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Erschienen in:
18.08.2022 | Thoracic Oncology
A Comprehensive Comparison of Different Nodal Subclassification Methods in Surgically Resected Non-Small-Cell Lung Cancer Patients
Erschienen in: Annals of Surgical Oncology | Ausgabe 13/2022
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Introduction
The revision of the N descriptor in non-small-cell lung cancer has been widely discussed in the past few years. Many different subclassification methods based on number or location of lymph nodes have been proposed for better distinguishing different N patients. This study aimed to systematically collect them and provide a comprehensive comparison among different subclassification methods in a large cohort.
Method
Pathological N1 or N2 non-small-cell lung cancer patients undergoing surgical resection between 2005 and 2016 in the Western China Lung Cancer Database were retrospectively reviewed. A literature review was conducted to collect previous subclassification methods. Kaplan-Meier and multivariable Cox analyses were used to examine the prognostic performance of subclassification methods. Decision curve analysis, Akaike’s information criterion, and area under the receiver operating curve concordance were also performed to evaluate the standardized net benefit of the subclassification methods.
Results
A total of 1625 patients were identified in our cohort. Eight subclassification methods were collected from previous articles and further grouped into subclassification based on number categories (node number or station number), location categories (lymph node zone or chain) or combination of number and location categories. Subclassification based on combination of lymph node location and number tended to have better discrimination ability in multivariable Cox analysis. No significant superiority among the different subclassification methods was observed in the three statistical models.
Conclusion
Subclassification based on the combination of location and number could be used to provide a more accurate prognostic stratification in surgically resected NSCLC and is worth further validation.