Comparison of two dose prediction models for cisplatin

Area of Science:

• Pharmacokinetics and Pharmacodynamics
• Oncology
• Clinical Pharmacology

Background:

• Cisplatin chemotherapy can cause significant toxicity.
• Individualized dosing strategies are needed to optimize therapeutic efficacy and minimize adverse effects.
• Accurate monitoring of plasma drug concentrations is crucial for dose adjustment.

Purpose of the Study:

• To develop and validate a limited sampling method for personalized cisplatin dosing.
• To establish a Bayesian approach for achieving target plasma concentrations of total platinum (Pt).
• To compare the efficacy of a Bayesian model versus a creatinine-based model for cisplatin dosing.

Main Methods:

• A Bayesian limited sampling method was developed and validated using plasma Pt concentrations during continuous cisplatin infusion.
• A retrospective and prospective evaluation of the Bayesian dosing model was performed.
• A second cisplatin dosing model was developed based on the correlation between Pt clearance and creatinine clearance or the Cockcroft index.

Main Results:

• The Bayesian dosing model achieved 95.0–104.8% of the actual cisplatin dose retrospectively.
• Prospectively, the Bayesian model reached 94.9% of the target plasma Pt concentration.
• The creatinine-based model achieved 85.3% of the theoretical Pt concentration, indicating lower accuracy.

Conclusions:

• The Bayesian limited sampling method provides reliable results for clinical application in cisplatin dosing.
• Personalized cisplatin dosing based on Bayesian analysis can improve drug concentration accuracy.
• Creatinine-based cisplatin dosing models require further refinement for optimal clinical use.