BACKGROUND: The mTOR inhibitor, everolimus, is approved for the treatment of metastatic renal cell carcinoma (RCC).
However, prognostic models are needed to determine the patients who would most benefit from this therapy. We have developed a model based on clinical parameters and patient stratification into risk groups to predict patients with RCC who will derive the most benefit from treatment with everolimus.
METHODS: We assessed retrospective data on 57 patients with RCC who received everolimus after previous treatment with immunotherapy or tyrosine kinase inhibitors to identify prognostic factors for progression-free survival (PFS) and overall survival (OS). In the original phase II study, patients received 10mg of everolimus daily without interruption and were assessed every other week for the first 8 weeks on therapy and every 4 weeks thereafter. Kaplan-Meier analysis was used to calculate OS and PFS. Univariate and multivariate analyses were constructed using the Cox proportional hazards model and a stepwise procedure to validate the data.
RESULTS: We grouped patients according to risk: 0 prognostic factors indicated favorable risk, 1 to 2 factors intermediate risk, and ≥3 factors poor risk. We found notable differences in median OS (29.6 mo for favorable risk, 14.3 mo for intermediate risk, and 7.2 mo for poor risk). Three risk factors (prior radiation treatment, no lung metastasis present at the start of treatment, and lymphocytes< 25cells/µl) in the multivariate analysis were found to be associated with PFS, and 4 risk factors were found to be associated with OS (bone metastasis at start of treatment, LDH>1.5×upper limit of normal, alkaline phosphatase>120U/l, and lymphocytes< 25cells/µl).
CONCLUSIONS: Our prognostic model includes 3 readily available clinical parameters for PFS and 4 readily available clinical parameters for OS to help stratify patients into poor, intermediate, and favorable prognosis groups for the treatment of everolimus in clear cell RCC. These intriguing results warrant further study in a larger patient population to validate the findings.
Written by:
Amato RJ, Flaherty A, Zhang Y, Ouyang F, Mohlere V. Are you the author?
Division of Oncology, Department of Internal Medicine, The University of Texas Health Science Center at Houston (Medical School), Memorial Hermann Cancer Center, Houston, TX.
Reference: Urol Oncol. 2013 Dec 6. pii: S1078-1439(13)00351-7.
doi: 10.1016/j.urolonc.2013.09.008
PubMed Abstract
PMID: 24321256
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