Objects: Inflammation is one of the hallmarks of cancer. Tumor-associated inflammatory response plays a crucial role in enhancing tumorigenesis. This study aimed to establish an effective predictive nomogram based on inflammation factors in patients with advanced non-small cell lung cancer (NSCLC). Methods: We retrospectively evaluated 887 patients with advanced NSCLC between November 2004 and December 2015 and randomly divided them into primary (n = 520) and validation cohorts (n = 367). Cox regression analysis was used to identify prognostic factors for building the nomogram. The predictive accuracy and discriminative ability of the nomogram were determined using a concordance index (C-index), calibration plot, and decision curve analysis and were compared to the TNM staging system. Results: The nomogram was established using independent risk factors (P < 0.05): age, TNM stage, C reaction protein-to-albumin ratio (CAR), and neutrophils (NEU). The C-index of the model for predicting OS had a superior discrimination power compared to that of the TNM staging system both in the primary [0.711 (95% CI: 0.675-0.747) vs 0.531 (95% CI: 0.488-0.574), P < 0.01] and validation cohorts [0.703, 95% CI: 0.671 -0.735 vs 0.582, 95% CI: 0.545-0.619, P < 0.01]. Decision curves also demonstrated that the nomogram had higher overall net benefits than that of the TNM staging system. Subgroup analyses revealed that the nomogram was a favorable prognostic parameter in advanced NSCLC (P < 0.05). The results were internally validated using the validation cohorts. Conclusions: The proposed nomogram with inflammatory factors resulted in an accurate prognostic prediction in patients with advanced NSCLC.
CITATION STYLE
Huang, Z., Xing, S., Zhu, Y., Qu, Y., Jiang, L., Sheng, J., … Xue, N. (2020). Establishment and Validation of Nomogram Model Integrated With Inflammation-Based Factors for the Prognosis of Advanced Non-Small Cell Lung Cancer. Technology in Cancer Research and Treatment, 19. https://doi.org/10.1177/1533033820971605
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