On-treatment risk model for predicting treatment response in advanced renal cell carcinoma.
Advanced renal cell carcinoma
C-Reactive protein
Checkpoint inhibitors
Predictive biomarker
Treatment-related adverse events
Journal
World journal of urology
ISSN: 1433-8726
Titre abrégé: World J Urol
Pays: Germany
ID NLM: 8307716
Informations de publication
Date de publication:
Oct 2023
Oct 2023
Historique:
received:
25
11
2022
accepted:
20
07
2023
medline:
23
10
2023
pubmed:
8
8
2023
entrez:
8
8
2023
Statut:
ppublish
Résumé
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. 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). 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). 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.
Identifiants
pubmed: 37552264
doi: 10.1007/s00345-023-04545-2
pii: 10.1007/s00345-023-04545-2
pmc: PMC10582135
doi:
Substances chimiques
C-Reactive Protein
9007-41-4
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2735-2742Informations de copyright
© 2023. The Author(s).
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