COST-EFFECTIVENESS OF TREATMENT IN RENAL CELL CARCINOMA ADJUSTED TO THE CLASSIFICATION MODELS

Introduction: The emergence of new drugs, their combinations and different treatment schemes, make determining the effectiveness of current treatments in clinical practice necessary and highlights the need for an evaluation of its economic impact on the health system. A retrospective study was conducted to evaluate the cost-effectiveness of first line treatment adjusted to the main classification models. Materials and methods: The primary end points were: median overall survival (mOS) and median progression-free survival (mPFS) times. The evaluation of cost-effectiveness throughout treatment was assessed by calculating the incremental cost-effectiveness ratio (ICER) based on the cost per year of life gained (YLG). Results: The study included 88 patients, grouped according to the drug used for first-line treatment. An increase of 4.9 (p = 0.000) in mPFS and 12.6 months (p = 0.000) for mOS was found among patients treated with sunitinib compared with those treated with temsirolimus. By adjusting the mPFS treatments according to the main classification models, we observe that a statistically significant difference remains between the treatments in both the Memorial Sloan-Kettering Cancer Center (MSKCC) and Hudes model. This was not found in the Heng model, in which there is a slight statistically insignificant difference in favor of temsirolimus. No differences were found in the mOS in any case. In the poor prognosis group, which is the prognostic criteria required for the use of temsirolimus, the incremental cost of sunitinib per month free of progression would be of 3,098.2(sic). Conclusions: Based on these results it appears that the use of temsirolimus as the most effective option for patients with a poor prognosis, as defined by the criteria in the pivotal trial of temsirolimus or the MSKCC model, may be questionable. However, a larger population would be needed in both groups to determine the relevance of these results.