Weiye Deng1, Ting Xu1, Yifan Wang2, Yujin Xu3, Pei Yang4, Daniel Gomez1, Zhongxing Liao5. 1. Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, 1400 Pressler St., Houston, TX, 77030-4008, United States. 2. Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Houston, TX, 77030, United States. 3. Department of Radiation Oncology, Zhejiang Cancer Hospital, No. 1, Banshandong Road, Gongshu District, Hanzhou, 310022, China. 4. Hunan Key Laboratory of Translational Radiation Oncology, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, 283 Tongzipo Road, Yuelu District, Changsha, Hunan, 410013, China. 5. Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, 1400 Pressler St., Houston, TX, 77030-4008, United States. Electronic address: zliao@mdanderson.org.
Abstract
OBJECTIVES: The number of positive lymph nodes (npLNs) and the lymph node ratio [LNR; npLNs/number of resected LNs] are useful for predicting survival among patients with non-small cell lung cancer (NSCLC). Here we compared the relative effectiveness of npLNs, LNR, and the log odds of positive lymph nodes (LODDS) to predict overall survival (OS) and cancer-specific survival (CSS) among patients with node-positive NSCLC. MATERIALS AND METHODS: We identified 5289 patients with NSCLC and lymph node involvement who had lobectomy or pneumonectomy in 2010-2013 from the Surveillance Epidemiology and End Results (SEER) database. Potential associations between npLNs, LNR, and LODDS with overall survival (OS) and cancer-specific survival (CSS) were assessed with Cox regression analysis. The goodness of fit of npLNs, LNR, and LODDS was compared with the -2 log-likelihood ratio (-2LLR) and by differences in Akaike's information criterion scores (ΔAIC). Tree-based recursive partitioning was applied to split ratio-based variables (LNR and LODDS) into low- and high-risk groups. Kaplan-Meier actuarial estimates of OS and CSS in the various npLNs, LNR, and LODDS subgroups were compared with log-rank tests. RESULTS AND CONCLUSION: Of 5289 patients, 2297 (43.3%) had <10 LNs retrieved and 2992 (56.6%) had ≥10 LNs harvested. Multivariate Cox analysis adjusted for significant factors indicated that LODDS, npLNs, and LNR were independent risk factors for OS and CSS. A LODDS model had the best fit compared with LNR or npLN models in predicting OS and CSS (P < 0.001, ΔAIC = 0). LODDS was slightly superior to LNR for patients with <10 resected LNs, and LNR was slightly superior to LODDS for patients with ≥10 resected LNs (P < 0.001). Higher LODDS was associated with worse OS and worse CSS (log-rank P for both <0.001). LODDS and LNR staging schemes outperformed those of npLNs for predicting OS and CSS. Published by Elsevier B.V.
OBJECTIVES: The number of positive lymph nodes (npLNs) and the lymph node ratio [LNR; npLNs/number of resected LNs] are useful for predicting survival among patients with non-small cell lung cancer (NSCLC). Here we compared the relative effectiveness of npLNs, LNR, and the log odds of positive lymph nodes (LODDS) to predict overall survival (OS) and cancer-specific survival (CSS) among patients with node-positive NSCLC. MATERIALS AND METHODS: We identified 5289 patients with NSCLC and lymph node involvement who had lobectomy or pneumonectomy in 2010-2013 from the Surveillance Epidemiology and End Results (SEER) database. Potential associations between npLNs, LNR, and LODDS with overall survival (OS) and cancer-specific survival (CSS) were assessed with Cox regression analysis. The goodness of fit of npLNs, LNR, and LODDS was compared with the -2 log-likelihood ratio (-2LLR) and by differences in Akaike's information criterion scores (ΔAIC). Tree-based recursive partitioning was applied to split ratio-based variables (LNR and LODDS) into low- and high-risk groups. Kaplan-Meier actuarial estimates of OS and CSS in the various npLNs, LNR, and LODDS subgroups were compared with log-rank tests. RESULTS AND CONCLUSION: Of 5289 patients, 2297 (43.3%) had <10 LNs retrieved and 2992 (56.6%) had ≥10 LNs harvested. Multivariate Cox analysis adjusted for significant factors indicated that LODDS, npLNs, and LNR were independent risk factors for OS and CSS. A LODDS model had the best fit compared with LNR or npLN models in predicting OS and CSS (P < 0.001, ΔAIC = 0). LODDS was slightly superior to LNR for patients with <10 resected LNs, and LNR was slightly superior to LODDS for patients with ≥10 resected LNs (P < 0.001). Higher LODDS was associated with worse OS and worse CSS (log-rank P for both <0.001). LODDS and LNR staging schemes outperformed those of npLNs for predicting OS and CSS. Published by Elsevier B.V.