33 research outputs found

    Long-Term Secondary Care Costs of Endometrial Cancer: A Prospective Cohort Study Nested within the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS).

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    BACKGROUND: There is limited evidence on the costs of Endometrial Cancer (EC) by stage of disease. We estimated the long-term secondary care costs of EC according to stage at diagnosis in an English population-based cohort. METHODS: Women participating in UKCTOCS and diagnosed with EC following enrolment (2001-2005) and prior to 31st Dec 2009 were identified to have EC through multiple sources. Survival was calculated through data linkage to death registry. Costs estimates were derived from hospital records accessed from Hospital Episode Statistics (HES) with additional patient level covariates derived from case notes and patient questionnaires. Missing and censored data was imputed using Multiple Imputation. Regression analysis of cost and survival was undertaken. RESULTS: 491 of 641 women with EC were included. Five year total costs were strongly dependent on stage, ranging from £9,475 (diagnosis at stage IA/IB) to £26,080 (diagnosis at stage III). Stage, grade and BMI were the strongest predictors of costs. The majority of costs for stage I/II EC were incurred in the first six months after diagnosis while for stage III / IV considerable costs accrued after the first six months. CONCLUSIONS: In addition to survival advantages, there are significant cost savings if patients with EC are detected earlier.The analysis underpinning this study was supported with a grant from Cancer Research UK (CRUK Grant No: A16008) awarded to RL (http://www.cancerresearchuk. org/funding-for-researchers). The trial (UKCTOCS) for which the patients in this study form a subgroup was funded by the Medical Research Council, Cancer Research UK, the Department of Health and the Eve Appeal

    How to Appropriately Extrapolate Costs and Utilities in Cost-Effectiveness Analysis

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    Costs and utilities are key inputs into any cost-effectiveness analysis. Their estimates are typically derived from individual patient-level data collected as part of clinical studies the follow-up duration of which is often too short to allow a robust quantification of the likely costs and benefits a technology will yield over the patient’s entire lifetime. In the absence of long-term data, some form of temporal extrapolation—to project short-term evidence over a longer time horizon—is required. Temporal extrapolation inevitably involves assumptions regarding the behaviour of the quantities of interest beyond the time horizon supported by the clinical evidence. Unfortunately, the implications for decisions made on the basis of evidence derived following this practice and the degree of uncertainty surrounding the validity of any assumptions made are often not fully appreciated. The issue is compounded by the absence of methodological guidance concerning the extrapolation of non-time-to-event outcomes such as costs and utilities. This paper considers current approaches to predict long-term costs and utilities, highlights some of the challenges with the existing methods, and provides recommendations for future applications. It finds that, typically, economic evaluation models employ a simplistic approach to temporal extrapolation of costs and utilities. For instance, their parameters (e.g. mean) are typically assumed to be homogeneous with respect to both time and patients’ characteristics. Furthermore, costs and utilities have often been modelled to follow the dynamics of the associated time-to-event outcomes. However, cost and utility estimates may be more nuanced, and it is important to ensure extrapolation is carried out appropriately for these parameters

    The evaluation of lifestyle interventions in the Netherlands

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    Back to the Consideration of Future Consequences Scale: Time to Reconsider?

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    A long life in good health: Subjective expectations regarding length and future health-related quality of life

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    BACKGROUND: Subjective life expectancy is considered relevant in predicting mortality and future demand for health services as well as for explaining peoples' decisions in several life domains, such as the perceived impact of health behaviour changes on future health outcomes. Such expectations and in particular subjective expectations regarding future health-related quality of life remain understudied. The purpose of this study was to investigate individuals' subjective quality adjusted life years (QALYs) expectation from age 65 onwards in a representative sample of the Dutch generic public. METHODS: A web-based questionnaire was administered to a sample of the adult population from the Netherlands. Information on subjective expectations regarding length and future health-related quality of life were combined into one single measure of subjective expected QALYs from age 65 onwards. This subjective QALY expectation was related to background, health and lifestyle variables. The implications of using different methods to construct our main outcome measure were addressed. RESULTS: Mean subjective expected QALYs from age 65 onwards was 11 QALYs (range -9 to 40 QALYs). Individuals with unhealthier lifestyles, chronic diseases, severe disorders or lower age of death of next of kin reported lower QALY expectations. Indicators were varyingly associated with either subjective life expectancy or future health-related quality of life, or both. CONCLUSION: Extending the concept of subjective life expectancy by correcting for expected quality of life appears to generate important additional information contributing to our understanding of people's perceptions regarding ageing and lifestyle choices
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