Literature DB >> 10561319

Survival and prognostic stratification of 670 patients with advanced renal cell carcinoma.

R J Motzer1, M Mazumdar, J Bacik, W Berg, A Amsterdam, J Ferrara.   

Abstract

PURPOSE: To identify prognostic factors and a model predictive for survival in patients with metastatic renal-cell carcinoma (RCC). PATIENTS AND METHODS: The relationship between pretreatment clinical features and survival was studied in 670 patients with advanced RCC treated in 24 Memorial Sloan-Kettering Cancer Center clinical trials between 1975 and 1996. Clinical features were first examined univariately. A stepwise modeling approach based on Cox proportional hazards regression was then used to form a multivariate model. The predictive performance of the model was internally validated through a two-step nonparametric bootstrapping process.
RESULTS: The median survival time was 10 months (95% confidence interval [CI], 9 to 11 months). Fifty-seven of 670 patients remain alive, and the median follow-up time for survivors was 33 months. Pretreatment features associated with a shorter survival in the multivariate analysis were low Karnofsky performance status (<80%), high serum lactate dehydrogenase (> 1.5 times upper limit of normal), low hemoglobin (< lower limit of normal), high "corrected" serum calcium (> 10 mg/dL), and absence of prior nephrectomy. These were used as risk factors to categorize patients into three different groups. The median time to death in the 25% of patients with zero risk factors (favorable-risk) was 20 months. Fifty-three percent of the patients had one or two risk factors (intermediate-risk), and the median survival time in this group was 10 months. Patients with three or more risk factors (poor-risk), who comprised 22% of the patients, had a median survival time of 4 months.
CONCLUSIONS: Five prognostic factors for predicting survival were identified and used to categorize patients with metastatic RCC into three risk groups, for which the median survival times were separated by 6 months or more. These risk categories can be used in clinical trial design and interpretation and in patient management. The low long-term survival rate emphasizes the priority of clinical investigation to identify more effective therapy.

Entities:  

Mesh:

Substances:

Year:  1999        PMID: 10561319     DOI: 10.1200/JCO.1999.17.8.2530

Source DB:  PubMed          Journal:  J Clin Oncol        ISSN: 0732-183X            Impact factor:   44.544


  473 in total

1.  Pegylated interferon alfa-2b as treatment of patients with solid tumors.

Authors:  Ronald M Bukowski
Journal:  Curr Oncol Rep       Date:  2003-03       Impact factor: 5.075

2.  Renal cell carcinoma: the search for a reliable biomarker.

Authors:  Nicholas J Farber; Christopher J Kim; Parth K Modi; Jane D Hon; Evita T Sadimin; Eric A Singer
Journal:  Transl Cancer Res       Date:  2017-06       Impact factor: 1.241

Review 3.  Treatment of metastatic renal cell carcinoma.

Authors:  Maxine Sun; Giovanni Lughezzani; Paul Perrotte; Pierre I Karakiewicz
Journal:  Nat Rev Urol       Date:  2010-05-11       Impact factor: 14.432

4.  Pancreatic metastases from renal cell carcinoma: the state of the art.

Authors:  Roberto Ballarin; Mario Spaggiari; Nicola Cautero; Nicola De Ruvo; Roberto Montalti; Cristina Longo; Anna Pecchi; Patrizia Giacobazzi; Giuseppina De Marco; Giuseppe D'Amico; Giorgio Enrico Gerunda; Fabrizio Di Benedetto
Journal:  World J Gastroenterol       Date:  2011-11-21       Impact factor: 5.742

5.  Heat shock-peptide complex vaccine as adjuvant therapy for high-risk patients with resected renal cell carcinoma.

Authors:  Oleg Shvarts; John Lam; Robert Figlin; Arie S Belldegrun
Journal:  Curr Urol Rep       Date:  2004-02       Impact factor: 3.092

6.  The functional assessment of cancer therapy-BRM (FACT-BRM): a new tool for the assessment of quality of life in patients treated with biologic response modifiers.

Authors:  J Bacik; M Mazumdar; B A Murphy; D L Fairclough; S Eremenco; T Mariani; R J Motzer; D Cella
Journal:  Qual Life Res       Date:  2004-02       Impact factor: 4.147

7.  Sensitivity analysis to investigate the impact of a missing covariate on survival analyses using cancer registry data.

Authors:  Brian L Egleston; Yu-Ning Wong
Journal:  Stat Med       Date:  2009-05-01       Impact factor: 2.373

8.  Stratification by risk factors predicts survival on the active treatment arm in a randomized phase II study of interferon-gamma plus/minus interferon-alpha in advanced renal cell carcinoma (E6890).

Authors:  Janice P Dutcher; Jason P Fine; Robert L Krigel; Barbara A Murphy; Paul L Schaefer; Marc S Ernstoff; Patrick J Loehrer
Journal:  Med Oncol       Date:  2003       Impact factor: 3.064

9.  Eg5 inhibitor, a novel potent targeted therapy, induces cell apoptosis in renal cell carcinoma.

Authors:  Sentai Ding; Zuohui Zhao; Dingqi Sun; Fei Wu; Dongbin Bi; Jiaju Lu; Naidong Xing; Liang Sun; Haihu Wu; Kejia Ding
Journal:  Tumour Biol       Date:  2014-05-07

10.  Breast metastasis from clear cell renal cell carcinoma.

Authors:  A Botticelli; G P De Francesco; D Di Stefano
Journal:  J Ultrasound       Date:  2013-07-05
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.