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the changes and implementation of the 8th edition of the International Association for the Study of Lung Cancers (IASLC) Staging Classification is must reading for every thoracic surgeon. It is a wonderful overview of the difficulties, even with huge numbers of patients, of breaking up a seemingly homogeneous disease into defined heterogeneous categories, and the proof is in the pudding that you can take these homogeneous yet still heterogeneous amalgams and validate the results. Even with these validations, do we actually know that these prognostic characteristics are gratifyingly sensitive and specific or are they just averaging outcomes over a given cohort of patients?
One of the confounding, but futuristically “hopeful” elements that he mentions in his overview is the idea of “granularity” or how deep can you go with the discovery of independent, unrelated factors, all of which could be combined in a statistical model to predict outcome. Could nonstandard TNM “granules” add accuracy to prognostication? The present “granularity” of lung cancer staging, although much improved from the 1970s, is probably at the “Model T level,” and we are just starting to realize, as did Giuliano and colleagues
for breast cancer, that lung cancer complexity is not just a forest, but a whole bunch of individual trees of different species. TNM histologic granularity has already been recognized by the IASLC adenocarcinoma classification system,
but further pathologic granularity will involve concerted recording of the size of the solid component within these adenocarcinomas. Which is more powerful: the size of solid or type of adenocarcinoma? “N” heterogeneity also needs to be addressed with regard to the influence of the number of N1 and N2 lymph nodes resected and prognosis, and this starts not only in the operating room but also at the pathology bench.
However, lung cancer therapists, PhDs, pathologists, epidemiologists, molecular biologists, and informatics gurus are now confronted with so much potential “granularity” in lung cancer from the literature that it may be no longer acceptable to just rely on our old friends' TNM. Just take the individual histologic subtypes, for example. Beginning in 2012
lung adenocarcinoma could be reclassified by 3 transcriptional subtypes (terminal respiratory unit, proximal inflammatory, and proximal proliferative), 3 methylation subtypes (CpG island methylator phenotype: high, medium, or low), histologic subtype (solid, acinar, lepidic, papillary/micropapillary, mucinous, and other), or 6 integrated subtypes consisting of quantitative difference by copy number, DNA methylation, and messenger RNA expression. For squamous cell carcinoma, TCGA describes 4 molecular subtypes (classic, basal, secretory, and primitive), 4 methylation clusters, and 3 distinct integrative clusters.
My head spins trying to “grade” these examples of granularity for clinical relevance right now…and so do the heads of the IASLC investigators who are in fact prospectively designing a prospective integrated clinical demographic, molecular, and histologic registry to supplement ongoing editions of the Lung Cancer Staging System. Nevertheless, staging moves forward to a day of integrated granules with the highest accuracy to forecast how our patients will do and treat them appropriately.
The eighth edition TNM stage classification for lung cancer: What does it mean on main street?.
Feature Editor's Note—The eighth edition of the American Joint Commission on Cancer TNM staging system for non–small cell lung cancer was introduced in January 2017 and will be implemented in the United States in January 2018. The eighth edition has been bolstered with a number of data-driven updates that will substantially affect the staging of early non–small cell lung cancer and are critical for the thoracic surgical oncologist to embrace in daily practice. New entities such as T1mi, T1c, M1c, and stage IA1 tumors, among others, will become regular in the language that we use to care for patients with lung cancer, and this staging framework is critical for advancing the field of thoracic oncology.