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

IF 5.4 3区 材料科学 Q2 CHEMISTRY, PHYSICAL ACS Applied Energy Materials Pub Date : 2023-12-31 DOI:10.1080/15384047.2023.2169040
Xueying Wang, Kui Cao, Erliang Guo, Xionghui Mao, Changming An, Lunhua Guo, Cong Zhang, Xianguang Yang, Ji Sun, Weiwei Yang, Xiaomei Li, Susheng Miao
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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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在T分类中整合DOI提高了喉部癌症分期的预测性能。
人们已经认识到,侵袭深度(DOI)与大多数类型癌症的患者生存率密切相关。本研究的目的是确定DOI在喉鳞状细胞癌(LSCC)中的最佳临界值及其预后价值。最重要的是,我们评估了五种候选改良T分类模型在LSCC患者中的预后表现。将哈尔滨医科大学癌症医院和中国医学科学院癌症医院的LSCC患者分为训练组(n=412)和验证组(n=147)。主要结果是总生存期(OS)和无复发生存期(RFS),并使用多变量回归模型分析DOI对预后的影响。我们根据其简单性、拟合优度和Harrell一致性指数确定了最优模型。对外部验证队列进行了进一步的独立测试。构建列线图是为了预测一个人在一年、三年和五年的OS发病率。在多变量分析中,我们发现DOI和OS之间存在显著相关性(中危侵袭深度HR,2.631;P
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来源期刊
ACS Applied Energy Materials
ACS Applied Energy Materials Materials Science-Materials Chemistry
CiteScore
10.30
自引率
6.20%
发文量
1368
期刊介绍: ACS Applied Energy Materials is an interdisciplinary journal publishing original research covering all aspects of materials, engineering, chemistry, physics and biology relevant to energy conversion and storage. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important energy applications.
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