Despite the importance of metastatic clear-cell renal cell carcinoma, studies on its economic burden in daily practice are sparse. The mean cost of illness of 224 French patients who started their first-line treatment with a targeted therapy was estimated at V71,185 ± 52,683. Five explanatory factors were identified, among them time of disease control for the metastatic first-line treatment ≥6 months.
Background: Targeted therapies have transformed the treatment of metastatic clear-cell renal cell carcinoma (mccRCC). Despite the importance of mccRCC, studies on its economic burden in daily practice are sparse. The purpose of this retrospective study was to evaluate cost of illness for 224 patients with mccRCC included in the cohort published by Thiery-Vuillemin et al (Factors influencing overall survival for patients with metastatic clear-cell renal cellcarcinoma in daily practice. Clin Genitourin Cancer 2018; 16:e297-305), and then to determine the explanatory factors of cost of illness.
Patients and Methods: The study was performed from the French Public Healthcare System perspective with lifetime horizon. Only direct medical costs were included. Multiple linear regression was used to search for explanatory factors of cost of illness. The robustness of results was assessed.
Results: The mean cost of illness was estimated at V71,185 _ 52,683. Outpatient/inpatient treatment and hospitalization represented 76.0% and 19.7% of this cost, respectively. After adjustment, 5 explanatory factors were identified: time of disease control for the metastatic first-line treatment _6 months, number of lines of treatment >2, nephrectomy at metastatic stage, lack of metastases at presentation, and age at metastatic diagnosis younger than 65 years. Individually, they increased cost of illness by 128%, 95%, 53%, 53%, and 23%, respectively.
Conclusion: Although it is difficult to transpose our economic evaluation results to those obtained in other countries, it should be noted that our findings were consistent with them and robust. To our knowledge, our study was the first to accurately identify explanatory factors of cost of illness. Identifying them could enable us to predict the budgetary effect on a regional level of managing patients who began their first-line treatment with a targeted therapy.