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Suicide among lymphoma patients.

Authors :
Zhou, Jie
Tian, Mengjie
Zhang, Xiangchen
Xiong, Lingyi
Huang, Jinlong
Xu, Mengfan
Xu, Hongli
Yin, Zhucheng
Wu, Fengyang
Hu, Junjie
Liang, Xinjun
Wei, Shaozhong
Source :
Journal of Affective Disorders. Sep2024, Vol. 360, p97-107. 11p.
Publication Year :
2024

Abstract

Higher suicide rates were observed in patients diagnosed with lymphoma. In this study, we accurately identified patients with high-risk lymphoma for suicide by constructing a nomogram with a view to effective interventions and reducing the risk of suicide. 235,806 patients diagnosed with lymphoma between 2000 and 2020 were picked from the Surveillance, Epidemiology, and End Results (SEER) database and randomly divided into training (N = 165,064) and validation set (N = 70,742). A combination of the Least absolute shrinkage and selection operator (LASSO) and Cox proportional hazards regression identified the predictors that constructed the nomogram. To assess the discrimination, calibration, clinical applicability, and generalization of this nomogram, we implemented receiver operating characteristic curves (ROC), calibration curves, decision curve analysis (DCA), and internal validation. The robustness of the results was assessed by the competing risks regression model. Age at diagnosis, gender, ethnicity, marital status, stage, surgery, radiotherapy, and annual household income were key predictors of suicide in lymphoma patients. A nomogram was created to visualize the risk of suicide after a lymphoma diagnosis. The c-index for the training set was 0.773, and the validation set was 0.777. The calibration curve for the nomogram fitted well with the diagonal and the clinical decision curve indicated its clinical benefit. The effects of unmeasured and unnoticed biases and confounders were difficult to eliminate due to retrospective studies. A convenient and reliable model has been constructed that will help to individualize and accurately quantify the risk of suicide in patients diagnosed with lymphoma. • Combining the results of lasso regression and Cox proportional hazards regression to filter predictors. • A suicide nomogram was developed with good performance by utilizing common but significant indictors. • The Fine and Gray competing risks model validated the robustness of this study. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01650327
Volume :
360
Database :
Academic Search Index
Journal :
Journal of Affective Disorders
Publication Type :
Academic Journal
Accession number :
177849246
Full Text :
https://doi.org/10.1016/j.jad.2024.05.158