The future of aortic surgery in Europe

At least every ten years, each specialty should reflect upon its past, its present and its future, in order to be able to reconfirm the direction in which it is headed, to adopt suggestions from inside and outside and, consequently, to improve. As such, the aim of this manuscript is to provide the interested reader with an overview of how aortic surgery and (perhaps more accurately) aortic medicine has evolved in Europe, and its present standing; also to provide a glimpse into the future, trying to disseminate the thoughts of a group of people actively involved in the development of aortic medicine in Europe, namely the Vascular Domain of the European Association of Cardio-Thoracic Surgery (EACTS).

The future of osteoporosis treatment - a research update

Osteoporosis is characterised by a progressive loss of bone mass and microarchitecture which leads to increased fracture risk. Some of the drugs available to date have shown reductions in vertebral and non-vertebral fracture risk. However, in the ageing population of industrialised countries, still more fractures happen today than are avoided, which highlights the large medical need for new treatment options, models, and strategies. Recent insights into bone biology, have led to a better understanding of bone cell functions and crosstalk between osteoblasts, osteoclasts, and osteocytes at the molecular level. In the future, the armamentarium against osteoporotic fractures will likely be enriched by (1.) new bone anabolic substances such as antibodies directed against the endogenous inhibitors of bone formation sclerostin and dickkopf-1, PTH and PTHrp analogues, and possibly calcilytics; (2.) new inhibitors of bone resorption such as cathepsin K inhibitors which may suppress osteoclast function without impairing osteoclast viability and thus maintain bone formation by preserving the osteoclast-osteoblast crosstalk, and denosumab, an already widely available antibody against RANKL which inhibits osteoclast formation, function, and survival; and (3.) new therapeutic strategies based on an extended understanding of the pathophysiology of osteoporosis which may include sequential therapies with two or more bone active substances aimed at optimising the management of bone capital acquired during adolescence and maintained during adulthood in terms of both quantity and quality. Finally, one of the future challenges will be to identify those patients and patient populations expected to benefit the most from a given drug therapy or regimen. The WHO fracture risk assessment tool FRAX® and improved access to bone mineral density measurements by DXA will play a key role in this regard.

Who Will Provide Long-Term Care in the Future?

Projects that long-term-care delivery system will face substantial barriers in the future in finding staff to provide services even without an increase in demand due to public or private insurance. Shift of the economy toward skilled service jobs; Changing demography of the work force; Policy elements and cohorts effects that shape the demand for long-term care personnel in the year 2000 and beyond.

Ethnosciences - A step towards the integration of scientific and non-scientific forms of knowledge in the management of natural resources for the future

Integration of indigenous knowledge and ethnoscientific approaches into contemporary frameworks for conservation and sustainable management of natural resources will become increasingly important in policies on an international and national level. We set the scene on how this can be done by exploring the key conditions and dimensions of a dialogue between ‘ontologies’ and the roles, which ethnosciences could play in this process. First, the roles which ethnosciences in the context of sustainable development were analysed, placing emphasis on the implications arising when western sciences aspire to relate to indigenous forms of knowledge. Secondly, the contributions of ethnosciences to such an ‘inter-ontological dialogue’ were explored, based on an ethnoecological study of the encounter of sciences and indigenous knowledge in the Andes of Bolivia, and reviewed experiences from mangrove systems in Kenya, India and Sri Lanka, and from case-studies in other ecosystems world-wide.

A Cox Model for Biostatistics of the Future

Professor Sir David R. Cox (DRC) is widely acknowledged as among the most important scientists of the second half of the twentieth century. He inherited the mantle of statistical science from Pearson and Fisher, advanced their ideas, and translated statistical theory into practice so as to forever change the application of statistics in many fields, but especially biology and medicine. The logistic and proportional hazards models he substantially developed, are arguably among the most influential biostatistical methods in current practice. This paper looks forward over the period from DRC's 80th to 90th birthdays, to speculate about the future of biostatistics, drawing lessons from DRC's contributions along the way. We consider "Cox's model" of biostatistics, an approach to statistical science that: formulates scientific questions or quantities in terms of parameters gamma in probability models f(y; gamma) that represent in a parsimonious fashion, the underlying scientific mechanisms (Cox, 1997); partition the parameters gamma = theta, eta into a subset of interest theta and other "nuisance parameters" eta necessary to complete the probability distribution (Cox and Hinkley, 1974); develops methods of inference about the scientific quantities that depend as little as possible upon the nuisance parameters (Barndorff-Nielsen and Cox, 1989); and thinks critically about the appropriate conditional distribution on which to base infrences. We briefly review exciting biomedical and public health challenges that are capable of driving statistical developments in the next decade. We discuss the statistical models and model-based inferences central to the CM approach, contrasting them with computationally-intensive strategies for prediction and inference advocated by Breiman and others (e.g. Breiman, 2001) and to more traditional design-based methods of inference (Fisher, 1935). We discuss the hierarchical (multi-level) model as an example of the future challanges and opportunities for model-based inference. We then consider the role of conditional inference, a second key element of the CM. Recent examples from genetics are used to illustrate these ideas. Finally, the paper examines causal inference and statistical computing, two other topics we believe will be central to biostatistics research and practice in the coming decade. Throughout the paper, we attempt to indicate how DRC's work and the "Cox Model" have set a standard of excellence to which all can aspire in the future.

Shaping the Future of Public Health: The Role of Biostatistics

Comments about the current place for the discipline of Biostatistics within Public Health (1993).