Patterns and Predictors of Recurrence after Partial Nephrectomy for Kidney Tumors

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Abstract

Purpose:

We sought to identify patterns and predictors of recurrence in patients with clinically localized renal cell carcinoma managed by partial nephrectomy.

Materials and Methods:

We performed a retrospective study of 830 consecutive cases of partial nephrectomy done between 2007 and 2015 for clinically localized renal cell carcinoma at a single institution. Patient demographics and pathological characteristics were correlated with recurrence patterns (overall, local and distant) and overall survival using Kaplan-Meier and Cox regression analyses. Differences in the recurrence patterns were evaluated.

Results:

Median patient age was 61 years and median tumor size was 3.1 cm. Overall, 11.6% of tumors were stage pT3, 39.3% were high grade, 2.9% had lymphovascular invasion and 7.1% had positive margins. Higher grade, higher stage, positive surgical margins and increased R.E.N.A.L. (radius, exophytic/endophytic properties, nearness of deepest tumor portion to collecting system or sinus, anterior/posterior and location relative to polar line) score were associated with shorter disease-free survival on Kaplan-Meier analysis. On multivariable regression pT (p <0.01), grade (p <0.01) and R.E.N.A.L. score (p = 0.03) remained independent predictors of disease-free survival. Predictors of metastasis were pT stage (HR 4.5) and grade (HR 3.9, both p <0.01), while R.E.N.A.L. score (HR 3.2, p = 0.03) was the single predictor of local recurrence. Five-year disease-free and overall survival probabilities were 91% and 94%, respectively. Local recurrence manifested and developed earlier than metastasis (median 13 vs 22 months, p <0.01).

Conclusions:

High pT stage, high grade and high R.E.N.A.L. score increase the risk of disease recurrence after partial nephrectomy. The pT stage and grade are predictors of metastasis, while R.E.N.A.L. score predicts local recurrence. Because relapse features and risk factors differ between the 2 recurrence patterns, they should be studied separately in the future.

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