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- W2891579114 abstract "e20069 Background: To explore the prognostic effect of log odds of positive lymph nodes (LODDS) in node-positive non-small cell lung cancer (NSCLC) patients, and evaluate whether a model incorporates the pN and LODDS is a more reliable prognostic determinant in these patients. Methods: Data of 9557 NSCLC patients (pT1-pT3, pN1-pN2, M0) with lymphadenectomy recorded in the Surveillance Epidemiology and End Results database between 2004 and 2009 were retrospectively studied. Results: In adjusted analyses, LODDS value was an independent prognostic factor for patients with node-positive NSCLC, as well as pN classification and MLN count. However, the LNR value lost its significance in multivariate regression model. Next, we established the pN-LODDS (N-L) classification model and observed that it had better discriminatory ability, monotonicity, and homogeneity for prognostic stratification, as well as more accurate time point OS prediction than either of pN, MLN and LODDS classifications alone. Moreover, besides the pN classification, the N-L model could serve as a referential indicator designing postoperative treatment in node-positive NSCLC patients. Analyses stratified by the N-L classification showed that postoperative radiotherapy was independently linked to prolonged survival in patients with N-L 3 classification, N-L 5 classification, and in pN2 subgroup of N-L 4 classification. Conclusions: Our findings indicated that the N-L classification model could serve as the optimal scheme for prognostic assessment in patients with node-positive NSCLC. Incorporating N-L classification into the staging system will enable clinicians to more accurately predict the prognosis and to guide the decision of regional therapy regiment." @default.
- W2891579114 created "2018-09-27" @default.
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- W2891579114 date "2017-05-20" @default.
- W2891579114 modified "2023-09-28" @default.
- W2891579114 title "A new nodal classification based on log odds and location of involved lymph nodes in lung cancer." @default.
- W2891579114 doi "https://doi.org/10.1200/jco.2017.35.15_suppl.e20069" @default.
- W2891579114 hasPublicationYear "2017" @default.
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