The Eighth Edition Lung Cancer Stage Classification

doi:10.1016/J.CHEST.2016.10.010

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The Eighth Edition Lung Cancer Stage Classification

Journal Article•DOI•

The Eighth Edition Lung Cancer Stage Classification

Frank C. Detterbeck¹, Daniel J. Boffa¹, Anthony W. Kim¹, Lynn T. Tanoue¹•Institutions (1)

Yale University¹

01 Jan 2017-Chest (Elsevier)-Vol. 151, Iss: 1, pp 193-203

TL;DR: This paper summarizes the eighth edition of lung cancer stage classification, which is the worldwide standard as of January 1, 2017, based on a large global database, a sophisticated analysis, extensive internal validation as well as multiple assessments confirming generalizability.

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About: This article is published in Chest.The article was published on 2017-01-01. It has received 987 citations till now. The article focuses on the topics: Cancer.

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Journal Article•DOI•

Precision Diagnosis and Treatment for Advanced Non–Small-Cell Lung Cancer

[...]

Martin Reck¹, Klaus F. Rabe¹•Institutions (1)

University of Kiel¹

30 Aug 2017-The New England Journal of Medicine

TL;DR: The authors of this review discuss recent progress in diagnostic and treatment approaches, including molecular characterization to determine the likelihood of a response to targeted agents and immunotherapies.

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Abstract: Smoking cessation has reduced the incidence of lung cancer. The authors of this review discuss recent progress in diagnostic and treatment approaches, including molecular characterization to determine the likelihood of a response to targeted agents and immunotherapies.

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495 citations

Journal Article•DOI•

Lung Cancers: Molecular Characterization, Clonal Heterogeneity and Evolution, and Cancer Stem Cells.

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Ugo Testa¹, Germana Castelli¹, Elvira Pelosi¹•Institutions (1)

Istituto Superiore di Sanità¹

27 Jul 2018-Cancers

TL;DR: Deep-sequencing studies supporting the heterogeneity of lung tumors at cellular level, with sub-clones exhibiting different combinations of mutations, show the phenomenon of clonal evolution, thus supporting the occurrence of a temporal tumor heterogeneity.

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Abstract: Lung cancer causes the largest number of cancer-related deaths in the world. Most (85%) of lung cancers are classified as non-small-cell lung cancer (NSCLC) and small-cell lung cancer (15%) (SCLC). The 5-year survival rate for NSCLC patients remains very low (about 16% at 5 years). The two predominant NSCLC histological phenotypes are adenocarcinoma (ADC) and squamous cell carcinoma (LSQCC). ADCs display several recurrent genetic alterations, including: KRAS, BRAF and EGFR mutations; recurrent mutations and amplifications of several oncogenes, including ERBB2, MET, FGFR1 and FGFR2; fusion oncogenes involving ALK, ROS1, Neuregulin1 (NRG1) and RET. In LSQCC recurrent mutations of TP53, FGFR1, FGFR2, FGFR3, DDR2 and genes of the PI3K pathway have been detected, quantitative gene abnormalities of PTEN and CDKN2A. Developments in the characterization of lung cancer molecular abnormalities provided a strong rationale for new therapeutic options and for understanding the mechanisms of drug resistance. However, the complexity of lung cancer genomes is particularly high, as shown by deep-sequencing studies supporting the heterogeneity of lung tumors at cellular level, with sub-clones exhibiting different combinations of mutations. Molecular studies performed on lung tumors during treatment have shown the phenomenon of clonal evolution, thus supporting the occurrence of a temporal tumor heterogeneity.

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218 citations

Cites background from "The Eighth Edition Lung Cancer Stag..."

...Importantly, the eighth edition lung cancer stage classification involves also the evaluation of carcinoma in situ and of minimally invasive carcinoma [9]....
[...]
...Finally, in the tumor evolution analysis, four driver genes had a significantly lower fraction of subclonal mutations, including TP53, KEAP1, STK11 and EGFR, thus suggesting a tumor initiation role for these genes [9]....
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Journal Article•DOI•

Toward personalized treatment approaches for non-small-cell lung cancer

[...]

Meina Wang¹, Roy S. Herbst¹, Chris Boshoff¹, Chris Boshoff²•Institutions (2)

Yale University¹, Pfizer²

01 Aug 2021-Nature Medicine

TL;DR: A major challenge to successful development of rational combination therapies will be the application of robust predictive biomarkers for clear-cut patient stratification, and the views on clinical research areas that could influence how NSCLC will be managed over the coming decade are provided.

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Abstract: Worldwide, lung cancer is the most common cause of cancer-related deaths. Molecular targeted therapies and immunotherapies for non-small-cell lung cancer (NSCLC) have improved outcomes markedly over the past two decades. However, the vast majority of advanced NSCLCs become resistant to current treatments and eventually progress. In this Perspective, we discuss some of the recent breakthrough therapies developed for NSCLC, focusing on immunotherapies and targeted therapies. We highlight our current understanding of mechanisms of resistance and the importance of incorporating genomic analyses into clinical studies to decipher these further. We underscore the future role of neoadjuvant and maintenance combination therapy approaches to potentially cure early disease. A major challenge to successful development of rational combination therapies will be the application of robust predictive biomarkers for clear-cut patient stratification, and we provide our views on clinical research areas that could influence how NSCLC will be managed over the coming decade.

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207 citations

Journal Article•DOI•

Prediction of disease-free survival by the PET/CT radiomic signature in non-small cell lung cancer patients undergoing surgery

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Margarita Kirienko¹, Luca Cozzi, Lidija Antunovic, Lisa Lozza, Antonella Fogliata¹, Emanuele Voulaz, Alexia Rossi¹, Arturo Chiti¹, Martina Sollini¹ - Show less +5 more•Institutions (1)

Humanitas University¹

01 Feb 2018-European Journal of Nuclear Medicine and Molecular Imaging

TL;DR: A radiomic signature, for either CT, PET, or PET/CT images, has been identified and validated for the prediction of disease-free survival in patients with non-small cell lung cancer treated by surgery.

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Abstract: Radiomic features derived from the texture analysis of different imaging modalities e show promise in lesion characterisation, response prediction, and prognostication in lung cancer patients The present study aimed to identify an images-based radiomic signature capable of predicting disease-free survival (DFS) in non-small cell lung cancer (NSCLC) patients undergoing surgery A cohort of 295 patients was selected Clinical parameters (age, sex, histological type, tumour grade, and stage) were recorded for all patients The endpoint of this study was DFS Both computed tomography (CT) and fluorodeoxyglucose positron emission tomography (PET) images generated from the PET/CT scanner were analysed Textural features were calculated using the LifeX package Statistical analysis was performed using the R platform The datasets were separated into two cohorts by random selection to perform training and validation of the statistical models Predictors were fed into a multivariate Cox proportional hazard regression model and the receiver operating characteristic (ROC) curve as well as the corresponding area under the curve (AUC) were computed for each model built The Cox models that included radiomic features for the CT, the PET, and the PET+CT images resulted in an AUC of 075 (95%CI: 065–085), 068 (95%CI: 057–080), and 068 (95%CI: 058–074), respectively The addition of clinical predictors to the Cox models resulted in an AUC of 061 (95%CI: 051–069), 064 (95%CI: 053–075), and 065 (95%CI: 050–072) for the CT, the PET, and the PET+CT images, respectively A radiomic signature, for either CT, PET, or PET/CT images, has been identified and validated for the prediction of disease-free survival in patients with non-small cell lung cancer treated by surgery

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125 citations

Journal Article•DOI•

Tumor Spread through Air Spaces Affects the Recurrence and Overall Survival in Patients with Lung Adenocarcinoma >2 to 3 cm

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Chenyang Dai¹, Huikang Xie¹, Hang Su¹, Yunlang She¹, Erjia Zhu¹, Ziwen Fan¹, F. Zhou¹, Yijiu Ren¹, Dong Xie¹, Hui Zheng¹, Xiermaimaiti Kadeer¹, Donglai Chen¹, Liping Zhang¹, Gening Jiang¹, Chunyan Wu¹, Chang Chen¹ - Show less +12 more•Institutions (1)

Tongji University¹

01 Jul 2017-Journal of Thoracic Oncology

TL;DR: Preliminary evidence is provided that STAS could be considered as a factor in a staging system to predict prognosis more precisely, especially in ADCs larger than 2 to 3 cm.

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118 citations

Cites result from "The Eighth Edition Lung Cancer Stag..."

...More importantly, the RFS and OS of patients with ADC larger than 2 to 3 cm with STAS were similar to those of patients with stage IB ADC.17 Thus, patients with ADC larger than 2 to 3 cm with STAS might benefit from postoperative chemotherapy.18,19 However, future studies with large and well-characterized cohorts are warranted to validate this hypothesis....
[...]
...More importantly, the RFS and OS of patients with ADC larger than 2 to 3 cm with STAS were similar to those of patients with stage IB ADC.(17) Thus, patients with ADC larger than 2 to 3 cm with STAS might benefit from postoperative chemotherapy....
[...]
...Furthermore, comparable RFS (p ¼ 0.091) and OS (p ¼ 0.443) rates were observed in patients with ADCs 3 cm or smaller with STAS present and those with stage IB ADC....
[...]
...However, the 5-year postoperative recurrence rate reaches 30%.1,2 Tumor spread through air spaces (STAS) was listed as an additional invasive pattern of lung ADC in the WHO guidelines.3,4 STAS is defined as single cells, micropapillary clusters, or solid nests that are observed within air spaces in the surrounding lung parenchyma beyond the edge of the tumor.5 Recently, several studies demonstrated clearly that STAS offers another convincing explanation for postoperative recurrence of ADC.5–10 Although much effort has been made in searching for biomarkers that can aid in predicting the prognosis of patients with ADC, tumor size is an irreplaceable prognostic factor because of the significant difference in survival outcome observed with each centimeter of increase in tumor size.11 Aside from estimating prognosis, tumor size also contributes to treatment decisions (postoperative chemotherapy) and serves as a common language when enrolling patients in clinical trials (lobectomy versus limited resection).12,13 However, the effects that the combination of STAS and tumor size have on survival have not yet been well studied....
[...]
...Specifically, STAS occurred less frequently in lepidic predominant ADC and more frequently in micropapillary and solid predominant ADC....
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References

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Book•

AJCC Cancer Staging Manual

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Mahul B. Amin, Stephen B. Edge, Frederick L. Greene, David R. Byrd, Robert K. Brookland, Mary Kay Washington, Jeffrey E. Gershenwald, Carolyn C. Compton, Kenneth R. Hess, Daniel C. Sullivan, J. Milburn Jessup, James D. Brierley, Lauri E. Gaspar, Richard L. Schilsky, Charles M. Balch, David P. Winchester, Elliot A. Asare, Martin Madera, Donna M. Gress, Laura R. Meyer - Show less +16 more

17 Sep 2013

TL;DR: Purposes and Principles of Cancer Staging and End-Results Reporting are explained.

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Abstract: General Information on Cancer Staging and End-Results Reporting.- Purposes and Principles of Cancer Staging.- Cancer Survival Analysis.- Head and Neck.- Lip and Oral Cavity.- Pharynx.- Larynx.- Nasal Cavity and Paranasal Sinuses.- Major Salivary Glands.- Thyroid.- Mucosal Melanoma of the Head and Neck.- Digestive System.- Esophagus and Esophagogastric Junction.- Stomach.- Small Intestine.- Colon and Rectum.- Anus.- Gastrointestinal Stromal Tumor.- Neuroendocrine Tumors.- Liver.- Intrahepatic Bile Ducts.- Gallbladder.- Perihilar Bile Ducts.- Distal Bile Duct.- Ampulla of Vater.- Exocrine and Endocrine Pancreas.- Thorax.- Lung.- Pleural Mesothelioma.- Musculoskeletal Sites.- Bone.- Soft Tissue Sarcoma.- Skin.- Cutaneous Squamous Cell Carcinoma and Other Cutaneous Carcinomas.- Merkel Cell Carcinoma.- Melanoma of the Skin.- Breast.- Breast.- Gynecologic Sites.- Vulva.- Vagina.- Cervix Uteri.- Corpus Uteri.- Ovary and Primary Peritoneal Carcinoma.- Fallopian Tube.- Gestational Trophoblastic Tumors.- Genitourinary Sites.- Penis.- Prostate.- Testis.- Kidney.- Renal Pelvis and Ureter.- Urinary Bladder.- Urethra.- Adrenal.- Ophthalmic Sites.- Carcinoma of the Eyelid.- Carcinoma of the Conjunctiva.- Malignant Melanoma of the Conjunctiva.- Malignant Melanoma of the Uvea.- Retinoblastoma.- Carcinoma of the Lacrimal Gland.- Sarcoma of the Orbit.- Ocular Adnexal Lymphoma.- Central Nervous System.- Brain and Spinal Cord.- Lymphoid Neoplasms.- Lymphoid Neoplasms.

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16,806 citations

Book•DOI•

TNM classification of malignant tumours

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Leslie H. Sobin, Mary Gospodarowicz, Ch. Wittekind

01 Jan 1987

TL;DR: Head and Neck Tumours.- Lip and Oral Cavity.- Pharynx.- Larynx.' Maxillary Sinus.- Salivary Glands.- Thyroid Gland.- Digestive System Tumour .

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Abstract: Head and Neck Tumours.- Lip and Oral Cavity.- Pharynx.- Larynx.- Maxillary Sinus.- Salivary Glands.- Thyroid Gland.- Digestive System Tumours.- Oesophagus.- Stomach.- Colon and Rectum.- Anal Canal.- Liver.- Gall Bladder.- Extrahepatic Bile Ducts.- Ampulla of Vater.- Pancreas.- Lung Tumours.- Tumours of Bone and Soft Tissues.- Bone.- Soft Tissue.- Skin Tumours.- Carcinoma of Skin.- Melanoma of Skin.- Breast Tumours.- Gynaecological Tumours.- Cervix Uteri.- Corpus Uteri.- Ovary.- Vagina.- Vulva.- Urological Tumours.- Prostate.- Testis.- Penis.- Urinary Bladder.- Kidney.- Renal Pelvis and Ureter.- Urethra.- Ophthalmic Tumours.- Carcinoma of Eyelid.- Malignant Melanoma of Eyelid.- Carcinoma of Conjunctiva.- Malignant Melanoma of Conjunctiva.- Malignant Melanoma of Uvea.- Retinoblastoma.- Sarcoma of Orbit.- Carcinoma of Lacrimal Gland.- Brain Tumours.- Hodgkin's Disease.- Non-Hodgkin's Lymphoma.- Paediatric Tumours.- Nephroblastoma (Wilms' Tumour).- Neuroblastoma.- Soft Tissue Sarcomas - Paediatric.

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15,624 citations

Journal Article•DOI•

The IASLC Lung Cancer Staging Project: proposals for the revision of the TNM stage groupings in the forthcoming (seventh) edition of the TNM Classification of malignant tumours.

[...]

Peter Goldstraw¹, John Crowley², Kari Chansky², Dorothy J. Giroux², Patti A. Groome³, Ramón Rami-Porta, Pieter E. Postmus⁴, Valerie W. Rusch⁵, Leslie H. Sobin⁶ - Show less +5 more•Institutions (6)

Imperial College London¹, Washington University in St. Louis², Queen's University³, VU University Amsterdam⁴, Memorial Sloan Kettering Cancer Center⁵, Armed Forces Institute of Pathology⁶

01 Aug 2007-Journal of Thoracic Oncology

TL;DR: Suggestions include additional cutoffs for tumor size, with tumors >7 cm moving from T2 to T3; reassigning the category given to additional pulmonary nodules in some locations; and reclassifying pleural effusion as an M descriptor.

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3,466 citations

Journal Article•DOI•

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.

[...]

Peter Goldstraw¹, Kari Chansky, John Crowley, Ramón Rami-Porta², Hisao Asamura³, Wilfried Ernst Erich Eberhardt⁴, Andrew G. Nicholson¹, Patti A. Groome⁵, Alan Mitchell, Vanessa Bolejack, David Ball⁶, David G. Beer⁷, Ricardo Beyruti⁸, Frank C. Detterbeck⁹, Wilfried Eberhardt⁴, John G. Edwards¹⁰, Françoise Galateau-Salle¹¹, Dorothy Giroux¹², Fergus V. Gleeson¹³, James Huang¹⁴, Catherine Kennedy¹⁵, Jhingook Kim¹⁶, Young Tae Kim¹⁷, Laura Kingsbury¹², Haruhiko Kondo¹⁸, Mark Krasnik¹⁹, Kaoru Kubota²⁰, Antoon Lerut²¹, Gustavo Lyons, Mirella Marino, Edith M. Marom²², Jan P. van Meerbeeck²³, Takashi Nakano²⁴, Anna K. Nowak²⁵, Michael D Peake²⁶, Thomas W. Rice²⁷, Kenneth E. Rosenzweig²⁸, Enrico Ruffini²⁹, Valerie W. Rusch¹⁴, Nagahiro Saijo, Paul Van Schil²³, Jean-Paul Sculier³⁰, Lynn Shemanski¹², Kelly G. Stratton¹², Kenji Suzuki³¹, Yuji Tachimori³², Charles F. Thomas³³, William D. Travis¹⁴, Ming-Sound Tsao³⁴, Andrew T. Turrisi³⁵, Johan Vansteenkiste²¹, Hirokazu Watanabe, Yi-Long Wu, Paul Baas³⁶, Jeremy J. Erasmus²², Seiki Hasegawa²⁴, Kouki Inai³⁷, Kemp H. Kernstine³⁸, Hedy L. Kindler³⁹, Lee M. Krug¹⁴, Kristiaan Nackaerts²¹, Harvey I. Pass⁴⁰, David C. Rice²², Conrad Falkson⁵, Pier Luigi Filosso²⁹, Giuseppe Giaccone⁴¹, Kazuya Kondo⁴², Marco Lucchi⁴³, Meinoshin Okumura⁴⁴, Eugene H. Blackstone²⁷, F. Abad Cavaco, E. Ansótegui Barrera, J. Abal Arca, I. Parente Lamelas, A. Arnau Obrer⁴⁵, R. Guijarro Jorge⁴⁵, D. Ball⁶, G.K. Bascom⁴⁶, A. I. Blanco Orozco, M. A. González Castro, M.G. Blum, D. Chimondeguy, V. Cvijanovic⁴⁷, S. Defranchi⁴⁸, B. de Olaiz Navarro, I. Escobar Campuzano², I. Macía Vidueira², E. Fernández Araujo⁴⁹, F. Andreo García⁴⁹, Kwun M. Fong, G. Francisco Corral, S. Cerezo González, J. Freixinet Gilart, L. García Arangüena, S. García Barajas⁵⁰, P. Girard, Tuncay Göksel, M. T. González Budiño⁵¹, G. González Casaurrán⁵⁰, J. A. Gullón Blanco, J. Hernández Hernández, H. Hernández Rodríguez, J. Herrero Collantes, M. Iglesias Heras, J. M. Izquierdo Elena, Erik Jakobsen, S. Kostas⁵², P. León Atance, A. Núñez Ares, M. Liao, M. Losanovscky, G. Lyons, R. Magaroles⁵³, L. De Esteban Júlvez⁵³, M. Mariñán Gorospe, Brian C. McCaughan¹⁵, Catherine J. Kennedy¹⁵, R. Melchor Íñiguez⁵⁴, L. Miravet Sorribes, S. Naranjo Gozalo, C. Álvarez de Arriba, M. Núñez Delgado, J. Padilla Alarcón, J. C. Peñalver Cuesta, Jongsun Park¹⁶, H. Pass⁴⁰, M. J. Pavón Fernández, Mara Rosenberg, Enrico Ruffini²⁹, V. Rusch¹⁴, J. Sánchez de Cos Escuín, A. Saura Vinuesa, M. Serra Mitjans, Trond Eirik Strand, Dragan Subotic, S.G. Swisher²², Ricardo Mingarini Terra⁸, Charles R. Thomas³³, Kurt G. Tournoy⁵⁵, P. Van Schil²³, M. Velasquez, Y.L. Wu, K. Yokoi - Show less +139 more•Institutions (55)

Imperial College London¹, University of Barcelona², Keio University³, University of Duisburg-Essen⁴, Queen's University⁵, Peter MacCallum Cancer Centre⁶, University of Michigan⁷, University of São Paulo⁸, Yale University⁹, Northern General Hospital¹⁰, University of Caen Lower Normandy¹¹, Fred Hutchinson Cancer Research Center¹², University of Oxford¹³, Memorial Sloan Kettering Cancer Center¹⁴, University of Sydney¹⁵, Sungkyunkwan University¹⁶, Seoul National University¹⁷, Kyorin University¹⁸, University of Copenhagen¹⁹, Nippon Medical School²⁰, Katholieke Universiteit Leuven²¹, University of Texas MD Anderson Cancer Center²², University of Antwerp²³, Hyogo College of Medicine²⁴, University of Western Australia²⁵, Glenfield Hospital²⁶, Cleveland Clinic²⁷, Icahn School of Medicine at Mount Sinai²⁸, University of Turin²⁹, Université libre de Bruxelles³⁰, Juntendo University³¹, National Cancer Research Institute³², Mayo Clinic³³, University of Toronto³⁴, Sinai Grace Hospital³⁵, Netherlands Cancer Institute³⁶, Hiroshima University³⁷, City of Hope National Medical Center³⁸, University of Chicago³⁹, New York University⁴⁰, Georgetown University⁴¹, University of Tokushima⁴², University of Pisa⁴³, Osaka University⁴⁴, University of Valencia⁴⁵, Good Samaritan Hospital⁴⁶, Military Medical Academy⁴⁷, Fundación Favaloro⁴⁸, Autonomous University of Barcelona⁴⁹, Complutense University of Madrid⁵⁰, University of Oviedo⁵¹, National and Kapodistrian University of Athens⁵², Rovira i Virgili University⁵³, Autonomous University of Madrid⁵⁴, Ghent University⁵⁵

01 Jan 2016-Journal of Thoracic Oncology

TL;DR: The methods used to evaluate the resultant Stage groupings and the proposals put forward for the 8th edition of the TNM Classification for lung cancer due to be published late 2016 are described.

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2,826 citations

Journal Article•DOI•

The IASLC Lung Cancer Staging Project: Proposals for the Revisions of the T Descriptors in the Forthcoming Eighth Edition of the TNM Classification for Lung Cancer

[...]

Ramón Rami-Porta, David Ball¹, John Crowley², Dorothy J. Giroux², James R. Jett³, William D. Travis⁴, Masahiro Tsuboi⁵, Eric Vallières, Peter Goldstraw - Show less +5 more•Institutions (5)

Peter MacCallum Cancer Centre¹, Washington University in St. Louis², Mayo Clinic³, Memorial Sloan Kettering Cancer Center⁴, Tokyo Medical University⁵

01 Jul 2007-Journal of Thoracic Oncology

TL;DR: Recommendations are to subclassify T1 into T1a, T1b, and T1c, and to group involvement of main bronchus as T2 regardless of distance from carina; to group partial and total atelectasis/pneumonitis as T1; to reclassify diaphragm invasion as T4; and to delete mediastinal pleura invasion as a T descriptor.

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1,511 citations

"The Eighth Edition Lung Cancer Stag..." refers background or methods in this paper

...The impact of size was analyzed using a running log rank statistic (initially in a p-stage N0 M0 R0 non-small cell lung cancer [NSCLC] cohort, but then substantiated in multiple others).(7) This confirmed previous size cutpoints and suggested further cutpoints in 1-cm increments....
[...]
...The T component analysis was on the basis of 10,230 c-stage and 22,257 p-stage tumors with sufficient detailed information.(7) The impact of size was analyzed using a running log rank statistic (initially in a p-stage N0 M0 R0 non-small cell lung cancer [NSCLC] cohort, but then substantiated in multiple others)....
[...]
...The T component is divided into five T categories that are defined by various T descriptors, as summarized in Table 3.(7) Size plays a prominent role in defining the T...
[...]
...Tumors with one vs more than one positive descriptor within a T category were considered, but this was not incorporated into the classification because of inconsistent differences.(6,7)...
[...]