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@ARTICLE{Tu:267541,
      author       = {Z. Tu and C. Li and Q. Hu$^*$ and J. Luo},
      title        = {{L}arysuicide: an online risk stratification system to
                      identify patients at high risk of suicide after the
                      laryngeal cancer diagnosis.},
      journal      = {Journal of cancer research and clinical oncology},
      volume       = {149},
      number       = {9},
      issn         = {0171-5216},
      address      = {Berlin},
      publisher    = {Springer},
      reportid     = {DKFZ-2023-00319},
      pages        = {6455-6465},
      year         = {2023},
      note         = {2023 Aug;149(9):6455-6465},
      abstract     = {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 $(95\%$ CI
                      0.723-0.767) in training set, 0.759 $(95\%$ CI 0.722-0.800)
                      in validation set, and 0.749 $(95\%$ CI 0.730-0.769) in
                      testing set. The AUC was 0.745 in training set, 0.759 in
                      validation set, and 0.749 in testing set. The calibration
                      curves showed good calibration. Decision curve analysis
                      demonstrated that Larysuicide was clinically useful. The
                      univariate regression analysis presented patients in the
                      high-risk group identified by Larysuicide suffered a
                      significantly higher risk of committing suicide after cancer
                      diagnosis.We constructed an online risk stratification
                      system which could help health-care professionals
                      efficiently identify patients at high risk of suicide after
                      the laryngeal cancer diagnosis. Larysuicide could be a
                      useful tool for health-care professionals to implement an
                      early and appropriate psychological intervention in context
                      of precision medicine.},
      keywords     = {Laryngeal cancer (Other) / Predictive model (Other) /
                      Psychological intervention (Other) / Risk assessment (Other)
                      / Suicide (Other)},
      cin          = {F100},
      ddc          = {610},
      cid          = {I:(DE-He78)F100-20160331},
      pnm          = {316 - Infektionen, Entzündung und Krebs (POF4-316)},
      pid          = {G:(DE-HGF)POF4-316},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:36763172},
      doi          = {10.1007/s00432-023-04635-z},
      url          = {https://inrepo02.dkfz.de/record/267541},
}