Development, Validation, and Visualization of a Web-Based Nomogram to Predict the Risk of Psychological Distress in Patients Undergoing Chemotherapy After Breast Cancer Surgery.

Cancer Nurs

Author Affiliations: Institute of Cancer Clinical Prevention and Control, Medical Department of Jingchu University of Technology, Jingmen (Mss Shi, Yi, Yang and Dr Yang); WuHan DongHu University, Wuhan (Ms Zhao); and Center for Environment and Health in Water Source Area of South-to-North Water Dive

Published: November 2024


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Article Abstract

Background: Psychological distress of postoperative chemotherapy patients with breast cancer is significant and has a serious impact on their quality of survival. Risk prediction models can efficiently assess patients' psychological distress and risk factors.

Objectives: To investigate the factors influencing psychological distress in postoperative chemotherapy patients with breast cancer and construct a nomogram model to predict the occurrence of psychological distress in patients.

Methods: Two hundred forty-seven women in treatment for breast cancer who were postoperative and receiving chemotherapy were recruited. Participants completed a distress management screening measure, a numerical rating scale, the Pittsburgh Sleep Quality Index, and demographic and clinical items.

Results: Experiencing significant psychological distress was reported by 65.6% of participants. The psychological distress risk prediction model included 5 variables: financial problems, appearance/shape, distant metastases, the Numerical Rating Scale Pain score, and fatigue. A web calculator was designed based on the model (https://77nomogram.shinyapps.io/dynnomapp/).

Conclusions: This study found that financial and appearance/shape problems, distant metastases, pain scores, and fatigue were predictors of greater psychological distress in women undergoing chemotherapy after breast cancer surgery. The model constructed in this study has good predictive efficacy.

Implications For Practice: This web-based nomogram model can help healthcare professionals quickly assess the likelihood of psychological distress in patients and screen for risk factors for psychological distress.

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http://dx.doi.org/10.1097/NCC.0000000000001415DOI Listing

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