A single-institution retrospective analysis of the differences between 7th and 8th edition of the UICC TNM staging system in patients with advanced lung cancer

Eur Rev Med Pharmacol Sci. 2020 Aug;24(16):8394-8401. doi: 10.26355/eurrev_202008_22636.

Abstract

Objective: The TNM (Tumor, Node, Metastasis) classification of Union for International Cancer Control is a system describing the anatomical extent of the solid tumors that leads to staging and decision on the type of treatment. The latter TNM system (2017) as compared to the previous version (2010) has brought numerous changes. Our aim was to examine whether significant changes in the new TNM edition have altered the components of the TNM classification in patients and the stage of the disease to which they are ascribed.

Patients and methods: The study is retrospective and is based on radiological examination reports and case reports of 100 patients of the Department of Pneumonology, Allergology and Oncology of the Medical University in Lublin, Poland. One hundred randomly selected patients, who were hospitalized at the Clinic between 2013 and 2018 with primary lung cancer were enrolled in the study. The chi-square test, Mann-Whitney U test, Kruskal-Wallis test and an appropriate post-hoc test were used in statistical analysis.

Results: It was calculated that the T descriptor evaluated as per TNM in revision 8th in comparison to revision 7th changed in 41% of patients, the M descriptor - in 29% of patients, which resulted in change in staging in 11 patients. In spite of this scale amendments, only three patients could be treated differently because of the change in the stage of the disease.

Conclusions: Changing the treatment method, including withdrawal from surgery, can help avoid unnecessary treatment, but on the other hand, may potentially reduce the patient's chances of survival by depriving them of the possibility of radical treatment.

MeSH terms

  • Female
  • Humans
  • Lung Neoplasms / pathology*
  • Lung Neoplasms / radiotherapy
  • Male
  • Models, Statistical*
  • Retrospective Studies