Literature DB >> 17868728

Prognostic factors of metastatic renal cell carcinoma after failure of immunotherapy: new paradigm from a large phase III trial with shark cartilage extract AE 941.

Bernard Escudier1, Toni K Choueiri, Stéphane Oudard, Cezary Szczylik, Sylvie Négrier, Alain Ravaud, Christine Chevreau, Peter Venner, Pierre Champagne, Daniel Croteau, Eric Dupont, Claude Hariton, Ronald M Bukowski.   

Abstract

PURPOSE: We analyzed prognostic factors, described survival and generated a prognostic model in patients with metastatic renal cell carcinoma in whom immunotherapy failed and who were potentially eligible for novel agents.
MATERIALS AND METHODS: An analysis of the relationship between clinical features and survival was performed in 300 patients with advanced renal cell carcinoma in whom immunotherapy had failed and who were subsequently treated as part of a single, phase III clinical trial with the anti-angiogenic agent Neovastat (shark cartilage extract AE 941). Clinical features were first examined univariately and a stepwise modeling approach based on Cox proportional hazard regression was then performed to generate a multivariate model.
RESULTS: Median and progression-free survival (prognostic factors) for the whole cohort was 12.6 and 2 months, respectively. Prognostic features associated with shorter survival on multivariate analysis were the number of metastatic sites (greater than 1), time from nephrectomy to metastatic disease (less than 2 years), high alkaline phosphatase, abnormal corrected serum Ca and high lactate dehydrogenase (greater than 1.5 x the upper limit of normal). Four prognostic subgroups were identified by counting the number of adverse prognostic factors. Median survival in patients with zero adverse prognostic factors was 15.6 months compared to 11.7 months in patients with 1, 8.5 months in patients with 2 and 3.5 months in patients with 3 or more.
CONCLUSIONS: We identified 4 risk groups to predict survival in previously treated patients with renal cell carcinoma. This model was based on data from what is to our knowledge the largest experience in this population. It should be used in clinical trial design, risk stratification and patient counseling.

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Year:  2007        PMID: 17868728     DOI: 10.1016/j.juro.2007.07.035

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


  20 in total

1.  Choosing phase II endpoints and designs: evaluating the possibilities.

Authors:  Michael LeBlanc; Catherine Tangen
Journal:  Clin Cancer Res       Date:  2012-03-08       Impact factor: 12.531

2.  Resampling phase III data to assess phase II trial designs and endpoints.

Authors:  Manish R Sharma; Theodore G Karrison; Yuyan Jin; Robert R Bies; Michael L Maitland; Walter M Stadler; Mark J Ratain
Journal:  Clin Cancer Res       Date:  2012-01-27       Impact factor: 12.531

3.  Comparative Study of Different Classification Models in Renal-Cell Carcinoma.

Authors:  Alejandro José Sastre-Heres; Irene Iglesias; Miguel Alaguero-Calero; Daniel Ruiz-Sánchez; Benito García-Díaz; Jaime Peña-Díaz
Journal:  Pathol Oncol Res       Date:  2018-02-17       Impact factor: 3.201

Review 4.  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

5.  Targeted therapy in renal cancer.

Authors:  Tanya B Dorff; Amir Goldkorn; David I Quinn
Journal:  Ther Adv Med Oncol       Date:  2009-11       Impact factor: 8.168

6.  Protective role of metalloproteinase inhibitor (AE-941) on ulcerative colitis in rats.

Authors:  Jing-Wei Mao; Xiao-Mei He; Hai-Ying Tang; Ying-De Wang
Journal:  World J Gastroenterol       Date:  2012-12-21       Impact factor: 5.742

7.  Lymphopenia is an independent predictor of inferior outcome in clear cell renal carcinoma.

Authors:  Sunil Saroha; Robert G Uzzo; Elizabeth R Plimack; Karen Ruth; Tahseen Al-Saleem
Journal:  J Urol       Date:  2012-10-04       Impact factor: 7.450

8.  Matrilin-1 is an inhibitor of neovascularization.

Authors:  Matthew J Foradori; Qian Chen; Cecilia A Fernandez; Jay Harper; Xin Li; Paul C W Tsang; Robert Langer; Marsha A Moses
Journal:  J Biol Chem       Date:  2014-04-01       Impact factor: 5.157

Review 9.  Targeted therapy for advanced renal cell carcinoma.

Authors:  C Coppin; L Le; F Porzsolt; T Wilt
Journal:  Cochrane Database Syst Rev       Date:  2008-04-16

10.  Thrombospondin-2 and LDH Are Putative Predictive Biomarkers for Treatment with Everolimus in Second-Line Metastatic Clear Cell Renal Cell Carcinoma (MARC-2 Study).

Authors:  Philip Zeuschner; Sebastian Hölters; Michael Stöckle; Barbara Seliger; Anja Mueller; Hagen S Bachmann; Viktor Grünwald; Daniel C Christoph; Arnulf Stenzl; Marc-Oliver Grimm; Fabian Brüning; Peter J Goebell; Marinela Augustin; Frederik Roos; Johanna Harde; Iris Benz-Rüd; Michael Staehler; Kerstin Junker
Journal:  Cancers (Basel)       Date:  2021-05-25       Impact factor: 6.639

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