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      Development and Validation of a Novel Nomogram for Predicting Tumor-Distant-Metastasis in Patients with Early T1-2 Stage Lung Adenocarcinoma

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          Abstract

          Background

          Distant metastasis in early T1-2 (diameter≤5 cm) stage lung adenocarcinoma (ET-LUAD) patients largely affect treatment strategies in clinical practice. However, the associated mechanism remains unclear and related studies is less. This study aimed to establish and validate a novel nomogram to predict the risk of distant metastasis in ET-LUAD.

          Methods

          A total of 258 patients diagnosed with ET-LUAD and not receiving any treatment were recruited into this study. The patients were randomly divided into a training cohort and validation cohort in a ratio of 1:2. Univariate and multivariate logistic regression analysis was used to select the most significant predictive risk factors associated with distant metastasis in the training cohort. The established nomogram was validated by the consistency index (C-index), calibration curve, and decision curve analysis (DCA).

          Results

          There were 124 patients with confirmed distant metastasis and 134 patients with non-distant metastases ET-LUAD were enrolled in the study. Multivariate logistic hazards regression analysis identified independent risk factors associated with distant metastasis to include platelet-to-lymphocyte ratios (PLR), lactate dehydrogenase (LDH), neural-specific enolase (NSE), carcinoembryonic antigen (CEA) and cytokeratin 19 fragments (Cyfra211), which were included in the establishment of the nomogram. The nomogram achieved a high consistency (C-index=0.792), good calibration, and high clinical application value in the validation cohort.

          Conclusion

          The established nomogram can be used to predict distant metastasis in high-risk ET-LUAD nonmetastasis patients and can also be used by doctors to guide preventive and individualized treatment for ET-LUAD patients.

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          Most cited references 41

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          Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

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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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                Author and article information

                Journal
                Ther Clin Risk Manag
                Ther Clin Risk Manag
                tcrm
                tcriskman
                Therapeutics and Clinical Risk Management
                Dove
                1176-6336
                1178-203X
                10 December 2020
                2020
                : 16
                : 1213-1225
                Affiliations
                [1 ]Department of Pathology, The First Affiliated Hospital of Nanchang University , Nanchang, Jiangxi, People’s Republic of China
                [2 ]First Clinical Medical College, Nanchang University , Nanchang, Jiangxi, People’s Republic of China
                [3 ]Department of Oncology, The First Affiliated Hospital of Nanchang University , Nanchang, Jiangxi, People’s Republic of China
                Author notes
                Correspondence: JinHong MeiDepartment of Pathology, The First Affiliated Hospital of Nanchang University , No. 17 Yong Wai Street, Nanchang, Jiangxi330006, People’s Republic of China Email mjhdoctor@126.com
                Chao ShiDepartment of Oncology, The First Affiliated Hospital of Nanchang University , No. 17 Yong Wai Street, Nanchang, Jiangxi330006, People’s Republic of China Email 43286143@qq.com
                Article
                272748
                10.2147/TCRM.S272748
                7735943
                © 2020 Gu et al.

                This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms ( https://www.dovepress.com/terms.php).

                Page count
                Figures: 5, Tables: 9, References: 41, Pages: 13
                Funding
                Funded by: the National Natural Science Foundation of China;
                This work was supported by the National Natural Science Foundation of China (grant number 81560410 to JH Mei). The funding sources had no role in the data collection, analysis or interpretation.
                Categories
                Original Research

                Medicine

                lung adenocarcinoma, distant metastasis, nomogram

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