Ana Dubon Garcia1, Roland Devlieger2, Ken Redekop3, Katleen Vandeweyer4, Stefan Verlohren5, Liona C Poon6. 1. Roche Diagnostics Belgium NV/SA, Berkenlaan 8, 1831 Diegem, Belgium. Electronic address: ana.dubon_garcia@roche.com. 2. Department of Obstetrics and Gynaecology, University Hospitals Leuven, Herestraat 49, 3000 Leuven, Belgium. Electronic address: roland.devlieger@uzleuven.be. 3. Erasmus School of Health Policy and Management, Erasmus University Rotterdam, Burgemeester Oudlaan 50, 3062 PA Rotterdam, The Netherlands. Electronic address: redekop@eshpm.eur.nl. 4. Roche Diagnostics Belgium NV/SA, Berkenlaan 8, 1831 Diegem, Belgium. Electronic address: katleen.vandeweyer1@gmail.com. 5. Department of Obstetrics (S.V.), Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, Berlin 10117, Germany. Electronic address: stefan.verlohren@charite.de. 6. Department of Obstetrics and Gynaecology, Chinese University of Hong Kong, Sha Tin, Hong Kong. Electronic address: liona.poon@cuhk.edu.hk.
Abstract
OBJECTIVES: To assess the cost-effectiveness of the Fetal Medicine Foundation (FMF) combined first-trimester pre-eclampsia (PE) screening algorithm, coupled with low-dose aspirin treatment in high-risk patients, compared to the standard of care (SOC; screening based on maternal risk factors) for nulliparous pregnancies in Belgium. STUDY DESIGN: A decision analytic model was used to estimate the costs and outcomes for patients screened using the SOC and for those using the FMF screening algorithm, from the Belgian payers' perspective. Where possible, the probabilities and associated costs at each decision point were calculated based on published literature and public databases. MAIN OUTCOME MEASURES: Cost-effectiveness was assessed using an incremental cost-effectiveness ratio. One-way sensitivity analyses were performed to assess the impact of independent variations in each model parameter. A probabilistic sensitivity analysis was used to estimate the impact of the overall uncertainty of the model on the estimated cost-effectiveness. RESULTS: Considering an estimated 51,309 pregnancies in nulliparous women in Belgium per year, the FMF screening algorithm resulted in fewer cases of pre-term PE compared with the SOC (479 versus 816 cases) and a cost saving of €28.67 per patient. The outcome in quality-adjusted life-years was similar for both screening approaches (FMF screening algorithm 1.8521 versus SOC 1.8518). The FMF screening algorithm was cost-saving and more effective in 99.4% of simulations. CONCLUSIONS: The FMF screening algorithm coupled with early intervention using low-dose aspirin has the potential to prevent an additional 337 cases of pre-term PE per year compared with the current SOC in this population, along with a cost saving.
OBJECTIVES: To assess the cost-effectiveness of the Fetal Medicine Foundation (FMF) combined first-trimester pre-eclampsia (PE) screening algorithm, coupled with low-dose aspirin treatment in high-risk patients, compared to the standard of care (SOC; screening based on maternal risk factors) for nulliparous pregnancies in Belgium. STUDY DESIGN: A decision analytic model was used to estimate the costs and outcomes for patients screened using the SOC and for those using the FMF screening algorithm, from the Belgian payers' perspective. Where possible, the probabilities and associated costs at each decision point were calculated based on published literature and public databases. MAIN OUTCOME MEASURES: Cost-effectiveness was assessed using an incremental cost-effectiveness ratio. One-way sensitivity analyses were performed to assess the impact of independent variations in each model parameter. A probabilistic sensitivity analysis was used to estimate the impact of the overall uncertainty of the model on the estimated cost-effectiveness. RESULTS: Considering an estimated 51,309 pregnancies in nulliparous women in Belgium per year, the FMF screening algorithm resulted in fewer cases of pre-term PE compared with the SOC (479 versus 816 cases) and a cost saving of €28.67 per patient. The outcome in quality-adjusted life-years was similar for both screening approaches (FMF screening algorithm 1.8521 versus SOC 1.8518). The FMF screening algorithm was cost-saving and more effective in 99.4% of simulations. CONCLUSIONS: The FMF screening algorithm coupled with early intervention using low-dose aspirin has the potential to prevent an additional 337 cases of pre-term PE per year compared with the current SOC in this population, along with a cost saving.