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Biomedical subjects

Mark Sculpher

Publications and source records attributed to Mark Sculpher.

32 records · Page 2Linked to original sources

Patients' preferences for the management of non-metastatic prostate cancer: discrete choice experiment.

OBJECTIVE: To establish which attributes of conservative treatments for prostate cancer are most important to men. DESIGN: Discrete choice experiment. SETTING: Two London hospitals. PARTICIPANTS: 129 men with non-metastatic prostate cancer, mean age 70 years; 69 of 118 (58%) with T stage 1 or 2 cancer at diagnosis. MAIN OUTCOME MEASURES: Men's preferences for, and trade-offs between, the attributes of diarrhoea, hot flushes, ability to maintain an erection, breast swelling or tenderness, physical energy, sex drive, life expectancy, and out of pocket expenses. RESULTS: The men's responses to changes in attributes were all statistically significant. When asked to assume a starting life expectancy of five years, the men were willing to make trade-offs between life expectancy and side effects. On average, they were most willing to give up life expectancy to avoid limitations in physical energy (mean three months) and least willing to trade life expectancy to avoid hot flushes (mean 0.6 months to move from a moderate to mild level or from mild to none). CONCLUSIONS: Men with prostate cancer are willing to participate in a relatively complex exercise that weighs up the advantages and disadvantages of various conservative treatments for their condition. They were willing to trade off some life expectancy to be relieved of the burden of troublesome side effects such as limitations in physical energy.

Aged↗

Cost effectiveness analysis of laparoscopic hysterectomy compared with standard hysterectomy: results from a randomised trial.

OBJECTIVE: To assess the cost effectiveness of laparoscopic hysterectomy compared with conventional hysterectomy (abdominal or vaginal). DESIGN: Cost effectiveness analysis based on two parallel trials: laparoscopic (n = 324) compared with vaginal hysterectomy (n = 163); and laparoscopic (n = 573) compared with abdominal hysterectomy (n = 286). PARTICIPANTS: 1346 women requiring a hysterectomy for reasons other than malignancy. MAIN OUTCOME MEASURE: One year costs estimated from NHS perspective. Health outcomes expressed in terms of QALYs based on women's responses to the EQ-5D at baseline and at three points during up to 52 weeks' follow up. RESULTS: Laparoscopic hysterectomy cost an average of 401 pounds sterling (708 dollars; 571 euros) more (95% confidence interval 271 pounds sterling to 542 pounds sterling) than vaginal hysterectomy but produced little difference in mean QALYs (0.0015, -0.015 to 0.018). Mean differences in cost and QALYs generated an incremental cost per QALY gained of 267 333 pounds sterling (471 789 dollars; 380 437 euros). The probability that laparoscopic hysterectomy is cost effective was below 50% for a large range of values of willingness to pay for an additional QALY. Laparoscopic hysterectomy cost an average of 186 pounds sterling (328 dollars; 265 euros) more than abdominal hysterectomy, although 95% confidence intervals crossed zero (-26 pounds sterling to 375 pounds sterling); there was little difference in mean QALYs (0.007, -0.008 to 0.023), resulting in an incremental cost per QALY gained of 26 571 pounds sterling (46 893 dollars; 37 813 euros). If the NHS is willing to pay 30 000 pounds sterling for an additional QALY, the probability that laparoscopic hysterectomy is cost effective is 56%. CONCLUSIONS: Laparoscopic hysterectomy is not cost effective relative to vaginal hysterectomy. Its cost effectiveness relative to the abdominal procedure is finely balanced.

Cost-Benefit Analysis↗

The use of probabilistic decision models in technology assessment : the case of total hip replacement.

There is increasing recognition that decision modelling is central to health technology assessment and, in particular, to analyses to support formal decision making regarding the funding of the use of new technologies. In part, the key role of decision analysis stems from the need to handle multiple sources of uncertainty in the available evidence. The use of probabilistic decision analysis is a means of reflecting the parameter uncertainty in models and presenting this in a comprehensible manner to decision makers. In this article, we demonstrate the potential role of probabilistic models using the case study of total hip replacement surgery.A cost-effectiveness model was constructed to compare the Charnley and Spectron hip prostheses in terms of lifetime costs and quality-adjusted life-years (QALYs). Revision rates were estimated from the Swedish National Total Hip Arthroplasty Register (1992-2000); the risk of revision with the Spectron prosthesis relative to the Charnley prosthesis was 0.67 (95% confidence interval [CI] 0.32, 1.02) for early revisions and 0.26 (95% CI 0.07, 0.46) for late revisions. This lower revision risk resulted in the Spectron generating more QALYs than the Charnley prosthesis. Based on mean costs and QALYs, the Spectron results in cost savings in younger patients, and generates incremental cost-effectiveness ratios of between pound1000 and pound16 000 in older patient groups. The probabilistic results from the model indicated that, if it is assumed that decision makers are willing to pay up to pound20 000 per additional QALY, the probability of the Spectron being the more cost-effective prosthesis ranged between 70% and 100%, depending on the age and sex of the patient.This article looks at the application of probabilistic decision modelling using total hip replacement as a case study to emphasis the need for decision models to quantify all sources of parameter uncertainty and to clearly distinguish parameter uncertainty from subgroup heterogeneity.

Adult↗

Incidence of fires and related injuries after giving out free smoke alarms: cluster randomised controlled trial.

OBJECTIVE: To measure the effect of giving out free smoke alarms on rates of fires and rates of fire related injury in a deprived multiethnic urban population. DESIGN: Cluster randomised controlled trial. SETTING: Forty electoral wards in two boroughs of inner London, United Kingdom. PARTICIPANTS: Primarily households including elderly people or children and households that are in housing rented from the borough council. INTERVENTION: 20 050 smoke alarms, fittings, and educational brochures distributed free and installed on request. MAIN OUTCOME MEASURES: Rates of fires and related injuries during two years after the distribution; alarm ownership, installation, and function. RESULTS: Giving out free smoke alarms did not reduce injuries related to fire (rate ratio 1.3; 95% confidence interval 0.9 to 1.9), admissions to hospital and deaths (1.3; 0.7 to 2.3), or fires attended by the fire brigade (1.1; 0.96 to 1.3). Similar proportions of intervention and control households had installed alarms (36/119 (30%) v 35/109 (32%); odds ratio 0.9; 95% confidence interval 0.5 to 1.7) and working alarms (19/118 (16%) v 18/108 (17%); 0.9; 0.4 to 1.8). CONCLUSIONS: Giving out free smoke alarms in a deprived, multiethnic, urban community did not reduce injuries related to fire, mostly because few alarms had been installed or were maintained.

Burns↗

Prevalence of working smoke alarms in local authority inner city housing: randomised controlled trial.

OBJECTIVES: To identify which type of smoke alarm is most likely to remain working in local authority inner city housing, and to identify an alarm tolerated in households with smokers. DESIGN: Randomised controlled trial. SETTING: Two local authority housing estates in inner London. PARTICIPANTS: 2145 households. INTERVENTION: Installation of one of five types of smoke alarm (ionisation sensor with a zinc battery; ionisation sensor with a zinc battery and pause button; ionisation sensor with a lithium battery and pause button; optical sensor with a lithium battery; or optical sensor with a zinc battery). MAIN OUTCOME MEASURE: Percentage of homes with any working alarm and percentage in which the alarm installed for this study was working after 15 months. RESULTS: 54.4% (1166/2145) of all households and 45.9% (465/1012) of households occupied by smokers had a working smoke alarm. Ionisation sensor, lithium battery, and there being a smoker in the household were independently associated with whether an alarm was working (adjusted odds ratios 2.24 (95% confidence interval 1.75 to 2.87), 2.20 (1.77 to 2.75), and 0.62 (0.52 to 0.74)). The most common reasons for non-function were missing battery (19%), missing alarm (17%), and battery disconnected (4%). CONCLUSIONS: Nearly half of the alarms installed were not working when tested 15 months later. Type of alarm and power source are important determinants of whether a household had a working alarm.

Electric Power Supplies↗

A rational framework for decision making by the National Institute For Clinical Excellence (NICE).

Regulatory and reimbursement authorities face uncertain choices when considering the adoption of health-care technologies. In this Viewpoint, we present an analytic framework that separates the issue of whether a technology should be adopted on the basis of existing evidence from whether more research should be demanded to support future decisions. We show the application of this framework to the assessment of heath-care technologies using a published analysis of a new drug treatment for Alzheimer's disease. The results of the analysis show that the amount and type of evidence required to support the adoption of a health technology will differ substantially between technologies with different characteristics. Additionally, the analysis can be used to aid the efficient design of research. We discuss the implications of adoption of this new framework for regulatory and reimbursement decisions.

Alzheimer Disease↗

Pre-operative optimisation employing dopexamine or adrenaline for patients undergoing major elective surgery: a cost-effectiveness analysis.

OBJECTIVE: To compare the cost and cost-effectiveness of a policy of pre-operative optimisation of oxygen delivery (using either adrenaline or dopexamine) to reduce the risk associated with major elective surgery, in high-risk patients. METHODS: A cost-effectiveness analysis using data from a randomised controlled trial (RCT). In the RCT 138 patients undergoing major elective surgery were allocated to receive pre-operative optimisation employing either adrenaline or dopexamine (assigned randomly), or to receive routine peri-operative care. Differential health service costs were based on trial data on the number and cause of hospital in-patient days and the utilisation of health care resources. These were costed using unit costs from a UK hospital. The cost-effectiveness analysis related differential costs to differential life-years during a 2 year trial follow-up. RESULTS: The mean number of in-patient days was 16 in the pre-optimised groups (19 adrenaline; 13 dopexamine) and 22 in the standard care group. The number (%) of deaths, over a 2 year follow-up, was 24 (26%) in the pre-optimised groups and 15 (33%) in the standard care group. The mean total costs were EUR 11,310 in the pre-optimised groups and EUR 16,965 in the standard care group. Life-years were 1.68 in the pre-optimised groups and 1.46 in the standard care group. The probability that pre-operative optimisation is less costly than standard care is 98%. The probability that it dominates standard care is 93%. CONCLUSIONS: Based on resource use and effectiveness data collected in the trial, pre-operative optimisation of high-risk surgical patients undergoing major elective surgery is cost-effective compared with standard treatment.

Bayes Theorem↗

Shared treatment decision making in a collectively funded health care system: possible conflicts and some potential solutions.

In recent years there has been a growth in the advocacy of shared decision making (SDM) between clinicians and patients as a way of practicing medicine. Although there is a range of perspectives on what SDM means, in essence it refers to greater involvement of the individual patient in deliberations about appropriate forms of clinical management. The patient's perception of the role of the doctor in SDM is crucial: for it to work successfully, the patient needs to be able to be confident that the doctor is focused on which treatment will generate the greatest benefit for them. However, the doctor also has responsibilities to others, in particular to other patients and potential patients within the collectively funded health care system. This dual responsibility can create a range of dilemmas for the clinician in the context of SDM: Should they inform patients about all effective treatments or just those that the health care system considers cost-effective? Do they risk losing patients from their books if they inform patients about their responsibilities to the health care system? SDM also raises questions about the wider principles of the health care system: Are its equity principles consistent with SDM? Should patients with a strong preference for an effective but non-cost-effective treatment be permitted to pay for it privately? This paper describes the nature of the conflicts that are likely to emerge if SDM diffuses within collectively funded health care systems, and considers a range of policy responses. It argues that the risk of conflict may be reduced by making a clear distinction between clinical guidelines (focusing on effectiveness) and system guidelines (focusing on cost-effectiveness).

Communication↗

Cost-effectiveness analysis of stratified versus stepped care strategies for acute treatment of migraine: The Disability in Strategies for Care (DISC) Study.

BACKGROUND: The Disability in Strategies for Care (DISC) study was the first large randomised controlled trial to compare alternative treatment strategies in the acute treatment of migraine. With 835 patients in its intention-to-treat efficacy analysis, DISC compared a stratified care strategy, where initial therapy was based on clinical need as determined by the Migraine Disability Assessment Scale (MIDAS) and two stepped care strategies (across attacks and within attacks), where first-line therapy with a simple combination analgesic was escalated, if response had been inadequate, to zolmitriptan, a migraine-specific therapy. OBJECTIVE: To report on the cost effectiveness of these three strategies from a societal perspective. STUDY DESIGN AND METHODS: A cost-effectiveness analysis was undertaken using data from the DISC study, and including both health service and productivity costs. Data were collected prospectively on drug usage (main therapy and rescue medication); resource use associated with adverse events was estimated by a clinician blinded to treatment strategy. Health service resource use was costed using UK unit costs (1999 to 2000 values). Data were collected using diary cards on the amount of time patients lost from work, and on reduced effectiveness at work, due to a migraine attack. This facilitated an estimate of the productivity costs associated with the treatment strategies. To assess cost effectiveness, the differences in costs between the strategies were related to the two primary outcome measures in the trial: headache response 2 hours after initial therapy and disability-adjusted time during the first 4 hours after initial therapy. RESULTS: Although the mean health service cost was higher in the stratified care group (mean over 6 attacks of pound 28.25 versus pound 11.74 and pound 23.15 in the stepped care across attacks group and within attacks group, respectively), mean productivity costs over 6 attacks were lower in the stratified group (pound 112.22 versus pound 144.70 and pound 127.53). The total mean cost over six attacks was, therefore, lowest in the stratified care group (pound 138.95 compared with pound 157.19 in the stepped care across attacks group and pound 148.53 in the stepped care within attacks group), although these differences did not reach statistical significance. In terms of headache response, stratified care was statistically significantly more effective than both forms of stepped care. Using disability-adjusted time, stratified care was statistically significantly more effective than stepped care across attacks, but not against stepped care within attacks. CONCLUSION: Given its lower mean costs and higher mean effectiveness, a stratified care strategy, which included zolmitriptan, was the dominant strategy and was unequivocally more cost effective from a societal perspective than either stepped care strategy. When the uncertainty around these means was considered, stratified care had the highest probability of being cost effective.

Cost-Benefit Analysis↗

Establishing the cost-effectiveness of new pharmaceuticals under conditions of uncertainty--when is there sufficient evidence?

Decisions about which health-care interventions represent adequate value to collectively funded health-care systems are as widespread as they are unavoidable. In the case of new pharmaceuticals, many countries now require formal cost-effectiveness analysis to inform this decision-making process. This requires evidence on parameters associated with health-related utilities, treatment effects, resource use, and costs, for which data from available regulatory trials are invariably absent or highly uncertain. This uncertainty results from a number of factors including the predominance of intermediate end points in the clinical evidence-base and the limited period of follow-up of patients in clinical studies. Despite these imperfections in the evidence base, decisions about whether new pharmaceuticals are sufficiently cost-effective for reimbursement cannot be side-stepped. Data limitations do, however, require the use of rigorous analytical methods to support decision making. Probabilistic decision models and value of information analysis offer a means of structuring decision problems, synthesizing all available data, characterizing the uncertainty in the decision, quantifying the cost of uncertainty, and establishing the expected value of perfect information. This analytical framework is important because it addresses two fundamental questions about new pharmaceuticals. First, is the product expected to be cost-effective on the basis of existing evidence? Second, is additional research concerning the product itself cost-effective? In addressing these questions, the analytical framework can establish when sufficient evidence exists to sustain a claim for a new pharmaceutical to be cost-effective.

Cost-Benefit Analysis↗

Probabilistic analysis and computationally expensive models: Necessary and required?

OBJECTIVE: To assess the importance of considering decision uncertainty, the appropriateness of probabilistic sensitivity analysis (PSA), and the use of patient-level simulation (PLS) in appraisals for the National Institute for Health and Clinical Excellence (NICE). METHODS: Decision-makers require estimates of decision uncertainty alongside expected net benefits (NB) of interventions. This requirement may be difficult in computationally expensive models, for example, those employing PLS. NICE appraisals published up until January 2005 were reviewed to identify those where the assessment group utilized a PLS model structure to estimate NB. After identifying PLS models, all appraisals published in the same year were reviewed. RESULTS: Among models using PLS, one out of six conducted PSA, compared with 16 out of 24 cohort models. Justification for omitting PSA was absent in most cases. Reasons for choosing PLS included treatment switching, sampling patient characteristics and dependence on patient history. Alternative modeling approaches exist to handle these, including semi-Markov models and emulators that eliminate the need for two-level simulation. Stochastic treatment switching and sampling baseline characteristics do not inform adoption decisions. Modeling patient history does not necessitate PLS, and can depend on the software used. PLS addresses nonlinear relationships between patient variability and model outputs, but other options exist. Increased computing power, emulators or closed-form approximations can facilitate PSA in computationally expensive models. CONCLUSIONS: In developing models analysts should consider the dual requirement of estimating expected NB and characterizing decision uncertainty. It is possible to develop models that meet these requirements within the constraints set by decision-makers.

Computer Simulation↗

Assessing the cost-effectiveness of new pharmaceuticals in epilepsy in adults: the results of a probabilistic decision model.

Epilepsy currently affects more than 400,000 people in the United Kingdom and 2.3 million in the United States. Drug therapy is the mainstay of treatment for patients with epilepsy, but therapies vary widely in their mechanism of action and acquisition cost. This article describes a decision model developed for the National Institute for Clinical Excellence in the United Kingdom. It compares the long-term cost-effectiveness of drugs licensed in adults for use in 3 situations: monotherapy for newly diagnosed patients, monotherapy for refractory patients, and combination therapy for refractory patients. The analysis separately considers the treatment of partial and generalized seizures. The full range of pharmaceutical therapies feasibly used in the UK health system was included in the analysis. The analysis showed that, on the basis of existing evidence, for newly diagnosed patients with partial seizures, carbamazepine and valproate are likely to be the most cost-effective mono-therapies. Carbamazepine is likely to be the most cost-effective 2nd-line monotherapy for refractory patients, and oxcarbazepine would probably be the most cost-effective adjunctive therapy for refractory patients if the willingness to pay for additional health benefits is greater than 18,000 pounds per quality-adjusted life year (QALY). For patients with generalized seizures, valproate is most likely to be cost-effective for newly diagnosed patients. For refractory patients, adjunctive topiramate is more cost-effective than monotherapy alone if the willingness to pay for additional health benefits is greater than 35,000 pounds per QALY. There is, however, considerable uncertainty regarding these results. Some of the methodological features of the study will be of value in designing cost-effectiveness analyses of other therapies for chronic conditions. These include the methods used to deal with the absence of head-to-head trial data and the need to reflect time dependency in Markov transition probabilities.

Adult↗

Cost-effectiveness analysis of treatments for chronic disease: using R to incorporate time dependency of treatment response.

When constructing decision-analytic models to evaluate the cost-effectiveness of alternative treatments, we often need to extrapolate beyond the available experimental data, as these typically relate to a limited period starting from the initiation of a new treatment or the diagnosis of the current disease state. We may also be required to extrapolate beyond the available experimental evidence to compare potential treatment sequences. Markov models are often used for this extrapolation. These models have the defining assumption that future transition probabilities are independent of past transitions. This means that, in general, transition probabilities cannot be conditional of the time spent in a given state. Where data exist to show that the risks of transition are conditional on the time spent in the treatment state, the simplifying Markov assumption can result in a loss in the model's "face validity," and misleading results might be generated. Several methods are available to incorporate time dependency into transition probabilities based on standard methods and software. These include the inclusion of tunnel states in Markov models and patient-level simulation, where a series of individual patients are simulated. This article considers the features and limitations of these methods and also describes a novel approach to building time dependency into a Markov model by incorporating an additional time dimension resulting in a "semi-Markov" model. An example of the implementation of such a model, using the R statistical programming language, is illustrated using a cost-effectiveness model for new epilepsy therapies.

Chronic Disease↗

An iterative Bayesian approach to health technology assessment: application to a policy of preoperative optimization for patients undergoing major elective surgery.

PURPOSE: This article presents an iterative framework for managing the dynamic process of health technology assessment. The framework uses Bayesian statistical decision theory and value of information (VOI) analysis to inform decision making regarding appropriate patient management and to direct future research effort over the lifetime of a technology. Within the article, the framework is applied to a policy decision regarding preoperative patient management before major elective surgery, for which trial data are available. METHOD: The evidence available prior to the trial is used to determine the appropriate method of patient management and to ascertain whether, at the time of commissioning, the trial was potentially worthwhile. The prior information is then updated with the trial data via a Bayesian analysis using informative priors. This post trial information set is then used to reassess the appropriate method for patient management and to determine whether there is a requirement for any further research. RESULTS: Prior to the trial, preoperative optimization with dopexamine is identified as the appropriate method of patient management. The results of the VOI analysis suggest that a short-term trial was potentially worthwhile (population expected value of perfect information [EVPI] = 48 million pounds sterling). Following the trial, the uncertainty surrounding the choice of appropriate patient management and the potential worth of further research had increased (population EVPI = 67 million pounds sterling). CONCLUSIONS: The article demonstrates the value and practicality of applying the iterative framework to the dynamic process of health technology assessment. It is only by formally incorporating all of the information available to decision makers, through informed priors, that the appropriate decisions can be made.

Aged↗