Cancer Biology & Therapy (Dec 2023)

Integrating DOI in T classification improves the predictive performance of laryngeal cancer staging

  • Xueying Wang,
  • Kui Cao,
  • Erliang Guo,
  • Xionghui Mao,
  • Changming an,
  • Lunhua Guo,
  • Cong Zhang,
  • Xianguang Yang,
  • Ji Sun,
  • Weiwei Yang,
  • Xiaomei Li,
  • Susheng Miao

DOI
https://doi.org/10.1080/15384047.2023.2169040
Journal volume & issue
Vol. 24, no. 1

Abstract

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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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