P. McEwan

Estimating the Incidence and Prevalence of Chronic Hepatitis C Infection in Taiwan Using Back Projection

OBJECTIVE Hepatitis C virus (HCV) infection is the leading cause of liver disease, and Taiwan has among the highest prevalence of HCV infection in the general population in Northeast Asia, estimated at between 2% and 4%. The aim of this study was to estimate the number of patients living with chronic HCV infection in Taiwan and quantify the expected numbers in each of the five Metavir fibrosis stages. METHODS We applied a back-projection approach, using observed hepatocellular carcinoma incidence between 1979 and 2008 and a smoothed Expectation-Maximization algorithm to maximize a Poisson likelihood to estimate the previous incidence of HCV infection. The algorithm was coded in Excel and combined with the MOdelling the NAtural histoRy and Cost-effectiveness of Hepatitis model (a hepatitis C natural history markov model) to predict the past and future numbers in each Metavir fibrosis stage. RESULTS Incident cases were predicted to have peaked in 1972 at 56,634 annually, with the prevalence peaking in 1986 at 763,737 infections and falling to 578,203 infections in 2012. It was estimated that in 2012, 127,795 (23.0%), 105,545 (19.0%), 81,211 (14.6%), 123,939 (22.3%), and 116,823 (21.1%) subjects were in fibrosis stages F0, F1, F2, F3, and F4, respectively. DISCUSSION Our study provides HCV infection prevalence estimates, stratified by Metavir fibrosis stage, in Taiwan for 2012. This has potential implications for budget planning, particularly with the availability of emerging therapies because fibrosis stage is predictive of both rapid and sustained virological response; therefore, planning expected treatment response in a given population could be enhanced with this additional information.

Healthcare resource implications of hypoglycemia-related hospital admissions and inpatient hypoglycemia: retrospective record-linked cohort studies in England

Objective Using a retrospective cohort study, the mean length of hospital stay (LoS) and total per-patient expenditure for hypoglycemia requiring admission to hospital were estimated. In a separate matched retrospective cohort study, the effect of inpatient hypoglycemia on LoS, expenditure, and risk of all-cause mortality while admitted was investigated. Methods The cohorts consisted of patients aged ≥18 years with a diagnosis of type 1 or 2 diabetes between January 1, 2002 and October 30, 2012 in the Clinical Practice Research Datalink database, who had initiated insulin treatment and had a recording of hypoglycemia in the same period. In the matched retrospective cohort study, exposed patients (who experienced hypoglycemia in hospital) were case-matched with patients who did not experience hypoglycemia during admission (unexposed). Generalized linear regression was used to estimate LoS. Risk of all-cause mortality was evaluated via logistic regression. Results In the retrospective cohort study (1131 patients), mean LoS was 5.46 (95% CI 4.62 to 6.45) days for type 1 diabetes, and 5.04 (95% CI 4.46 to 5.71) days for type 2 diabetes. Mean cost per admission was £1034 (95% CI £855 to £1253). In the matched retrospective cohort study (1079 pairs of patients), exposed patients had a mean LoS of 11.91 days (95% CI 10.96 to 12.94 days) versus 4.80 (95% CI 4.41 to 5.23) for unexposed patients, p<0.0001. Exposed patients had a higher mortality risk compared with unexposed patients (OR 1.439 (95% CI 1.060to 1.952), p=0.0195). Total average per-patient cost for exposed patients was GBP (£)2235, 40% (p<0.0001) higher than total average admission cost in unexposed patients. Conclusions Hypoglycemia has a significant negative impact on patient outcomes, healthcare resource use, and expenditure.

The Importance of Accounting for Baseline Hypoglycaemia Frequency When Modelling Hypoglycaemia Disutility In Type 1 Diabetes Mellitus.

unlicensed comparator bevacizumab, the frequency and duration of treatment, and the extrapolation of visual acuity beyond short-term observed trial data. The trial evidence used ranged from 6 months to 3 years and included evidence for treatment in one eye only. Most TAs modelled one treated eye only, with crude adjustments applied to account for bilateral treatment. Only the most recent appraisal for aflibercept in central RVO modelled the visual acuity of both eyes. All other uncertainties were consistent throughout the identified TAs. ConClusions: The main uncertainties are in which eye(s) patients are treated in practice and the extrapolation of outcomes beyond trial data. Modelling is limited by short-term clinical trial evidence that provides evidence for the treatment of one eye only.

Contrasting Model Predicted Life Expectancy In Patients With Type 2 Diabetes Across Different Mortality Risk Prediction Models Versus Data From The Canadian Chronic Disease Surveillance System.

Objectives: Alzheimer’s disease (AD) afflicts up to 9% of people aged 65 and over worldwide, with prevalence projected to increase. AD is associated with reduced quality of life and high treatment and management costs. A number of recently developed screening and preventative interventions offer reduction in resource use and improvement in quality of life for AD patients. The majority of existing models for economic evaluation of AD interventions focus on pharmaceuticals and due to their limited scope and time-horizon are unsuitable for evaluation of screening and preventative strategies. It is proposed to develop a decision model to ascertain the most cost-effective ‘mix’ of preventative and screening methods for Denmark. The objective of this study is to develop and validate such a model for economic evaluation of non-pharmaceutical interventions for AD MethOds: A Markov model was developed, representing transitions of a hypothetical cohort of 65 year olds from ‘no AD’ to different stages of AD (Very Mild through to Severe). AD could either be ‘identified’ or ‘not identified’ to reflect the difference in costs associated with treatment and management. Due to absence of Danish data, the model utilised transition probabilities based on US data; AD-associated costs and utilities were obtained from Danish and Swedish data, respectively. The model was externally validated against an epidemiological study of AD in Denmark to predict prevalence and stage of AD by age. Results: The model accurately predicted Danish age-specific prevalence of AD, although the prevalence for the 75-79 age group was overestimated by 3%. The model also produced accurate predictions of the distribution of AD severity. cOnclusiOns: The model provides a simple and robust framework for economic evaluation of screening and other non-pharmaceutical interventions for AD. The lack of up to date epidemiological data on AD is a challenge for model validation and introduces uncertainty.