Cost-utility analysis of TAVI compared with surgery in patients with severe aortic stenosis at low risk of surgical mortality in the Netherlands

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.

An Erythropoietin-Independent Mechanism of Erythrocytic Precursor Proliferation Underlies Hypoxia Tolerance in Sea Nomads

The Bajau Sea Nomads were recently demonstrated to have evolved larger spleens as an adaptation to millennia of a marine foraging lifestyle. The large-spleen phenotype appears to derive from increases in thyroid hormone (TH) production as a result of reduced expression of phosphodiesterase 10A (PDE10A), though the exact mechanism remains unknown. Through pharmacological inhibition of PDE10A using the selective inhibitor MP-10 in mice, we were able to mimic the Bajau adaptation and show that treated mice had significantly larger spleens than control animals. This difference appears connected to an excess of early stage erythrocytes and an apparent increase in red blood cell (RBC) precursor proliferation in response to increased TH. However, we determined that the stimulation of RBC production in the mouse model via TH is Erythropoietin (EPO)-independent, unlike in the altitude (chronic hypoxemia) response. We confirmed this using human GWAS data; although the Bajau PDE10A variants are significantly associated with increased TH levels and RBC count, they are not associated with EPO levels, nor are other strongly thyroid-associated SNPs. We therefore suggest that an EPO-independent mechanism of stimulating RBC precursor proliferation via TH upregulation underlies the increase in spleen size observed in Sea Nomad populations.

Multi-ethnic genome-wide association study for atrial fibrillation

Atrial fibrillation (AF) affects more than 33 million individuals worldwide1 and has a complex heritability2. We conducted the largest meta-analysis of genome-wide association studies (GWAS) for AF to date, consisting of more than half a million individuals, including 65,446 with AF. In total, we identified 97 loci significantly associated with AF, including 67 that were novel in a combined-ancestry analysis, and 3 that were novel in a European-specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait locus analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate genes enriched within cardiac developmental, electrophysiological, contractile and structural pathways. These results extend our understanding of the biological pathways underlying AF and may facilitate the development of therapeutics for AF.

Clinical, biomarker, and genetic predictors of specific types of atrial fibrillation in a community-based cohort: data of the PREVEND study

Aims

Atrial fibrillation (AF) may present variously in time, and AF may progress from self-terminating to non-self-terminating AF, and is associated with impaired prognosis. However, predictors of AF types are largely unexplored. We investigate the clinical, biomarker, and genetic predictors of development of specific types of AF in a community-based cohort.

Methods

We included 8042 individuals (319 with incident AF) of the PREVEND study. Types of AF were compared, and multivariate multinomial regression analysis determined associations with specific types of AF.

Results

Mean age was 48.5 ± 12.4 years and 50% were men. The types of incident AF were ascertained based on electrocardiograms; 103(32%) were classified as AF without 2-year recurrence, 158(50%) as self-terminating AF, and 58(18%) as non-self-terminating AF. With multivariate multinomial logistic regression analysis, advancing age (P< 0.001 for all three types) was associated with all AF types, male sex was associated with AF without 2-year recurrence and self-terminating AF (P= 0.031 and P= 0.008, respectively). Increasing body mass index and MR-proANP were associated with both self-terminating (P= 0.009 and P< 0.001) and non-self-terminating AF (P= 0.003 and P< 0.001). The only predictor associated with solely self-terminating AF is prescribed anti-hypertensive treatment (P= 0.019). The following predictors were associated with non-self-terminating AF; lower heart rate (P= 0.018), lipid-lowering treatment prescribed (P= 0.009), and eGFR <60 mL/min/1.73 m2 (P= 0.006). Three known AF-genetic variants (rs6666258, rs6817105, and rs10821415) were associated with self-terminating AF.

Conclusions

We found clinical, biomarker and genetic predictors of specific types of incident AF in a community-based cohort. The genetic background seems to play a more important role than modifiable risk factors in self-terminating AF.

Genetic Obesity and the Risk of Atrial Fibrillation: Causal Estimates from Mendelian Randomization

BACKGROUND

Observational studies have identified an association between body mass index (BMI) and incident atrial fibrillation (AF). Inferring causality from observational studies, however, is subject to residual confounding, reverse causation, and bias. The primary objective of this study was to evaluate the causal association between BMI and AF by using genetic predictors of BMI.

METHODS

We identified 51 646 individuals of European ancestry without AF at baseline from 7 prospective population-based cohorts initiated between 1987 and 2002 in the United States, Iceland, and the Netherlands with incident AF ascertained between 1987 and 2012. Cohort-specific mean follow-up ranged from 7.4 to 19.2 years, over which period there was a total of 4178 cases of incident AF. We performed a Mendelian randomization with instrumental variable analysis to estimate a cohort-specific causal hazard ratio for the association between BMI and AF. Two genetic instruments for BMI were used: FTO genotype (rs1558902) and a BMI gene score comprising 39 single-nucleotide polymorphisms identified by genome-wide association studies to be associated with BMI. Cohort-specific estimates were combined by random-effects, inverse variance-weighted meta-analysis.

RESULTS

In age- and sex-adjusted meta-analysis, both genetic instruments were significantly associated with BMI (FTO: 0.43 [95% confidence interval, 0.32-0.54] kg/m² per A-allele, P<0.001; BMI gene score: 1.05 [95% confidence interval, 0.90-1.20] kg/m² per 1-U increase, P<0.001) and incident AF (FTO, hazard ratio, 1.07 [1.02-1.11] per A-allele, P=0.004; BMI gene score, hazard ratio, 1.11 [1.05-1.18] per 1-U increase, P<0.001). Age- and sex-adjusted instrumental variable estimates for the causal association between BMI and incident AF were hazard ratio, 1.15 (1.04-1.26) per kg/m², P=0.005 (FTO) and 1.11 (1.05-1.17) per kg/m², P<0.001 (BMI gene score). Both of these estimates were consistent with the meta-analyzed estimate between observed BMI and AF (age- and sex-adjusted hazard ratio 1.05 [1.04-1.06] per kg/m², P<0.001). Multivariable adjustment did not significantly change findings.

CONCLUSIONS

Our data are consistent with a causal relationship between BMI and incident AF. These data support the possibility that public health initiatives targeting primordial prevention of obesity may reduce the incidence of AF.

Cluster Individuals Based on Phenotype and Determine the Risk for Atrial Fibrillation in the PREVEND and Framingham Heart Study Populations

Background

Risk prediction of atrial fibrillation (AF) is of importance to improve the early diagnosis and treatment of AF. Latent class analysis takes into account the possible existence of classes of individuals each with shared risk factors, and maybe a better method of incorporating the phenotypic heterogeneity underlying AF.

Methods and findings

Two prospective community-based cohort studies from Netherlands and United States were used. Prevention of Renal and Vascular End-stage Disease (PREVEND) study, started in 1997, and the Framingham Heart Study (FHS) Offspring cohort started in 1971, both with 10-years follow-up. The main objective was to determine the risk of AF using a latent class analysis, and compare the discrimination and reclassification performance with traditional regression analysis. Mean age in PREVEND was 49±13 years, 49.8% were men. During follow-up, 250(3%) individuals developed AF. We built a latent class model based on 18 risk factors. A model with 7 distinct classes (ranging from 341 to 1517 individuals) gave the optimum tradeoff between a high statistical model-likelihood and a low number of model parameters. All classes had a specific profile. The incidence of AF varied; class 1 0.0%, class 2 0.3%, class 3 7.5%, class 4 0.2%, class 5 1.3%, class 6 4.2%, class 7 21.7% (p<0.001). The discrimination (C-statistic 0.830 vs. 0.842, delta-C -0.013, p = 0.22) and reclassification (IDI -0.028, p<0.001, NRI -0.090, p = 0.049, and category-less-NRI -0.049, p = 0.495) performance of both models was comparable. The results were successfully replicated in a sample of the FHS study (n = 3162; mean age 58±9 years, 46.3% men).

Conclusions

Latent class analysis to build an AF risk model is feasible. Despite the heterogeneity in number and severity of risk factors between individuals at risk for AF, latent class analysis produces distinguishable groups.

Twenty-eight genetic loci associated with ST-T-wave amplitudes of the electrocardiogram

The ST-segment and adjacent T-wave (ST-T wave) amplitudes of the electrocardiogram are quantitative characteristics of cardiac repolarization. Repolarization abnormalities have been linked to ventricular arrhythmias and sudden cardiac death. We performed the first genome-wide association meta-analysis of ST-T-wave amplitudes in up to 37 977 individuals identifying 71 robust genotype–phenotype associations clustered within 28 independent loci. Fifty-four genes were prioritized as candidates underlying the phenotypes, including genes with established roles in the cardiac repolarization phase (SCN5A/SCN10A, KCND3, KCNB1, NOS1AP and HEY2) and others with as yet undefined cardiac function. These associations may provide insights in the spatiotemporal contribution of genetic variation influencing cardiac repolarization and provide novel leads for future functional follow-up.