Upcoming events

Biological samples are being increasingly collected and banked as part of clinical trials, this workshop will be of practical value to those planning or currently managing a clinical trial or the sample collection / biobank aspect of a trial.
 
Contributors include: Professor Tim Maughan, University of Cardiff;  Professor Sir Kenneth Calman, Chair National Cancer Research Institute;  Professor Chris Womack, AstraZeneca;  Dr James Brenton, University of Cambridge

Who should attend: Primary investigators (clinicians or scientists), clinical trials network staff, clinical trials unit staff, NHS R&D managers, tissue bank administrators / managers / technical staff, pathologists, patients, patient advocates, ethicists, regulators, and funders of research and infrastructure or anyone else involved in the collection, storage and use of human biological samples in clinical research.
 
NB. The Royal College of Pathologists has awarded 5 CPD credits to this meeting.

A roadshow of one-day workshops entitled Ethical Principles Relating to Consent for Use of Anonymised Samples in Research which will be held in a number of locations across the UK during 2010. The workshop programme has been developed as a collaboration between onCore UK and the National Research Ethics Service (NRES), and is aimed at a broad research audience including Researchers, R&D officers/managers and REC Members and Co-ordinators. Workshops are planned in London, Scotland, South-West, Central and North-East England. Each workshop will follow the same programme content although individual speakers may vary. We will send out a notice for each meeting as the date is confirmed. The London workshop will be held on Tuesday 16th March 2010. .

Workshop 2: Risk, Probability and Harm

16 April 2010, 10.30–17.30

Registration is not yet open.

There are at least two ways that risks demand our attention: by the probability of their materialising, and by how bad would be the harm if they did. But probability and harm are different kinds of concepts, and each is a focus of controversy, which working epidemiologists need to negotiate. Is probability a property of individuals (or can it be)? This view may be appealing in interpretations of quantum mechanics, where it is debatable whether 'hidden variables' can explain apparently probabilistic phenomena. But even if irreducible chances are the right interpretation of quantum mechanics, it is not obvious that the rationale will apply carry over to higher level sciences such as epidemiology, where the existence of hidden variables is beyond doubt. Maybe, then, the appropriate understanding of probability for epidemiology is purely statistical, reducing to average frequency in a specified population. But then it is not clear what basis we have for moving from the observed average frequencies on which our probability estimates are based, to the unobserved frequencies which (in practical applications) they estimate. The concept of harm bears more subtly but no less directly on epidemiology. For one thing, the kind of harm that epidemiology studies requires some thought, and is not necessarily dictated by clinical medicine. To take the obvious example, suicide is a public health concern, but never a clinical one (even if prevention of suicide may be). Moreover, the range of health conditions studied by epidemiology is increasing. The relation between harm and autonomy is also complex, and poorly articulated in the public health context. Whereas an individual smoker might be able to refuse clinical treatment for lung cancer, the population of smokers generally cannot avoid public health initiatives on smoking. And it is not clear how, if at all, their (various) desires can or should be taken into account when counting the cost of smoking to public health. Finally, there is a question as to whether risk is itself a kind of harm, so that exposing someone to an increased risk of lung cancer by passive smoking is harming them even if they do not in fact develop lung cancer. This relates in turn to legal questions about how causation is proved in toxic tort cases, where the correct presentation and interpretation of epidemiological evidence is of paramount importance.

http://www.hps.cam.ac.uk/epidemiology/workshop2.html

The 2010 event is specifically aimed at bringing together researchers from the diverse reaches of test evaluation, from in vitro test developers, industry and regulatory representatives, through to methodologists, guideline developers and practising clinicians, in the hope of improving current understanding through knowledge exchange, and forging diverse experiences and perspectives to delineate the future direction of diagnostic test research.

Submission deadline: 31st March 2010. Early-bird registration now open - closes 14th May 2010: £325 (Not-for-profit) or £650 (Commercial)

Venue: Medical School, University of Birmingham, Edgbaston, Birmingham, B15 2TT

Workshop 3: Explanation and Intervention

24 September 2010, 10.30–17.30

Registration is not yet open.

The currency of contemporary epidemiology is the risk factor. But what is a risk factor? The term arises in part from the focus of epidemiology, unusually (but not uniquely) among sciences, on intervention. This suggests interesting questions about the relation between explanation and successful intervention. How much do we need to understand before we can fruitfully intervene? Risk factors seem to offer a way to design interventions in circumstances of incomplete knowledge, either about the circumstances or the nature of the cases of illness in question. But (to put a modern spin on Jacob Henle) a physicist might identify as risk factors for falling the removal of boards and beams, the cutting of ropes, the opening up of holes, and so forth – and without coming any nearer to a theory of gravity. This objection appears to be born out by history: the most dramatically successful interventions have tended to be closely linked to improvements in our understanding. Is that historical claim correct? If so, it would seem that our ability to explain why illness occurs is linked to our ability to cure and prevent it. But how? Do risk factors encourage epidemiologists, and their colleagues studying functional genomics, knock-out models, and similar, to seek explanations? Or do they allow potentially dangerous misunderstandings about the scientific and practical import of the results they represent? Is it a naïve mistake to suggest that public health interventions might be best served by seeking general explanations on the model of the physical sciences? The answers to these questions bear directly on the future direction of epidemiology and how it can appropriately employ its conceptual tools.