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Comparative analysis of methodologies for predicting overall survival in patients with non-small cell lung cancer based on the number and rate of resected positive lymph nodes: A study based on the SEER database for 2010 through 2019

Clin Respir J. 2023 Sep 18. doi: 10.1111/crj.13699. Online ahead of print.


BACKGROUND: Lymph node (LN) metastasis is crucial in non-small cell lung cancer (NSCLC) prognosis and treatment, but the TNM system lacks LN quantity consideration. Our goal is to investigate the role of positive LNs (nPLN) and positive LN rate (LNR) in overall survival (OS) and assess whether they offer higher value in prognostic assessment of NSCLC than N-stage.

METHODS: Patients were stratified into four subgroups using X-Tile software. Statistical analysis was conducted using the Kaplan-Meier method, univariate analysis, and multivariate Cox regression analysis. Model performance was evaluated using the Harrell consistency index (C-index), Akaike information criterion (AIC), and Bayesian information criterion (BIC). The prognostic performance of the nodal classification was validated using overall survival as the endpoint.

RESULTS: The survival curves demonstrate distinct disparities between each nPLN and LNR category. A pronounced trend toward deteriorating overall survival from N-PLN 1 to N-PLN 2+ was observed across all tumor size categories. However, the differences between each LNR category were only significant for tumors ≤3 cm and 5-7 cm. Notably, both nPLN and LNR classifications displayed a higher C-index, lower AIC, and lower BIC compared with the N staging. Furthermore, the LNR classification provided superior prognostic stratification when compared with the nPLN classification.

CONCLUSIONS: Our results demonstrate that nPLN and LNR classifications may offer improved prognostic performance compared with the current N classification for LN-positive NSCLC patients. Nonetheless, more studies are needed to assess the feasibility of incorporating these classifications into the next TNM staging system.

PMID:37723579 | DOI:10.1111/crj.13699

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