BackgroundAtrial fibrillation is associated with higher mortality. Identification of causes of death and contemporary risk factors for all‐cause mortality may guide interventions.Methods and ResultsIn the Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET AF) study, patients with nonvalvular atrial fibrillation were randomized to rivaroxaban or dose‐adjusted warfarin. Cox proportional hazards regression with backward elimination identified factors at randomization that were independently associated with all‐cause mortality in the 14 171 participants in the intention‐to‐treat population. The median age was 73 years, and the mean CHADS 2 score was 3.5. Over 1.9 years of median follow‐up, 1214 (8.6%) patients died. Kaplan–Meier mortality rates were 4.2% at 1 year and 8.9% at 2 years. The majority of classified deaths (1081) were cardiovascular (72%), whereas only 6% were nonhemorrhagic stroke or systemic embolism. No significant difference in all‐cause mortality was observed between the rivaroxaban and warfarin arms (P=0.15). Heart failure (hazard ratio 1.51, 95% CI 1.33–1.70, P<0.0001) and age ≥75 years (hazard ratio 1.69, 95% CI 1.51–1.90, P<0.0001) were associated with higher all‐cause mortality. Multiple additional characteristics were independently associated with higher mortality, with decreasing creatinine clearance, chronic obstructive pulmonary disease, male sex, peripheral vascular disease, and diabetes being among the most strongly associated (model C‐index 0.677).ConclusionsIn a large population of patients anticoagulated for nonvalvular atrial fibrillation, ≈7 in 10 deaths were cardiovascular, whereas <1 in 10 deaths were caused by nonhemorrhagic stroke or systemic embolism. Optimal prevention and treatment of heart failure, renal impairment, chronic obstructive pulmonary disease, and diabetes may improve survival.Clinical Trial Registration URL: https://www.clinicaltrials.gov/. Unique identifier: NCT00403767.
Objective: This study aimed to provide an overview of biosimilar policies in 10 EU MSs.Methods: Ten EU MS pharmaceutical markets (Belgium, France, Germany, Greece, Hungary, Italy, Poland, Spain, Sweden, and the UK) were selected. A comprehensive literature review was performed to identify supply-side and demand-side policies in place in the selected countries.Results: Supply-side policies for biosimilars commonly include price linkage, price re-evaluation, and tendering; the use of internal or external reference pricing varies between countries; health technology assessment is conducted in six countries. Regarding demand-side policies, pharmaceutical prescription budgets or quotas and monitoring of prescriptions (with potential financial incentives or penalties) are in place in eight and in seven countries respectively. Switching is generally allowed, but is solely the physician’s responsibility. Automatic substitution is not recommended, or even forbidden, in most EU MSs. Prescription conditions or guidelines that apply to biosimilars are established in nearly all surveyed EU MSs.Conclusions: Important heterogeneity in policies on biosimilars was seen between (and even within) selected countries, which may partly explain variations in biosimilar uptake. Supply-side policies targeting price have been reported to limit biosimilar penetration in the long term, despite short-term savings, while demand-side policies are considered to positively impact uptake.
Background & Objectives: Potential drivers and barriers of biosimilar uptake were mainly analysed through qualitative approaches. The study objective was to conduct a quantitative analysis and identify drivers of biosimilar uptake of all available biosimilars in the European Union (EU). Methods: A three-step process was established to identify key drivers for the uptake of biosimilars in the top 10 EU member states (MS) pharmaceutical markets (Belgium, France, Germany, Greece, Hungary, Italy, Poland, Spain, Sweden, and the UK): (1) literature review to identify incentive policies in place to enhance biosimilars adoption; (2) assessment of biosimilar market dynamics based on database analysis; (3) regression model analysis on price using the following explicative variables: incentive policies; price difference between the biosimilar and the originator product; distribution channel; generic uptake and generic price cut; pharmaceutical expenditure per capita; and market competition. Results: At the study cut-off date, 20 biosimilars were available on the market. Incentive policies applied to biosimilars were found to be heterogeneous across countries, and uptakes of biosimilars were also very heterogeneous between different therapeutic classes and countries. Results from the model demonstrated that incentive policies and the date of first biosimilar market entry were correlated to biosimilar uptake. Pharmaceutical expenditure per capita and the highest generic uptake were inversely correlated with biosimilar uptake. Average generic price discount over originator and the number of biosimilars showed a trend toward statistical significance for correlation with biosimilar uptake, but did not reach the significance threshold. Biosimilar price discount over original biologic price, the number of analogues, and the distribution channel were not correlated with the biosimilar uptake. Conclusions: Understanding drivers of biosimilar uptake becomes a critical issue to inform policy decision-makers. This study showed that incentive policies to enhance uptake remain an important driver of biosimilar penetration, while biosimilar price discounts have no impact. Future research is warranted when the biosimilar market gains maturity.
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