ABSTRACT
Background: Quantification of COVID-19 burden may be useful to support the future allocation of resources. Objective: To evaluate the public health impact of COVID-19 in French ambulatory patients with at least one risk factor for severe disease. Study design: A Markov model was used to estimate life years, costs, number of hospitalisations, number of deaths and long/prolonged COVID forms over a time horizon of 2 years. The hospitalisation probabilities were derived from an early access cohort, and the hospitalisation stay characteristics were derived from the French national hospital discharge database. Several scenario analyses were conducted. Results: The number of hospitalisations reached 256 per 1,000 patients over the acute phase (first month of simulation), and 382 per 1,000 patients over 2 years. The number of deaths was 37 per 1,000 patients, and the number of long/prolonged COVID forms reached 407 per 1,000 patients. These translated into a reduction of 0.7 days of life per patient in the first month, with an associated cost of 1,578, and a reduction of 27 days of life over the time horizon, with an associated cost of 4,280. The highest burden was observed for patients over 80 years old, and those not vaccinated. The scenarios with a less severe situation or new treatments available showed a non-negligible burden reduction. Conclusion: This study allowed us to quantify the considerable burden related to COVID-19 in infected patients, with at least one risk factor for severe form. Strategies with the ability to substantially reduce this burden in France are urgently required.
ABSTRACT
OBJECTIVE: This article describes the Personalized Reimbursement Model (PRM) program methodology, limitations, achievement and perspectives in using real-world data of cancer drugs use to improve and personalize drug pricing and reimbursement in France. MATERIALS AND METHODS: PRM platform aggregates Electronic Pharmacy Records (EPR) data from French medical centers (PRM centers) to build retrospective cohorts of patients treated with injectable cancer drugs in a hospital setting. Data extracted on January 1st, 2020, from breast cancer (BC) patients who received trastuzumab, trastuzumab emtansin or pertuzumab since January 1st, 2011, and from lung cancer (LC) patients who received bevacizumab or atezolizumab since January 1st, 2015, enabled recovering their injectable cancer drugs history from diagnosis date until December 30th, 2019, and served as dataset for assessment. RESULTS: 123 PRM centers provided data from 30,730 patients (25,660 BC and 5,070 LC patients respectively). Overall, 20,942 (82%) of BC and 4,716 (93%) of LC patients were analyzed. Completion rate was above 98% for patients characteristics, diagnostic and treatment related data. PRM centers cover 48% and 33% of BC and LC patients in-hospital therapeutic management in France, respectively. Distribution of BC and LC patients therapeutic management, by medical center category and geographic location, was similar in PRM centers to all French medical centers, ensuring the representativeness of the PRM platform. CONCLUSION: PRM Platform enabled building a national database generating on demand Real-World Evidence based on EPR. This enabled the first performance-based risk-sharing arrangements based on PRM data, between the CEPS and Roche, for atezolizumab cancer immunotherapy in metastatic non-small cell lung cancer indication.
