Abstract

ObjectivesThis study aimed to estimate the relationship between 7th TNM classification and IASLC/ATS/ERS classification with regard to tumor size and pathological status and to determine the utility of these classifications for predicting prognosis in resected node-negative adenocarcinoma with tumor size ≤2.0cm and >2.0–3.0cm. Materials and methodsWe reviewed 321 pN0M0 lung adenocarcinoma cases resected at Hiroshima University Hospital from January 1991 to December 2010. Histological differences between T1a and T1b based on the IASLC/ATS/ERS classification were estimated and followed by evaluation of overall survival (OS) and recurrence-free interval (RFI) based on differences in tumor size and histological features. ResultsWe found 188 cases of pT1a-1bN0M0 (135 T1a, 53 T1b). Pathological T1a tumors included significantly more adenocarcinoma in situ (AIS) cases and minimally invasive adenocarcinoma (MIA) cases than T1b tumors (60.7% vs 18.8%, respectively; p<0.0001), while more invasive adenocarcinoma cases were included in pT1b. By considering the two classifications simultaneously, the 5-year OS rates of T1a AIS/MIA, T1b AIS/MIA, T1a invasive adenocarcinoma, and T1b invasive adenocarcinoma were 97.5%, 87.5%, 95.8%, and 86.8%, respectively. The 5-year RFIs of T1a AIS/MIA, T1b AIS/MIA, T1a invasive adenocarcinoma, and T1b invasive adenocarcinoma were 100%, 100%, 91.3%, and 72.5%, respectively. T1a AIS/MIA and T1b AIS/MIA could be separated as good prognostic cases with a 100% RFI. Multivariate analysis indicated that only T1b invasive adenocarcinoma was an independent factor for predicting recurrence (p=0.001). ConclusionCompared to a single classification, combining TNM and IASLC/ATS/ERS classifications could provide more detail information concerning disease recurrence. AIS and MIA should be handled equally, regardless of tumor size, because their non-/less invasive status is more useful for predicting prognosis than their tumor size classification. In contrast, the T descriptors based on TNM classification are important for predicting prognosis in invasive adenocarcinoma.

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