Literature DB >> 12441925

An outcome prediction model for patients with clear cell renal cell carcinoma treated with radical nephrectomy based on tumor stage, size, grade and necrosis: the SSIGN score.

Igor Frank1, Michael L Blute, John C Cheville, Christine M Lohse, Amy L Weaver, Horst Zincke.   

Abstract

PURPOSE: Currently outcome prediction in renal cell carcinoma is largely based on pathological stage and tumor grade. We developed an outcome prediction model for patients treated with radical nephrectomy for clear cell renal cell carcinoma, which was based on all available clinical and pathological features significantly associated with death from renal cell carcinoma.
MATERIALS AND METHODS: We identified 1,801 adult patients with unilateral clear cell renal cell carcinoma treated with radical nephrectomy between 1970 and 1998. Clinical features examined included age, sex, smoking history, and signs and symptoms at presentation. Pathological features examined included 1997 TNM stage, tumor size, nuclear grade, histological tumor necrosis, sarcomatoid component, cystic architecture, multifocality and surgical margin status. Cancer specific survival was estimated using the Kaplan-Meier method. Cox proportional hazards regression models were used to test associations between features studied and outcome. The selection of features included in the multivariate model was validated using bootstrap methodology.
RESULTS: Mean followup was 9.7 years (range 0.1 to 31). Estimated cancer specific survival rates at 1, 3, 5, 7 and 10 years were 86.6%, 74.0%, 68.7%, 63.8% and 60.0%, respectively. Several features were multivariately associated with death from clear cell renal cell carcinoma, including 1997 TNM stage (p <0.001), tumor size 5 cm. or greater (p <0.001), nuclear grade (p <0.001) and histological tumor necrosis (p <0.001).
CONCLUSIONS: In patients with clear cell renal cell carcinoma 1997 TNM stage, tumor size, nuclear grade and histological tumor necrosis were significantly associated with cancer specific survival. We present a scoring system based on these features that can be used to predict outcome.

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Mesh:

Year:  2002        PMID: 12441925     DOI: 10.1097/01.ju.0000035885.91935.d5

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


  289 in total

1.  Prediction of site-specific metastases in surgically treated nonmetastatic renal cell cancer. Changes of follow-up protocol.

Authors:  I Frank; H Zincke
Journal:  Urologe A       Date:  2004-09       Impact factor: 0.639

2.  Prognostic factors in renal cell carcinoma.

Authors:  Börje Ljungberg
Journal:  Urologe A       Date:  2004-09       Impact factor: 0.639

3.  Pathological implications of areas of lower enhancement on contrast-enhanced computed tomography in renal-cell carcinoma: additional information for selecting candidates for surveillance protocols.

Authors:  Miguel Villalobos-Gollás; Bernardo Aguilar-Davidov; Carolina Culebro-García; Martha O Gómez-Alvarado; Priscila Rojas-Garcia; Raúl Ibarra-Fombona; Norma Uribe-Uribe; Guillermo Feria-Bernal; Ricardo Castillejos-Molina; Mariano Sotomayor; Fernando Gabilondo; Francisco Rodríguez-Covarrubias
Journal:  Int Urol Nephrol       Date:  2012-05-22       Impact factor: 2.370

Review 4.  Lessons learned from the International Renal Cell Carcinoma-Venous Thrombus Consortium (IRCC-VTC).

Authors:  Juan I Martínez-Salamanca; Estefania Linares; Javier González; Roberto Bertini; Joaquín A Carballido; Thomas Chromecki; Gaetano Ciancio; Sia Daneshmand; Christopher P Evans; Paolo Gontero; Axel Haferkamp; Markus Hohenfellner; William C Huang; Theresa M Koppie; Viraj A Master; Rayan Matloob; James M McKiernan; Carrie M Mlynarczyk; Francesco Montorsi; Hao G Nguyen; Giacomo Novara; Sascha Pahernik; Juan Palou; Raj S Pruthi; Krishna Ramaswamy; Oscar Rodriguez Faba; Paul Russo; Shahrokh F Shariat; Martin Spahn; Carlo Terrone; Derya Tilki; Daniel Vergho; Eric M Wallen; Evanguelos Xylinas; Richard Zigeuner; John A Libertino
Journal:  Curr Urol Rep       Date:  2014-05       Impact factor: 3.092

5.  Use of the University of California Los Angeles Integrated Staging System (UISS) to predict survival in localized renal cell carcinoma in an Asian population.

Authors:  Chi-Fai Ng; Siu-Ho Wan; Annie Wong; Fernand M M Lai; Pun Hui; Chi-Wai Cheng
Journal:  Int Urol Nephrol       Date:  2006-12-19       Impact factor: 2.370

Review 6.  Contemporary imaging modalities for the surveillance of patients with renal cell carcinoma.

Authors:  Matthew K Tollefson; Naoki Takahashi; Bradley C Leibovich
Journal:  Curr Urol Rep       Date:  2007-01       Impact factor: 3.092

Review 7.  Adjuvant Therapy Options in Renal Cell Carcinoma: Where Do We Stand?

Authors:  Nieves Martinez Chanza; Abhishek Tripathi; Lauren C Harshman
Journal:  Curr Treat Options Oncol       Date:  2019-05-03

8.  Development and evaluation of BioScore: a biomarker panel to enhance prognostic algorithms for clear cell renal cell carcinoma.

Authors:  Alexander S Parker; Bradley C Leibovich; Christine M Lohse; Yuri Sheinin; Susan M Kuntz; Jeanette E Eckel-Passow; Michael L Blute; Eugene D Kwon
Journal:  Cancer       Date:  2009-05-15       Impact factor: 6.860

Review 9.  Renal cell carcinoma: risk assessment and prognostic factors for newly diagnosed patients.

Authors:  Tracy M Downs; Matthew Schultzel; Helen Shi; Catherine Sanders; Zunera Tahir; Georgia Robins Sadler
Journal:  Crit Rev Oncol Hematol       Date:  2008-11-06       Impact factor: 6.312

10.  Ascorbic acid-induced TET activation mitigates adverse hydroxymethylcytosine loss in renal cell carcinoma.

Authors:  Niraj Shenoy; Tushar D Bhagat; John Cheville; Christine Lohse; Sanchari Bhattacharyya; Alexander Tischer; Venkata Machha; Shanisha Gordon-Mitchell; Gaurav Choudhary; Li-Fan Wong; LouAnn Gross; Emily Ressigue; Bradley Leibovich; Stephen A Boorjian; Ulrich Steidl; Xiaosheng Wu; Kith Pradhan; Benjamin Gartrell; Beamon Agarwal; Lance Pagliaro; Masako Suzuki; John M Greally; Dinesh Rakheja; R Houston Thompson; Katalin Susztak; Thomas Witzig; Yiyu Zou; Amit Verma
Journal:  J Clin Invest       Date:  2019-03-04       Impact factor: 14.808

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