What is the best treatment strategy for incidentally detected small renal masses? A decision analysis


Robert Abouassaly, MD, MSc, FRCSC, Assistant Professor, University Hospitals Case Medical Center, 11100 Euclid Avenue, LKS 5046, Cleveland, Ohio, USA, 44106. e-mail: robert.abouassaly@uhhospitals.org


Study Type – Therapy (decision analysis)

Level of Evidence 1b


• To determine the optimal treatment for incidentally detected small renal masses between radical nephrectomy, partial nephrectomy, ablative therapy (AT) and active surveillance (AS) using a decision-analytic Markov model.


• The reference case was an otherwise healthy 60-year-old patient.

• Health utilities and probabilities for postoperative complications, progression to chronic renal insufficiency (CRI), local and systemic recurrence, disease-specific and all-cause mortality were derived from published literature.

• Outcome measures included life expectancy and quality-adjusted life expectancy.

• Extensive sensitivity analyses were performed, including probabilistic sensitivity analyses.


• The mean life expectancy was 18.49 years for partial nephrectomy, 18.09 years for laparoscopic radical nephrectomy, 17.85 years for AT and 17.70 years for AS.

• External validation of our model yielded similar cancer-specific survival rates to the published literature.

• AS became preferred if age at presentation was >74 years, the probability of systemic recurrence on AS was <1.3%/year or when the hazard ratio of death with CRI was >1.63.

• AT became preferred when the probability of systemic recurrence on AT was <1.2%/year, whereas laparoscopic radical nephrectomy was preferred when the risk of CRI with this treatment was <6.6%/year.


• Based on current literature, our model emphasizes the importance of balance between disease control and preserving renal function on life expectancy, and justifies initial active intervention with partial nephrectomy in younger patients.

• Our results are consistent with recent American Urological Association guidelines for the management of this disease.

• However, data used in the model were mostly derived from retrospective data, and thus are subject to selection bias, particularly with respect to AS and AT.