Selective nuclear morphometry as a prognostic factor of survival in renal cell carcinoma

In the present study, we sought to determine the predictive value of select ive nuclear morphometry (SNM) for patient outcome in renal cell carcinoma ( RCC). Tumor samples of 140 renal adenocarcinomas diagnosed and treated with radical nephrectomy and hilar lymphadenectomy between 1970 and 1988 with a minimum follow up of 5 years in all the cases were studied by SNM. The mor phometric analysis was performed in the most malignant tumor selected zone. Selection was based on cytological criteria including nuclear grade. Nucle ar morphometric features analyzed were: area, perimeter, major diameter, ma jor and minor diameter of the equivalent ellipse, volume of the equivalent ellipse and sphere, circumference diameter, and shape factors. The results showed that in the selected zone tumor nuclei were larger than in the zones selected at random. There was an inverse correlation between morphometric parameters and survival and a direct one between tumoral grade and stage. T umors of the long-term survival group of patients presented nuclei with sma ller morphometric measurements than tumors of short term survival group, wi th significant differences between them (p<0.05). In the survival analysis carried out by the Kaplan-Meier method significant differences existed betw een different groups formed from break point for: area, perimeter, major di ameter, major and minor diameter of the ellipse, volume of the ellipse and sphere, circumference diameter and perimeter shape factor. In the multivari ate analysis carried out by the Cox method, the feature with the most predi ctable value related to survival, was the tumor stage. Morphometric value w ith the highest punctuation in the test was major nuclear diameter. The res t of the morphometric values (except elliptic shape factor and elongation f actor) were also significant but they did not improve prognostic informatio n of the major nuclear diameter. SNM offers a useful aid in a more objectiv e grading of RCC. Multivariate Cox analysis revealed additional value of ka ryometry to tumor stage. SNM can be a useful tool for stratification of pat ients with RCC.