Risk factors and a model to predict toxicity-related treatment discontinuation in patients with metastatic renal cell carcinoma treated with VEGF-targeted therapy: Results from the International Metastatic RCC Database Consortium.

Authors

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Marina Dusevic Kaymakcalan

Dana-Farber Cancer Institute, Boston, MA

Marina Dusevic Kaymakcalan , Wanling Xie , Laurence Albiges , Scott A. North , Christian K. Kollmannsberger , Martin Smoragiewicz , Nils Kroeger , Connor Wells , Sun Young Rha , Jae-Lyun Lee , Andre Poisl Fay , Daniel Yick Chin Heng , Toni K. Choueiri

Organizations

Dana-Farber Cancer Institute, Boston, MA, Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, Institut Gustave Roussy, University of Paris Sud, Villejuif, France, Cross Cancer Institute, Edmonton, AB, Canada, BC Cancer Agency, Vancouver Cancer Centre, Vancouver, BC, Canada, BC Cancer Agency, Vancouver, BC, Canada, Department of Urology, University Medicine Greifswald, Greifswald, Germany, Tom Baker Cancer Centre, University of Calgary, Calgary, AB, Canada, Yonsei University College of Medicine, Seoul, South Korea, Department of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea, Oncology Service and Oncology Research Unit, HSL/PUCRS, Porto Alegre, Brazil

Research Funding

No funding sources reported

Background: VEGF targeted therapy (VEGF-TT) are standard in advanced metastatic renal cell carcinoma (mRCC), however, toxicities that can lead to drug discontinuation can have a significant impact on patient (pt) outcomes. We aimed to identify risk factors for toxicity and develop the first model to predict toxicity-related treatment discontinuation (TrRD) in mRCC pts treated with VEGF-TT. Methods: Baseline characteristics and treatment outcome data were collected on 936 mRCC pts on first-line VEGF-TT from 7 IMDC institutions. TrTD was analyzed using a competing risk regression model for treatment discontinuation. Results: Median follow up was 23 months. Treatment discontinuation occurred in 833 pts (89%), of which 198 (23.8%) were related to drug toxicity. Sunitinib was the most common VEGF-TT (77%) in our series followed by sorafenib (18.4%). Median time on therapy was 7.1 months in all pts and 4.4 months for pts with TrTD. Most common toxicities leading to TrTD included fatigue, diarrhea and mucositis. On multivariate analysis, significant adverse predictors for TrTD (p<0.05) were: age (≥60 years), baseline glomerular filtration rate (GFR) <30 cc/min, number of metastatic sites (>1), and baseline sodium level (<LLN). A model was developed using the number of patient risk factors to predict the risk of TrTD (Table). Conclusions: In the largest series reported to date, age, GFR, number of metastatic sites, and baseline sodium level were found to be independent risk factors that predict toxicity-related treatment discontinuation in mRCC pts treated with VEGF-TT. Based on the number of risk factors present, we built the first model to predict treatment-related drug discontinuation. This model can be used for treatment and frequency of monitoring considerations in clinical practice.

Novel model to predict toxicity-related treatment discontinuation in mRCC patients on VEGF-TT.

Risk groupN (%)HRp value
HIGH(≥3 RF)95 (12)3.98<0.0001
INTN(2 RF)208 (25)2.35<0.0001
LOW (0/1 RF)516 (63)1.00

Risk groups were derived based on number of risk factors (RF).* The RF is 1 for age ≥60 and is 2 for age≥70.

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Abstract Details

Meeting

2015 Genitourinary Cancers Symposium

Session Type

Poster Session

Session Title

General Poster Session C: Renal Cancer

Track

Renal Cell Cancer

Sub Track

Renal Cell Cancer

Citation

J Clin Oncol 33, 2015 (suppl 7; abstr 464)

DOI

10.1200/jco.2015.33.7_suppl.464

Abstract #

464

Poster Bd #

E22

Abstract Disclosures