The new TNM 7 lung cancer staging system seems to be a better predictor of local or regional recurrence of lung cancer following surgery, according to a study published in the April issue of the Journal of Thoracic Oncology.
Being able to better define which patients might experience a cancer recurrence is important, especially given the controversies surrounding the use of adjuvant therapies, particularly postoperative radiation therapy (RT), for patients with non-small cell lung cancer (NSCLC).
In 2009, the International Association for the Study of Lung Cancer (IASLC) published its 7th edition of the tumor, node, metastasis (TNM) classification, which was developed in collaboration with the American Joint Committee on Cancer and the Union Internationale Contre le Cancer. The changes were based on an analysis of a large international database.
Researchers at Duke University School of Medicine in Durham, N.C., analyzed 709 patients who had undergone surgery for non-small cell lung cancer between 1995 and 2005. Stage was assigned based on both TNM 6 and TNM 7. The 5-year actuarial risk of local/regional recurrence (LRR) for all patients was 23%. None of the patients received any adjuvant chemotherapy or radiation therapy.
When patients were converted from TNM 6 to TNM 7, about 13% were placed in a higher stage and 8% in a lower stage. For most malignancies, increasing stage is generally associated with a higher risk of disease recurrence.
Five-year rates of local/regional recurrence for stages IA, IB, IIA, IIB and IIIA disease using TNM 6 were 16%, 26%, 43%, 35% and 40%, respectively. Using TNM 7, the corresponding rates were 16%, 23%, 37%, 39% and 30%.
"The TNM 7 system seems to be a better predictor for LRR after surgery for NSCLC than TNM 6," researchers wrote in the study. "This information may prove to be valuable when designing future studies of postoperative RT."
The above post is reprinted from materials provided by International Association for the Study of Lung Cancer. Note: Materials may be edited for content and length.
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