Relationship Between Tumor Size and Survival in Non–Small-Cell Lung Cancer (NSCLC): An Analysis of the Surveillance, Epidemiology, and End Results (SEER) Registry. Issue 4 (April 2015)

• Record Type: Journal Article
• Authors: Zhang, Jianjun; Gold, Kathryn A.; Lin, Heather Y.; Swisher, Stephen G.; Xing, Yan; Lee, J. Jack; Kim, Edward S.; William, William N.
• Is Part Of: Journal of thoracic oncology. Volume 10:Issue 4(2015)
• Publication Date: 2015-04
• Subjects: Non–small-cell lung cancer -- Tumor size -- Survival -- SEER; Chest -- Cancer -- Periodicals; Thoracic Neoplasms -- Periodicals; 616.99494005
• DOI: 10.1097/JTO.0000000000000456
• Languages: English
• ISSNs: 1556-0864

Abstract

Abstract : Introduction: Tumor size is a known prognostic factor for early stage non–small-cell lung cancer (NSCLC), but its significance in node-positive and locally invasive NSCLC has not been extensively characterized. We queried the Surveillance, Epidemiology, and End Results database to evaluate the prognostic value of tumor size for early stage and node-positive and locally invasive NSCLC. Methods: Patients in Surveillance, Epidemiology, and End Results registry with NSCLC diagnosed between 1998 and 2003 were analyzed. Tumor size was analyzed as a continuous variable. Other demographic variables included age, gender, race, histology, primary tumor extension, node status, and primary treatment modality (surgery vs. radiation). The Kaplan–Meier method was used to estimate overall survival (OS). Cox proportional hazard model was used to evaluate whether tumor size was an independent prognostic factor. Results: In all, 52, 287 eligible patients were subgrouped based on tumor extension and node status. Tumor size had a significant effect on OS in all subgroups defined by tumor extension or node status. In addition, tumor size also had statistically significant effect on OS in 15 of 16 subgroups defined by tumor extension and nodal status after adjustment for other clinical variables. Our model incorporating tumor size had significantly better predictive accuracy than our alternative model without tumor size. Conclusions: Tumor size is an independent prognostic factor, for early stage and node-positive and locally invasive disease. Prediction tools, such as nomograms, incorporating more detailed information not captured in detail by the routine tumor, node, metastasis classification, may improve prediction accuracy of OS in NSCLC.