Immune-Related Adverse Events Can Predict Progression-Free and Overall Survival In Patients With Metastatic Renal Cell Carcinoma Treated With Immune Checkpoint Inhibitors

Abstract

Background

Different combination therapies using anti - PD-1 / PD-L1 or CTLA-4 immune checkpoint inhibition (ICI) are widely used in patients with metastatic renal cell carcinoma (mRCC). In the absents of established biomarkers, immune-related adverse events (irAEs) have been discussed as potential predictors of response.

Methods

In this retrospective cohort study, data of 134 patients with mRCC undergoing ICI treatment (Nivolumab, Ipilimumab and Nivolumab, Pembrolizumab and Axitinib or Avelumab and Axitinib) between 2015 and 2021 were analyzed. To examine the utility of irAEs as predictors of overall survival (OS) and progression-free survival (PFS), separate Kaplan–Meier analyses and Cox proportional regression analyses were applied. Landmark analysis was conducted after 12 weeks to reduce immortal time bias.

Result

irAEs were observed in 85 patients (63.4%). Cutaneous (n = 52, 38.8%), endocrine (n = 33, 24.6%) and hepatic (n = 19, 14.2%) irAEs were most commonly observed. In Kaplan–Meier analysis, patients experiencing irAEs showed favorable median PFS (15 months, 95% CI, 9.91-20.09) compared to the non-irAE group (5 months, 95% CI, 3.56-6.44, P < .001). The median OS was 25 months (95% CI, 16.79-33.21) in the non-irAE group, while it was not reached in the irAE group (P = .002). In multivariable analysis, the presence of any irAE was associated with favorable PFS (HR 0.46 [95% CI, 0.26-0.82] P = .008) and OS (HR: 0.28 [95% CI, 0.12-0.63] P = .002), respectively. Landmark analysis after 12 weeks showed mixed results depending on the classification of the irAE group at the landmark time.

Conclusion

The presence of irAEs under ICI therapy in patients with mRCC is associated with better PFS and OS. Thus, manageable irAEs should not be cause for premature discontinuation of ICI therapy, as they seem to indicate favorable outcomes.

Considering the time-dependent nature of irAEs is crucial estimating their value as predictive markers.