Abstract
The objective is to elaborate a survival model that integrates anatomic factors, according to the 2010 seventh edition of the tumour-node-metastasis (TNM) staging, with clinical and molecular factors.
Pathologic TNM-descriptors (Group A), clinical variables (Group B), laboratory parameters (Group C) and molecular markers [tissue microarrays] (Group D) were collected from 512 early NSCLC with complete resection. A multivariate analysis steped supervised learning classification algorithm was used.
The prognostic performance by groups is: areas under the ROC curve (C-index): 0.67 (Group A), 0.65 (Group B), 0.57 (Group C) and 0.65 (Group D). Considering together all variables selected for each of the 4 Groups (Integrated Group) the C-index was 0.74 (95%CI, 0.70–0.79), with statistically significant differences compared with each isolated group (from p=0.006 to p<0.001). Variables with the greatest prognostic discrimination are the presence of another ipsilobar nodule and tumour size >3 cm; followed by other anatomic and clinical factors; and molecular expressions of mammalian target of rapamycin (phospho-mTOR), Ki67cell proliferation index and p-Acetil-CoA-Carboxylase.
This study on early NSCLC shows the benefit from integrating pTNM, clinical and molecular factors into a composite prognostic model. The model of the Integrated Group classified patients with significantly higher accuracy compared to the TNM-2010 staging.
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