Lung Cancer: Lung Cancer: Diagnosis and Prognosis |

An Analysis of Surveillance, Epidemiology, and End Result Database and a Prognostic Nomogram for Postoperative Small Cell Lung Cancer Patients FREE TO VIEW

Jiaxi He, PhD; Jianfei Shen, PhD
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Guangzhou Medical University 1st Affiliated Hospital, Guangzhou, China

Copyright 2016, American College of Chest Physicians. All Rights Reserved.

Chest. 2016;149(4_S):A274. doi:10.1016/j.chest.2016.02.286
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SESSION TITLE: Lung Cancer: Diagnosis and Prognosis

SESSION TYPE: Original Investigation Slide

PRESENTED ON: Saturday, April 16, 2016 at 09:45 AM - 11:15 AM

PURPOSE: Surgery is one of the feasible treatments in small cell lung cancer (SCLC), but the prognostic factors for the postoperative SCLC patients have not been characterized clearly. We utilized the Surveillance, Epidemiology, and End Result (SEER) database to indentify the potential prognostic factors of postoperative SCLC patients and establish an effective nomogram for prediction.

METHODS: Patients who had been diagnosed SCLC between 2004 and 2012 in SEER were analyzed. The Kaplan-Meier method was used to estimate the overall survival (OS) between no-surgery and surgery patients. Cox regression was performed to identify the independent prognostic factors. Four Cox models were established using different staging system and compared by concordance index (C-index) and calibration curve. The results were validated using bootstrap resampling method.

RESULTS: A total of 45226 SCLC patients were identified. After applying the exclusion criteria, 867 postoperative patients were included and analyzed. In the multivariate analysis, prognostic factors were age, sex, surgery, radiation sequence, tumor diameter, tumor extension, T stage, N stage, number of lymph node examination, grade of pathological differentiation and metastasis, which were used to established nomograms. The C-index of the nomogram incorporating tumor size and extension was 0.7063 (95%CI 0.6812-0.7314), which was higher than other conventional classifications such as AJCC TNM Classification, VALSG and IASLC staging systems. The validation of the nomogram demonstrated that it had an ideal predictive accuracy.

CONCLUSIONS: Operation is associated with a better survival of SCLC patients. The tumor size and extension are important independent prognostic factors. The nomogram incorporating tumor size, extension and other variables is an ideal prognostic prediction tool of OS for postoperative SCLC patients, which has better predictive accuracy than other conventional classifications.

CLINICAL IMPLICATIONS: In the comparisons between nomogram and other conventional classifications of SCLC, nomogram shows superior accuracy in the prediction of postoperative survival in SCLC patients.

DISCLOSURE: The following authors have nothing to disclose: Jiaxi He, Jianfei Shen

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