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Article

Prediction of Major Depressive Disorder Following Beta-Blocker Therapy in Patients with Cardiovascular Diseases

by
Suho Jin
1,
Kristin Kostka
2,
Jose D. Posada
3,
Yeesuk Kim
4,
Seung In Seo
5,
Dong Yun Lee
6,
Nigam H. Shah
3,
Sungwon Roh
7,
Young-Hyo Lim
8,
Sun Geu Chae
9,
Uram Jin
10,
Sang Joon Son
6,
Christian Reich
2,
Peter R. Rijnbeek
11,
Rae Woong Park
1,12,* and
Seng Chan You
1,*
1
Department of Biomedical Informatics, Ajou University School of Medicine, Suwon 16499, Korea
2
Real World Solutions, IQVIA, Cambridge, MA 02139, USA
3
Department of Medicine, School of Medicine, Stanford University, Stanford, CA 94305, USA
4
Department of Orthopaedic Surgery, College of Medicine, Hanyang University, Seoul 04763, Korea
5
Department of Internal Medicine, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul 05355, Korea
6
Department of Psychiatry, Ajou University School of Medicine, Suwon 16499, Korea
7
Department of Psychiatry, College of Medicine, Hanyang University, Seoul 04763, Korea
8
Division of Cardiology, Department of Internal Medicine, College of Medicine, Hanyang University, Seoul 04763, Korea
9
Department of Industrial Engineering, Hanyang University, Seoul 04763, Korea
10
Department of Cardiology, Ajou University School of Medicine, Suwon 16499, Korea
11
Department of Medical Informatics, Erasmus Medical Center, 3015 GD Rotterdam, The Netherlands
12
Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon 16499, Korea
 
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*
Authors to whom correspondence should be addressed.
J. Pers. Med. 2020, 10(4), 288; https://doi.org/10.3390/jpm10040288
Submission received: 4 November 2020 / Revised: 11 December 2020 / Accepted: 15 December 2020 / Published: 18 December 2020
(This article belongs to the Special Issue Personalized Medicine for Cardiovascular Disease)
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Abstract

Incident depression has been reported to be associated with poor prognosis in patients with cardiovascular disease (CVD), which might be associated with beta-blocker therapy. Because early detection and intervention can alleviate the severity of depression, we aimed to develop a machine learning (ML) model predicting the onset of major depressive disorder (MDD). A model based on L1 regularized logistic regression was trained against the South Korean nationwide administrative claims database to identify risk factors for the incident MDD after beta-blocker therapy in patients with CVD. We identified 50,397 patients initiating beta-blockers for CVD, with 774 patients developing MDD within 365 days after initiating beta-blocker therapy. An area under the receiver operating characteristic curve (AUC) of 0.74 was achieved. A history of non-selective beta-blockers and factors related to anxiety disorder, sleeping problems, and other chronic diseases were the most strong predictors. AUCs of 0.62–0.71 were achieved in the external validation conducted on six independent electronic health records and claims databases in the USA and South Korea. In conclusion, an ML model that identifies patients at high-risk for incident MDD was developed. Application of ML to identify susceptible patients for adverse events of treatment may serve as an important approach for personalized medicine.
Keywords: adrenergic beta-antagonists; depressive disorder; machine learning; cardiovascular diseases adrenergic beta-antagonists; depressive disorder; machine learning; cardiovascular diseases

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MDPI and ACS Style

Jin, S.; Kostka, K.; Posada, J.D.; Kim, Y.; Seo, S.I.; Lee, D.Y.; Shah, N.H.; Roh, S.; Lim, Y.-H.; Chae, S.G.; et al. Prediction of Major Depressive Disorder Following Beta-Blocker Therapy in Patients with Cardiovascular Diseases. J. Pers. Med. 2020, 10, 288. https://doi.org/10.3390/jpm10040288

AMA Style

Jin S, Kostka K, Posada JD, Kim Y, Seo SI, Lee DY, Shah NH, Roh S, Lim Y-H, Chae SG, et al. Prediction of Major Depressive Disorder Following Beta-Blocker Therapy in Patients with Cardiovascular Diseases. Journal of Personalized Medicine. 2020; 10(4):288. https://doi.org/10.3390/jpm10040288

Chicago/Turabian Style

Jin, Suho, Kristin Kostka, Jose D. Posada, Yeesuk Kim, Seung In Seo, Dong Yun Lee, Nigam H. Shah, Sungwon Roh, Young-Hyo Lim, Sun Geu Chae, and et al. 2020. "Prediction of Major Depressive Disorder Following Beta-Blocker Therapy in Patients with Cardiovascular Diseases" Journal of Personalized Medicine 10, no. 4: 288. https://doi.org/10.3390/jpm10040288

APA Style

Jin, S., Kostka, K., Posada, J. D., Kim, Y., Seo, S. I., Lee, D. Y., Shah, N. H., Roh, S., Lim, Y.-H., Chae, S. G., Jin, U., Son, S. J., Reich, C., Rijnbeek, P. R., Park, R. W., & You, S. C. (2020). Prediction of Major Depressive Disorder Following Beta-Blocker Therapy in Patients with Cardiovascular Diseases. Journal of Personalized Medicine, 10(4), 288. https://doi.org/10.3390/jpm10040288

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