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Indicators related to lung cancer recurrence, metastases and survival can inform treatment of patients

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NCI Press Office


A new study describes prognostic factors for lung cancer spread and recurrence, as well as subsequent risk of death from the disease. NCI investigators evaluated these indicators in nearly 2,100 people in the Lombardy region of Italy who were diagnosed with lung cancer between 2002 and 2005 and who had participated in the Environment and Genetics in Lung cancer Etiology (EAGLE) study. The researchers estimated risks of metastasis and recurrence for surgically-treated (stage IA-IIIA) and non-surgically treated patients (stage IIIB-IV). Stage I lung cancer is small and localized at the site where the cancer arose, whereas stage IV disease has spread throughout the body. The investigators observed that regardless of cancer stage, grade, or type of lung cancer, patients in the study were more likely to have distant metastasis than local recurrence. The experts noted that their estimates are likely applicable to the general population. The study appeared online March 23, 2015, in JNCI. 

Maria Teresa Landi, M.D. Ph.D., senior investigator in the Division of Cancer Epidemiology and Genetics, NCI, and her colleagues documented other important prognostic patterns. Within one year of metastasis, over half of the patients died. Patients with surgically treated non-small cell carcinoma had an increasing risk of brain metastases with increasing tumor grade. Patients with stage IIA disease were much more likely to have a recurrence of their cancer or die than those with stage IB disease. In stage IA and IB disease, about one-third of patients had a recurrence. Among patients diagnosed with stage IIA, IIB, or IIIA, about two-thirds had a recurrence. The absolute risk of recurrence was virtually identical in adenocarcinoma and squamous cell carcinoma patients. These data highlight the need for more effective drug treatments overall and for specific subgroups. The reported risks at various stages of disease can be useful for designing clinical trials, whose power depends on absolute numbers of events, noted the investigators.