PURPOSE: We determined whether a relationship exists between primary tumor size and histopathological features in cases of localized renal cancer. MATERIALS AND METHODS: SEER data were used to create a cohort of patients who were diagnosed with localized node negative renal masses from 1988 to 2004. Nuclear grade was divided into low and high grade groups. We used a multinomial logistic model to predict the probability of nuclear grade and histological subtype with increasing primary tumor size. RESULTS: SEER data showed that 19,932 patients with localized renal masses were evaluated. The overall nuclear grade distribution was 80% and 20% for low and high grade tumors, respectively. A multinomial logistic model revealed that the probability of a high grade tumor increased with size. For each 1 cm increase in size of a primary localized renal cell carcinoma the odds of high grade disease increased by 13% (OR 1.13, p <0.001). Multinomial models also predicted that the odds of papillary vs clear cell renal cell carcinoma decreased with tumor size. Conversely the odds of chromophobe vs clear cell renal cell carcinoma increased with increasing tumor size. CONCLUSIONS: Most localized node negative renal cell carcinomas are low grade. Although the probability of a high grade tumor increases with size, almost 85% of renal cell carcinomas smaller than 4 cm and 70% of localized renal cell carcinomas larger than 7 cm demonstrate low nuclear grade. The probability of detecting particular histological subtypes also varies with increasing tumor size. These data suggest that many localized renal tumors can grow large locally without acquiring metastatic potential.
PURPOSE: We determined whether a relationship exists between primary tumor size and histopathological features in cases of localized renal cancer. MATERIALS AND METHODS: SEER data were used to create a cohort of patients who were diagnosed with localized node negative renal masses from 1988 to 2004. Nuclear grade was divided into low and high grade groups. We used a multinomial logistic model to predict the probability of nuclear grade and histological subtype with increasing primary tumor size. RESULTS: SEER data showed that 19,932 patients with localized renal masses were evaluated. The overall nuclear grade distribution was 80% and 20% for low and high grade tumors, respectively. A multinomial logistic model revealed that the probability of a high grade tumor increased with size. For each 1 cm increase in size of a primary localized renal cell carcinoma the odds of high grade disease increased by 13% (OR 1.13, p <0.001). Multinomial models also predicted that the odds of papillary vs clear cell renal cell carcinoma decreased with tumor size. Conversely the odds of chromophobe vs clear cell renal cell carcinoma increased with increasing tumor size. CONCLUSIONS: Most localized node negative renal cell carcinomas are low grade. Although the probability of a high grade tumor increases with size, almost 85% of renal cell carcinomas smaller than 4 cm and 70% of localized renal cell carcinomas larger than 7 cm demonstrate low nuclear grade. The probability of detecting particular histological subtypes also varies with increasing tumor size. These data suggest that many localized renal tumors can grow large locally without acquiring metastatic potential.
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