TY  - JOUR
AU  - Tu, Zegui
AU  - Li, Caili
AU  - Hu, Qipeng
AU  - Luo, Jieyan
TI  - Larysuicide: an online risk stratification system to identify patients at high risk of suicide after the laryngeal cancer diagnosis.
JO  - Journal of cancer research and clinical oncology
VL  - 149
IS  - 9
SN  - 0171-5216
CY  - Berlin
PB  - Springer
M1  - DKFZ-2023-00319
SP  - 6455-6465
PY  - 2023
N1  - 2023 Aug;149(9):6455-6465
AB  - Patients with laryngeal cancer have more than five times the incidence of suicide compared with the general population. In this study, we aimed to develop an online risk stratification system, named Larysuicide, to identify patients at high risk of suicide after the laryngeal cancer diagnosis.Forty-two thousand and sixty-six American patients from the SEER-18 database and 4207 Chinese patients from our center were included in this study. We randomly assigned American patients into the training set and validation set at a ratio of 7:3, and all Chinese patients remained as an independent external testing set. LASSO regression model was applied for data dimension reduction, feature selection, and Larysuicide building. The performance of model was evaluated and validated by C-index, AUC, calibration curves, decision curve analysis (DCA), and univariate regression analysis.The Larysuicide developed with seven selected features-age, race, cancer site, pathological subtype, grade, stage at presentation, and radiation. The model showed good discrimination, with a C-index of 0.745 (95
KW  - Laryngeal cancer (Other)
KW  - Predictive model (Other)
KW  - Psychological intervention (Other)
KW  - Risk assessment (Other)
KW  - Suicide (Other)
LB  - PUB:(DE-HGF)16
C6  - pmid:36763172
DO  - DOI:10.1007/s00432-023-04635-z
UR  - https://inrepo02.dkfz.de/record/267541
ER  -