Integration of oncology and palliative care : a Lancet Oncology Commission

Full integration of oncology and palliative care relies on the specific knowledge and skills of two modes of care: the tumour-directed approach, the main focus of which is on treating the disease; and the host-directed approach, which focuses on the patient with the disease. This Commission addresses how to combine these two paradigms to achieve the best outcome of patient care. Randomised clinical trials on integration of oncology and palliative care point to health gains: improved survival and symptom control, less anxiety and depression, reduced use of futile chemotherapy at the end of life, improved family satisfaction and quality of life, and improved use of health-care resources. Early delivery of patient-directed care by specialist palliative care teams alongside tumour-directed treatment promotes patient-centred care. Systematic assessment and use of patient-reported outcomes and active patient involvement in the decisions about cancer care result in better symptom control, improved physical and mental health, and better use of health-care resources. The absence of international agreements on the content and standards of the organisation, education, and research of palliative care in oncology are major barriers to successful integration. Other barriers include the common misconception that palliative care is end-of-life care only, stigmatisation of death and dying, and insufficient infrastructure and funding. The absence of established priorities might also hinder integration more widely. This Commission proposes the use of standardised care pathways and multidisciplinary teams to promote integration of oncology and palliative care, and calls for changes at the system level to coordinate the activities of professionals, and for the development and implementation of new and improved education programmes, with the overall goal of improving patient care. Integration raises new research questions, all of which contribute to improved clinical care. When and how should palliative care be delivered? What is the optimal model for integrated care? What is the biological and clinical effect of living with advanced cancer for years after diagnosis? Successful integration must challenge the dualistic perspective of either the tumour or the host, and instead focus on a merged approach that places the patient's perspective at the centre. To succeed, integration must be anchored by management and policy makers at all levels of health care, followed by adequate resource allocation, a willingness to prioritise goals and needs, and sustained enthusiasm to help generate support for better integration. This integrated model must be reflected in international and national cancer plans, and be followed by developments of new care models, education and research programmes, all of which should be adapted to the specific cultural contexts within which they are situated. Patient-centred care should be an integrated part of oncology care independent of patient prognosis and treatment intention. To achieve this goal it must be based on changes in professional cultures and priorities in health care

Detection, modelling and implications of non-normality in financial economics : normal inverse Gaussian modelling of Norwegian stock market returns and consumption growth

This thesis shows that the Norwegian stock market deviates significantly from what one might think of as a baseline model with identically and independently normally distributed returns. Firstly, the stock market return does not seem to be normally distributed over any observation frequency (daily, monthly and quarterly) we have investigated in this thesis. More specifically, the return distribution is both leptokurtic and negatively skewed. Secondly, the empirical return distribution is time-varying; we find both autocorrelation in returns and volatility clustering. Both of these deviations from the baseline model can potentially have important implications for theoretical models and practical applications. In this paper, we will model the return distribution with a normal inverse Gaussian (NIG) distribution, which we indeed find to outperform Gaussian distributions both in- and out of sample. Our NIG modelling approach allows us to deviate from the normality assumption, but it is not able to capture the dependencies across time. This model of returns turns out to be useful in risk measurement, where the baseline model grossly underestimate well-known metrics such as value at risk and expected shortfall the NIG model fits these measures nicely. This thesis also applies a bivariate NIG distribution to a theoretical model of equilibrium risk-free interest rates and the equity premium, suggested by Aase and Lillestøl (2015), in order to explain the equity premium puzzle. The NIG model allows for fatter tails and negative skewness in the joint return and consumption distribution, thereby reducing the implied risk aversion parameter and increasing the impatience rate of the representative consumer. Although the model takes us in the right direction in terms of both implied parameters, the improvement is only slightly more than negligible and it happens at the cost of a great increase in complexity.nhhma

Reliability of estimating the room volume from a single room impulse response

The methods investigated for the room volume estimation are based on geometrical acoustics, eigenmode, and diffuse field models and no data other than the room impulse response are available. The measurements include several receiver positions in a total of 12 rooms of vastly different sizes and acoustic characteristics. The limitations in identifying the pivotal specular reflections of the geometrical acoustics model in measured room impulse responses are examined both theoretically and experimentally. The eigenmode method uses the theoretical expression for the Schroeder frequency and the difficulty of accurately estimating this frequency from the varying statistics of the room transfer function is highlighted. Reliable results are only obtained with the diffuse field model and a part of the observed variance in the experimental results is explained by theoretical expressions for the standard deviation of the reverberant sound pressure and the reverberation time. The limitations due to source and receiver directivity are discussed and a simple volume estimation method based on an approximate relationship with the reverberation time is also presented.Imaging Science and TechnologyApplied Science