Predicting Disease Recurrence, Early Progression, and Overall Survival Following Surgical Resection for High-risk Localized and Locally Advanced Renal Cell Carcinoma.

Risk stratification for localized renal cell carcinoma (RCC) relies heavily on retrospective models, limiting their generalizability to contemporary cohorts.

To introduce a contemporary RCC prognostic model, developed using prospective, highly annotated data from a phase III adjuvant trial.

The model utilizes outcome data from the ECOG-ACRIN 2805 (ASSURE) RCC trial.

The primary outcome for the model is disease-free survival (DFS), with overall survival (OS) and early disease progression (EDP) as secondary outcomes. Model performance was assessed using discrimination and calibration tests.

A total of 1735 patients were included in the analysis, with 887 DFS events occurring over a median follow-up of 9.6 yr. Five common tumor variables (histology, size, grade, tumor necrosis, and nodal involvement) were included in each model. Tumor histology was the single most powerful predictor for each model outcome. The C-statistics at 1 yr were 78.4% and 81.9% for DFS and OS, respectively. Degradation of the DFS, DFS validation set, and OS model's discriminatory ability was seen over time, with a global c-index of 68.0% (95% confidence interval or CI [65.5, 70.4]), 68.6% [65.1%, 72.2%], and 69.4% (95% CI [66.9%, 71.9%], respectively. The EDP model had a c-index of 75.1% (95% CI [71.3, 79.0]).

We introduce a contemporary RCC recurrence model built and internally validated using prospective and highly annotated data from a clinical trial. Performance characteristics of the current model exceed available prognostic models with the added benefit of being histology inclusive and TNM agnostic.

Important decisions, including treatment protocols, clinical trial eligibility, and life planning, rest on our ability to predict cancer outcomes accurately. Here, we introduce a contemporary renal cell carcinoma prognostic model leveraging high-quality data from a clinical trial. The current model predicts three outcome measures commonly utilized in clinical practice and exceeds the predictive ability of available prognostic models.

European urology. 2021 Mar 08 [Epub ahead of print]

Andres F Correa, Opeyemi A Jegede, Naomi B Haas, Keith T Flaherty, Michael R Pins, Adebowale Adeniran, Edward M Messing, Judith Manola, Christopher G Wood, Christopher J Kane, Michael A S Jewett, Janice P Dutcher, Robert S DiPaola, Michael A Carducci, Robert G Uzzo

Department of Surgical Oncology, Fox Chase Cancer Center, Philadelphia, PA, USA. Electronic address: ., ECOG-ACRIN Biostatistics Center, Dana-Farber Cancer Institute, Boston, MA, USA., Abramson Cancer Center of University of Pennsylvania, Philadelphia, PA, USA., Henri and Belinda Termeer Center for Targeted Therapy, Cancer Center, Massachusetts General Hospital, Boston, MA, USA., Advocate Lutheran General Hospital, Park Ridge, IL, USA., Yale New Haven Hospital, Yale University, New Haven, CT, USA., Department of Urology, University of Rochester, Rochester, NY, USA., M. D. Anderson Cancer Center, University of Texas, Houston, TX, USA., Moores Cancer Center, University of California-San Diego, La Jolla, CA, USA., Departments of Surgery (Urology) and Surgical Oncology, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Canada., Cancer Research Foundation, New York, NY, USA., Dean's Office, University of Kentucky College of Medicine, Lexington, KY, USA., Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins Hospital, Baltimore, MD, USA., Department of Surgical Oncology, Fox Chase Cancer Center, Philadelphia, PA, USA.

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