A risk model for non-small cell lung cancer using clinicopathological variables, angiogenesis and oncoprotein expression.

Abstract

BACKGROUND: The aim of this study was to investigate new prognostic factors, by using a prognostic model, that could help to identify the patient group with the greatest probability of death. PATIENTS AND METHODS: First, the clinicopathological variables were analyzed. Second, microvessels were immunohistochemically (IHC) stained with factor VIII-related antibody and then counted in the most intense vascularization area or hotspot, using an automatic image analyzer. In addition, biological angiogenesis-related factors such as vascular endothelial growth factor (VEGF) and inducible nitric oxide synthase expression (iNOS) were also studied. Finally, we evaluated the IHC expression of p53 and p21WAF1 tumor supressor proteins. RESULTS: The significant independent predictors were: tumor size (p=0.0063), angiogenesis (p=0.0271) and p21WAF1 (p=0.0478). Thus, the most important factor was tumor size 2.7462 [95% CI=1.3307-5.6673]. Finally, these variables were included in a risk model, in order to identify the group with the highest associated probability of death. CONCLUSION: The analysis of several prognostic factors could establish a more accurate patient risk profile.