Health state utility data in Cystic Fibrosis: A systematic review

Introduction: Cystic fibrosis (CF) is a life-limiting, hereditable condition, with the highest prevalence in Europe. CF treatments have led to improvements in clinical symptoms, disease management and decelerated disease progression. However, little is known about the health state utility (HSU) associated with CF disease states, adverse events, and changes in disease severity. Although HSU data have contributed to existing health economic modelling studies, a lack of such data have been highlighted. This systematic review aims to provide a summary of HSU-related research in CF and highlight related research gaps. Methods: Online searches were performed in six databases and studies in any of the following categories were included: (1) estimation of HSUs in CF; (2) mapping studies between patient-reported outcome measures (PROMs) and HSUs; (3) economic evaluations on the management of CF that report primary HSU data; and (4) any CF clinical trial that reported HSU as an outcome. Results: A total of 17 studies were reviewed, of which 12 provided HSU values for specific CF populations. The remaining five articles provided HSU data that were broken down by CF relevant health states, including lung transplantations, pulmonary exacerbation (PEx) events and forced expiratory volume in 1 s (FEV 1). Conclusion: Current HSU data in CF are limited and there is considerable scope for further research, both in providing HSU values for CF and in investigating methods for HSU elicitation/evaluation in CF populations

Robotic Arthroplasty Clinical and cost Effectiveness Randomised controlled trial (RACER-knee) : a study protocol

Introduction Robotic-assisted knee replacement systems have been introduced to healthcare services worldwide in an effort to improve clinical outcomes for people, although high-quality evidence that they are clinically, or cost-effective remains sparse. Robotic-arm systems may improve surgical accuracy and could contribute to reduced pain, improved function and lower overall cost of total knee replacement (TKR) surgery. However, TKR with conventional instruments may be just as effective and may be quicker and cheaper. There is a need for a robust evaluation of this technology, including cost-effectiveness analyses using both within-trial and modelling approaches. This trial will compare robotic-assisted against conventional TKR to provide high-quality evidence on whether robotic-assisted knee replacement is beneficial to patients and cost-effective for healthcare systems. Methods and analysis The Robotic Arthroplasty Clinical and cost Effectiveness Randomised controlled trial-Knee is a multicentre, participant-assessor blinded, randomised controlled trial to evaluate the clinical and cost-effectiveness of robotic-assisted TKR compared with TKR using conventional instruments. A total of 332 participants will be randomised (1:1) to provide 90% power for a 12-point difference in the primary outcome measure; the Forgotten Joint Score at 12 months postrandomisation. Allocation concealment will be achieved using computer-based randomisation performed on the day of surgery and methods for blinding will include sham incisions for marker clusters and blinded operation notes. The primary analysis will adhere to the intention-to-treat principle. Results will be reported in line with the Consolidated Standards of Reporting Trials statement. A parallel study will collect data on the learning effects associated with robotic-arm systems. Ethics and dissemination The trial has been approved by an ethics committee for patient participation (East Midlands—Nottingham 2 Research Ethics Committee, 29 July 2020. NRES number: 20/EM/0159). All results from the study will be disseminated using peer-reviewed publications, presentations at international conferences, lay summaries and social media as appropriate. Trial registration number ISRCTN27624068

Advancing the Health Economic evidence available to inform economic models and decisions about appropriate Cystic Fibrosis care

Cystic Fibrosis (CF) is a genetic disease which impacts multiple organs in the body. As a result, CF individuals require lifelong care. Over the years, there has been an increase in the availability of treatments for CF leading to improvements in health. However, these improvements can place significant burden on the NHS. Economic evaluations capture both the costs and the benefits of treatment, which can be further extended through health economic modelling. This framework allows decision makers to make recommendations on the use of such treatments in the NHS. This thesis focuses on improving evidence availability for the health economic modelling of CF treatments and decision about appropriate care. A review of health economic modelling studies was carried out. Studies were evaluated for model structure, data inputs and modelling methods for areas requiring improvement. The evidence from the review and discussion with clinical experts was used to develop a De Novo health economic model. Regression modelling was used to generate novel health state transition and cost data from the U.K. CF Data Registry (2005-2016). An exemplar cost-utility analysis on Orkambi® was conducted to validate the De Novo model and input data. Statistical tests, between model consistency, clinical expert opinion and the observed data was used for validation. The results of the study show that the input data were comparable to data found in the literature and used in existing health economic models. The De Novo model produced comparable ICER and cost estimates to those found in the literature. The methods of the work conducted in this thesis can be applied to other Data Registries. They prove to be a strong supportive tool with great potential to improve the cost effectiveness evaluation of existing and novel treatments in the future

Integrated care rapid review

<p>Rapid review of integrated care </p

Acanthamoeba polyphaga trophozoite binding of representative fungal single cell forms

Acanthamoeba polyphaga trophozoites bind yeast cells of Candida albicans isolates within a few hours, leaving few cells in suspension or still attached to trophozoite surfaces. The nature of yeast cell recognition, mediated by an acanthamoebal trophozoite mannose binding protein is confirmed by experiments utilizing concentration dependent mannose hapten blocking. Similarly, acapsulate cells of Cryptococcus neoformans are also bound within a relatively short timescale. However, even after protracted incubation many capsulate cells of Cryptococcus remain in suspension, suggesting that the capsulate cell form of this species is not predated by acanthamoebal trophozoites. Further aspects of the association of Acanthamoeba and fungi are apparent when studying their interaction with conidia of the biocontrol agent Coniothyrium minitans. Conidia which readily bind with increasing maturity of up to 42 days, were little endocytosed and even released. Cell and conidial surface mannose as determined by FITC-lectin binding, flow cytometry with associated ligand binding analysis and hapten blocking studies demonstrates the following phenomena. Candida isolates and acapsulate Cryptococcus expose most mannose, while capsulate Cryptococcus cells exhibit least exposure commensurate with yeast cellular binding or lack of trophozoites. Conidia of Coniothyrium, albeit in a localized fashion, also manifest surface mannose exposure but as shown by Bmax values, in decreasing amounts with increasing maturity. Contrastingly such conidia experience greater trophozoite binding with maturation, thereby questioning the primacy of a trophozoite mannose-binding-protein recognition model