A Markov model of Diabetic Retinopathy Progression for the Economic Evaluation of a novel DR prognostic device, CHERE Working Paper 2007/14

The initial diagnosis of Diabetic Retinopathy (DR) is often in the advance stages of the condition, as patients are only promoted for an examination when sight has been affected. An innovative prognostic technique has recently been made available which can non-invasively detect the damaging effects of high blood glucose before the development of clinical symptoms. This innovation offers the opportunity to patients to make the necessary behavioural and medicinal modification to prevent further progress of the disease. This paper reports the development of a Markov model which emulates the natural progression of Diabetic Retinopathy based on data from clinical trials. The purpose of such a model is to estimate the chronic cost and health outcomes of DR, and it may be modified to reflect the potential changes in current practice or condition changes, hence allowing for an economic evaluation of the DR prognostic test. The implications and limitations of the model were also discussed in the paper.Diabetic retinopathy, economic evaluation

Prognostic indication of power cable degradation

The reliability and the health performance of network assets are of a great interest due to power network operators. This project investigates methods of developing a prognostic capability for evaluating the health and long term performance of ageing distribution cable circuits. From the instant of installation and operation, the insulating materials of a cable will begin to age as a result of a combination of mechanical, thermal and electrical factors. Development of simulation models can significantly improve the accuracy of prognostics, allowing the targeting of maintenance and reduction of in service failures [1]. Real-time measurements taken close to underground cables can update the simulation models giving a more accurate prognostic model.Currently the project investigates a thermal prognostic simulation model which will predict the likely temperature impact on a cable at burial depth according to weather conditions and known loading. Anomalies of temperature measurements along the cable compared to predicted temperatures will indicate a possible degradation activity in a cable. An experimental surface trough has been set up where operation of power cables is simulated with a control system which is able to model any cable loading. The surface temperature of the cable is continuously monitored as well as the weather conditions such as solar radiation, soil moisture content, wind speed, humidity, rainfall and air-temperature<br/

A Robust Gene Expression Prognostic Signature for Overall Survival in High-Grade Serous Ovarian Cancer.

The objective of this research was to develop a robust gene expression-based prognostic signature and scoring system for predicting overall survival (OS) of patients with high-grade serous ovarian cancer (HGSOC). Transcriptomic data of HGSOC patients were obtained from six independent studies in the NCBI GEO database. Genes significantly deregulated and associated with OS in HGSOCs were selected using GEO2R and Kaplan-Meier analysis with log-rank testing, respectively. Enrichment analysis for biological processes and pathways was performed using Gene Ontology analysis. A resampling/cross-validation method with Cox regression analysis was used to identify a novel gene expression-based signature associated with OS, and a prognostic scoring system was developed and further validated in nine independent HGSOC datasets. We first identified 488 significantly deregulated genes in HGSOC patients, of which 232 were found to be significantly associated with their OS. These genes were significantly enriched for cell cycle division, epithelial cell differentiation, p53 signaling pathway, vasculature development, and other processes. A novel 11-gene prognostic signature was identified and a prognostic scoring system was developed, which robustly predicted OS in HGSOC patients in 100 sampling test sets. The scoring system was further validated successfully in nine additional HGSOC public datasets. In conclusion, our integrative bioinformatics study combining transcriptomic and clinical data established an 11-gene prognostic signature for robust and reproducible prediction of OS in HGSOC patients. This signature could be of clinical value for guiding therapeutic selection and individualized treatment

Clinical prediction models to inform individualized decision-making in subfertile couples : a stratified medicine approach

Funding This work was supported by a Chief Scientist Office Postdoctoral Training Fellowship in Health Services Research and Health of the Public Research (Ref PDF/12/06). The views expressed in this paper represent the views of the authors and not necessarily the views of the funding body.Peer reviewedPostprin

Major challenges in prognostics: study on benchmarking prognostic datasets

Even though prognostics has been defined to be one of the most difficult tasks in Condition Based Maintenance (CBM), many studies have reported promising results in recent years. The nature of the prognostics problem is different from diagnostics with its own challenges. There exist two major approaches to prognostics: data-driven and physics-based models. This paper aims to present the major challenges in both of these approaches by examining a number of published datasets for their suitability for analysis. Data-driven methods require sufficient samples that were run until failure whereas physics-based methods need physics of failure progression

Telomere dysfunction accurately predicts clinical outcome in chronic lymphocytic leukaemia, even in patients with early stage disease

© 2014 John Wiley & Sons Ltd. Defining the prognosis of individual cancer sufferers remains a significant clinical challenge. Here we assessed the ability of high-resolution single telomere length analysis (STELA), combined with an experimentally derived definition of telomere dysfunction, to predict the clinical outcome of patients with chronic lymphocytic leukaemia (CLL). We defined the upper telomere length threshold at which telomere fusions occur and then used the mean of the telomere 'fusogenic' range as a prognostic tool. Patients with telomeres within the fusogenic range had a significantly shorter overall survival (P  <  0·0001; Hazard ratio [HR] = 13·2, 95% confidence interval [CI]  = 11·6-106·4) and this was preserved in early-stage disease patients (P  <  0·0001, HR=19·3, 95% CI = 17·8-802·5). Indeed, our assay allowed the accurate stratification of Binet stage A patients into those with indolent disease (91% survival at 10 years) and those with poor prognosis (13% survival at 10 years). Furthermore, patients with telomeres above the fusogenic mean showed superior prognosis regardless of their IGHV mutation status or cytogenetic risk group. In keeping with this finding, telomere dysfunction was the dominant variable in multivariate analysis. Taken together, this study provides compelling evidence for the use of high-resolution telomere length analysis coupled with a definition of telomere dysfunction in the prognostic assessment of CLL

Evaluating methodological quality of Prognostic models Including Patient-reported HeAlth outcomes in oncologY (EPIPHANY): A systematic review protocol

Introduction While there is mounting evidence of the independent prognostic value of patient-reported outcomes (PROs) for overall survival (OS) in patients with cancer, it is known that the conduct of these studies may hold a number of methodological challenges. The aim of this systematic review is to evaluate the quality of published studies in this research area, in order to identify methodological and statistical issues deserving special attention and to also possibly provide evidence-based recommendations. Methods and analysis An electronic search strategy will be performed in PubMed to identify studies developing or validating a prognostic model which includes PROs as predictors. Two reviewers will independently be involved in data collection using a predefined and standardised data extraction form including information related to study characteristics, PROs measures used and multivariable prognostic models. Studies selection will be reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, with data extraction form using fields from the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS) checklist for multivariable models. Methodological quality assessment will also be performed and will be based on prespecified domains of the CHARMS checklist. As a substantial heterogeneity of included studies is expected, a narrative evidence synthesis will also be provided. Ethics and dissemination Given that this systematic review will use only published data, ethical permissions will not be required. Findings from this review will be published in peer-reviewed scientific journals and presented at major international conferences. We anticipate that this review will contribute to identify key areas of improvement for conducting and reporting prognostic factor analyses with PROs in oncology and will lay the groundwork for developing future evidence-based recommendations in this area of research. Prospero registration number CRD42018099160

A Similarity-Based Prognostics Approach for Remaining Useful Life Prediction

Physics-based and data-driven models are the two major prognostic approaches in the literature with their own advantages and disadvantages. This paper presents a similarity-based data-driven prognostic methodology and efficiency analysis study on remaining useful life estimation results. A similarity-based prognostic model is modified to employ the most similar training samples for RUL estimations on each time instance. The presented model is tested on; Virkler’s fatigue crack growth dataset, a drilling process degradation dataset, and a sliding chair degradation of a turnout system dataset. Prediction performances are compared utilizing an evaluation metric. Efficiency analysis of optimization results show that the modified similarity-based model performs better than the original definition