PURPOSE: Fuhrman grade represents a key determinant of the natural history of small renal masses that represent renal cell carcinoma. We tested whether renal mass biopsy prediction of Fuhrman grade in the nephrectomy specimen could be safely substituted for by an accurate statistical model. To date the best available model has shown poor accuracy (55.6%), which is close to flipping a coin (50%) and clearly inadequate for use in clinical practice.MATERIALS AND METHODS: We identified 1,139 patients with T1aN0M0 renal cell carcinoma treated with partial or radical nephrectomy at 11 participating institutions from 1989 to 2004. This cohort was used in univariate and multivariate logistic regression models predicting high Fuhrman grade (III-IV) at nephrectomy. Predictors included age at diagnosis, gender, tumor size and symptom classification. Multivariate logistic regression coefficients were used to generate a nomogram.RESULTS: The rate of Fuhrman grade III-IV in patients with T1aN0M0 renal cell carcinoma was 12.3%. Stratifying patients with Fuhrman grade III-IV by age, gender, histological subtypes and sample size failed to reveal statistically significant differences. On univariate analysis predicting Fuhrman grade III-IV at nephrectomy only tumor size was a statistically significant predictor (p = 0.05). The most accurate multivariate nomogram for Fuhrman grade III-IV prediction was 58.3% (95% CI 57.8-58.9) accurate. Of all tested predictors only tumor size achieved independent predictor status (p = 0.009).CONCLUSIONS: Our analysis derived in European patients shows that statistical models cannot safely replace renal mass biopsy based prediction of Fuhrman grade III-IV at nephrectomy. Our findings corroborate a report from the United States in which a similar model had 55.6% accuracy. Jointly the studies indicate that statistical models are unreliable and cannot safely be substituted for renal mass biopsy in North American or European patients.

Can renal mass biopsy assessment of tumor grade be safely substituted for by a predictive model?

ARTIBANI, Walter;
2009-01-01

Abstract

PURPOSE: Fuhrman grade represents a key determinant of the natural history of small renal masses that represent renal cell carcinoma. We tested whether renal mass biopsy prediction of Fuhrman grade in the nephrectomy specimen could be safely substituted for by an accurate statistical model. To date the best available model has shown poor accuracy (55.6%), which is close to flipping a coin (50%) and clearly inadequate for use in clinical practice.MATERIALS AND METHODS: We identified 1,139 patients with T1aN0M0 renal cell carcinoma treated with partial or radical nephrectomy at 11 participating institutions from 1989 to 2004. This cohort was used in univariate and multivariate logistic regression models predicting high Fuhrman grade (III-IV) at nephrectomy. Predictors included age at diagnosis, gender, tumor size and symptom classification. Multivariate logistic regression coefficients were used to generate a nomogram.RESULTS: The rate of Fuhrman grade III-IV in patients with T1aN0M0 renal cell carcinoma was 12.3%. Stratifying patients with Fuhrman grade III-IV by age, gender, histological subtypes and sample size failed to reveal statistically significant differences. On univariate analysis predicting Fuhrman grade III-IV at nephrectomy only tumor size was a statistically significant predictor (p = 0.05). The most accurate multivariate nomogram for Fuhrman grade III-IV prediction was 58.3% (95% CI 57.8-58.9) accurate. Of all tested predictors only tumor size achieved independent predictor status (p = 0.009).CONCLUSIONS: Our analysis derived in European patients shows that statistical models cannot safely replace renal mass biopsy based prediction of Fuhrman grade III-IV at nephrectomy. Our findings corroborate a report from the United States in which a similar model had 55.6% accuracy. Jointly the studies indicate that statistical models are unreliable and cannot safely be substituted for renal mass biopsy in North American or European patients.
2009
kidney; carcinoma; renal cell; statistical; models; biopsy; Europe
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/364487
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