Orphan drugs revisited.
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Attitude of Health Personnel↗
Biomedical subjects
K Claxton
Publications and source records attributed to K Claxton.
Wickedness or folly? The ethics of NICE's decisions.
A rebuttal is provided to each of the arguments adduced by John Harris, an Editor-in-Chief of the Journal of Medical Ethics, in two editorials in the journal in support of the view that National Institute for Health and Clinical Excellence's procedures and methods for making recommendations about healthcare procedures for use in the National Health Service in England and Wales are the product of "wickedness or folly or more likely both", "ethically illiterate as well as socially divisive", responsible for the "perversion of science as well as of morality" and are "contrary to basic morality and contrary to human rights".
Academies and Institutes↗
Reviewing the evidence for wound bed preparation.
This paper explores the nature of evidence and how it has evolved in recent years, and sets out a process for assembling and assessing the evidence to support wound bed preparation as an effective method of managing chronic wounds
Anti-Infective Agents, Local↗
A series of systematic reviews to inform a decision analysis for sampling and treating infected diabetic foot ulcers.
OBJECTIVES: To review systematically the evidence on the performance of diagnostic tests used to identify infection in diabetic foot ulcers (DFUs) and of interventions to treat infected DFUs. To use estimates derived from the systematic reviews to create a decision analytic model in order to identify the most effective method of diagnosing and treating infection and to identify areas of research that would lead to large reductions in clinical uncertainty. DATA SOURCES: Electronic databases covering period from inception of the database to November 2002. REVIEW METHODS: Selected studies were assessed against validated criteria and described in a narrative review. The structure of a decision analytic model was derived for two groups of patients in whom diagnostic tests were likely to be used. RESULTS: Three studies that investigated the performance of diagnostic tests for infection on populations including people with DFUs found that there was no evidence that single items on a clinical examination checklist were reliable in identifying infection in DFUs, that wound swabs perform poorly against wound biopsies, and that semi-quantitative analysis of wound swabs may be a useful alternative to quantitative analysis. However, few people with DFUs were included, so it was not possible to tell whether diagnostic performance differs for DFUs relative to wounds of other aetiologies. Twenty-three studies investigated the effectiveness (n = 23) or cost-effectiveness (n = 2) of antimicrobial agents for DFUs. Eight studied intravenous antibiotics, five oral antibiotics, four different topical agents such as dressings, four subcutaneous granulocyte colony stimulating factor (G-CSF), one evaluated oral and topical Ayurvedic preparations and one compared topical sugar versus antibiotics versus standard care. The majority of trials were underpowered and were too dissimilar to be pooled. There was no strong evidence for recommending any particular antimicrobial agent for the prevention of amputation, resolution of infection or ulcer healing. Topical pexiganan cream may be as effective as oral antibiotic treatment with ofloxacin for the resolution of local infection. Ampicillin and sulbactam were less costly than imipenem and cilastatin, a growth factor (G-CSF) was less costly than standard care and cadexomer iodine dressings may be less costly than daily dressings. A decision analytic model was derived for two groups of people, those for whom diagnostic testing would inform treatment--people with ulcers which do not appear infected but whose ulcer is not progressing despite optimal concurrent treatment--and those in whom a first course of antibiotics (prescribed empirically) have failed. There was insufficient information from the systematic reviews or interviews with experts to populate the model with transition probabilities for the sensitivity and specificity of diagnosis of infection in DFUs. Similarly, there was insufficient information on the probabilities of healing, amputation or death in the intervention studies for the two populations of interest. Therefore, we were unable to run the model to inform the most effective diagnostic and treatment strategy. CONCLUSIONS: The available evidence is too weak to be able to draw reliable implications for practice. This means that, in terms of diagnosis, infection in DFUs cannot be reliably identified using clinical assessment. This has implications for determining which patients need formal diagnostic testing for infection, on whether empirical treatment with antibiotics (before the results of diagnostic tests are available) leads to better outcomes, and on identifying the optimal methods of diagnostic testing. With respect to treatment, it is not known whether treatment with systemic or local antibiotics leads to better outcomes or whether any particular agent is more effective. Limited evidence suggests that both G-CSF and cadexomer iodine dressings may be less expensive than 'standard' care, that ampicillin/sulbactam may be less costly than imipenem/cilastatin, and that an unlicensed cream (pexiganan) may be as effective as oral ofloxacin. Further research is needed to ascertain the characteristics of infection in people with DFUs that influence healing and amputation outcomes, to determine whether detecting infection prior to treatment offers any benefit over empirical therapy, and to establish the most effective and cost-effective methods for detecting infection, as well as the relative effectiveness and cost-effectiveness of antimicrobial interventions for DFU infection.
Ampicillin↗
Etanercept and infliximab for the treatment of psoriatic arthritis: a systematic review and economic evaluation.
OBJECTIVES: To evaluate the clinical effectiveness, safety, tolerability and cost-effectiveness of etanercept and infliximab for the treatment of active and progressive psoriatic arthritis (PsA) in patients who have inadequate response to standard treatment, including disease-modifying antirheumatic drug (DMARD) therapy. DATA SOURCES: Electronic databases were searched up to July 2004. REVIEW METHODS: A systematic review evaluated the clinical efficacy and adverse effects of etanercept and infliximab. The efficacy of DMARDs in the treatment of PsA was also reviewed and treatments were compared using Bayesian evidence synthesis methods. Following evaluation of existing economic evaluations of etanercept and infliximab in PsA, a new economic model was developed (the York Model). This utilised the results from the evidence synthesis and data from a range of other sources. RESULTS: Across the two trials, at 12 weeks, around 65% of patients treated with etanercept achieved an American College of Rheumatology (ACR) 20 {pooled relative risk (RR) 4.19 [95% confidence interval (CI) 2.74 to 6.42]}, demonstrating a basic degree of efficacy in terms of arthritis-related symptoms. In addition, around 45% of patients treated with etanercept achieved an ACR 50 [pooled RR 10.84 (95% CI 4.47 to 26.28)] and around 12% achieved an ACR 70 [pooled RR 16.28 (95% CI 2.20 to 120.54)], demonstrating a good level of efficacy. The subgroup analyses conducted in one trial revealed that the effect of etanercept was not dependent upon patients' concomitant use of methotrexate. In addition, almost 85% of patients treated with etanercept achieved a Psoriatic Arthritis Response Criteria (PsARC) [pooled RR 2.60 (95% CI 1.96 to 3.45). The Psoriatic Area and Severity Index (PASI) results indicate some beneficial effect on psoriasis at 12 weeks; however, the data are sparse. The statistically significant reduction (improvement) in Health Assessment Questionnaire (HAQ) score with etanercept compared with placebo indicates a beneficial effect of etanercept on function. Similar results were seen at 24 weeks, except that the results for PASI 75 and PASI 50 now achieved statistical significance and data for Total Sharp Score annualised rate of progression were available; this was statistically significantly lower in etanercept-treated patients than in placebo-treated patients. Uncontrolled follow-up of patients indicates that treatment benefit may be maintained for at least 50 weeks. At 16 weeks, 65% of patients treated with infliximab achieved an ACR 20 [RR 6.80 (95% CI 2.89 to 16.01)], demonstrating a basic degree of efficacy in terms of arthritis-related symptoms. This level of efficacy was not dependent upon patients' concomitant use of methotrexate. Almost half the patients treated with infliximab achieved an ACR 50 [RR 49.00 (95% CI 3.06 to 785.06)] and over one-quarter achieved an ACR 70 [RR 31.00 (95% CI 1.90 to 504.86)] compared with none of the placebo group, demonstrating a good level of efficacy. In addition, 75% of patients treated with infliximab achieved a PsARC [RR 3.55 (95% CI 2.05 to 6.13)]. The beneficial treatment effect on psoriasis was also statistically significant with a mean difference in percentage change from baseline in PASI of -5 (95% CI -6.8 to -3.3), as was the percentage improvement from baseline in HAQ score with infliximab compared with placebo [mean difference 51.4 (95% CI 48.08 to 54.72)], indicating a beneficial effect of infliximab on functional status. Uncontrolled data from all measures of joint disease, psoriasis and HAQ collected up to 50 weeks of follow-up reflect those at 16 weeks. There were no radiographic assessments, so nothing can be determined about the potential or otherwise of infliximab to delay the progression of joint disease. Using the York cost-effectiveness model, infliximab was consistently dominated by etanercept because of its higher acquisition and administration costs without superior effectiveness. The incremental cost per quality-adjusted life-year (QALY) gained of etanercept compared with palliative care ranged from 14,818 pounds (females, 40-year time horizon) to 49,374 pounds (males, 1-year time horizon) if it is assumed that, when patients eventually fail on biological therapy, their disability (in terms of HAQ score) deteriorates by the same amount as it improved when they initially respond to treatment (rebound equal to gain). Results for etanercept ranged from 25,443 pounds (females, 40-year time horizon) to 49,441 pounds (males, 1-year time horizon) per QALY gained under the assumption that, when patients fail on therapy, their disability level returns to what it would have been had they never responded (rebound equal to natural history). CONCLUSIONS: The limited data available indicated that etanercept and infliximab are efficacious in the treatment of PsA with beneficial effects on both joint and psoriasis symptoms and on functional status. Short-term data indicated that etanercept can delay joint disease progression, but long-term data are needed. There are no controlled data as yet to indicate that infliximab can delay joint disease progression. Treatment with both etanercept and infliximab for 12 weeks demonstrated a significant degree of efficacy, with no statistically significant difference between them. For both drugs, adverse events were common with mild injection/infusion reactions being the main treatment-related effect. The York model indicated that etanercept is more cost-effective than infliximab as it has a lower cost with little difference in outcomes. The cost-effectiveness of etanercept is also sensitive to assumptions made about the extent of disease progression when patients are responding to therapy. The number of years for which a patient can be safely on biologicals is uncertain so these results should be considered with caution. Further research should include long-term controlled trials to confirm benefits, review adverse events and to explore further the implications of biologic therapy.
Anti-Inflammatory Agents↗
A pilot study on the use of decision theory and value of information analysis as part of the NHS Health Technology Assessment programme.
OBJECTIVES: To demonstrate the benefits of using appropriate decision-analytic methods and value of information analysis (DA-VOI). Also to establish the feasibility and implications of applying these methods to inform the prioritisation process of the NHS Health Technology Assessment (HTA) programme, and possibly extending their use therein. DATA SOURCES: Three research topics that were considered by the HTA panels in the September 2002 and February 2003 prioritisation rounds. REVIEW METHODS: A brief and non-technical overview of DA-VOI methods was circulated to the panels and Prioritisation Strategy Group (PSG). For each case study the results were presented to the panels and the PSG in the form of brief case-study reports. Feedback on the DA-VOI analysis and its presentation was obtained in the form of completed questionnaires from panel members, and reports from panel senior lecturers and PSG members. RESULTS: Although none of the research topics identified met all of the original selection criteria for inclusion as case studies in the pilot, it was possible to construct appropriate decision-analytic models and conduct probabilistic analysis for each topic. In each case, the tasks were completed within the time-frame required by the existing HTA research prioritisation process. The brief case-study reports provided a description of the decision problem, a summary of the current evidence base and a characterisation of decision uncertainty in the form of cost-effectiveness acceptability curves. Estimates of value of information for the decision problem were presented for relevant patient groups and clinical settings, as well as the value of information associated with particular model inputs. The implications for the value of research in each of the areas were presented in general terms. Details were also provided on what the analysis suggested regarding the design of any future research in terms of features such as the relevant patient groups and comparators, and whether experimental design was likely to be required. CONCLUSIONS: The pilot study showed that, even with very short timelines, it is possible to undertake DA-VOI that can feed into the priority-setting process that has been developed for the HTA programme. There are however a number of areas that need to be established at the beginning of the process, such as clarification of the nature of the decision problem for which additional research is being considered, explicitness about which existing data should be used and how data that exhibit particular weaknesses should be down-weighted in the analysis. Other areas, including optimum application of researcher time, integrating the vignette (a summary of the clinical problem and existing evidence) and the use of DA-VOI, training, use of sensitivity analyses, and deployment of clinical expertise, are also considered in terms of the potential implementation of DA-VOI within the HTA programme. Recommendations for further research include how literature searching should focus on those variables to which the model's results are most sensitive and with the highest expected value of perfect information; methods of evidence synthesis (multiple parameter synthesis) to consider the evidence surrounding multiple comparators and networks of evidence; and ways in which the value of sample information can be used by the NHS HTA programme and other research funders to decide on the most efficient design of new evaluative research. There is also a need for an analytical framework to be developed that can jointly address the question of whether additional resources would better be devoted to additional research or interventions to change clinical practice.
Biomedical Technology↗
Review of guidelines for good practice in decision-analytic modelling in health technology assessment.
OBJECTIVES: To identify existing guidelines and develop a synthesised guideline plus accompanying checklist. In addition to provide guidance on key theoretical, methodological and practical issues and consider the implications of this research for what might be expected of future decision-analytic models. DATA SOURCES: Electronic databases. REVIEW METHODS: A systematic review of existing good practice guidelines was undertaken to identify and summarise guidelines currently available for assessing the quality of decision-analytic models that have been undertaken for health technology assessment. A synthesised good practice guidance and accompanying checklist was developed. Two specific methods areas in decision modelling were considered. The first method's topic is the identification of parameter estimates from published literature. Parameter searches were developed and piloted using a case-study model. The second topic relates to bias in parameter estimates; that is, how to adjust estimates of treatment effect from observational studies where there are risks of selection bias. A systematic literature review was conducted to identify those studies looking at quantification of bias in parameter estimates and the implication of this bias. RESULTS: Fifteen studies met the inclusion criteria and were reviewed and consolidated into a single set of brief statements of good practice. From this, a checklist was developed and applied to three independent decision-analytic models. Although the checklist provided excellent guidance on some key issues for model evaluation, it was too general to pick up on the specific nuances of each model. The searches that were developed helped to identify important data for inclusion in the model. However, the quality of life searches proved to be problematic: the published search filters did not focus on those measures specific to cost-effectiveness analysis and although the strategies developed as part of this project were more successful few data were found. Of the 11 studies meeting the criteria on the effect of selection bias, five concluded that a non-randomised trial design is associated with bias and six studies found 'similar' estimates of treatment effects from observational studies or non-randomised clinical trials and randomised controlled trials (RCTs). One purpose of developing the synthesised guideline and checklist was to provide a framework for critical appraisal by the various parties involved in the health technology assessment process. First, the guideline and checklist can be used by groups that are reviewing other analysts' models and, secondly, the guideline and checklist could be used by the various analysts as they develop their models (to use it as a check on how they are developing and reporting their analyses). The Expert Advisory Group (EAG) that was convened to discuss the potential role of the guidance and checklist felt that, in general, the guidance and checklist would be a useful tool, although the checklist is not meant to be used exclusively to determine a model's quality, and so should not be used as a substitute for critical appraisal. CONCLUSIONS: The review of current guidelines showed that although authors may provide a consistent message regarding some aspects of modelling, in other areas conflicting attributes are presented in different guidelines. In general, the checklist appears to perform well, in terms of identifying those aspects of the model that should be of particular concern to the reader. The checklist cannot, however, provide answers to the appropriateness of the model structure and structural assumptions, as these may be seen as a general problem with generic checklists and do not reflect any shortcoming with the synthesised guidance and checklist developed here. The assessment of the checklist, as well as feedback from the EAG, indicated the importance of its use in conjunction with a more general checklist or guidelines on economic evaluation. Further methods research into the following areas would be valuable: the quantification of selection bias in non-controlled studies and in controlled observational studies; the level of bias in the different non-RCT study designs; a comparison of results from RCTs with those from other non-randomised studies; assessment of the strengths and weaknesses of alternative ways to adjust for bias in a decision model; and how to prioritise searching for parameter estimates.
Benchmarking↗
Representing uncertainty: the role of cost-effectiveness acceptability curves.
Decision-making in health care is inevitably undertaken in a context of uncertainty concerning the effectiveness and costs of health care interventions and programmes. One method that has been suggested to represent this uncertainty is the cost-effectiveness acceptability curve. This technique, which directly addresses the decision-making problem, has advantages over confidence interval estimation for incremental cost-effectiveness ratios. However, despite these advantages, cost-effectiveness acceptability curves have yet to be widely adopted within the field of economic evaluation of health care technologies. In this paper we consider the relationship between cost-effectiveness acceptability curves and decision-making in health care, suggest the introduction of a new concept more relevant to decision-making, that of the cost-effectiveness frontier, and clarify the use of these techniques when considering decisions involving multiple interventions. We hope that as a result we can encourage the greater use of these techniques.
Confidence Intervals↗
A dynamic programming approach to the efficient design of clinical trials.
If the prospective evaluation of all feasible strategies of patient management is not possible or efficient then this poses a number of questions: (i) which clinical decision problems will be worth evaluating through prospective clinical research; (ii) if a clinical decision problem is worth evaluating which of the many competing alternatives should be considered "relevant" and be compared in the evaluation; (iii) what is the optimal (technically efficient) scale of this prospective research; (iv) what is an optimal allocation of trial entrants between the competing alternatives; and (v) what is the value of this proposed research? The purpose of this paper is to present a Bayesian decision theoretic approach to the value of information which can provide answers to each of these questions. An analysis of the value of sample information was combined with dynamic programming and applied to numerical examples of sequential decision problems. The analysis demonstrates that this approach can be used to establish: optimal sample size; optimal sample allocation; and the societal payoff to proposed research. This approach provides a consistent way to identify which of the competing alternatives can be regarded as "relevant" and should be included in any evaluative study design. Bayesian decision theory can provide a general methodological framework that can ensure consistency in decision making between service provision, research and development, and the design, conduct and interpretation clinical research.
Bayes Theorem↗
Introduction. Bayesian approaches to technology assessment and decision making.
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Bayes Theorem↗
Bayesian value-of-information analysis. An application to a policy model of Alzheimer's disease.
A framework is presented that distinguishes the conceptually separate decisions of which treatment strategy is optimal from the question of whether more information is required to inform this choice in the future. The authors argue that the choice of treatment strategy should be based on expected utility, and the only valid reason to characterize the uncertainty surrounding outcomes of interest is to establish the value of acquiring additional information. A Bayesian decision theoretic approach is demonstrated through a probabilistic analysis of a published policy model of Alzheimer's disease. The expected value of perfect information is estimated for the decision to adopt a new pharmaceutical for the population of patients with Alzheimer's disease in the United States. This provides an upper bound on the value of additional research. The value of information is also estimated for each of the model inputs. This analysis can focus future research by identifying those parameters where more precise estimates would be most valuable and indicating whether an experimental design would be required. We also discuss how this type of analysis can also be used to design experimental research efficiently (identifying optimal sample size and optimal sample allocation) based on the marginal cost and marginal benefit of sample information. Value-of-information analysis can provide a measure of the expected payoff from proposed research, which can be used to set priorities in research and development. It can also inform an efficient regulatory framework for new healthcare technologies: an analysis of the value of information would define when a claim for a new technology should be deemed substantiated and when evidence should be considered competent and reliable when it is not cost-effective to gather any more information.
Alzheimer Disease↗
Assessing quality in decision analytic cost-effectiveness models. A suggested framework and example of application.
Despite the growing use of decision analytic modelling in cost-effectiveness analysis, there is a relatively small literature on what constitutes good practice in decision analysis. The aim of this paper is to consider the concept of 'validity' and 'quality' in this area of evaluation, and to suggest a framework by which quality can be demonstrated on the part of the analyst and assessed by the reviewer and user. The paper begins by considering the purpose of cost-effectiveness models and argues that the their role is to identify optimum treatment decisions in the context of uncertainty about future states of the world. The issue of whether such models can be defined as 'scientific' is considered. The notion that decision analysis undertaken at time t can only be considered scientific if its outputs closely predict the results of a trial undertaken at time t + 1 is rejected as this ignores the need to make decisions on the basis of currently available evidence. Rather, the scientific characteristic of decision models is based on the fact that, in principle at least, such analyses can be falsified by comparison of two states of the world, one where resource allocation decisions are based on formal decision analysis and the other where such decisions are not. This section of the paper also rejects the idea of exact codification of scientific method in general, and of decision analysis in particular, as this risks rejecting potentially valuable models, may discourage the development of novel methods and can distort research priorities. However, the paper argues that it is both possible and necessary to develop a framework for assessing quality in decision models. Building on earlier work, various dimensions of quality in decision modelling are considered: model structure (disease states, options, time horizon and cycle length); data (identification, incorporation, handling uncertainty); and consistency (internal and external). Within this taxonomy a (nonexhaustive) list of questions about quality is suggested which are illustrated by their application to a specific published model. The paper argues that such a framework can never be prescriptive about every aspect of decision modelling. Rather, it should encourage the analyst to provide an explicit and comprehensive justification of their methods, and allow the user of the model to make an informed judgment about the relevance, coherence and usefulness of the analysis.
Clinical Trials as Topic↗
Redefining the analytical approach to pharmacoeconomics.
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Bayes Theorem↗
Bayesian approaches to the value of information: implications for the regulation of new pharmaceuticals.
The current regulation of new pharmaceuticals is inefficient because it demands arbitrary amounts of information, the type of information demanded is not relevant to decision-makers and the same standards of evidence are applied across different technologies. Bayesian decision theory and an analysis of the value of both perfect and sample information is used to consider the efficient regulation of new pharmaceuticals. This type of analysis can be used to decide whether the evidence in an economic study provides 'sufficient substantiation' for an economic claim, and assesses whether evidence can be regarded as 'competent and reliable'.
Bayes Theorem↗
The irrelevance of inference: a decision-making approach to the stochastic evaluation of health care technologies.
The literature which considers the statistical properties of cost-effectiveness analysis has focused on estimating the sampling distribution of either an incremental cost-effectiveness ratio or incremental net benefit for classical inference. However, it is argued here that rules of inference are arbitrary and entirely irrelevant to the decisions which clinical and economic evaluations claim to inform. Decisions should be based only on the mean net benefits irrespective of whether differences are statistically significant or fall outside a Bayesian range of equivalence. Failure to make decisions in this way by accepting the arbitrary rules of inference will impose costs which can be measured in terms of resources or health benefits forgone. The distribution of net benefit is only relevant to deciding whether more information is required. A framework for decision making and establishing the value of additional information is presented which is consistent with the decision rules in CEA. This framework can distinguish the simultaneous but conceptually separate steps of deciding which alternatives should be chosen, given existing information, from the question of whether more information should be acquired. It also ensures that the type of information acquired is driven by the objectives of the health care system, is consistent with the budget constraint on service provision and that research is designed efficiently.
Bayes Theorem↗
Pregnancy outcomes in women potentially exposed to solvent-contaminated drinking water in San Jose, California.
During 1980-1981, solvents leaked from an underground storage tank of a semiconductor firm in southern Santa Clara County, California, contaminating local drinking water. The contaminated well was closed in December 1981. An epidemiologic study conducted in 1983 confirmed statistically significant excesses of adverse pregnancy outcomes in an exposed community compared with an unexposed community, but could not establish a causal connection between the leak and the adverse outcomes. This study expanded the first study; adverse pregnancy outcomes occurring in 1980-1985 were studied in two communities exposed to the contaminated drinking water and in two demographically comparable but unexposed communities. The period 1980-1981 was the time period in which the well was considered to have been contaminated and 1982-1985 was considered the postcontamination time period. Both exposed and unexposed communities were considered unexposed during the latter period (1982-1985). Out of 10,055 households surveyed, interviews were conducted with 1,105 women who reported one or more eligible pregnancies. Miscarriages and birth defects were validated by medical record review or physician reports. Although the authors again observed statistically significant excesses of spontaneous abortions and birth defects in the originally studied exposed area in 1980-1981, they observed deficits of these outcomes in the second exposed study area. Adjustment for potential confounders did not alter these findings. Analyses of pregnancy outcomes during 1981 in relation to exposure estimates based on hydrogeologic modeling of water and contaminant distribution within the exposed areas also indicated that the leak was not likely to have caused the observed excesses of adverse pregnancy outcomes in the originally studied area.
Abnormalities, Drug-Induced↗
An epidemiological study of petroleum refinery employees.
A cohort study of 14179 current and former Chevron USA employees at the Richmond and El Segundo, California, refineries was conducted. The cohort consisted of everyone working at either refinery for a minimum of one year. The observed mortality of the cohort, by cause, was compared with the expected based on the United States mortality rates, standardised for age, race, sex, and calendar time. Analyses by refinery, job category, hire date, duration of employment, and latency were performed. For the entire cohort, mortality from all causes was 72.4% of that expected, a deficit that was statistically significant. In addition, a significantly lower mortality was found for all forms of cancer combined, digestive cancer, lung cancer, heart disease, non-malignant respiratory disease, diseases of the digestive system, and accidents. Only lymphopoietic cancer showed a pattern of increased risk suggestive of a possible relation to an occupational exposure. The excess appears confined to cancer of lymphatic tissue (not leukaemias) at Richmond, and only among those hired before 1948. A follow up case analysis of the deaths from lymphatic cancer failed to identify a common exposure pattern.
Brain Neoplasms↗
An economic approach to clinical trial design and research priority-setting.
Whilst significant advances have been made in persuading clinical researchers of the value of conducting economic evaluation alongside clinical trials, a number of problems remain. The most fundamental is the fact that economic principles are almost entirely ignored in the traditional approach to trial design. For example, in the selection of an optimal sample size no consideration is given to the marginal costs or benefits of sample information. In the traditional approach this can lead to either unbounded or arbitrary sample sizes. This paper presents a decision-analytic approach to trial design which takes explicit account of the costs of sampling, the benefits of sample information and the decision rules of cost-effectiveness analysis. It also provides a consistent framework for setting priorities in research funding and establishes a set of screens (or hurdles) to evaluate the potential cost-effectiveness of research proposals. The framework permits research priority setting based explicitly on the budget constraint faced by clinical practitioners and on the information available prior to prospective research. It demonstrates the link between the value of clinical research and the budgetary restrictions on service provision, and it provides practical tools to establish the optimal allocation of resources between areas of clinical research or between service provision and research.
Bayes Theorem↗