DOI: https://doi.org/10.1007/s00213-017-4634-5

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