Exploration of a Machine Learning Model Using Self-rating Questionnaires for Detecting Depression in Patients with Breast Cancer

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Abstract

Objective

Given the long-term and severe distress experienced during breast cancer treatment, detecting depression among breast cancer patients is clinically crucial. This study aimed to explore a machine-learning model using self-report questionnaires to screen for depression in patients with breast cancer.

Methods

A total of 327 patients who visited the breast cancer clinic were included in this study. Depressive symptoms were measured using the Patient Health Questionnaire-9 (PHQ-9), Beck Depression Inventory (BDI), and Hospital Anxiety and Depression Scale (HADS). The depression was evaluated according to the Diagnostic and Statistical Manual of Mental Disorders 5th edition. The prediction model’s performance based on supervised machine learning was conducted using MATLAB2022.

Results

The BDI showed an area under the curve (AUC) of 0.785 when using the logistic regression (LR) classifier. The HADS and PHQ-9 showed an AUC of 0.784 and 0.756 when using the linear discriminant analysis, respectively. The combinations of BDI and HADS showed an AUC of 0.812 when using the LR. The combinations of PHQ-9, BDI, and HADS showed an AUC of 0.807 when using LR.

Conclusion

The combination model with BDI and HADS in breast cancer patients might be better than the method using a single scale. In future studies, it is necessary to explore strategies that can improve the performance of the model by integrating the method using questionnaires and other methods.

Related collections

Most cited references 35

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While considerable attention has focused on improving the detection of depression, assessment of severity is also important in guiding treatment decisions. Therefore, we examined the validity of a brief, new measure of depression severity. The Patient Health Questionnaire (PHQ) is a self-administered version of the PRIME-MD diagnostic instrument for common mental disorders. The PHQ-9 is the depression module, which scores each of the 9 DSM-IV criteria as "0" (not at all) to "3" (nearly every day). The PHQ-9 was completed by 6,000 patients in 8 primary care clinics and 7 obstetrics-gynecology clinics. Construct validity was assessed using the 20-item Short-Form General Health Survey, self-reported sick days and clinic visits, and symptom-related difficulty. Criterion validity was assessed against an independent structured mental health professional (MHP) interview in a sample of 580 patients. As PHQ-9 depression severity increased, there was a substantial decrease in functional status on all 6 SF-20 subscales. Also, symptom-related difficulty, sick days, and health care utilization increased. Using the MHP reinterview as the criterion standard, a PHQ-9 score > or =10 had a sensitivity of 88% and a specificity of 88% for major depression. PHQ-9 scores of 5, 10, 15, and 20 represented mild, moderate, moderately severe, and severe depression, respectively. Results were similar in the primary care and obstetrics-gynecology samples. In addition to making criteria-based diagnoses of depressive disorders, the PHQ-9 is also a reliable and valid measure of depression severity. These characteristics plus its brevity make the PHQ-9 a useful clinical and research tool.

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A self-assessment scale has been developed and found to be a reliable instrument for detecting states of depression and anxiety in the setting of an hospital medical outpatient clinic. The anxiety and depressive subscales are also valid measures of severity of the emotional disorder. It is suggested that the introduction of the scales into general hospital practice would facilitate the large task of detection and management of emotional disorder in patients under investigation and treatment in medical and surgical departments.

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The Hospital Anxiety and Depression Scale (HAD) was evaluated in a Swedish population sample. The purpose of the study was to compare the HAD with the Beck Depression Inventory (BDI) and Spielberger's State Trait Anxiety Inventory (STAI). A secondary aim was to examine the factor structure of the HAD. The results indicated that the factor structure was quite strong, consistently showing two factors in the whole sample as well as in different subsamples. The correlations between the total HAD scale and BDI and STAI, respectively, were stronger than those obtained using the different subscales of the HAD (the anxiety and depression subscales). As expected, there was also a stronger correlation between the HAD and the non-physical items of the BDI. It was somewhat surprising that the factor analyses were consistently extracting two factors, 'depression' and 'anxiety', while on the other hand both BDI and STAI tended to correlate more strongly with the total HAD score than with the specific depression and anxiety HAD subscales. Nevertheless, the HAD appeared to be (as was indeed originally intended) a useful clinical indicator of the possibility of depression and clinical anxiety.

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All references

Author and article information

Journal

Journal ID (nlm-ta): Clin Psychopharmacol Neurosci

Journal ID (iso-abbrev): Clin Psychopharmacol Neurosci

Title: Clinical Psychopharmacology and Neuroscience

Publisher: Korean College of Neuropsychopharmacology

ISSN (Print): 1738-1088

ISSN (Electronic): 2093-4327

Publication date (Print): 31 August 2024

Publication date (Electronic): 20 March 2024

Publication date PMC-release: 20 March 2024

Volume: 22

Issue: 3

Pages: 466-472

Affiliations

[1 ]Breast Cancer Clinic of Busan Cancer Center, Pusan National University Hospital, Busan, Korea

[2 ]Biomedical Research Institute, Pusan National University Hospital, Busan, Korea

[3 ]Department of Surgery, Pusan National University School of Medicine, Busan, Korea

[4 ]Department of Psychiatry, Pusan National University Hospital, Busan, Korea

[5 ]Department of Psychiatry, Pusan National University School of Medicine, Yangsan, Korea

[6 ]Department of Psychology, Gyeoungsang National University, Jinju, Korea

Author notes

Address for correspondence: Eunsoo Moon Department of Psychiatry and Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, 179 Gudeok-ro, Seo-gu, Busan 49241, Korea , E-mail: esmun@ 123456hanmail.net , ORCID: https://orcid.org/0000-0002-8863-3413, Taewoo Kang, Department of Surgery (Busan Cancer Center) and Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, 179 Gudeok-ro, Seo-gu, Busan 49241, Korea , E-mail: taewoo.d.kang@ 123456gmail.com , ORCID: https://orcid.org/0000-0002-6279-0904

Author information

Heeseung Park https://orcid.org/0000-0001-9889-5217

Kyungwon Kim https://orcid.org/0000-0001-8947-9078

Eunsoo Moon https://orcid.org/0000-0002-8863-3413

Hyun Ju Lim https://orcid.org/0000-0002-8962-8173

Hwagyu Suh https://orcid.org/0000-0002-0360-6708

Kyoung-Eun Kim https://orcid.org/0000-0001-6487-0935

Taewoo Kang https://orcid.org/0000-0002-6279-0904

Article

Publisher ID: cpn-22-3-466

DOI: 10.9758/cpn.23.1147

PMC ID: 11289607

PubMed ID: 39069686

SO-VID: 487bccaa-95cd-425f-8a3b-77e344b77ca8

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

History

Date received : 6 December 2023

Date revision received : 7 February 2024

Date accepted : 26 February 2024

Funding

Funding This study was supported by Biomedical Research Institute Grant (20210080), Pusan National University Hospital, Republic of Korea.