Optimizing the management of patients with small renal masses in a Canadian context: A Markov decision-analysis model
Keywords:biopsy, decision analysis, kidney cancer
Introduction: The management of patients with a small renal mass (SRM) varies significantly. The objective of this study was to determine which initial management strategy resulted in the greatest quality- adjusted life months (QALM) for an index patient with a SRM.
Methods: A Markov decision analysis was used to determine the effect of 1) treating patients with a partial nephrectomy (PN); 2) active surveillance (AS); and 3) renal mass biopsy on QALM over a 10-year horizon. All relevant health states were modelled. Biopsy sensitivity and specificity were modelled assuming an 80% prevalence of cancer using procedural pathology as the gold standard. Health state utilities were obtained from the Tufts Medical Centre Cost-Effective Analysis Registry. Deterministic sensitivity analyses were used to test key assumptions.
Results: Over a 10-year time horizon for a 70-year-old male with a 2 cm SRM, the biopsy strategy resulted in 38.07 QALM, whereas treating all patients with PN resulted in 37.69 QALM and AS in 36.25 QALM. The model was most sensitive to the probability that a patient would remain alive at baseline. Biopsy was the preferred strategy when sensitivity was greater than 77%. As the underlying probability of cancer increased, the threshold of renal mass biopsy sensitivity to still favor biopsy increased.
Conclusions: Renal mass biopsy is the preferred initial management strategy for an index patient with a SRM to optimize QALM. When the probability of cancer is high, centers should aim for a sensitivity of at least 77% in order to consider a biopsy as the first strategy.
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