OBJECTIVES: Secondary hyperparathyroidism (SHPT) is a common condition in dialysis, characterized by high levels of associated laboratory parameters (LABS): parathyroid hormone (PTH), serum calcium (Ca) and phosphorous (P). Cinacalcet can be effective in controlling LABS in SHPT. Objective of this study was to develop a model to simulate the impact of cinacalcet versus standard treatment (ST) on patient mortality. METHODS: The model used the latest data on cinacalcet efficacy in lowering LABS from the OPTIMA and ADVANCE interventional trials together with the estimated relationship between LABS and mortality from the ARO observational study on 7970 haemodialysis patients treated in European Fresenius Medical Care facilities. Patient-level data from the 6-month OPTIMA and 12-month ADVANCE studies were pooled and regression models were fitted with post-treatment values as the response to derive functions predicting 12-month LABS values from their starting values, patient characteristics and treatment. After 12 months LABS were assumed constant except for PTH in ST (assumption of a 170 pg/ml per year increase). Mortality was calculated as that of the dialysis population multiplied by relative risks as function of LABS. The model was compared with a Block observational study analyzing mortality rates (26-month follow-up) in 19,186 haemodialysis patients treated at the DaVita dialysis provider in the US. The simulation was run with patient characteristics replicating the DaVita cohort and base mortality rates from the US Renal Data System. RESULTS: The simulated death rates (year 1: cinacalcet 18.4%, ST 22.6%, RR=0.81; year 2: cinacalcet 32.9%, ST 40.8%, RR=0.81) were close to the observed data in the Block study (year 1: cinacalcet 15%, ST 20%, RR=0.75; year 2: cinacalcet 30%, ST 37%, RR=0.81). CONCLUSIONS: The model showed effects of cinacalcet on mortality similar to those observed in the DaVita US cohort. This mortality model will be a useful tool for future health-economic analyses of cinacalcet in SHPT.