International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society classification predicts occult lymph node metastasis in clinically mediastinal node-negative lung adenocarcinoma.
Ontology highlight
ABSTRACT: OBJECTIVES:We investigated the role of the 2011 International Association for the Study of Lung Cancer, American Thoracic Society, and European Respiratory Society (IASLC/ATS/ERS) classification in predicting occult lymph node metastasis in clinically mediastinal node-negative lung adenocarcinoma. METHODS:We reviewed lung adenocarcinoma patients who had clinically N2-negative status, were evaluated by preoperative positron emission tomography combined with computed tomography (PET/CT) and had undergone lobectomy or pneumonectomy at Memorial Sloan Kettering Cancer Center (n = 297). Tumours were classified according to the 2011 IASLC/ATS/ERS classification. The associations between occult lymph node metastasis and clinicopathological variables were analysed using Fisher's exact test and logistic regression analysis. RESULTS:Thirty-two (11%) cN0-1 patients had occult mediastinal lymph node metastasis (pN2) whereas 25% of cN1 patients had pN2 disease. Increased micropapillary pattern was associated with increased risk of pN2 disease (P = 0.001). On univariate analysis, high maximum standard uptake value of the primary tumour on PET/CT (P = 0.019) and the presence of micropapillary (P = 0.014) and solid pattern (P = 0.014) were associated with occult pN2 disease. On multivariable analysis, micropapillary pattern was positively associated with risk of pN2 disease (odds ratio = 3.41; 95% confidence intervals = 1.42-8.19; P = 0.006). CONCLUSIONS:The presence of micropapillary pattern is an independent predictor of occult mediastinal lymph node metastasis. Our observations have potential therapeutic implications for management of early-stage lung adenocarcinoma.
SUBMITTER: Yeh YC
PROVIDER: S-EPMC4678972 | biostudies-literature | 2016 Jan
REPOSITORIES: biostudies-literature
ACCESS DATA