On-treatment risk model for predicting treatment response in advanced renal cell carcinoma
Melis Guer1, Andreas Janitzky2, Martin Schostak2
1Clinic of Urology, Uro-Oncology, Robot-Assisted and Focal Therapy, University Hospital Magdeburg, Magdeburg, Germany. melis.guer@med.ovgu.de.
Purpose:
The field of immunotherapy combinations for advanced renal cell carcinoma (aRCC) has been expanded in recent years. However, the treatment response varies widely among individual patients. It is still a challenge to predict oncological outcome in clinical practice. We assessed the impact of an activated immune system reflected by changes in C-reactive protein (CRP) levels and the early onset of treatment-related adverse events (TRAEs) on the treatment response.
Methods:
In this retrospective analysis of 57 aRCC patients, CRP kinetics based on previous descriptions of CRP flare-response, CRP response or CRP non-response, and the TRAEs, which occurred within a month after therapy initiation, were obtained for this study. According to logistic regression analysis of both factors, we stratified the patients into risk groups: the presence of CRP flare-response/response and early onset of TRAE (low-risk group); the presence of a single factor (intermediate-risk group); and without both factors (high-risk group).
Results:
Ten patients (17%) experienced primary disease progression. No progressive disease was observed in the low-risk group, while 60% (n = 6/10) of the high-risk group showed a primary disease progression. Significantly, an increased risk of disease progression was observed by patients without CRP response and TRAEs (p < 0.001).
Conclusion:
The present analysis displays the predictive value of the on-treatment risk model based on CRP kinetics and the early onset of TRAEs, which can be easy to implement in clinical practice to optimize the treatment monitoring.
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