Risk factors analysis and risk prediction model of anxiety and depression in patients with prostate cancer after castration
10.3760/cma.j.cn431274-20240918-01432
- VernacularTitle:去势后前列腺癌患者焦虑抑郁的危险因素分析及风险预测模型
- Author:
Xuelian LI
1
;
Weiping DONG
;
Song XUE
;
Ruiping SU
;
Bo LI
;
Guojun WU
;
Ruixiao LI
Author Information
1. 西安市中医医院外科，西安 710000
- Publication Type:Journal Article
- Keywords:
Prostatic neoplasms;
Androgen deprivation therapy;
Anxiety;
Depression
- From:
Journal of Chinese Physician
2025;27(7):989-993
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze the risk factors of anxiety and depression in prostate cancer patients after castration, and establish a risk prediction model.Methods:A retrospective analysis was conducted on the data of 60 prostate cancer patients treated in Xi′an People′s Hospital from January 2019 to January 2022. The patients were divided into a training group ( n=42) and a validation group ( n=18) at a ratio of 7∶3. The patients received surgical castration and medical castration. One month after castration, the Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS) were used to evaluate the anxiety symptoms and depression levels of the patients, respectively. Univariate and multivariate logistic regression analyses were used to identify the risk factors for negative emotions in prostate cancer patients after castration, and a risk prediction model was established. Results:In the training group, 19 patients had a SAS score ≥50, and 21 patients had an SDS score ≥50. Based on these scores, the training group was divided into a negative emotion group ( n=19) and an emotional stability group ( n=23). Multivariate logistic regression analysis showed that marital status, castration scheme, and postoperative Visual Analogue Scale (VAS) score were independent influencing factors for negative emotions in prostate cancer patients after castration ( OR=3.589, 3.364, 5.912, all P<0.05). In both the training group and the validation group, the risk scores of patients with negative emotions were significantly higher than those with emotional stability. In the training group, the area under the curve (AUC) of the risk prediction model for predicting negative emotions was 0.747, with a specificity of 71.02% and a sensitivity of 66.11%; in the validation group, the AUC, specificity, and sensitivity were 0.761, 66.59%, and 76.21%, respectively. The Hosmer-Lemeshow test showed that χ 2 was 4.285 6, P value was 0.830, and the c-index was 0.773(0.692-0.854). The calibration curve showed that the predicted curve was basically consistent with the actual curve, indicating that the prediction model had good discriminative ability and accuracy. Decision curve analysis showed that the model had high clinical significance. Conclusions:Marital status, castration scheme, and postoperative VAS score are important factors affecting anxiety and depression in prostate cancer patients after castration, and the regression model can successfully predict the risk of negative emotions.
