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      A large real-world cohort study of examined lymph node standards for adequate nodal staging in early non-small cell lung cancer

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          Abstract

          Background

          The current National Comprehensive Cancer Network (NCCN) guidelines for non-small cell lung cancer (NSCLC) recommend that surgeons sample is not clear. We aimed to define a minimal number of examined lymph nodes for removal or sampling for optimized nodal staging recommendation, with a focus on T 1–3N 0M 0 patients.

          Methods

          A total of 55,101 consecutive patients were selected, including 52,099 patients with US Surveillance, Epidemiology, and End Results (SEER) data and 3,002 patients in a Chinese multicenter database from 11 thoracic referral centers, who underwent complete resection plus lymph node dissection or sampling for stage T 1–3N 0M 0 NSCLC. Propensity score-matching analysis was performed with R software, and a cut-off value was calculated using X-tile software. Survival was evaluated using the Kaplan-Meier method and Cox proportional hazard models.

          Results

          Five-year survival rates with respect to total examined lymph nodes numbers (examined lymph nodes <10 vs. examined lymph nodes ≥10) were 69% and 64% (group A), 66% and 63% (group B), 62% and 58% (group C), 81% and 75% (group D). There were significant differences between examined lymph nodes <10 and examined lymph nodes >10 in each group (P<0.001).

          Conclusions

          A minimum of 10 examined lymph nodes would significantly improve T 1–3N 0M 0 NSCLC prognosis and patients’ survival rates if implemented as a minimum standard for lymphadenectomy. Therefore, we recommended a minimum of 10 examined lymph nodes for T 1–3N 0M 0 patients.

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          Most cited references21

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          Cancer statistics, 2019

          Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths that will occur in the United States and compiles the most recent data on cancer incidence, mortality, and survival. Incidence data, available through 2015, were collected by the Surveillance, Epidemiology, and End Results Program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data, available through 2016, were collected by the National Center for Health Statistics. In 2019, 1,762,450 new cancer cases and 606,880 cancer deaths are projected to occur in the United States. Over the past decade of data, the cancer incidence rate (2006-2015) was stable in women and declined by approximately 2% per year in men, whereas the cancer death rate (2007-2016) declined annually by 1.4% and 1.8%, respectively. The overall cancer death rate dropped continuously from 1991 to 2016 by a total of 27%, translating into approximately 2,629,200 fewer cancer deaths than would have been expected if death rates had remained at their peak. Although the racial gap in cancer mortality is slowly narrowing, socioeconomic inequalities are widening, with the most notable gaps for the most preventable cancers. For example, compared with the most affluent counties, mortality rates in the poorest counties were 2-fold higher for cervical cancer and 40% higher for male lung and liver cancers during 2012-2016. Some states are home to both the wealthiest and the poorest counties, suggesting the opportunity for more equitable dissemination of effective cancer prevention, early detection, and treatment strategies. A broader application of existing cancer control knowledge with an emphasis on disadvantaged groups would undoubtedly accelerate progress against cancer.
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            The IASLC Lung Cancer Staging Project: Proposals for Revision of the TNM Stage Groupings in the Forthcoming (Eighth) Edition of the TNM Classification for Lung Cancer.

            The IASLC Staging and Prognostic Factors Committee has collected a new database of 94,708 cases donated from 35 sources in 16 countries around the globe. This has now been analysed by our statistical partners at Cancer Research And Biostatistics and, in close collaboration with the members of the committee proposals have been developed for the T, N, and M categories of the 8th edition of the TNM Classification for lung cancer due to be published late 2016. In this publication we describe the methods used to evaluate the resultant Stage groupings and the proposals put forward for the 8th edition.
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              X-tile: a new bio-informatics tool for biomarker assessment and outcome-based cut-point optimization.

              The ability to parse tumors into subsets based on biomarker expression has many clinical applications; however, there is no global way to visualize the best cut-points for creating such divisions. We have developed a graphical method, the X-tile plot that illustrates the presence of substantial tumor subpopulations and shows the robustness of the relationship between a biomarker and outcome by construction of a two dimensional projection of every possible subpopulation. We validate X-tile plots by examining the expression of several established prognostic markers (human epidermal growth factor receptor-2, estrogen receptor, p53 expression, patient age, tumor size, and node number) in cohorts of breast cancer patients and show how X-tile plots of each marker predict population subsets rooted in the known biology of their expression.
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                Author and article information

                Journal
                Transl Lung Cancer Res
                Transl Lung Cancer Res
                TLCR
                Translational Lung Cancer Research
                AME Publishing Company
                2218-6751
                2226-4477
                February 2021
                February 2021
                : 10
                : 2
                : 815-825
                Affiliations
                [1 ]Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, China;
                [2 ]Cancer Hospital of University of Chinese Academy of Sciences; Zhejiang Cancer Hospital , Hangzhou, China;
                [3 ]Affiliated Hospital of Qingdao University , Qingdao, China;
                [4 ]Fujian Cancer Hospital , Fuzhou, China;
                [5 ]Affiliated Tumor Hospital of Guangxi Medical University , Nanning, China;
                [6 ]Nantong Third People’s Hospital, Nantong University, Nantong, China;
                [7 ]Ningbo First Hospital of Zhejiang University , Ningbo, China;
                [8 ]Affiliated Jiangyin Hospital of Southeast University, Jiangyin, China;
                [9 ]The Second Hospital of Jilin University , Changchun, China;
                [10 ]The Second Affiliated Hospital of Medical College, Xi’an Jiaotong University , Xi’an, China;
                [11 ]Taizhou Hospital of Zhejiang Province, Wenzhou Medical University, Linhai, China;
                [12 ]Affiliated Jinling Hospital, Medical School of Nanjing University , Nanjing, China;
                [13 ]Southern Medical University , Guangzhou, China;
                [14 ]The First Affiliated Hospital, Sun Yat-sen University , Guangzhou, China
                Author notes

                Contributions: (I) Conception and design: W Yao, Z Zhu; (II) Administrative support: Z Song, W Jiao, C Xu, Q Huang, C An, J Shi, G Yu, P Sun, Y Zhang, J Shen; (III) Provision of study materials or patients: H Yang; (IV) Collection and assembly of data: W Mei; (V) Data analysis and interpretation: J Qian, Y Song; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

                [#]

                These authors contributed equally to this work.

                Correspondence to: Jun Qian, PhD. School of Biomedical Engineering, Southern Medical University, 1023 Shatainan Road, Guangzhou 510515, China. Email: qianjun_gz@ 123456126.com ; Dr. Wang Yao, MD. The First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Second Road, Guangzhou 510060, China. Email: yaow7@ 123456mail.sysu.edu.cn ; Dr. Han Yang, MD, PhD. Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou 510060, China. Email: yanghan@ 123456sysucc.org.cn .
                Article
                tlcr-10-02-815
                10.21037/tlcr-20-1024
                7947406
                33718024
                5582359f-217b-4915-a685-8aafa1e920e9
                2021 Translational Lung Cancer Research. All rights reserved.

                Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0.

                History
                : 06 September 2020
                : 23 December 2020
                Categories
                Original Article

                non-small cell lung cancer (nsclc),examined lymph node (eln),minimal number,nodal staging,cohort study

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