TY - JOUR
T1 - Predicting Disease Recurrence, Early Progression, and Overall Survival Following Surgical Resection for High-risk Localized and Locally Advanced Renal Cell Carcinoma
AU - Correa, Andres F.
AU - Jegede, Opeyemi A.
AU - Haas, Naomi B.
AU - Flaherty, Keith T.
AU - Pins, Michael R.
AU - Adeniran, Adebowale
AU - Messing, Edward M.
AU - Manola, Judith
AU - Wood, Christopher G.
AU - Kane, Christopher J.
AU - Jewett, Michael A.S.
AU - Dutcher, Janice P.
AU - DiPaola, Robert S.
AU - Carducci, Michael A.
AU - Uzzo, Robert G.
N1 - Publisher Copyright:
© 2021 European Association of Urology
PY - 2021/7
Y1 - 2021/7
N2 - Background: Risk stratification for localized renal cell carcinoma (RCC) relies heavily on retrospective models, limiting their generalizability to contemporary cohorts. Objective: To introduce a contemporary RCC prognostic model, developed using prospective, highly annotated data from a phase III adjuvant trial. Design, setting, and participants: The model utilizes outcome data from the ECOG-ACRIN 2805 (ASSURE) RCC trial. Outcome measurements and statistical analysis: 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. Results and limitations: 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]). Conclusions: 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. Patient summary: 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.
AB - Background: Risk stratification for localized renal cell carcinoma (RCC) relies heavily on retrospective models, limiting their generalizability to contemporary cohorts. Objective: To introduce a contemporary RCC prognostic model, developed using prospective, highly annotated data from a phase III adjuvant trial. Design, setting, and participants: The model utilizes outcome data from the ECOG-ACRIN 2805 (ASSURE) RCC trial. Outcome measurements and statistical analysis: 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. Results and limitations: 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]). Conclusions: 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. Patient summary: 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.
KW - ASSURE trial
KW - Disease-free survival
KW - Prognostic model
KW - Renal cell carcinoma
UR - http://www.scopus.com/inward/record.url?scp=85102248582&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85102248582&partnerID=8YFLogxK
U2 - 10.1016/j.eururo.2021.02.025
DO - 10.1016/j.eururo.2021.02.025
M3 - Article
C2 - 33707112
AN - SCOPUS:85102248582
SN - 0302-2838
VL - 80
SP - 20
EP - 31
JO - European Urology
JF - European Urology
IS - 1
ER -