Observational Study
Copyright ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Oncol. Apr 24, 2025; 16(4): 102208
Published online Apr 24, 2025. doi: 10.5306/wjco.v16.i4.102208
Construction of a nomogram-based risk prediction model for depressive symptoms in middle-aged and young breast cancer patients
Ye Mao, Rui-Xin Shi, Lei-Ming Gao, An-Ying Xu, Jia-Ning Li, Bei Wang, Jun-Yuan Wu
Ye Mao, Rui-Xin Shi, Lei-Ming Gao, School of Nursing, Nanjing University of Chinese Medicine, Nanjing 210023, Jiangsu Province, China
An-Ying Xu, School of Artificial Intelligence and Information Technology, Nanjing University of Chinese Medicine, Nanjing 210023, Jiangsu Province, China
Jia-Ning Li, Bei Wang, Department of Nursing, Province Academy of Traditional Chinese Medicine, Nanjing 210028, Jiangsu Province, China
Bei Wang, Department of Nursing, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing 210028, Jiangsu Province, China
Jun-Yuan Wu, Department of Critical Care Medicine, Province Academy of Traditional Chinese Medicine, Nanjing 210028, Jiangsu Province, China
Co-corresponding authors: Bei Wang and Jun-Yuan Wu.
Author contributions: Mao Y designed the research and wrote the paper; Mao Y, Wang B, Wu JY, and Li JN conceived the work; Shi RX and Gao LM performed data acquisition; Mao Y and Xu AY analyzed and interpreted the data; Wang B, Wu JY, and Li JN performed critical revision of the manuscript. All authors have read the article and approved the submitted version. Designating Wang B and Wu JY as co-corresponding authors is justified due to their significant and distinct contributions to this research. Wang B, with her expertise in breast cancer, played a critical role in the conceptualization and methodology of the study, ensuring its alignment with current academic standards. Meanwhile, Wu JY contributed extensively in statistical analysis, leading the data analysis and interpretation phases, which were essential for drawing robust conclusions. This dual leadership reflects an equitable distribution of responsibilities and recognizes the collaborative nature of our interdisciplinary project. Having two points of contact not only facilitates continuous support for peer reviewers and future inquiries from readers but also enhances the accessibility and responsiveness of our research team. It promotes a culture of collaboration and acknowledges the equal contributions of both authors, thereby upholding academic integrity and fairness.
Supported by Jiangsu Provincial Cadre Healthcare Scientific Research Grant Project, No. BJ23019; Jiangsu Provincial Association of Maternal and Child Healthcare Scientific Research Grant Project, No. FYX202350; Special Fund for the Project of Enhancing Academic Capability of Integrative Nursing, No. ZXYJHHL-K-2023-M20; Jiangsu Provincial Graduate Student Practice and Innovation Program Project, No. SJCX24_0833; and the Training Project for Backbone Talents in Traditional Chinese Medicine Nursing in Nanjing Region, No. Ningwei Zhongyi[2023] No. 8.
Institutional review board statement: This study was approved by the Ethics Committee of the Jiangsu Provincial Hospital of Integrated Traditional Chinese and Western Medicine (Approval No. 2023-LWKYZ-075).
Informed consent statement: All study participants, or their legal guardian, provided informed written consent prior to study enrollment.
Conflict-of-interest statement: We have no financial relationships to disclose.
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Data sharing statement: Technical appendix, statistical code, and dataset are available from the corresponding author at wwthk1998@163.com.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Bei Wang, Department of Nursing, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, No. 100 Hongshan Road, Qixia District, Nanjing 210028, Jiangsu Province, China. wwthk1998@163.com
Received: October 12, 2024
Revised: January 4, 2025
Accepted: February 14, 2025
Published online: April 24, 2025
Processing time: 165 Days and 8.1 Hours
Abstract
BACKGROUND

Breast cancer (BC) is the second most common malignancy globally. Young and middle-aged patients face more pressures from diagnosis, treatment, costs, and psychological issues like self-image concerns, social barriers, and professional challenges. Compared to other age groups, they have higher recurrence rates, lower survival rates, and increased risk of depression. Research is lacking on factors influencing depressive symptoms and predictive models for this age group.

AIM

To analyze factors influencing depressive symptoms in young/middle-aged BC patients and construct a depression risk predictive model.

METHODS

A total of 360 patients undergoing BC treatment at two tertiary hospitals in Jiangsu Province, China from November 2023 to April 2024 were included in the study. Participants were surveyed using a general information questionnaire, the patient health questionnaire depression scale, the visual analog scale for pain, the revised family support scale, and the long form of the international physical activity questionnaire. Univariate and multivariate analyses were conducted to identify the factors affecting depression in middle-aged and young BC patients, and a predictive model for depression risk was developed based on these findings.

RESULTS

Among the 360 middle-aged and young BC patients, the incidence rate of depressive symptoms was 38.61% (139/360). Multivariate analysis revealed that tumor grade, patient’s monthly income, pain score, family support score, and physical activity score were factors influencing depression in this patient group (P < 0.05). The risk prediction model constructed based on these factors yielded an area under the receiver operating characteristic curve of 0.852, with a maximum Youden index of 0.973, sensitivity of 86.80%, specificity of 89.50%, and a diagnostic odds ratio of 0.552. The Hosmer-Lemeshow test for goodness of fit indicated an adequate model fit (χ2 = 0.360, P = 0.981).

CONCLUSION

The constructed predictive model demonstrates good predictive performance and can serve as a reference for medical professionals to early identify high-risk patients and implement corresponding preventive measures to decrease the incidence of depressive symptoms in this population.

Keywords: Breast cancer; Middle-aged and young adults; Depression; Risk factors; Predictive model; Survey research

Core Tip: Breast cancer is the second most common malignancy globally. Young and middle-aged patients have higher recurrence rates, lower survival rates, and increased depression risks. This study analyzed factors influencing depressive symptoms among 360 patients treated at two hospitals in Jiangsu Province, China from November 2023 to April 2024. Key factors included tumor grade, patient income, pain score, family support, and physical activity. The predictive model showed an receiver operating characteristic curve of 0.852, aiding early identification and prevention of depression in this patient group.