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DOI 纳入 T 分期可提高喉癌分期的预测性能。

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

机构信息

Department of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University, changsha, China.

Department of Head and Neck Surgery, Harbin Medical University Cancer Hospital, Harbin, China.

出版信息

Cancer Biol Ther. 2023 Dec 31;24(1):2169040. doi: 10.1080/15384047.2023.2169040.

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.

摘要

已经认识到,对于大多数类型的癌症,浸润深度(DOI)与患者生存密切相关。本研究旨在确定喉鳞状细胞癌(LSCC)中 DOI 的最佳截断值及其预后价值。最重要的是,我们评估了五个候选改良 T 分类模型在 LSCC 患者中的预后表现。将哈尔滨医科大学附属肿瘤医院和中国医学科学院肿瘤医院的 LSCC 患者分为训练组(n=412)和验证组(n=147)。主要结局是总生存期(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佳模型。进一步在外部验证队列中进行了独立测试。构建了列线图以预测个体在 1、3 和 5 年内的 OS 率。在多变量分析中,我们发现 DOI 与 OS(中危浸润深度 HR,2.631;P<0.001。高危浸润深度:HR,5.287;P<0.001)和 RFS(高危浸润深度:HR,1.937;P=0.016)显著相关。基于低 Akaike 信息准则评分、一致性指数的提高和 Kaplan-Meier 曲线,模型 4 优于美国癌症联合委员会(AJCC)分期系统。在当前 AJCC 分期系统中纳入 DOI 可以提高 LSCC 患者 T 分类的区分度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c58/9897798/de537846761a/KCBT_A_2169040_F0001_OC.jpg

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