Literature DB >> 19836799

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

Claudio Jeldres1, Maxine Sun, Daniel Liberman, Giovanni Lughezzani, Alexandre de la Taille, Jacques Tostain, Antoine Valeri, Luca Cindolo, Vincenzo Ficarra, Walter Artibani, Richard Zigeuner, Arnaud Mejean, Jean Luc Descotes, Eric Lechevallier, Peter F Mulders, Paul Perrotte, Jean-Jacques Patard, Pierre I Karakiewicz.   

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.

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Year:  2009        PMID: 19836799     DOI: 10.1016/j.juro.2009.08.053

Source DB:  PubMed          Journal:  J Urol        ISSN: 0022-5347            Impact factor:   7.450


  16 in total

1.  Pre-treatment neutrophil-to-lymphocyte ratio predicts tumor pathology in newly diagnosed renal tumors.

Authors:  Boyd R Viers; R Houston Thompson; Christine M Lohse; John C Cheville; Bradley C Leibovich; Stephen A Boorjian; Matthew K Tollefson
Journal:  World J Urol       Date:  2016-04-06       Impact factor: 4.226

2.  External validation of the RENAL nephrometry score nomogram for predicting high-grade renal cell carcinoma in solid, enhancing, and small renal masses.

Authors:  Kyo Chul Koo; Hanna Yoo; Tae Young Shin; Jongchan Kim; Young Deuk Choi; Koon Ho Rha; Won Sik Ham
Journal:  World J Urol       Date:  2013-09-07       Impact factor: 4.226

3.  The changing face of renal-cell carcinoma.

Authors:  Gennady Bratslavsky; Ziya Kirkali
Journal:  J Endourol       Date:  2010-05       Impact factor: 2.942

4.  Anatomic features of enhancing renal masses predict malignant and high-grade pathology: a preoperative nomogram using the RENAL Nephrometry score.

Authors:  Alexander Kutikov; Marc C Smaldone; Brian L Egleston; Brandon J Manley; Daniel J Canter; Jay Simhan; Stephen A Boorjian; Rosalia Viterbo; David Y T Chen; Richard E Greenberg; Robert G Uzzo
Journal:  Eur Urol       Date:  2011-04-01       Impact factor: 20.096

Review 5.  Predictive models for the practical management of renal cell carcinoma.

Authors:  Lui Shiong Lee; Min-Han Tan
Journal:  Nat Rev Urol       Date:  2012-01-10       Impact factor: 14.432

Review 6.  Active surveillance of small renal masses.

Authors:  Marc C Smaldone; Anthony T Corcoran; Robert G Uzzo
Journal:  Nat Rev Urol       Date:  2013-04-09       Impact factor: 14.432

7.  Magnetic Resonance Imaging Radiomics Analyses for Prediction of High-Grade Histology and Necrosis in Clear Cell Renal Cell Carcinoma: Preliminary Experience.

Authors:  Durgesh K Dwivedi; Yin Xi; Payal Kapur; Ananth J Madhuranthakam; Matthew A Lewis; Durga Udayakumar; Robert Rasmussen; Qing Yuan; Aditya Bagrodia; Vitaly Margulis; Michael Fulkerson; James Brugarolas; Jeffrey A Cadeddu; Ivan Pedrosa
Journal:  Clin Genitourin Cancer       Date:  2020-05-23       Impact factor: 2.872

8.  Feasibility and Outcomes of Renal Mass Biopsy for Anatomically Complex Renal Tumors.

Authors:  Selma Masic; Marshall Strother; Laura C Kidd; Brian Egleston; Avery Braun; Abhishek Srivastava; Marc Smaldone; Barton Milestone; Rosaleen Parsons; Rosalia Viterbo; Richard Greenberg; David Chen; Alexander Kutikov; Robert Uzzo
Journal:  Urology       Date:  2021-08-08       Impact factor: 2.633

9.  Potential role of (124)I-girentuximab in the presurgical diagnosis of clear-cell renal cell cancer.

Authors:  Marc C Smaldone; David Yt Chen; Jian Q Yu; Elizabeth R Plimack
Journal:  Biologics       Date:  2012-11-19

10.  Small renal masses: surgery or surveillance.

Authors:  Eu Chang Hwang; Ho Song Yu; Dong Deuk Kwon
Journal:  Korean J Urol       Date:  2013-05-14
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