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Integrating DOI in T classification improves the predictive performance of laryngeal cancer staging.
Wang, Xueying; Cao, Kui; Guo, Erliang; Mao, Xionghui; An, Changming; Guo, Lunhua; Zhang, Cong; Yang, Xianguang; Sun, Ji; Yang, Weiwei; Li, Xiaomei; Miao, Susheng.
Afiliación
  • Wang X; Department of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University, changsha, China.
  • Cao K; Department of Head and Neck Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
  • Guo E; Department of Laboratory, Harbin Medical University Cancer Hospital, Harbin, China.
  • Mao X; Department of Surgery, the 2nd Affiliated Hospital of Harbin Medical University, Harbin, China.
  • An C; Department of Head and Neck Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
  • Guo L; Department of Head and Neck Surgery, Chinese National Cancer Center & Chinese Academy of Medical Sciences Cancer Hospital, Beijing, China.
  • Zhang C; Department of Head and Neck Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
  • Yang X; Department of Head and Neck Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
  • Sun J; Department of Head and Neck Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
  • Yang W; Department of Head and Neck Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
  • Li X; Department of Pathology, Harbin Medical University, Harbin, China.
  • Miao S; Department of Pathology, Harbin Medical University Cancer Hospital, Harbin, China.
Cancer Biol Ther ; 24(1): 2169040, 2023 12 31.
Article en En | MEDLINE | ID: mdl-36729904
ABSTRACT
It has been recognized that depth of invasion (DOI) is closely associated with patient survival for most types of cancer. The purpose of this study was to determine the DOI optimal cutoff value and its prognostic value in laryngeal squamous carcinoma (LSCC). Most importantly, we evaluated the prognostic performance of five candidate modified T-classification models in patients with LSCC. LSCC patients from Harbin Medical University Cancer Hospital and Chinese Academy of Medical Sciences Cancer Hospital were divided into training group (n = 412) and validation group (n = 147). The primary outcomes were overall survival (OS) and relapse-free survival (RFS), and the effect of DOI on prognosis was analyzed using a multivariable regression model. We identified the optimal model based on its simplicity, goodness of fit and Harrell's consistency index. Further independent testing was performed on the external validation queue. The nomograms was constructed to predict an individual's OS rate at one, three, and five years. In multivariate analysis, we found significant associations between DOI and OS (Depth of Medium-risk invasion HR, 2.631; P < .001. Depth of high-risk invasion HR, 5.287; P < .001) and RFS (Depth of high-risk invasion HR, 1.937; P = .016). Model 4 outperformed the American Joint Committee on Cancer (AJCC) staging system based on a low Akaike information criterion score, improvement in the concordance index, and Kaplan-Meier curves. Inclusion of DOI in the current AJCC staging system can improve the differentiation of T classification in LSCC patients.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Neoplasias Laríngeas / Neoplasias de Cabeza y Cuello Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Cancer Biol Ther Asunto de la revista: NEOPLASIAS / TERAPEUTICA Año: 2023 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Neoplasias Laríngeas / Neoplasias de Cabeza y Cuello Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Cancer Biol Ther Asunto de la revista: NEOPLASIAS / TERAPEUTICA Año: 2023 Tipo del documento: Article