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Background Novel diagnostic triage and testing strategies to support early detection of cancer could improve clinical outcomes. Most apparently promising diagnostic tests ultimately fail because of inadequate performance in real-world, low prevalence populations such as primary care or general community populations. They should therefore be systematically evaluated before implementation to determine whether they lead to earlier detection, are cost-effective, and improve patient safety and quality of care, while minimising over-investigation and over-diagnosis. Methods We performed a systematic scoping review of frameworks for the evaluation of tests and diagnostic approaches. Results We identified 16 frameworks: none addressed the entire continuum from test development to impact on diagnosis and patient outcomes in the intended population, nor the way in which tests may be used for triage purposes as part of a wider diagnostic strategy. Informed by these findings, we developed a new framework, the ‘CanTest Framework’, which proposes five iterative research phases forming a clear translational pathway from new test development to health system implementation and evaluation. Conclusion This framework is suitable for testing in low prevalence populations, where tests are often applied for triage testing and incorporated into a wider diagnostic strategy. It has relevance for a wide range of stakeholders including patients, policymakers, purchasers, healthcare providers and industry.

Background The presence of circulating cell-free DNA from tumours in blood (ctDNA) is of major importance to those interested in early cancer detection, as well as to those wishing to monitor tumour progression or diagnose the presence of activating mutations to guide treatment. In 2014, the UK Early Cancer Detection Consortium undertook a systematic mapping review of the literature to identify blood-based biomarkers with potential for the development of a non-invasive blood test for cancer screening, and which identified this as a major area of interest. This review builds on the mapping review to expand the ctDNA dataset to examine the best options for the detection of multiple cancer types. Methods The original mapping review was based on comprehensive searches of the electronic databases Medline, Embase, CINAHL, the Cochrane library, and Biosis to obtain relevant literature on blood-based biomarkers for cancer detection in humans (PROSPERO no. CRD42014010827). The abstracts for each paper were reviewed to determine whether validation data were reported, and then examined in full. Publications concentrating on monitoring of disease burden or mutations were excluded. Results The search identified 94 ctDNA studies meeting the criteria for review. All but 5 studies examined one cancer type, with breast, colorectal and lung cancers representing 60% of studies. The size and design of the studies varied widely. Controls were included in 77% of publications. The largest study included 640 patients, but the median study size was 65 cases and 35 controls, and the bulk of studies (71%) included less than 100 patients. Studies either estimated cfDNA levels non-specifically or tested for cancer-specific mutations or methylation changes (the majority using PCR-based methods). Conclusion We have systematically reviewed ctDNA blood biomarkers for the early detection of cancer. Pre-analytical, analytical, and post-analytical considerations were identified which need to be addressed before such biomarkers enter clinical practice. The value of small studies with no comparison between methods, or even the inclusion of controls is highly questionable, and larger validation studies will be required before such methods can be considered for early cancer detection.

Background A Target Product Profile (TPP) outlines the necessary characteristics of an innovative product to address an unmet clinical need. TPPs could be used to better guide manufacturers in the development of ‘fit for purpose’ tests, thus increasing the likelihood that novel tests will progress from bench to bedside. However, there is currently no guidance on how to produce a TPP specifically for medical tests. Methods A systematic review was conducted to summarise the methods currently used to develop TPPs for medical tests, the sources used to inform these recommendations and the test characteristics for which targets are made. Database and website searches were conducted in November 2018. TPPs written in English for any medical test were included. Based on an existing framework, test characteristics were clustered into commonly recognised themes. Results Forty-four TPPs were identified, all of which focused on diagnostic tests for infectious diseases. Three core decision-making phases for developing TPPs were identified: scoping, drafting and consensus-building. Consultations with experts and the literature mostly informed the scoping and drafting of TPPs. All TPPs provided information on unmet clinical need and desirable analytical performance, and the majority specified clinical validity characteristics. Few TPPs described specifications for clinical utility, and none included cost-effectiveness. Conclusions We have identified a commonly used framework that could be beneficial for anyone interested in drafting a TPP for a medical test. Currently, key outcomes such as utility and cost-effectiveness are largely overlooked within TPPs though and we foresee this as an area for further improvement.

Early identification and prognostic stratification of delayed graft function following renal transplantation has significant potential to improve outcome. Mass spectrometry analysis of serum samples, before and on day 2 post transplant from five patients with delayed graft function and five with an uncomplicated transplant, identified aminoacylase-1 (ACY-1) as a potential outcome biomarker. Following assay development, analysis of longitudinal samples from an initial validation cohort of 55 patients confirmed that the ACY-1 level on day 1 or 2 was a moderate predictor of delayed graft function, similar to serum creatinine, complementing the strongest predictor cystatin C. A further validation cohort of 194 patients confirmed this association with area under ROC curves (95% CI) for day 1 serum (138 patients) of 0.74 (0.67–0.85) for ACY-1, 0.9 (0.84–0.95) for cystatin C, and 0.93 (0.88–0.97) for both combined. Significant differences in serum ACY-1 levels were apparent between delayed, slow, and immediate graft function. Analysis of long-term follow-up for 54 patients with delayed graft function showed a highly significant association between day 1 or 3 serum ACY-1 and dialysis-free survival, mainly associated with the donor–brain–dead transplant type. Thus, proteomic analysis provides novel insights into the potential clinical utility of serum ACY-1 levels immediately post transplantation, enabling subdivision of patients with delayed graft function in terms of long-term outcome. Our study requires independent confirmation.

Lack of reproducibility is an ongoing problem in some areas of the biomedical sciences. Poor experimental design and a failure to engage with experienced statisticians at key stages in the design and analysis of experiments are two factors that contribute to this problem. The RIPOSTE (Reducing IrreProducibility in labOratory STudiEs) framework has been developed to support early and regular discussions between scientists and statisticians in order to improve the design, conduct and analysis of laboratory studies and, therefore, to reduce irreproducibility. This framework is intended for use during the early stages of a research project, when specific questions or hypotheses are proposed. The essential points within the framework are explained and illustrated using three examples (a medical equipment test, a macrophage study and a gene expression study). Sound study design minimises the possibility of bias being introduced into experiments and leads to higher quality research with more reproducible results.

Target Product Profiles (TPPs) outline the characteristics that new health technologies require to address an unmet clinical need. To date, published TPPs for medical tests have focused on infectious diseases, mostly in the context of low- and middle-income countries. Recently, there have been calls for a broader use of TPPs as a mechanism to ensure that diagnostic innovation is aligned with clinical needs, yet the methodology underpinning TPP development remains suboptimal. Here, we propose that early economic evaluation (EEE) should be integrated within the TPP methodology to create a more rigorous framework for the development of “fit-for-purpose” tests. We discuss the potential benefits that EEE could bring to the core activities underpinning TPP development—scoping, drafting, consensus building, and updating—and argue that using EEE to help inform TPPs provides a more objective, evidence-based, and transparent approach to defining test specifications.

We explored the acceptability of a personalised proteomic risk intervention for patients at increased risk of type 2 diabetes and their healthcare providers, as well as their experience of participating in the delivery of proteomic-based risk feedback in UK primary care. Advances in proteomics now allow the provision of personalised proteomic risk reports, with the intention of achieving positive behaviour change. This technology has the potential to encourage behaviour change in people at risk of developing type 2 diabetes. A semi-structured interview study was carried out with patients at risk of type 2 diabetes and their healthcare providers in primary care in the North of England. Participants (n = 17) and healthcare provider (n = 4) were interviewed either face to face or via telephone. Data were analysed using thematic analysis. This qualitative study was nested within a single-arm pilot trial and undertaken in primary care. The personalised proteomic risk intervention was generally acceptable and the experience was positive. The personalised nature of the report was welcomed, especially the way it provided a holistic approach to risks of organ damage and lifestyle factors. Insights were provided as to how this may change behaviour. Some participants reported difficulties in understanding the format of the presentation of risk and expressed surprise at receiving risk estimates for conditions other than type 2 diabetes. Personalised proteomic risk interventions have the potential to provide holistic and comprehensive assessments of risk factors and lifestyle factors which may lead to positive behaviour change.

Polyester scaffolds have been used as an alternative to autogenous tissues for the reconstruction of the anterior cruciate ligament (ACL). They are biocompatible and encourage tissue infiltration, leading to neoligament formation. However, rupture can occur, caused by abrasion of the scaffold against the bone tunnels through which it is implanted. Good early tissue induction is therefore considered essential to protect the scaffold from this abrasion. Enamel matrix derivative (EMD) is used clinically in the treatment of periodontal disease. It is a complex mix of proteins with growth factor-like activity, which enhances periodontal ligament fibroblast attachment, proliferation, and differentiation, leading to the regeneration of periodontal bone and ligament tissues. We hypothesized that EMD might, in a similar manner, enhance tissue induction around scaffolds used in ACL reconstruction. This preliminary investigation adopted a translational approach, modelling in vitro 3 possible clinical modes of EMD administration, to ascertain the suitability of each protocol for application in an animal model or clinically. Preliminary investigations in monolayer culture indicated that EMD had a significant dose-dependent stimulatory effect ( p < 0.05, n = 6) on the proliferation of bovine primary synovial cells. However, pre-treating culture plates with EMD significantly inhibited cell attachment ( p < 0.01, n = 6). EMD's effects on synovial cells, seeded onto ligament scaffolds, were then investigated in several in vitro experiments modelling 3 possible modes for clinical EMD administration (pre-, intra-, and post-operative). In the pre-operative model, EMD was adsorbed onto scaffolds before the addition of cells. In the intra-operative model, EMD and cells were added simultaneously to scaffolds in the culture medium. In the post-operative model, cells were pre-seeded onto scaffolds before EMD was administered. EMD significantly inhibited cell adhesion in the pre-operative model ( p < 0.05, n = 6) and had no significant benefit in the intra-operative model. In the post-operative model, the addition of EMD to previously cell-seeded scaffolds significantly increased their total deoxyribonucleic acid content ( p < 0.01, n = 5). EMD's stimulative effect on cell proliferation in vitro suggests that it may accelerate scaffold colonization by cells (and in turn tissue induction) in situ . However, its inhibitory effect on synovial cell attachment in vitro implies that it may only be suited to post-operative administration.

The growing investment by governments and electric utilities in energy efficiency programs highlights the need for simple tools to help assess and explain the size of the potential resource. One technique that is commonly used in this effort is to characterize electricity savings in terms of avoided power plants, because it is easier for people to visualize a power plant than it is to understand an abstraction such as billions of kilowatt-hours. Unfortunately, there is no standardization around the characteristics of such power plants. In this letter we define parameters for a standard avoided power plant that have physical meaning and intuitive plausibility, for use in back-of-the-envelope calculations. For the prototypical plant this article settles on a 500MW existing coal plant operating at a 70% capacity factor with 7% T&D losses. Displacing such a plant for one year would save 3billion kWh/year at the meter and reduce emissions by 3 million metric tons of CO2 per year. The proposed name for this metric is the Rosenfeld, in keeping with the tradition among scientists of naming units in honor of the person most responsible for the discovery and widespread adoption of the underlying scientific principle in question—DrArthur HRosenfeld.

The growing investment by governments and electric utilities in energy efficiency programs highlights the need for simple tools to help assess and explain the size of the potential resource. One technique that is commonly used in this effort is to characterize electricity savings in terms of avoided power plants, because it is easier for people to visualize a power plant than it is to understand an abstraction such as billions of kilowatt-hours. Unfortunately, there is no standardization around the characteristics of such power plants. In this letter we define parameters for a standard avoided power plant that have physical meaning and intuitive plausibility, for use in back-of-the-envelope calculations. For the prototypical plant this article settles on a 500 MW existing coal plant operating at a 70percent capacity factor with 7percent T&D losses. Displacing such a plant for one year would save 3 billion kW h per year at the meter and reduce emissions by 3 million metric tons of CO2 per year. The proposed name for this metric is the Rosenfeld, in keeping with the tradition among scientists of naming units in honor of the person most responsible for the discovery and widespread adoption of the underlying scientific principle in question--Dr. Arthur H. Rosenfeld.