Cost-Effectiveness Analysis of Apixaban Versus Edoxaban in Patients with Atrial Fibrillation for Stroke Prevention

OBJECTIVE: Our objective was to assess the cost effectiveness of apixaban versus edoxaban in the prevention of stroke and systemic embolism (SE) in patients with atrial fibrillation (AF) in Spain. METHODS: We customized a Markov model with ten health states to estimate the lifetime economic and clinical outcomes in 6-week cycles. The efficacy (clinical event rates per 100 patient-years) and safety data were derived from a pairwise indirect treatment comparison. The analysis was conducted from both the national health service (NHS) and societal perspectives, and included pharmaceutical costs (retail price plus value-added tax (VAT) and applicable national deductions) according to daily dosages (apixaban 10 mg (5 mg twice daily (bid)) and edoxaban 60 or 30 mg) and complications and disease-management costs, obtained from national databases. Utilities for quality-adjusted life-year (QALY) calculations reflected EuroQoL 5-Dimension scores in patients with AF. An annual discount rate of 3% was applied for costs (euro, year 2019 values) and outcomes. RESULTS: In a 1000-patient cohort, apixaban 5 mg bid versus edoxaban 60 mg could avoid five strokes, six major bleedings and 29 clinically relevant non-major bleedings (CRNMBs). Compared with edoxaban 30 mg, apixaban could avoid 21 strokes and two SEs. An increase in bleedings was observed with apixaban (seven haemorrhagic strokes, 48 major bleedings and 17 CRNMBs). Apixaban yielded 0.04 additional QALYs compared with edoxaban 60 mg or 30 mg. Incremental costs/QALY were euro9639.33 and euro354.22 for apixaban versus edoxaban 60 mg and edoxaban 30 mg, respectively, from the NHS perspective and euro7756.62 for apixaban versus edoxaban 60 mg from the societal perspective. Apixaban was dominant versus edoxaban 30 mg from the societal perspective. Sensitivity analyses confirmed the robustness of the model. CONCLUSIONS: This study suggests that apixaban 5 mg bid is a cost-effective alternative to edoxaban for stroke prevention in the AF population in Spain

The biological function of some human transcription factor binding motifs varies with position relative to the transcription start site

A number of previous studies have predicted transcription factor binding sites (TFBSs) by exploiting the position of genomic landmarks like the transcriptional start site (TSS). The studies’ methods are generally too computationally intensive for genome-scale investigation, so the full potential of ‘positional regulomics’ to discover TFBSs and determine their function remains unknown. Because databases often annotate the genomic landmarks in DNA sequences, the methodical exploitation of positional regulomics has become increasingly urgent. Accordingly, we examined a set of 7914 human putative promoter regions (PPRs) with a known TSS. Our methods identified 1226 eight-letter DNA words with significant positional preferences with respect to the TSS, of which only 608 of the 1226 words matched known TFBSs. Many groups of genes whose PPRs contained a common word displayed similar expression profiles and related biological functions, however. Most interestingly, our results included 78 words, each of which clustered significantly in two or three different positions relative to the TSS. Often, the gene groups corresponding to different positional clusters of the same word corresponded to diverse functions, e.g. activation or repression in different tissues. Thus, different clusters of the same word likely reflect the phenomenon of ‘positional regulation’, i.e. a word's regulatory function can vary with its position relative to a genomic landmark, a conclusion inaccessible to methods based purely on sequence. Further integrative analysis of words co-occurring in PPRs also yielded 24 different groups of genes, likely identifying cis-regulatory modules de novo. Whereas comparative genomics requires precise sequence alignments, positional regulomics exploits genomic landmarks to provide a ‘poor man's alignment’. By exploiting the phenomenon of positional regulation, it uses position to differentiate the biological functions of subsets of TFBSs sharing a common sequence motif