Primary Apoptosis as a Prognostic Index for the Classification of Metastatic Renal Cell Carcinoma

2002 ◽  
pp. 460-464 ◽  
Author(s):  
E. N. RICHTER ◽  
K. OEVERMANN ◽  
N. BUENTIG ◽  
S. ST??RKEL ◽  
I. DALLMANN ◽  
...  
2002 ◽  
Vol 168 (2) ◽  
pp. 460-464 ◽  
Author(s):  
E.N. Richter ◽  
K. Oevermann ◽  
N. Buentig ◽  
S. Störkel ◽  
I. Dallmann ◽  
...  

2019 ◽  
Vol 49 (8) ◽  
pp. 780-785
Author(s):  
Go Kaneko ◽  
Suguru Shirotake ◽  
Koshiro Nishimoto ◽  
Yasumasa Miyazaki ◽  
Keiichi Ito ◽  
...  

Abstract Background International Metastatic Renal Cell Carcinoma Database Consortium model predicts the outcomes of metastatic renal cell carcinoma stratified into favorable, intermediate, and poor risk groups (FG, IG, and PG, respectively), with approximately 50% of patients being classified as IG. We aimed to generate better risk model based on the sub-classification of IG. Methods We analyzed records of 213 consecutive patients receiving molecular targeted therapy. Age, gender, histology, type of initial molecular targeted therapy, serum laboratory data, previous nephrectomy and immunotherapy, and metastatic sites were used for IG sub-stratification. Modified and original models were compared using a concordance correlation coefficient analysis. Results Median follow-up was 17.8 months. Serum albumin, serum C-reactive protein, and bone metastases were independent predictors of overall survival (OS) in IG. IG was sub-classified into low-, middle-, and high-risk IG according to the number of predictors. The following modified model was developed: modified FG (FG & low-risk IG), modified IG (middle-risk IG), and modified PG (PG & high-risk IG). Concordance indices for original and modified models were 0.68 and 0.73, respectively (P < 0.001). OS was significantly longer in modified PG treated with mammalian target of rapamycin inhibitors as second-line therapy than with tyrosine kinase inhibitors, whereas this was not observed in the original model. Conclusions We successfully developed modified IMDC model using a two-step process: the original IMDC plus an IG sub-stratification, and demonstrated that it predicts outcomes more accurately than original model.


2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 5109-5109 ◽  
Author(s):  
P. Royston ◽  
J. Bacik ◽  
P. Elson ◽  
J. B. Manola ◽  
M. Mazumdar

5109 Background: Numerous well-designed retrospective studies of prognostic factors (pf) for survival (S) in metastatic renal cell carcinoma (mRCC) patients (pts) have been conducted since 1986. However, no single model for describing S in this population has been universally accepted. Methods: Authors of several existing prognostic indices, and others, formed the IKCWG to develop a single validated S model. The IKCWG has established a comprehensive database of previously reported clinical pf from 3748 previously untreated mRCC pts entered on institution review board approved clinical trials conducted by 11 centers in Europe and the United States from 1975–2002. Results: Median age at study entry was 58, 70% of pts were male, 89% had ECOG performance status (PS) 0 or 1; 75% had prior nephrectomy. 72%, 30%, and 19% of pts had lung, bone, and liver metastases (mets), respectively. 72% received interferon-a and/or interleukin-2 based treatments (tx); 25% were txd with chemotherapy/hormones only; 3% received other tx. 88% of pts have died; median S was 11.1 months (m). All examined factors except sex, age, and histology impacted S at p<.001 in univariable analysis. Multivariable analysis using a log-logistic model stratified by center and multivariable fractional polynomials was performed to identify independent predictors of S. Missing data were handled using multiple imputation methods. Using p=.0044 as the criterion for variable selection to avoid overly complex models, a model comprising tx, PS, number of met sites, interval from diagnosis to tx, and pre-tx hemoglobin, WBC, LDH, alkaline phosphatase and calcium was identified. The 25th and 75th percentiles of the prognostic index formed by multiplying each factor by its regression coefficient were used as cutpoints to form three risk (r) groups with median S times (SE) of: favorable r (n=937; 27.8 (0.4) m), intermediate r (n=1874; 11.4 (0.2) m), and poor r (n=937; 4.1 (0.1) m). Conclusions: 9 clinical factors can be used to model S in mRCC and form 3 distinct prognostic groups. Additional model building to determine if model complexity can be reduced further, validation in independent data and comparison to existing prognostic models are underway. No significant financial relationships to disclose.


2007 ◽  
Vol 52 (1) ◽  
pp. 163-169 ◽  
Author(s):  
Yutaka Toyoda ◽  
Nobuo Shinohara ◽  
Toru Harabayashi ◽  
Takashige Abe ◽  
Tomoshige Akino ◽  
...  

Cancers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2849
Author(s):  
Emilio Esteban ◽  
Francisco Exposito ◽  
Guillermo Crespo ◽  
Julio Lambea ◽  
Alvaro Pinto ◽  
...  

Sunitinib and pazopanib are standard first-line treatments for patients with metastatic renal cell carcinoma (mRCC). Nonetheless, as the number of treatment options increases, there is a need to identify biomarkers that can predict drug efficacy and toxicity. In this prospective study we evaluated a set of biomarkers that had been previously identified within a secretory signature in mRCC patients. This set includes tumor expression of c-Met and serum levels of HGF, IL-6, IL-8, CXCL9, CXCL10 and CXCL11. Our cohort included 60 patients with mRCC from 10 different Spanish hospitals who received sunitinib (n = 51), pazopanib (n = 4) or both (n = 5). Levels of biomarkers were studied in relation to response rate, progression-free survival (PFS) and overall survival (OS). High tumor expression of c-Met and high basal serum levels of HGF, IL-6, CXCL11 and CXCL10 were significantly associated with reduced PFS and/or OS. In multivariable Cox regression analysis, CXCL11 was identified as an independent biomarker predictive of shorter PFS and OS, and HGF was an independent predictor of reduced PFS. Correlation analyses using our cohort of patients and patients from TCGA showed that HGF levels were significantly correlated with those of IL-6, CXCL11 and CXCL10. Bioinformatic protein–protein network analysis revealed a significant interaction between these proteins, all this suggesting a coordinated expression and secretion. We also developed a prognostic index that considers this group of biomarkers, where high values in mRCC patients can predict higher risk of relapse (HR 5.28 [2.32–12.0], p < 0.0001). In conclusion, high plasma HGF, CXCL11, CXCL10 and IL-6 levels are associated with worse outcome in mRCC patients treated with sunitinib or pazopanib. Our findings also suggest that these factors may constitute a secretory cluster that acts coordinately to promote tumor growth and resistance to antiangiogenic therapy.


2007 ◽  
Vol 177 (4S) ◽  
pp. 364-364 ◽  
Author(s):  
Surena F. Matin ◽  
Christopher G. Wood ◽  
Shi-Ming Tu ◽  
Nizar M. Tannir ◽  
Eric Jonasch

2005 ◽  
Vol 173 (4S) ◽  
pp. 173-174
Author(s):  
Quinton V. Cancel ◽  
Benjamin K. Yang ◽  
Zhen Su ◽  
Jens Dannull ◽  
Philipp Dahm ◽  
...  

2006 ◽  
Vol 175 (4S) ◽  
pp. 551-552
Author(s):  
Erich K. Lang ◽  
Richard J. Macchia ◽  
Raju Thomas ◽  
Ronald Davis ◽  
Douglas Slakey ◽  
...  

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