Search

Cancer care poses a significant economic burden, challenging healthcare budgets to balance patient benefits with affordability. Radiotherapy takes up only a limited part of oncology budgets, but the cost is rarely clear-cut due to influential factors such as complexity of treatments, highly-trained personnel and technologies. Health-economic appraisal is complex and can be performed in several ways, balancing costs and outcomes, but not all approaches are equally suitable for assessment of radiotherapy interventions. The concept of «value-based healthcare» offers a broader perspective to health-economic appraisal, considering various outcomes and the cost of the total cycle of care, thus addressing some of the challenges in radiotherapy: the diversity of interventions, a broad range of outcomes (including organ preservation or local control) and challenges in evidence generation. However, as the existing value-based frameworks in oncology are aimed at systemic therapies, a tailored approach for radiotherapy interventions is necessary to enhance access to innovative care and optimize resource allocation. This article explores the economic aspects of radiotherapy, providing an overview of radiotherapy cost determinants and calculations, discussing different health-economic strategies and value-based healthcare, and how these can address the specific challenges in radiotherapy.

Introduction: Cancer causes a substantial burden to our society, both from a health and an economic perspective. To improve cancer patient outcomes and lower society expenses, early diagnosis and timely treatment are essential. The recent COVID-19 crisis has disrupted the care trajectory of cancer patients, which may affect their prognosis in a potentially negative way. The purpose of this paper is to present a flexible decision-analytic Markov model methodology allowing the evaluation of the impact of delayed cancer care caused by the COVID-19 pandemic in Belgium which can be used by researchers to respond to diverse research questions in a variety of disruptive events, contexts and settings., Methods: A decision-analytic Markov model was developed for 4 selected cancer types (i.e. breast, colorectal, lung, and head and neck), comparing the estimated costs and quality-adjusted life year losses between the pre-COVID-19 situation and the COVID-19 pandemic in Belgium. Input parameters were derived from published studies (transition probabilities, utilities and indirect costs) and administrative databases (epidemiological data and direct medical costs). One-way and probabilistic sensitivity analyses are proposed to consider uncertainty in the input parameters and to assess the robustness of the model's results. Scenario analyses are suggested to evaluate methodological and structural assumptions., Discussion: The results that such decision-analytic Markov model can provide are of interest to decision makers because they help them to effectively allocate resources to improve the health outcomes of cancer patients and to reduce the costs of care for both patients and healthcare systems. Our study provides insights into methodological aspects of conducting a health economic evaluation of cancer care and COVID-19 including insights on cancer type selection, the elaboration of a Markov model, data inputs and analysis., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Khan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

We develop a compact physics model for hot-carrier degradation (HCD) that is valid over a wide range of gate and drain voltages (Vgs and Vds, respectively). Special attention is paid to the contribution of secondary carriers (generated by impact ionization) to HCD, which was shown to be significant under stress conditions with low Vgs and relatively high Vds. Implementation of this contribution is based on refined modeling of carrier transport for both primary and secondary carriers. To validate the model, we employ foundry-quality n-channel transistors and a broad range of stress voltages {Vgs,Vds}.

We study how nitridation, applied to SiON gate layers, impacts the reliability of planar metal-oxide-semiconductor field effect transistors (MOSFETs) subjected to negative and positive bias temperature instability (N/PBTI) as well as hard breakdown (HBD) characteristics of these devices. Experimental data demonstrate that p-channel transistors with SiON layers characterized by a higher nitrogen concentration have poorer NBTI reliability compared to their counterparts with a lower nitrogen content, while PBTI in n-channel devices is negligibly weak in all samples independently of the nitrogen concentration. The Weibull distribution of HBD fields extracted from experimental data in devices with a higher N density are shifted towards lower values with respect to that measured in MOSFETs, and SiON films have a lower nitrogen concentration. Based on these findings, we conclude that a higher nitrogen concentration results in the aggravation of BTI robustness and HBD characteristics.

Introduction: Timely access to radiotherapy innovations remains suboptimal, partly because there is no commonly agreed appraisal system suitable for the broad range of radiotherapy interventions. The Health Economics in Radiation Oncology (HERO) programme of ESTRO therefore engaged in building a radiotherapy-specific value-based framework. We report on a first step towards that aim, documenting the available definitions and classification systems for radiotherapy interventions., Methods: A systematic literature search was carried out in Pubmed and Embase, following PRISMA methodology and using search terms on 'innovation', 'radiotherapy', 'definition' and 'classification'. Data were extracted from articles that met prespecified inclusion criteria., Results: Out of 13,353 articles, 25 met the inclusion criteria, resulting in the identification of 7 definitions of innovation and 15 classification systems applicable to radiation oncology. Iterative appraisal divided the classification systems into two groups. A first group of 11 systems categorized innovations according to the perceived magnitude of innovation, typically 'minor' versus 'major'. The remaining 4 systems categorised innovations according to radiotherapy-specific characteristics, such as the type of radiation equipment or radiobiological properties. Here, commonly used terms as 'technique' or 'treatment' were found to be used in different meanings., Discussion: There is no widely accepted definition or classification system for radiotherapy innovations. The data however suggest that unique properties of radiotherapy interventions can be used to categorise innovations in radiation oncology. Still, there remains a need for clear terminology denoting radiotherapy-specific characteristics., Conclusion: Building on this review, the ESTRO-HERO project will define what is required for a radiotherapy-specific value-based assessment tool., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

We identify correlation between the drain currents in pristine n-channel FinFET transistors and changes in time-0 currents induced by hot-carrier stress. To achieve this goal, we employ our statistical simulation model for hot-carrier degradation (HCD), which considers the effect of random dopants (RDs) on HCD. For this analysis we generate a set of 200 device instantiations where each of them has its own unique configuration of RDs. For all "samples" in this ensemble we calculate time-0 currents (i.e. currents in undamaged FinFETs) and then degradation characteristics such as changes in the linear drain current and device lifetimes. The robust correlation analysis allows us to identify correlation between transistor lifetimes and drain currents in unstressed devices, which implies that FinFETs with initially higher currents degrade faster, i.e. have more prominent linear drain current changes and shorter lifetimes. Another important result is that although at stress conditions the distribution of drain currents becomes wider with stress time, in the operating regime drain current variability diminishes. Finally, we show that if random traps are also taken into account, all the obtained trends remain the same.