{"title":"从预后角度看,能否将 IIB 期肺癌分为若干亚组?一项建模研究。","authors":"Necati Çitak, Volkan Erdoğu, Yunus Aksoy, Atilla Pekçolaklar, Muzaffer Metin, Adnan Sayar","doi":"10.1080/00015458.2023.2251802","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Whether changes should be made to the TNM classification of non-small cell lung cancer (NSCLC) according to the newly proposed nodal classification is unclear. We aim to compare the survival between stage-IIB subsets using a modelling study performed using the newly proposed nodal classification.</p><p><strong>Patients and methods: </strong>A total of 682 patients with stage-IIB NSCLC based on the 8th TNM classification were analysed. Hazard ratio (HR) values calculated from survival comparisons between stage-IIB subgroups were used to create a model for patients with stage-IIB NSCLC, and modelling was performed according to the HR values that were close to each other.</p><p><strong>Results: </strong>Patients with T1N1a cancer had the best survival rate (58.2%), whereas the worst prognosis was observed in those with T2bN1b cancer (39.2%). The models were created using the following HR results: Model A (T1N1a, <i>n</i> = 85; 12.4%), Model B (T2a/T2bN1a and T3N0, <i>n</i> = 438; 64.2%), and Model C (T1/T2a/T2bN1b, <i>n</i> = 159; 23.4%). There was a significant difference between the models in terms of overall survival (<i>p</i> = 0.03). The median survival time was 69 months in Model A, 56 months in Model B, and 47 months in Model C (Model A vs. Model B, <i>p</i> = 0.224; Model A vs. Model C, <i>p</i> = 0.01; and Model B vs. Model C, <i>p</i> = 0.04). Multivariate analysis showed that age (<i>p</i> < 0.001), pleural invasion (<i>p</i> < 0.001), and the developed modelling system (<i>p</i> = 0.02) were independently negative prognostic factors.</p><p><strong>Conclusion: </strong>There was a prognostic difference between stage-IIB subsets in NSCLC patients. The model created for stage-IIB lung cancer showed a high discriminatory power for prognosis.</p>","PeriodicalId":6935,"journal":{"name":"Acta Chirurgica Belgica","volume":" ","pages":"191-199"},"PeriodicalIF":0.6000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Can stage-IIB lung cancer be divided into subgroups in terms of prognosis? A modelling study<sup />.\",\"authors\":\"Necati Çitak, Volkan Erdoğu, Yunus Aksoy, Atilla Pekçolaklar, Muzaffer Metin, Adnan Sayar\",\"doi\":\"10.1080/00015458.2023.2251802\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Whether changes should be made to the TNM classification of non-small cell lung cancer (NSCLC) according to the newly proposed nodal classification is unclear. We aim to compare the survival between stage-IIB subsets using a modelling study performed using the newly proposed nodal classification.</p><p><strong>Patients and methods: </strong>A total of 682 patients with stage-IIB NSCLC based on the 8th TNM classification were analysed. Hazard ratio (HR) values calculated from survival comparisons between stage-IIB subgroups were used to create a model for patients with stage-IIB NSCLC, and modelling was performed according to the HR values that were close to each other.</p><p><strong>Results: </strong>Patients with T1N1a cancer had the best survival rate (58.2%), whereas the worst prognosis was observed in those with T2bN1b cancer (39.2%). The models were created using the following HR results: Model A (T1N1a, <i>n</i> = 85; 12.4%), Model B (T2a/T2bN1a and T3N0, <i>n</i> = 438; 64.2%), and Model C (T1/T2a/T2bN1b, <i>n</i> = 159; 23.4%). There was a significant difference between the models in terms of overall survival (<i>p</i> = 0.03). The median survival time was 69 months in Model A, 56 months in Model B, and 47 months in Model C (Model A vs. Model B, <i>p</i> = 0.224; Model A vs. Model C, <i>p</i> = 0.01; and Model B vs. Model C, <i>p</i> = 0.04). Multivariate analysis showed that age (<i>p</i> < 0.001), pleural invasion (<i>p</i> < 0.001), and the developed modelling system (<i>p</i> = 0.02) were independently negative prognostic factors.</p><p><strong>Conclusion: </strong>There was a prognostic difference between stage-IIB subsets in NSCLC patients. The model created for stage-IIB lung cancer showed a high discriminatory power for prognosis.</p>\",\"PeriodicalId\":6935,\"journal\":{\"name\":\"Acta Chirurgica Belgica\",\"volume\":\" \",\"pages\":\"191-199\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2024-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Acta Chirurgica Belgica\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1080/00015458.2023.2251802\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/8/28 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q4\",\"JCRName\":\"SURGERY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Chirurgica Belgica","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/00015458.2023.2251802","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/8/28 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"SURGERY","Score":null,"Total":0}
引用次数: 0
摘要
导言:非小细胞肺癌(NSCLC)的TNM分类是否应根据新提出的结节分类法进行修改,目前尚不清楚。我们的目的是使用新提出的结节分类进行建模研究,比较 IIB 期亚组之间的生存率:患者和方法:共分析了682例根据第8次TNM分类的IIB期NSCLC患者。通过比较 IIB 期亚组之间的生存率计算出的危险比(HR)值被用于创建 IIB 期 NSCLC 患者的模型,并根据彼此接近的 HR 值进行建模:结果:T1N1a 癌症患者的生存率最高(58.2%),而 T2bN1b 癌症患者的预后最差(39.2%)。根据以下 HR 结果创建了模型:模型 A(T1N1a,n = 85;12.4%)、模型 B(T2a/T2bN1a 和 T3N0,n = 438;64.2%)和模型 C(T1/T2a/T2bN1b,n = 159;23.4%)。两种模式的总生存期有明显差异(P = 0.03)。模型 A 的中位生存时间为 69 个月,模型 B 为 56 个月,模型 C 为 47 个月(模型 A vs. 模型 B,p = 0.224;模型 A vs. 模型 C,p = 0.01;模型 B vs. 模型 C,p = 0.04)。多变量分析显示,年龄(p p = 0.02)是独立的负面预后因素:结论:NSCLC 患者的 IIB 期亚群之间存在预后差异。结论:NSCLC 患者在 IIB 期亚群之间存在预后差异,为 IIB 期肺癌建立的模型对预后有较高的判别能力。
Can stage-IIB lung cancer be divided into subgroups in terms of prognosis? A modelling study.
Introduction: Whether changes should be made to the TNM classification of non-small cell lung cancer (NSCLC) according to the newly proposed nodal classification is unclear. We aim to compare the survival between stage-IIB subsets using a modelling study performed using the newly proposed nodal classification.
Patients and methods: A total of 682 patients with stage-IIB NSCLC based on the 8th TNM classification were analysed. Hazard ratio (HR) values calculated from survival comparisons between stage-IIB subgroups were used to create a model for patients with stage-IIB NSCLC, and modelling was performed according to the HR values that were close to each other.
Results: Patients with T1N1a cancer had the best survival rate (58.2%), whereas the worst prognosis was observed in those with T2bN1b cancer (39.2%). The models were created using the following HR results: Model A (T1N1a, n = 85; 12.4%), Model B (T2a/T2bN1a and T3N0, n = 438; 64.2%), and Model C (T1/T2a/T2bN1b, n = 159; 23.4%). There was a significant difference between the models in terms of overall survival (p = 0.03). The median survival time was 69 months in Model A, 56 months in Model B, and 47 months in Model C (Model A vs. Model B, p = 0.224; Model A vs. Model C, p = 0.01; and Model B vs. Model C, p = 0.04). Multivariate analysis showed that age (p < 0.001), pleural invasion (p < 0.001), and the developed modelling system (p = 0.02) were independently negative prognostic factors.
Conclusion: There was a prognostic difference between stage-IIB subsets in NSCLC patients. The model created for stage-IIB lung cancer showed a high discriminatory power for prognosis.
期刊介绍:
Acta Chirurgica Belgica (ACB) is the official journal of the Royal Belgian Society for Surgery (RBSS) and its affiliated societies. It publishes Editorials, Review papers, Original Research, and Technique related manuscripts in the broad field of Clinical Surgery.