Analysis of @entity1149 heterogeneity, proliferative and 18F-FDG PET indices reveals Ki67 prognostic role in XXXX .

@entity1 @entity419 @entity706 @entity5 @entity957 @entity1149 @entity2862 @entity420
AIMS: The @entity5 metabolic and proliferative indices in predicting @entity1149 ( @entity1149 ) @entity1 ' prognosis is unclear. We correlated @entity2862 18 @entity419 (FDG)-positron emission tomography (PET) value and Ki67 index to @entity1 ' survival, taking into account @entity5 heterogeneity, disease characteristics and genetic aberrations. METHODS AND RESULTS: A series of 383 NSCLCs was arranged into tissue microarrays and Ki67 staining was analysed by immunohistochemistry. The maximum standardized uptake (SUV(MAX) ) value detected by @entity419 -PET analysis was calculated over a region of interest. @entity957 had higher proliferative and metabolic activities than @entity420 , and the two measures were correlated significantly. The hot-spot Ki67 value was correlated with @entity1 ' survival and the cut-off to discriminate @entity1 in the survival risk groups was 20%. Ki67 hot-spot values were greater in @entity706 kinase (ALK) rearranged @entity5 . @entity420 showed the highest intratumour heterogeneity in proliferative activity and the hot-spot Ki67 value predicted only the prognosis of @entity1 in this group. Although @entity5 metabolic activity was not associated with @entity1 ' prognosis, a SUV(MAX) > 2 was related to nodal metastases, @entity5 size and grade. CONCLUSIONS: Our results highlight how @entity5 heterogeneity influences evaluation of prognostic biomarkers. Our data support Ki67 evaluation to estimate @entity1149 @entity1 ' prognosis, particularly for @entity420 .
