On-treatment risk model for predicting treatment response in advanced renal cell carcinoma

Melis Guer, Andreas Janitzky,Martin Schostak

World journal of urology(2023)

引用 2|浏览5
暂无评分
摘要
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.
更多
查看译文
关键词
Advanced renal cell carcinoma,C-Reactive protein,Predictive biomarker,Checkpoint inhibitors,Treatment-related adverse events
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要