The need for informed consent is considered from the patient's viewpoint by an examination of the shortcomings of the UK Ductal Carcinoma In Situ (DCIS) trial and its failure satisfactorily to accrue both profession and patient. The impersonal, negative aspects of the informed consent process in the research situation are contrasted with the positive benefits of confidence fostered by the traditional doctor/patient relationship. The need for new research with a partnership between patient and profession, the necessity for rigorous re-assessment of (...) treatments and care both within and outside of trials to avoid waste by the perpetration of unnecessary treatments together with the need for evaluation of the efficacy of treatments employed outside of trials, especially in 'new' conditions, to foster progress and maintain public confidence in the profession, is advocated. (shrink)

Embryo research, cloning, assisted conception, neonatal care, savior siblings, organ transplants, drug trials – modern developments have transformed the field of medicine almost beyond recognition in recent decades and the law struggles to keep up. At the same time legal claims against doctors and the NHS has grown and doctors feel under siege. In this highly acclaimed and very accessible book, Margaret Brazier and Emma Cave provide an incisive survey of the legal situation in areas as diverse as fertility treatment, (...) surrogacy, patient consent, euthanasia and the definition of death, malpractice and medical privacy. (shrink)

This paper outlines the approaches of two apparently competing schools of statistics. The criticisms made by supporters of Bayesian statistics about conventional Frequentist statistics are explained, and the Bayesian claim that their method enables research into new treatments without the need for clinical trials is examined in detail. Several further important issues are considered, including: the use of historical controls and data routinely collected on patients; balance in randomised trials; the possibility of giving information to patients; patient choice and patient (...) autonomy; and how widely the results of clinical trials can be used. It is concluded that good statistical techniques in the design and analysis of medical studies are essential, but the statistical school used in developing such techniques is relatively unimportant. (shrink)

As each week beings more stories of doctors, lawyers and other professionals abusing their powers, while clients demand extra services as at a time of shrinking resources; it is imperative that all practising professionals have an understanding of professional ethics. In _The Ground of Profesional Ethics_, Daryl Koehn discusses the practical issues in depth, such as the level of service clients can justifiably expect from professionals, when service to a client may be legitimately terminated and circumstances in which client confidences (...) can be broken. She argues that, while clients may legitimately expect professionals to promote their interests, professionals are not morally bound to do whatever a client wants. _The Ground of Professional Ethics_ is important reading for all practising professionals, as well as those who study or have an interest in the subject of professional ethics. (shrink)

The medical concept of prognosis is analysed into its basic constituents: patient data, medical intervention, outcome, utilities and probabilities; and sources of utility and probability values are discussed. Prognosis cannot be divorced from contemplated medical action, nor from action to be taken by the patient in response to prognostication. Regrettably, the usual decision-theoretic approach ignores this latter aspect. Elicitation of utilities, decision contemplation and prognostic counselling interweave, diagnostics playing a subsidiary role in decision-oriented clinical practice. At times the doctor has (...) grounds for withholding information. As this is known to the patient, prognostic counselling becomes a conflict-prone and rationality-thwarting activity. The meaning of standard phrases such as prognosis of a disease, the prognosis of this patient, the prognosis is unknown, is examined. (shrink)

This paper describes a Bayesian approach to the design and analysis of clinical trials, and compares it with the frequentist approach. Both approaches address learning under uncertainty. But they are different in a variety of ways. The Bayesian approach is more flexible. For example, accumulating data from a clinical trial can be used to update Bayesian measures, independent of the design of the trial. Frequentist measures are tied to the design, and interim analyses must be planned for frequentist measures to (...) have meaning. Its flexibility makes the Bayesian approach ideal for analysing data from clinical trials. In carrying out a Bayesian analysis for inferring treatment effect, information from the clinical trial and other sources can be combined and used explicitly in drawing conclusions. Bayesians and frequentists address making decisions very differently. For example, when choosing or modifying the design of a clinical trial, Bayesians use all available information, including that which comes from the trial itself. The ability to calculate predictive probabilities for future observations is a distinct advantage of the Bayesian approach to designing clinical trials and other decisions. An important difference between Bayesian and frequentist thinking is the role of randomization. (shrink)