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BACKGROUND: There is growing evidence to support the benefits of transcatheter aortic valve implantation (TAVI) over surgical aortic valve replacement (SAVR) in patients with symptomatic severe aortic stenosis (sSAS) who are at high- or intermediate-risk of surgical mortality. The PARTNER 3 trial showed clinical benefits with SAPIEN 3 TAVI compared with SAVR in patients at low risk of surgical mortality. Whether TAVI is also cost-effective compared with SAVR for low-risk patients in the Dutch healthcare system remains uncertain. This article presents an analysis using PARTNER 3 outcomes and costs data from the Netherlands to inform a cost-utility model and examine cost implications of TAVI over SAVR in a Dutch low-risk population. METHODS: A two-stage cost-utility analysis was performed using a published and validated health economic model based on adverse events with both TAVI and SAVR interventions from a published randomized low risk trial dataset, and a Markov model that captured lifetime healthcare costs and patient outcomes post-intervention. The model was adapted using Netherlands-specific cost data to assess the cost-effectiveness of TAVI and SAVR. Uncertainty was addressed using deterministic and probabilistic sensitivity analyses. RESULTS: TAVI generated 0.89 additional quality-adjusted life years (QALYs) at a 4742 increase in costs per patient compared with SAVR over a lifetime time horizon, representing an incremental cost-effectiveness ratio (ICER) of 5346 per QALY gained. Sensitivity analyses confirm robust results, with TAVI remaining cost-effective across several sensitivity analyses. CONCLUSIONS: Based on the model results, compared with SAVR, TAVI with SAPIEN 3 appears cost-effective for the treatment of Dutch patients with sSAS who are at low risk of surgical mortality. Qualitative data suggest broader societal benefits are likely and these findings could be used to optimize appropriate intervention selection for this patient population.
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BACKGROUND: It is unknown whether population based single assessment of cardiovascular disease (CVD) risk and feedback to individuals and general practitioners results in initiation of preventive cardiovascular pharmacotherapy in those at risk. METHODS: The population based cohort study Lifelines was linked to the IADB.nl pharmacy database to assess information on the initiation of preventive medication (N = 48,770). At the baseline visit, information on cardiovascular risk factors was collected and reported to the participants and their general practitioners. An interrupted-time-series-analysis was plotted, in which the start year of blood pressure and lipid lowering medication was displayed in years before or after the baseline visit. Subsequently, predictors of the initiation of pharmacotherapy were determined and possible reduction in cardiovascular events that could be achieved by optimal treatment of individuals at risk. RESULTS: Before the Lifelines baseline visit, 34% (out of 1,527, 95% Confidence interval (CI) 32%-36%) and 30% (out of 1,991, 95%CI 28%-32%) of the individuals at risk had a blood pressure or lipid lowering drug prescription, respectively. In those at risk, the use of blood pressure lowering medication, increased substantially during the year of the baseline visit. Treating individuals at increased risk (≥5% 10-year risk) with lipid or blood pressure lowering medication (N = 8515 and N = 6899) would have prevented 162 and 183 CVD events, respectively, in the upcoming five years. CONCLUSION: Primary prevention of CVD in the general population appears suboptimal. Feedback of cardiovascular risk factors resulted in a substantial increase of blood pressure lowering medication and extrapolated health benefits.
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There is ongoing debate on the association between eosinophil count and diseases, as previous studies were inconsistent. We studied the relationship of eosinophil count with 22 complex metabolic, cardiac, and pulmonary traits and diseases. From the population-based LifeLines Cohort Study (N = 167,729), 13,301 individuals were included. We focused on relationship of eosinophil count with three classes of metabolic (7 traits, 2 diseases), cardiac (6 traits, 2 diseases), and pulmonary (2 traits, 2 diseases) outcomes. Regression analyses were applied in overall, women and men, while adjusted for age, sex, BMI and smoking. A p-value of <0.00076 was considered statistically significant. 58.2% of population were women (mean±SD 51.3±11.1 years old). In overall, one-SD higher of ln-eosinophil count was associated with a 0.04 (±SE ±0.002;p = 6.0×10-6) SD higher levels in ln-BMI, 0.06 (±0.007;p = 3.1×10-12) SD in ln-TG, 0.04 (±0.003;p = 7.0×10-6) SD in TC, 0.04 (±0.004;p = 6.3×10-7) SD in LDL, 0.04 (±0.006;p = 6.0×10-6) SD in HbA1c; and with a 0.05 (±0.004;p = 1.7×10-8) SD lower levels in HDL, 0.05 (±0.007;p = 3.4×10-23) SD in FEV1, and 0.09 (±0.001;p = 6.6×10-28) SD in FEV1/FVC. A higher ln-eosinophil count was associated with 1.18 (95%CI 1.09-1.28;p = 2.0×10-5) odds ratio of obesity, 1.29 (1.19-1.39;p = 1.1×10-10) of metabolic syndrome, 1.40 (1.25-1.56;p = 2.7×10-9) of COPD and 1.81 (1.61-2.03;p = 1.0×10-23) of asthma. Similar results were found in women. We found no association between ln-eosinophil count either with blood pressure indices in overall, women and men; or with BMI, LDL, HbA1c and obesity in men. In a large population based cohort, we confirmed eosinophil count as a potential factor implicated in metabolic and pulmonary outcomes.