Pancreatic cancer (PC) has a poor prognosis, with a 5-year survival of 3-4%. This is mainly due to late diagnosis because of diffuse symptoms, where 80-85% of the patients are inoperable. Consequently, early diagnosis would be of significant benefit, resulting in a potential 5-year survival of 30-40%. However, new technologies must be carefully evaluated concerning effectiveness and healthcare costs. We have developed a framework for modelling cost and health effects from early detection of PC, which for the first time allowed us to analyse its cost-effectiveness. A probabilistic cohort model for estimating costs and quality adjusted life-years (QALY) arising from screening for PC, compared to a "wait-and-see"-approach, was designed. The test accuracy, Swedish survival and costs by tumour stage, expected life gain from early detection and pretest probabilities in risk groups, were retrieved from previous investigations. In a cohort of newly diagnosed diabetic patient (incidence 0.71%) the incremental cost per QALY gained (ICER) was e13,500, which is considered cost-effective in Europe. Results were mainly sensitive to the incidence with the ICER ranging from e315 to e204,000 (familial PC 35% and general population 0.046%, respectively). This is the first study focusing on clinical implementation of advanced testing and what is required for novel technologies in cancer care to be cost-effective. The model clearly demonstrated the potential of multiplexed proteomictesting of PC and also identified the requirements for test accuracy. Consequently, it can serve as a model for assessing the possibilities to introduce advanced test platforms also for other cancer indications.Early diagnosis has been estimated by the World Health Organization to form the basis for a cure in 30% of all cancer indications (www.who.int/cancer/en/index.html). Although many biomarkers have been suggested to be able to prognosticate and predict disease outcome, very few, if any, has demonstrated enough accuracy to be implemented for screening of high-risk patient groups. 1 However, the technology development in proteomics has, over the last few years, paved the way for new possibilities. The realisation that by identifying signatures, i.e. combination of biomarkers, rather than single biomarkers, have demonstrated enough accuracy for a test focusing on screening and risk assessment of cancer patients. 2,3 This was recently demonstrated by the identification of a biomarker signature in serum that was strongly associated with ductal pancreatic cancer (PC), thus, for the first time indicating the possibility for an improved diagnosis of this indication, otherwise a disease displaying a very poor prognosis. 4 The development and implementation of new technologies in health care is, however, undertaken in a context of uncertainty concerning the effectiveness and resource costs of health care. Therefore, two types of decisions need to be taken: those concerning provision of the services based on the existing information and those concerned with fu...

A naturalistic mirror-image study found that switching to long-acting injectable risperidone led to sizeable reductions in inpatient resource use. These results coincide with the findings of other international studies.

The rising trend in the prevalence of obesity, which is a major risk factor for a number of diseases notably diabetes and cardiovascular diseases, has become a major public health concern in many countries during the past decades. This development has also led to an increased cost burden on the public health care delivery system that has been documented in many studies. The standard approach taken for estimating the cost burden attributed to a risk factor is the so-called PAR (Population Attributed Risk) approach; an approach that is based on cross-sectional data. In this paper, the methods and findings of two studies that have documented the cost burden attributed to overweight and obesity on the public health care delivery system in Sweden are contrasted: one using the PAR approach and one using a statistical modeling approach based on longitudinal hospital care data for 15 years for 33 000 individuals. The main motivation for this paper is that the study using the PAR approach is only available in the Swedish language. The PAR approach estimated a cost burden of 3 600 million SEK (390 million Euro), equavalent to 1.9% of national health care expenditure, out of which 1 800 million SEK (190 million Euro) were spent on hospital care. The statistical modeling approach estimated the corresponding cost burden for hospital care at 2 100 million SEK (230 million Euro). The statistical modeling approach presents no estimates of the total cost burden attributed to overweight and obesity.

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Disease progression in multiple sclerosis leads to dramatic changes in a person's ability to perform daily activities and increases reliance on external help. This study aims to describe and to estimate costs of formal/informal home care and quality of life related to multiple sclerosis. A mailed survey to a random sample of MS sufferers (n = 1500) collected data on the number of hours of home care received, type of help, productivity losses, quality of life, and disease characteristics. Costs for home care were estimated in 2012 € and factors that may influence the likelihood of getting home care were also evaluated. Formal care was given to 27% of the respondents (n = 839) at an average of 238.7 hrs/month at a mean monthly cost of €2873/person with MS. Informal care was received by 49% of the respondents at an average of 47.3 hrs/month at a mean monthly cost of €389/person with MS. Utilities across disease severity are as follows: mild MS = 0.709 (sd = 0.233), moderate MS = 0.562 (sd = 0.232), and severe MS = 0.284 (sd = 0.283). Total home care costs increased with increasing disease severity. Informal caregiving contributes significantly to MS home care in Sweden.

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A629 ment was associated with 38% fewer unplanned admissions (981 vs. 604, X 1 2 = 89.2, p< 0.001) and 58% fewer unplanned bed nights (8,817 vs. 3,681, X 1 2 = 2109.8, p< 0.001) in the year following treatment initiation compared with the year before. A 14% reduction in all outpatient appointments was also observed, due principally to a 25% reduction in neurological outpatient appointments (from 7,826 to 5,901, X 1 2 = 269.7, p< 0.001). Evidence from this study indicates that duration of treatment is a significant factor in this response; patients receiving between 12 and 14 doses (n= 1,122) experienced 70% reduction in unplanned admissions and 90% reduction in unplanned bed nights. ConClusions: Our data support the notion that natalizumab treatment significantly reduces unplanned hospital treatment and outpatient attendance.