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Article Abstract

Objectives: Preoperative models, based on patient and tumor characteristics, predict risk for adverse outcomes after nephrectomy. Changes in renal tumor characteristics over the last decades, warrant further evaluation using contemporary cohorts. We aimed to validate a previously published preoperative nomogram predicting 12-year metastasis-free probability after nephrectomy for localized renal tumors in a contemporary cohort.

Patients And Methods: After obtaining institutional review board approval, data of 1,760 patients who underwent nephrectomy for a localized renal mass between 2005 and 2011 were reviewed. Preoperative images were evaluated for the presence of tumor necrosis, lymphadenopathy, and tumor size. The study outcome was metastatic-free probability. Model discrimination was assessed with Gönen and Heller's concordance probability estimate, and calibration was evaluated.

Results: The cohort included 1,102 male and 658 female patients with a median age of 60 years. Most patients presented incidentally (84%). On imaging, 3% had evidence of lymphadenopathy, 55% had necrosis and median tumor diameter was 3.7 cm (interquartile range [IQR]: 2.5, 5.5). Median follow-up in non-metastatic patients was 7.7 years (IQR: 5.3, 9.7). Estimated 12-year metastatic-free probability was 88% (86%-90%). The model showed strong discrimination (concordance probability estimate [CPE]: 0.77), and fair calibration. The time-dependent receiver operating characteristic (ROC) curves showed strong discrimination at all-time points and the area under the curve (AUC) for year 12 was 0.83 (95% Confidence Interval: 0.78-0.89).

Conclusions: We validated the preoperative nomogram of 12-year metastasis-free probability in a contemporary cohort despite different tumor characteristics. Future studies should evaluate the role of preoperative risk stratification in patient selection for neoadjuvant treatment.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7607679PMC
http://dx.doi.org/10.1016/j.urolonc.2020.07.019DOI Listing

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