Background
Nivolumab is an immune checkpoint inhibitor (ICI) that selectively inhibits programmed cell death protein 1 activation, restoring antitumor immunity. ICIs are indicated for various types of advanced solid tumors; however, not all patients benefit from them, and tools that could be used in the clinic to predict response to treatment represent an unmet need. Here we describe the development of a new population pharmacokinetic (PPK) model in patients treated with nivolumab in clinical trials. Applying the model to a patient population with renal cell carcinoma identified nivolumab clearance and plasma concentration as predictors of overall survival (OS).
Methods
A custom liquid chromatography with tandem mass spectrometry method for quantifying nivolumab plasma concentration was developed and validated following the European Medicines Agency guidelines for bioanalytical method validation. The PPK model was developed using data from patients treated in the NIVIPIT (n=38) and NIVOREN (n=137) trials of nivolumab in metastatic melanoma and renal cell carcinoma, respectively. The PPK model was used to determine pharmacokinetic (PK) parameters such as baseline clearance and simulate individual clearance changes over time. The relationship between PK characteristics (including clearance at Cycle 1 (CLC1), plasma concentration at Cycle 3 and clinical outcomes was assessed in 137 patients treated in NIVOREN. Kaplan-Meier methodology was used in time-to-event analyses.
Results
In 137 patients, the median nivolumab CLC1 was 6 mL/hour and the median plasma concentration at Cycle 3 was 48 µg/mL. Median follow-up was 21.0 months (95% CI 20.2 to 22.5 months) with a survival rate at 6 months of 91.2% and 77.9% at 12 months. In univariate analysis, OS was significantly higher in patients with CLC1<6 mL/hour versus ≥6 mL/hour (HR 2.2 (95% CI 1.2 to 4.1), p=0.0146). Shorter OS was observed in patients with plasma concentration at Cycle 3 below the median (48 µg/mL) versus those above the median (HR 0.4 (95% CI 0.2 to 0.8), p=0.0069). Multivariate analysis showed a trend towards lower clearance, but this did not reach statistical significance (p=0.0694).
Conclusions
Results of the study may potentially be used to predict outcomes of nivolumab therapy in patients with renal cell carcinoma. Additional applications may include guiding dose adjustments of nivolumab in those who are less likely to respond to the initial dose.