Biomedical subjects

Neil Hawkins

Publications and source records attributed to Neil Hawkins.

5 recordsLinked to original sources

PubMed2006

Cost-effectiveness of a supplementary class-based exercise program in the treatment of knee osteoarthritis.

OBJECTIVES: The aim of this study was to assess the cost-effectiveness of a class-based exercise program supplementing a home-based program when compared with a home-based program alone. In addition, we estimated the probability that the supplementary class program is cost-effective over a range of values of a decision maker's willingness to pay for an additional quality-adjusted life-year (QALY). METHODS: The resource use and effectiveness data were collected as part of the clinical trial detailed elsewhere. Unit costs were estimated from published sources. The net benefit approach to cost-effectiveness analysis is used to estimate the probability of the intervention being cost-effective. RESULTS: The addition of a supplementary class-based group results in an increase in QALYs and lower costs. For all plausible values of a decision maker's willingness to pay for a QALY, the supplementary class group is likely to be cost-effective. CONCLUSIONS: The addition of a class-based exercise program is likely to be cost-effective and, on current evidence, should be implemented.

Cost-Benefit Analysis↗

PubMed2005

Estimating mean QALYs in trial-based cost-effectiveness analysis: the importance of controlling for baseline utility.

In trial-based cost-effectiveness analysis baseline mean utility values are invariably imbalanced between treatment arms. A patient's baseline utility is likely to be highly correlated with their quality-adjusted life-years (QALYs) over the follow-up period, not least because it typically contributes to the QALY calculation. Therefore, imbalance in baseline utility needs to be accounted for in the estimation of mean differential QALYs, and failure to control for this imbalance can result in a misleading incremental cost-effectiveness ratio. This paper discusses the approaches that have been used in the cost-effectiveness literature to estimate absolute and differential mean QALYs alongside randomised trials, and illustrates the implications of baseline mean utility imbalance for QALY calculation. Using data from a recently conducted trial-based cost-effectiveness study and a micro-simulation exercise, the relative performance of alternative estimators is compared, showing that widely used methods to calculate differential QALYs provide incorrect results in the presence of baseline mean utility imbalance regardless of whether these differences are formally statistically significant. It is demonstrated that multiple regression methods can be usefully applied to generate appropriate estimates of differential mean QALYs and an associated measure of sampling variability, while controlling for differences in baseline mean utility between treatment arms in the trial.

Cost-Benefit Analysis↗

PubMedDate not supplied

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↗

PubMedDate not supplied

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↗

PubMedDate not supplied

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↗