Construction and verification of a predictive model for depression risk of patients with somatization symptoms
BackgroundPatients with somatization symptoms are at elevated risk of depression, yet underdiagnosis persists due to cultural tendencies (e.g., in China) to express psychological distress via physical complaints. Existing predictive models lack integration of sociocultural and physiological factors,...
Saved in:
| Main Authors: | , , , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-04-01
|
| Series: | Frontiers in Psychiatry |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1555513/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850049276575481856 |
|---|---|
| author | Liming Tang Jinrong Zhong Mei’e Zeng Weiwei Deng Chunmei Huang Shuifen Ye Fengjin Li Dongqin Lai Wanling Huang Bin Chen Xiaoyuan Deng Xiaoying Lai Lirong Wu Bilan Zou Hanzhong Qiu Ying Liao |
| author_facet | Liming Tang Jinrong Zhong Mei’e Zeng Weiwei Deng Chunmei Huang Shuifen Ye Fengjin Li Dongqin Lai Wanling Huang Bin Chen Xiaoyuan Deng Xiaoying Lai Lirong Wu Bilan Zou Hanzhong Qiu Ying Liao |
| author_sort | Liming Tang |
| collection | DOAJ |
| description | BackgroundPatients with somatization symptoms are at elevated risk of depression, yet underdiagnosis persists due to cultural tendencies (e.g., in China) to express psychological distress via physical complaints. Existing predictive models lack integration of sociocultural and physiological factors, particularly in non-Western populations.ObjectiveTo develop a culturally tailored risk-prediction model for depression in patients with somatization symptoms, emphasizing early identification and personalized intervention.MethodsA prospective cohort study included 200 somatization patients (SSS≥38, PHQ-2<3) from a Chinese hospital (May 2020–August 2022). LASSO regression identified predictors from 18 variables, followed by multivariate logistic regression to construct a nomogram. Model performance was assessed via ROC-AUC, calibration curves, Hosmer-Lemeshow test, and decision curve analysis (DCA). Internal validation used 200 bootstrap resamples.ResultsFive independent predictors were identified: advanced age (OR=1.11, 95% CI: 1.02–1.20), poor self-rated health (OR=2.07, 95% CI: 1.04–4.30), lack of co-residence with children (OR=1.63, 95% CI: 1.10–2.42), low income (OR=1.45, 95% CI: 1.05–2.01), and self-medication (OR=1.32, 95% CI: 1.01–1.73). The nomogram demonstrated strong discrimination (AUC=0.810, 95% CI: 0.728–0.893) and calibration (Hosmer-Lemeshow p=0.32). DCA confirmed clinical utility: at threshold probabilities >5%, the model provided higher net benefit than “treat-all” or “treat-none” strategies.ConclusionThis model integrates sociocultural (e.g., family structure) and behavioral factors to predict depression risk in somatizing patients, particularly in East Asian contexts. It offers a practical tool for clinicians to prioritize high-risk individuals, reducing diagnostic delays and healthcare burdens. Future multicenter studies should validate its generalizability and incorporate biomarkers (e.g., inflammatory markers) to enhance mechanistic insights. |
| format | Article |
| id | doaj-art-833ba1d442754c8fb2811e75c6dcb7b1 |
| institution | DOAJ |
| issn | 1664-0640 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychiatry |
| spelling | doaj-art-833ba1d442754c8fb2811e75c6dcb7b12025-08-20T02:53:44ZengFrontiers Media S.A.Frontiers in Psychiatry1664-06402025-04-011610.3389/fpsyt.2025.15555131555513Construction and verification of a predictive model for depression risk of patients with somatization symptomsLiming TangJinrong ZhongMei’e ZengWeiwei DengChunmei HuangShuifen YeFengjin LiDongqin LaiWanling HuangBin ChenXiaoyuan DengXiaoying LaiLirong WuBilan ZouHanzhong QiuYing LiaoBackgroundPatients with somatization symptoms are at elevated risk of depression, yet underdiagnosis persists due to cultural tendencies (e.g., in China) to express psychological distress via physical complaints. Existing predictive models lack integration of sociocultural and physiological factors, particularly in non-Western populations.ObjectiveTo develop a culturally tailored risk-prediction model for depression in patients with somatization symptoms, emphasizing early identification and personalized intervention.MethodsA prospective cohort study included 200 somatization patients (SSS≥38, PHQ-2<3) from a Chinese hospital (May 2020–August 2022). LASSO regression identified predictors from 18 variables, followed by multivariate logistic regression to construct a nomogram. Model performance was assessed via ROC-AUC, calibration curves, Hosmer-Lemeshow test, and decision curve analysis (DCA). Internal validation used 200 bootstrap resamples.ResultsFive independent predictors were identified: advanced age (OR=1.11, 95% CI: 1.02–1.20), poor self-rated health (OR=2.07, 95% CI: 1.04–4.30), lack of co-residence with children (OR=1.63, 95% CI: 1.10–2.42), low income (OR=1.45, 95% CI: 1.05–2.01), and self-medication (OR=1.32, 95% CI: 1.01–1.73). The nomogram demonstrated strong discrimination (AUC=0.810, 95% CI: 0.728–0.893) and calibration (Hosmer-Lemeshow p=0.32). DCA confirmed clinical utility: at threshold probabilities >5%, the model provided higher net benefit than “treat-all” or “treat-none” strategies.ConclusionThis model integrates sociocultural (e.g., family structure) and behavioral factors to predict depression risk in somatizing patients, particularly in East Asian contexts. It offers a practical tool for clinicians to prioritize high-risk individuals, reducing diagnostic delays and healthcare burdens. Future multicenter studies should validate its generalizability and incorporate biomarkers (e.g., inflammatory markers) to enhance mechanistic insights.https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1555513/fullpredictive modeldepression risksomatization symptomsclinical 49 validationrisk factors identification |
| spellingShingle | Liming Tang Jinrong Zhong Mei’e Zeng Weiwei Deng Chunmei Huang Shuifen Ye Fengjin Li Dongqin Lai Wanling Huang Bin Chen Xiaoyuan Deng Xiaoying Lai Lirong Wu Bilan Zou Hanzhong Qiu Ying Liao Construction and verification of a predictive model for depression risk of patients with somatization symptoms Frontiers in Psychiatry predictive model depression risk somatization symptoms clinical 49 validation risk factors identification |
| title | Construction and verification of a predictive model for depression risk of patients with somatization symptoms |
| title_full | Construction and verification of a predictive model for depression risk of patients with somatization symptoms |
| title_fullStr | Construction and verification of a predictive model for depression risk of patients with somatization symptoms |
| title_full_unstemmed | Construction and verification of a predictive model for depression risk of patients with somatization symptoms |
| title_short | Construction and verification of a predictive model for depression risk of patients with somatization symptoms |
| title_sort | construction and verification of a predictive model for depression risk of patients with somatization symptoms |
| topic | predictive model depression risk somatization symptoms clinical 49 validation risk factors identification |
| url | https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1555513/full |
| work_keys_str_mv | AT limingtang constructionandverificationofapredictivemodelfordepressionriskofpatientswithsomatizationsymptoms AT jinrongzhong constructionandverificationofapredictivemodelfordepressionriskofpatientswithsomatizationsymptoms AT meiezeng constructionandverificationofapredictivemodelfordepressionriskofpatientswithsomatizationsymptoms AT weiweideng constructionandverificationofapredictivemodelfordepressionriskofpatientswithsomatizationsymptoms AT chunmeihuang constructionandverificationofapredictivemodelfordepressionriskofpatientswithsomatizationsymptoms AT shuifenye constructionandverificationofapredictivemodelfordepressionriskofpatientswithsomatizationsymptoms AT fengjinli constructionandverificationofapredictivemodelfordepressionriskofpatientswithsomatizationsymptoms AT dongqinlai constructionandverificationofapredictivemodelfordepressionriskofpatientswithsomatizationsymptoms AT wanlinghuang constructionandverificationofapredictivemodelfordepressionriskofpatientswithsomatizationsymptoms AT binchen constructionandverificationofapredictivemodelfordepressionriskofpatientswithsomatizationsymptoms AT xiaoyuandeng constructionandverificationofapredictivemodelfordepressionriskofpatientswithsomatizationsymptoms AT xiaoyinglai constructionandverificationofapredictivemodelfordepressionriskofpatientswithsomatizationsymptoms AT lirongwu constructionandverificationofapredictivemodelfordepressionriskofpatientswithsomatizationsymptoms AT bilanzou constructionandverificationofapredictivemodelfordepressionriskofpatientswithsomatizationsymptoms AT hanzhongqiu constructionandverificationofapredictivemodelfordepressionriskofpatientswithsomatizationsymptoms AT yingliao constructionandverificationofapredictivemodelfordepressionriskofpatientswithsomatizationsymptoms |