Aihong Zheng, Yiwen Wang, Shuang Li, Yingjie Wang, Hong'en Xu, Jieni Ding, Bingchen Chen, Tao Song, Lei Lai
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Additionally, multivariate analysis was employed to identify significant predictors, which were further visualized using a nomogram. Finally, calibration curve, C-index, and decision curve analysis (DCA) were applied to assess the performance of the different staging systems.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>A total of 5384 patients with ASCC were analyzed, revealing superior discrimination OS by the TNM9th edition compared to that by the TNM8th edition. Multivariate analysis identified the T and N stages as significant OS predictors (all <i>p</i> < 0.001). However, ambiguity persisted in stage III subgroups within the TNM9th edition, showing OS times of 102 months for stage IIIA disease, 88 months for stage IIIB disease, and 128 months for stage IIIC disease (all <i>p</i> > 0.05). Correlation analysis demonstrated an increased correlation for the T stage between the TNM8th and 9th editions (<i>ρ</i> value from 0.7 to 0.89), while the N stage correlation decreased (<i>ρ</i> value from 0.84 to 0.56). VIA and the prognostic nomogram highlighted the greater importance of the T stage over the N stage. Based on these findings, a new staging system was developed, and its clinical utility was confirmed through calibration curves, C-index values (from 0.598 to 0.604), and DCAs.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>Our new staging system exhibited slightly better prognostic value compared to the TNM9th staging systems for nonmetastatic ASCC and warrants further validation.</p>\n </section>\n </div>","PeriodicalId":139,"journal":{"name":"Cancer Medicine","volume":null,"pages":null},"PeriodicalIF":2.9000,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cam4.70119","citationCount":"0","resultStr":"{\"title\":\"Comparison of the TNM9th and 8th editions for localized and locally advanced anal squamous cell carcinoma treated nonsurgically and proposal of a new stage grouping system\",\"authors\":\"Aihong Zheng, Yiwen Wang, Shuang Li, Yingjie Wang, Hong'en Xu, Jieni Ding, Bingchen Chen, Tao Song, Lei Lai\",\"doi\":\"10.1002/cam4.70119\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Objective</h3>\\n \\n <p>To compare the survival discrimination of the TNM9th and 8th editions for localized and locally advanced anal squamous cell carcinoma (ASCC) treated nonsurgically and suggest a simple revised staging system with data from the Surveillance, Epidemiology, and End Results (SEER) database.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>Overall survival (OS) was the primary endpoint. 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引用次数: 0
摘要
目的比较TNM第9版和第8版对非手术治疗的局部和局部晚期肛门鳞状细胞癌（ASCC）的生存判别，并利用监测、流行病学和最终结果（SEER）数据库中的数据提出一个简单的修订分期系统：方法：以总生存期（OS）为主要终点。采用卡普兰-梅耶法和对数秩检验对T期和N期以及不同分期系统进行生存率比较，然后进行相关性分析和变量重要性分析（VIA）。此外，还采用了多变量分析来确定重要的预测因素，并使用提名图进一步将其直观化。最后，应用校准曲线、C指数和决策曲线分析（DCA）来评估不同分期系统的性能：结果：共对5384例ASCC患者进行了分析，结果显示TNM9版的分辨OS优于TNM8版。多变量分析发现，T分期和N分期是预测OS的重要指标（均为P 0.05）。相关性分析表明，TNM 第 8 版和第 9 版之间的 T 分期相关性增加（ρ 值从 0.7 升至 0.89），而 N 分期相关性降低（ρ 值从 0.84 降至 0.56）。VIA 和预后提名图强调了 T 分期比 N 分期更重要。基于这些发现，我们开发了一套新的分期系统，并通过校准曲线、C指数值（从0.598到0.604）和DCA证实了其临床实用性：结论：与 TNM9th 分期系统相比，我们的新分期系统对非转移性 ASCC 的预后价值略高，值得进一步验证。
Comparison of the TNM9th and 8th editions for localized and locally advanced anal squamous cell carcinoma treated nonsurgically and proposal of a new stage grouping system
Objective
To compare the survival discrimination of the TNM9th and 8th editions for localized and locally advanced anal squamous cell carcinoma (ASCC) treated nonsurgically and suggest a simple revised staging system with data from the Surveillance, Epidemiology, and End Results (SEER) database.
Methods
Overall survival (OS) was the primary endpoint. Survival comparisons between the T and N stages and the different staging systems were performed using the Kaplan–Meier method and log-rank test, followed by correlation analysis and variable importance analysis (VIA). Additionally, multivariate analysis was employed to identify significant predictors, which were further visualized using a nomogram. Finally, calibration curve, C-index, and decision curve analysis (DCA) were applied to assess the performance of the different staging systems.
Results
A total of 5384 patients with ASCC were analyzed, revealing superior discrimination OS by the TNM9th edition compared to that by the TNM8th edition. Multivariate analysis identified the T and N stages as significant OS predictors (all p < 0.001). However, ambiguity persisted in stage III subgroups within the TNM9th edition, showing OS times of 102 months for stage IIIA disease, 88 months for stage IIIB disease, and 128 months for stage IIIC disease (all p > 0.05). Correlation analysis demonstrated an increased correlation for the T stage between the TNM8th and 9th editions (ρ value from 0.7 to 0.89), while the N stage correlation decreased (ρ value from 0.84 to 0.56). VIA and the prognostic nomogram highlighted the greater importance of the T stage over the N stage. Based on these findings, a new staging system was developed, and its clinical utility was confirmed through calibration curves, C-index values (from 0.598 to 0.604), and DCAs.
Conclusions
Our new staging system exhibited slightly better prognostic value compared to the TNM9th staging systems for nonmetastatic ASCC and warrants further validation.
期刊介绍：
Cancer Medicine is a peer-reviewed, open access, interdisciplinary journal providing rapid publication of research from global biomedical researchers across the cancer sciences. The journal will consider submissions from all oncologic specialties, including, but not limited to, the following areas:
Clinical Cancer Research
Translational research ∙ clinical trials ∙ chemotherapy ∙ radiation therapy ∙ surgical therapy ∙ clinical observations ∙ clinical guidelines ∙ genetic consultation ∙ ethical considerations
Cancer Biology:
Molecular biology ∙ cellular biology ∙ molecular genetics ∙ genomics ∙ immunology ∙ epigenetics ∙ metabolic studies ∙ proteomics ∙ cytopathology ∙ carcinogenesis ∙ drug discovery and delivery.
Cancer Prevention:
Behavioral science ∙ psychosocial studies ∙ screening ∙ nutrition ∙ epidemiology and prevention ∙ community outreach.
Bioinformatics:
Gene expressions profiles ∙ gene regulation networks ∙ genome bioinformatics ∙ pathwayanalysis ∙ prognostic biomarkers.
Cancer Medicine publishes original research articles, systematic reviews, meta-analyses, and research methods papers, along with invited editorials and commentaries. Original research papers must report well-conducted research with conclusions supported by the data presented in the paper.
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