Interdisciplinary pharmacometrics linking oseltamivir pharmacology, influenza epidemiology and health economics to inform antiviral use in pandemics.

AIMS: A modular interdisciplinary platform was developed to investigate the economic impact of oseltamivir treatment by dosage regimen under simulated influenza pandemic scenarios. METHODS: The pharmacology module consisted of a pharmacokinetic distribution of oseltamivir carboxylate daily area under the concentration-time curve at steady state (simulated for 75 mg and 150 mg twice daily regimens for 5 days) and a pharmacodynamic distribution of viral shedding duration obtained from phase II influenza inoculation data. The epidemiological module comprised a susceptible, exposed, infected, recovered (SEIR) model to which drug effect on the basic reproductive number (R0 ), a measure of transmissibility, was linked by reduction of viral shedding duration. The number of infected patients per population of 100 000 susceptible individuals was simulated for a series of pandemic scenarios, varying oseltamivir dose, R0 (1.9 vs. 2.7), and drug uptake (25%, 50%, and 80%). The number of infected patients for each scenario was entered into the health economics module, a decision analytic model populated with branch probabilities, disease utility, costs of hospitalized patients developing complications, and case-fatality rates. Change in quality-adjusted life years was determined relative to base case. RESULTS: Oseltamivir 75 mg relative to no treatment reduced the median number of infected patients, increased change in quality-adjusted life years by deaths averted, and was cost-saving under all scenarios; 150 mg relative to 75 mg was not cost effective in low transmissibility scenarios but was cost saving in high transmissibility scenarios. CONCLUSION: This methodological study demonstrates proof of concept that the disciplines of pharmacology, disease epidemiology and health economics can be linked in a single quantitative framework.

Real-world evidence of improved healthcare utilization in patients with schizophrenia or schizoaffective disorder after early treatment of paliperidone palmitate once-monthly treatment in Hong Kong.

BACKGROUND: Very few data are available to demonstrate the economic benefit of early paliperidone palmitate once-monthly long-acting injectable (PP1M) treatment in patients with schizophrenia or schizoaffective disorder. METHODS AND MATERIALS: This study has retrospectively compared the healthcare utilization and associated costs of pre- and post-PPIM treatment in 413 patients with schizophrenia or schizoaffective disorder recruited from three major public hospitals providing psychiatric services in Hong Kong. Patients were categorized into early treatment (≤3 years since diagnosis) and chronic (>3 years) groups, and also whether they were receiving polypharmacy (POP). RESULTS: It was found that patients who were started on early therapy with no POP had the most favourable outcomes. Overall results of the entire cohort, including both early and late treatments, indicate that there was a slight increase in annual in-patient days (IP) per patient and outpatient visit (OP) by 3.18 and 1.87, respectively, and a decrease in emergency room visit (ER) of 0.9 (p < 0.05). For non-polypharmacy (NP) patients receiving early PP1M therapy, there was a significant decrease in IP and ER of 21.56 (p < 0.05) and 1.15 (p < 0.05), respectively, but an increase in OP of 1.88 (p < 0.05). For patients with POP, there was an all-across increase in IP and all-across decrease in OP and ER. In monetary terms, a NP patient receiving early therapy may have an overall saving of HKD40,878 (USD5,241, 1USD = 7.8HKD) per year compared to HKD6,224 (USD798) in patients where therapy was given after 3 years. For patients with POP, there was an all-across increase in overall spending despite reductions in OP and ER. CONCLUSIONS: From the 413 patients studied, potential annual savings is higher by early administration of PPIM in patients with NP. Analysis using multivariate linear regression based on generalized estimating equations and sensitivity analysis using a linear mixed model supported the findings.