Improving IMDC criteria in patients with metastatic renal cell carcinoma through the addition of initial metastatic site in bone, brain, and liver.

2020 ◽  
Vol 38 (6_suppl) ◽  
pp. 754-754
Author(s):  
Vincenzo Di Nunno ◽  
Francesco Massari ◽  
Annalisa Guida ◽  
Carolina Alves Costa Silva ◽  
Lisa Derosa ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Metastatic Renal Cell Carcinoma ◽  
Renal Cell ◽  
Prognostic Model ◽  
Cox Regression ◽  
Risk Patients ◽  
Prognostic Stratification ◽  
Patient Prognosis ◽  
Significant Factors

754 Background: IMDC criteria are largely adopted to estimate patient prognosis. In a retrospective study we assessed that the addition of first site of metastases in brain bone and liver (bbl) metastases as variable improves prognostic stratification of patients (pts) with metastatic renal cell carcinoma (mRCC). We performed a validation study in an external cohort of patients with mRCC. Methods: All consecutive mRCC pts treated at a single institute and included in the local IGReCC database. All pts received at least one line of targeted therapy or ICIs. Primary outcome was OS from first line start. Univariate and multivariate analysis (cox regression model) were performed. Bootstrap was also carried out for validation. Results: 1073 mRCC pts were analysed (808 with known IMDC score). Of 13 initial variables considered for prognostic model, the presence of bbl as first site/s of metastases plus the 6 variables included in IMDC resulted as statistically significant factors associated with OS (table). By including this new parameter we developed a 7-variables based score (IMDC-7). Patients with 0, 1-2 and≥3 positive variable/s were considered as good, intermediate and poor risk patients respectively. 56 (22%) pts moved from good (IMDC) to intermediate (IMDC-7) and 66 (15.4%) pts moved from intermediate (IMDC) to poor (IMDC-7) group (table). Final bias corrected concordance c-index was 0.69 and 0.71 in overall cohort and in pts treated with ICI (n=241). Conclusions: The addition of bbl primary metastases to the others IMDC variables improves prognostic predictive power of the model.[Table: see text]

A proposed new model for prognostic stratification of poor-risk patients with metastatic renal cell carcinoma (mRCC) in the era of targeted therapy.

2014 ◽  
Vol 32 (15_suppl) ◽  
pp. e15588-e15588 ◽  
Author(s):  
Daniele Santini ◽  
Matteo Santoni ◽  
Ugo De Giorgi ◽  
Stefano Iacobelli ◽  
Giuseppe Procopio ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Targeted Therapy ◽  
Cell Carcinoma ◽  
Metastatic Renal Cell Carcinoma ◽  
Renal Cell ◽  
New Model ◽  
Poor Risk ◽  
Risk Patients ◽  
Prognostic Stratification

scholarly journals The VENUSS prognostic model to predict disease recurrence following surgery for non-metastatic papillary renal cell carcinoma: development and evaluation using the ASSURE prospective clinical trial cohort

BMC Medicine ◽  
2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Tobias Klatte ◽  
Kevin M. Gallagher ◽  
Luca Afferi ◽  
Alessandro Volpe ◽  
Nils Kroeger ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Prognostic Model ◽  
Disease Recurrence ◽  
Intermediate Risk ◽  
Net Benefit ◽  
Prognostic Groups ◽  
Risk Patients

Abstract Background The current World Health Organization classification recognises 12 major subtypes of renal cell carcinoma (RCC). Although these subtypes differ on molecular and clinical levels, they are generally managed as the same disease, simply because they occur in the same organ. Specifically, there is a paucity of tools to risk-stratify patients with papillary RCC (PRCC). The purpose of this study was to develop and evaluate a tool to risk-stratify patients with clinically non-metastatic PRCC following curative surgery. Methods We studied clinicopathological variables and outcomes of 556 patients, who underwent full resection of sporadic, unilateral, non-metastatic (T1–4, N0–1, M0) PRCC at five institutions. Based on multivariable Fine-Gray competing risks regression models, we developed a prognostic scoring system to predict disease recurrence. This was further evaluated in the 150 PRCC patients recruited to the ASSURE trial. We compared the discrimination, calibration and decision-curve clinical net benefit against the Tumour, Node, Metastasis (TNM) stage group, University of California Integrated Staging System (UISS) and the 2018 Leibovich prognostic groups. Results We developed the VENUSS score from significant variables on multivariable analysis, which were the presence of VEnous tumour thrombus, NUclear grade, Size, T and N Stage. We created three risk groups based on the VENUSS score, with a 5-year cumulative incidence of recurrence equalling 2.9% in low-risk, 15.4% in intermediate-risk and 54.5% in high-risk patients. 91.7% of low-risk patients had oligometastatic recurrent disease, compared to 16.7% of intermediate-risk and 40.0% of high-risk patients. Discrimination, calibration and clinical net benefit from VENUSS appeared to be superior to UISS, TNM and Leibovich prognostic groups. Conclusions We developed and tested a prognostic model for patients with clinically non-metastatic PRCC, which is based on routine pathological variables. This model may be superior to standard models and could be used for tailoring postoperative surveillance and defining inclusion for prospective adjuvant clinical trials.

Can Systemic Immune-Inflammation Index Create a New Perspective for the IMDC Scoring System in Patients with Metastatic Renal Cell Carcinoma?

2021 ◽  
pp. 1-8
Author(s):  
Fatma Bugdayci Basal ◽  
Cengiz Karacin ◽  
Irem Bilgetekin ◽  
Omur Berna Oksuzoglu
Keyword(s):  
Renal Cell Carcinoma ◽  
Prognostic Factor ◽  
Regression Model ◽  
Cell Carcinoma ◽  
Metastatic Renal Cell Carcinoma ◽  
Renal Cell ◽  
Cox Regression ◽  
Independent Prognostic Factor ◽  
Cox Regression Model ◽  
Kaplan Meier

Introduction: The aim of the study was to evaluate impact of the systemic immune-inflammation index (SII) on prognosis and survival within the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) score groups. Methods: The records of 187 patients with metastatic renal cell carcinoma (RCC) were reviewed retrospectively. The SII was calculated as follows: SII = Neutrophil × Platelet/Lymphocyte. The patients were categorized into 2 groups based on a median SII of 730 (×109 per 1 L) as SII low (<730) and SII high (≥730). The Kaplan-Meier method was used for survival analysis and a Cox regression model was utilized to determine independent predictors of survival. Results: The median age was 61 years (range: 34–86 years). Kaplan-Meier tests revealed significant differences in survival between the SII-low and SII-high levels (27.0 vs. 12.0 months, respectively, p < 0.001). The Cox regression model revealed that SII was an independent prognostic factor. The implementation of the log-rank test in the IMDC groups according to the SII level provided the distinction of survival in the favorable group (SII low 49.0 months vs. SII high 11.0 months, p < 0.001), in the intermediate group (SII low 26.0 vs. SII high 15.0 months, p = 0.007), and in the poor group (SII low 19.0 vs. SII high 6.0 months, p = 0.019). Conclusion: The SII was an independent prognostic factor and provided significant differences in survival for the favorable, intermediate, and poor IMDC groups. Thus, the SII added to the IMDC score may be clinically beneficial in predicting survival.

Efficacy of systemic treatment for metastatic renal cell carcinoma (mRCC) guided by comprehensive genomic profiling (CGP).

2019 ◽  
Vol 37 (27_suppl) ◽  
pp. 63-63
Author(s):  
Paulo Gustavo Bergerot ◽  
Cristiane Decat Bergerot ◽  
Nazli Dizman ◽  
Nicholas Salgia ◽  
Joann Hsu ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Metastatic Renal Cell Carcinoma ◽  
Renal Cell ◽  
Cox Regression ◽  
Clinical Care ◽  
Genomic Profiling ◽  
Genomic Alterations ◽  
Comprehensive Genomic Profiling

63 Background: Comprehensive genomic profiling (CGP) has been used to guide treatment selection in metastatic renal cell carcinoma (mRCC). This study sought to determine if genomic alterations guided treatment and contributed to improved outcomes. Methods: From a single institution, patients (pts) diagnosed with mRCC who had CGP in the course of clinical care were identified. Pts were tested on a CLIAA-certified platform (FoundationOne; Cambridge, MA). Pts who died/initiated hospice within the 30 days after the test was performed or who were lost to follow-up were excluded. Duration of therapy (DOT) was measured as months between first and last day of therapy following CGP test. The Kaplan-Meier method was undertaken to estimate the association of CGP-directed therapy with overall survival (OS). Cox regression was also performed and adjusted for histologic subgroup. Results: A total of 64 patients underwent CGP between February 2014 and August 2018. From this group, 15 patients were excluded due to death/hospice within 30 d (n = 10) and lack of follow-up (n = 5). Median age at diagnosis was 60 years (range, 24-84), and 79% were male. Most patients (69%) were diagnosed with clear cell RCC. The median identified genomic alterations (GAs) was 3 (range, 0-7). The most common GAs were VHL (54%), PBRM1 (28%), TERT (21%), TP53 (15%), BAP1 (13%), and SETD2 (13%). Of the 49 patients included in this analysis, 47% had actionable mutations based on their CGP results. Of those, 13 patients received directed-therapy of whom 57% had stable disease, 28% had partial response, and 14% had progressive disease. The median time from CGP test to treatment was 1 month (range, 0-17). The median duration of directed-therapy was 12 months (range, 1-28) and of non-directed therapy was 4 months (range, 1-40) (P = 0.04). Directed-therapy was significantly associated with better OS (adjusted HR, 0.32 [95% CI, 0.13 to 0.82]; P = 0.018) compared to non-directed therapy. Conclusions: This study provides preliminary evidence to justify CGP-guided therapy in mRCC. Forthcoming studies should prospectively explore the use of CGP in treatment allocation for mRCC to validate these findings.

Second-line VEGF TKI after IO combination therapy: Results from the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC).

2020 ◽  
Vol 38 (6_suppl) ◽  
pp. 684-684
Author(s):  
Igor Stukalin ◽  
Shaan Dudani ◽  
Connor Wells ◽  
Chun Loo Gan ◽  
Sumanta K. Pal ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Combination Therapy ◽  
Cell Carcinoma ◽  
Metastatic Renal Cell Carcinoma ◽  
Renal Cell ◽  
Cox Regression ◽  
Response Rates ◽  
Second Line ◽  
First Line ◽  
Cox Regression Analysis

684 Background: Immuno-Oncology (IO) combinations are standard of care first-line treatment for metastatic renal cell carcinoma (mRCC). Data on therapy with vascular endothelial growth factor (VEGF) tyrosine kinase inhibitors (TKI) post-progression on IO-combination therapy are limited. Methods: Using the IMDC, a retrospective analysis was done on mRCC patients treated with second-line VEGF TKIs after receiving IO combination therapy. Patients received first-line ipilimumab+nivolumab (IOIO) or anti-PD(L)1+anti-VEGF (IOVE). Baseline variables and second-line IMDC risk factors were collected. Overall response rates (ORR), time to treatment failure (TTF) and overall survival (OS) were determined. Multivariable Cox regression analysis was performed. Results: 142 patients were included. 75 patients received IOIO and 67 received IOVE pretreatment. The ORR of 2nd line therapy was 17/46 (37%) and 7/57 (12%) in the IOIO and IOVE pretreated groups, respectively (p<0.01). 2nd-line TTF was 5.4 months (95% CI 4.1-8.3) for the IOIO- and 4.6 months (95% CI 3.7-5.8) for the IOVE-pretreated group (p=0.37). 2nd-line median OS was 17.2 months (95% CI 10.8-35.1) and 11.8 months (95% CI 9.9-21.3) for the prior IOIO and IOVE groups, respectively (p=0.13). The hazard ratio adjusted by IMDC for IOVE vs IOIO pretreatment was 1.22 (95% CI 0.73-2.07, p=0.45) for 2nd line TTF and 1.43 (95% CI 0.74-2.8, p=0.29) for 2nd line OS. Conclusions: VEGF TKIs show activity after combination IO therapy. Response rates are higher in patients treated with VEGF TKIs after first-line IOIO compared to after IOVE. In patients with VEGF TKI after IOIO or IOVE, no difference in OS and TTF was observed.[Table: see text]

Checkpoint inhibitors in metastatic renal cell carcinoma patients including elderly subgroups: Results from the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC).

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 4580-4580
Author(s):  
Steven Yip ◽  
Connor Wells ◽  
Raphael Brandao Moreira ◽  
Alex Wong ◽  
Sandy Srinivas ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Metastatic Renal Cell Carcinoma ◽  
Real World ◽  
Renal Cell ◽  
Cox Regression ◽  
Cell Cancer ◽  
Second Line ◽  
Cox Regression Analysis ◽  
Poor Risk

4580 Background: Immuno-oncology (IO) checkpoint inhibitor treatment outcomes are poorly characterized in the real world metastatic renal cell cancer (mRCC) patient population, including geriatric patients. Methods: Using the IMDC database, a retrospective analysis was performed on mRCC patients treated with IO, as listed below. Patients received one or more lines of IO therapy, with or without a targeted agent. Duration of treatment (DOT) and overall response rates (ORR) were calculated. Cox regression analysis was performed to examine the association between age as a continuous variable and DOT. Results: 312 mRCC patients treated with IO were included. In patients who were evaluable, ORR to IO therapy was 29% (32% first-, 22% second-, 33% third-, and 32% fourth-line treatment (Tx)). Patients treated with second-line IO therapy were divided into favorable, intermediate, and poor risk using IMDC criteria; the corresponding median DOT rates were not reached (NR), 8.6 mo, and 1.9 mo, respectively (p<0.0001). Based upon age, hazard ratios were calculated in the first- through fourth-line therapy setting, ranging from 1.03 to 0.97. Conclusions: The ORR to IO appears to remain consistent, regardless of line of therapy. In the second-line, IMDC criteria appear to appropriately stratify patients into favorable, intermediate, and poor risk groups for DOT. Premature OS data will be updated. In contrast to clinical trial data, longer DOT is observed in real world practice. Age may not be a factor influencing DOT. [Table: see text]

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