Adult lifetime cost of hemophilia B management in the US: payer and societal perspectives from a decision analytic model

Aims Hemophilia B (HB) is a rare congenital disorder characterized by bleeding-related complications which are managed by prophylactic or post-bleeding event (“on-demand”) replacement of clotting factor IX (FIX). The standard of care for severe HB is life-long prophylaxis with standard half-life (SHL) or extended half-life (EHL) products given every 2–3 or 7–14 days, respectively. FIX treatment costs in the US have been investigated, but the lifetime costs of HB treatment have not been well characterized, particularly related to the impact of joint health deterioration and associated health resource utilization. We developed a decision-analytic model to explore outcomes, costs and underlying cost drivers associated with FIX treatment options over the lifetime of an adult with severe or moderately severe HB. Materials and methods With participation from clinicians, health technology assessment specialists and patient advocates, a Markov model was constructed to estimate bleeding events and costs associated with health states including “bleed into joint”, “bleed not into joint”, “no bleed” and “death”. Sub-models of joint health were based on 0, 1, or ≥2 areas of chronic joint damage. US third-party payer and societal perspectives were considered with a lifetime horizon; sensitivity analyses tested the robustness of primary findings. Results Total adult lifetime costs per patient with severe and moderately severe HB were $21,086,607 for SHL FIX prophylaxis,$22,987,483 for EHL FIX prophylaxis, and $20,971,826 for on-demand FIX treatment. For FIX prophylaxis, the cost of FIX treatment accounts for >90% of the total HB treatment costs. Conclusions This decision analytic model demonstrated significant economic burden associated with the current HB treatment paradigm

An experimental and theoretical study of exciplex-forming compounds containing trifluorobiphenyl and 3,6-di-tert-butylcarbazole units and their performances in OLEDs

Derivatives of trifluorobiphenyl and 3,6-di-tert-butylcarbazole were synthesised as potential components of emitting layers of OLEDs. Molecular design of the compounds was performed taking into consideration the hydrogen bonding ability of the fluorine atom and electron-donating ability of the carbazole moiety. Their toluene solutions exhibited very high triplet-energy values of 3.03 eV and 3.06 eV. Ionisation energies of the compounds in the solid-state were found to be in the range from 5.98 to 6.17 eV. Density functional theory (DFT) calculations using the ωB97XD functional, with the ω parameter tuned in the presence of the solvent, uncovered singlet–triplet energy splitting in good agreement with the experimental results. The materials were tested in the emissive layers of OLEDs, showing the ability to form exciplexes with complementary electron-accepting 2,4,6-tris[3-(diphenylphosphinyl)phenyl]-1,3,5-triazine. Using the synthesised compounds as exciplex-forming materials, highly efficient exciplex emission-based OLEDs were developed. In the best case, a high maximum current efficiency of 24.8 cd A−1, and power and external quantum efficiencies of 12.2 lm W−1 and 7.8%, respectively, were achieved

Precision Health Economics and Outcomes Research to Support Precision Medicine: Big Data Meets Patient Heterogeneity on the Road to Value

The “big data” era represents an exciting opportunity to utilize powerful new sources of information to reduce clinical and health economic uncertainty on an individual patient level. In turn, health economic outcomes research (HEOR) practices will need to evolve to accommodate individual patient–level HEOR analyses. We propose the concept of “precision HEOR”, which utilizes a combination of costs and outcomes derived from big data to inform healthcare decision-making that is tailored to highly specific patient clusters or individuals. To explore this concept, we discuss the current and future roles of HEOR in health sector decision-making, big data and predictive analytics, and several key HEOR contexts in which big data and predictive analytics might transform traditional HEOR into precision HEOR. The guidance document addresses issues related to the transition from traditional to precision HEOR practices, the evaluation of patient similarity analysis and its appropriateness for precision HEOR analysis, and future challenges to precision HEOR adoption. Precision HEOR should make precision medicine more realizable by aiding and adapting healthcare resource allocation. The combined hopes for precision medicine and precision HEOR are that individual patients receive the best possible medical care while overall healthcare costs remain manageable or become more cost-efficient