Published online Feb 19, 2024. doi: 10.5498/wjp.v14.i2.255
Peer-review started: November 3, 2023
First decision: November 16, 2023
Revised: November 29, 2023
Accepted: January 16, 2024
Article in press: January 16, 2024
Published online: February 19, 2024
Processing time: 95 Days and 2.6 Hours
Cancer-related anxiety and depression are common severe psychological stress reactions in clinical practice, with their incidence rates varying among patients with different types of cancer. Prostate cancer (PC), a common type of cancer that is usually diagnosed in the advanced stages, makes radical surgery impossible. In addition, the disease is accompanied by complications such as physical pain and bone metastasis, which brings a heavy physical and mental burden to patients. Therefore, in the clinical treatment of PC, we should pay attention to not only the adverse reactions of the body, but also the occurrence of psychological symptoms such as anxiety and depression, so as to improve the prognosis of patients.
The motivation for this study is to understand the factors that influence postoperative anxiety and depression in PC patients, based on which healthcare professionals can develop effective intervention and support strategies to meet the mental health needs of these patients.
The objective of this study is to analyze the risk factors affecting postoperative anxiety and depression in PC patients, and to explore the effects of marital status, castration scheme, and postoperative Visual Analogue Scale (VAS score) on anxiety and depression. In addition, the study aims to establish a prediction model using logistic regression analysis to evaluate the risk of adverse emotional outcomes of these patients.
In this study, retrospective analysis was used to investigate the relationship between various clinical factors and postoperative anxiety and depression in PC patients. Data such as marital status, castration scheme, and postoperative VAS score were collected and analyzed. Using the logistic regression model, a risk scoring system was developed to predict the occurrence of adverse emotional outcomes.
Marital status, castration scheme, and postoperative VAS score were identified to be important factors affecting postoperative anxiety and depression in PC patients. The logistic regression model successfully predicted the risk of adverse emotional outcomes, with an area under the curve of 0.743. The model exhibited high generalization with a verified area under the curve of 0.755.
The findings highlight the importance of psychological symptoms, especially anxiety and depression, in the clinical management of patients with PC. Marital status, castration scheme, and postoperative VAS score are identified as important predictors of adverse emotional outcomes. The logistic regression model shows good accuracy, which is helpful to individualize and improve the predictive ability of psychological risk in PC patients.
Although this study successfully identified the risk factors and developed a risk prediction model, there are still some limitations. Further research is needed to explore the long-term outcomes of patients and the impact of adverse emotional outcomes on patient prognosis, and to validate the generalization of the model with more data. Future research collaborations and data collection are important to further understand and apply this predictive model in PC.