PMID- 36030468 OWN - NLM STAT- MEDLINE DCOM- 20230120 LR - 20230120 IS - 1434-4726 (Electronic) IS - 0937-4477 (Linking) VI - 280 IP - 2 DP - 2023 Feb TI - A deep learning-based model predicts survival for patients with laryngeal squamous cell carcinoma: a large population-based study. PG - 789-795 LID - 10.1007/s00405-022-07627-w [doi] AB - OBJECTIVES: To assess the performance of DeepSurv, a deep learning-based model in the survival prediction of laryngeal squamous cell carcinoma (LSCC) using the Surveillance, Epidemiology, and End Results (SEER) database. METHODS: In this large population-based study, we developed and validated a deep learning survival neural network using pathologically diagnosed patients with LSCC from the SEER database between January 2010 and December 2018. Totally 13 variables were included in this network, including patients baseline characteristics, stage, grade, site, tumor extension and treatment details. Based on the total risk score derived from this algorithm, a three-knot restricted cubic spline was plotted to exhibit the difference of survival benefits from two treatment modalities. RESULTS: Totally 6316 patients with LSCC were included in the study, of which 4237 cases diagnosed between 2010 and 2015 were selected as the development cohort, and the rest (2079 cases diagnosed from 2016 to 2018) were the validation cohort. A state-of-the-art deep learning-based model based on 23 features (i.e., 13 variables) was generated, which showed more superior performance in the prediction of overall survival (OS) than the tumor, node, and metastasis (TNM) staging system (C-index for DeepSurv vs TNM staging = 0.71; 95% CI 0.69-0.74 vs 0.61; 95% CI 0.60-0.63). Interestingly, a significantly nonlinear association between total risk score and treatment effectiveness was observed. When the total risk score ranges 0.1-1.5, surgical treatment brought more survival benefits than nonsurgical one for LSCC patients, especially in 70.5% of patients staged III-IV. CONCLUSIONS: The deep learning-based model shows more potential benefits in survival estimation for patients with LSCC, which may potentially serve as an auxiliary approach to provide reliable treatment recommendations. CI - (c) 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. FAU - Liao, Fang AU - Liao F AD - Sichuan Provincial Center for Mental Health, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu, 610072, China. AD - Key Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu, 610072, China. FAU - Wang, Wei AU - Wang W AD - West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China. FAU - Wang, Jinyu AU - Wang J AUID- ORCID: 0000-0001-8301-6638 AD - Sichuan Provincial Center for Mental Health, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu, 610072, China. wangjyd2003@163.com. AD - Key Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu, 610072, China. wangjyd2003@163.com. LA - eng PT - Journal Article DEP - 20220828 PL - Germany TA - Eur Arch Otorhinolaryngol JT - European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery JID - 9002937 SB - IM MH - Humans MH - Squamous Cell Carcinoma of Head and Neck/therapy/pathology MH - Prognosis MH - Neoplasm Staging MH - *Carcinoma, Squamous Cell/pathology MH - *Deep Learning MH - *Head and Neck Neoplasms/pathology MH - *Laryngeal Neoplasms/pathology OTO - NOTNLM OT - Deep learning OT - Individualized treatment modality OT - Laryngeal squamous cell carcinoma OT - Overall survival EDAT- 2022/08/29 06:00 MHDA- 2023/01/21 06:00 CRDT- 2022/08/28 13:58 PHST- 2022/04/11 00:00 [received] PHST- 2022/08/21 00:00 [accepted] PHST- 2022/08/29 06:00 [pubmed] PHST- 2023/01/21 06:00 [medline] PHST- 2022/08/28 13:58 [entrez] AID - 10.1007/s00405-022-07627-w [pii] AID - 10.1007/s00405-022-07627-w [doi] PST - ppublish SO - Eur Arch Otorhinolaryngol. 2023 Feb;280(2):789-795. doi: 10.1007/s00405-022-07627-w. Epub 2022 Aug 28.