Subcutaneous and sublingual immunotherapy for seasonal allergic rhinitis: a systematic review and indirect comparison.

BACKGROUND: Severe allergic rhinitis uncontrolled by pharmacotherapy can adversely affect quality of life. Both subcutaneous immunotherapy (SCIT) and sublingual immunotherapy (SLIT) have demonstrated effectiveness in this patient group; however, it remains uncertain which route of administration is more effective. OBJECTIVES: We sought to update existing systematic reviews on the clinical effectiveness of SCIT and SLIT versus placebo, to undertake a systematic review of head-to-head trials, and to compare the relative effectiveness of SCIT and SLIT in an adjusted indirect comparison. METHODS: Standard systematic review methods aimed at minimizing bias were used. Double-blind, randomized, placebo-controlled trials of SCIT or SLIT or trials of SCIT versus SLIT were included. Meta-analysis and indirect comparison meta-analysis with meta-regression were performed. RESULTS: Updated meta-analyses confirmed statistically significant benefits for SCIT and SLIT compared with placebo in adults and, to a lesser extent, in children. Only 1 head-to-head trial met the inclusion criteria; both this and the indirect comparisons did not provide conclusive results in favor of either SCIT or SLIT based on symptom-medication or quality-of-life scores. There was a trend toward favoring SCIT for symptom and medication scores. CONCLUSIONS: Although there is clear evidence of effectiveness of both SCIT and SLIT, superiority of one mode of administration over the other could not be consistently demonstrated through indirect comparison, and further research is needed to establish the comparative effectiveness of SCIT versus SLIT.

Meta-analysis of the accuracy of two diagnostic tests used in combination: application to the ddimer test and the wells score for the diagnosis of deep vein thrombosis.

OBJECTIVES: It is standard practice for diagnostic tests to be evaluated against gold standards in isolation. In routine clinical practice, however, it is commonplace for multiple tests to be used before making definitive diagnoses. This article describes a meta-analytic modeling framework developed to estimate the accuracy of the combination of two diagnostic tests, accounting for the likely nonindependence of the tests. METHODS: A novel multicomponent framework was developed to synthesize information available on different parameters in the model. This allows data to be included from studies evaluating single tests or both tests. Different likelihoods were specified for the different sources of data and linked by means of common parameters. The framework was applied to evaluate the diagnostic accuracy of the Ddimer test and the Wells score for deep vein thrombosis, and the results were compared with those of a model in which independence of tests was assumed. All models were evaluated by using Bayesian Markov chain Monte Carlo simulation methods. RESULTS: The results showed the importance of allowing for the (likely) nonindependence of tests in the meta-analysis model when evaluating a combination of diagnostic tests. The analysis also highlighted the relatively limited impact of those studies that evaluated only one of the two tests of interest. CONCLUSIONS: The models developed allowed the assumption of independence between diagnostic tests to be relaxed while combining a broad array of relevant information from disparate studies. The framework also raises questions regarding the utility of studies limited to the evaluation of single diagnostic tests.

Evaluating the cost-effectiveness of diagnostic tests in combination: is it important to allow for performance dependency?

OBJECTIVES: To investigate the importance of accounting for potential performance dependency when evaluating the cost-effectiveness of two diagnostic tests used in combination. METHODS: Two meta-analysis models were fitted to estimate the diagnostic accuracy of Wells score and Ddimer in combination. The first model assumes that the two tests perform independently of one another; thus, two separate meta-analyses were fitted to the Ddimer and Wells score data and then combined. The second model allows for any performance dependency of the two tests by incorporating published data on the accuracy of Ddimer stratified by Wells score, as well as studies of Ddimer alone and Wells score alone. The results from the two meta-analysis models were input into a decision model to assess the impact that assumptions regarding performance dependency have on the overall cost-effectiveness of the tests. RESULTS: The results highlight the importance of accounting for potential performance dependency when evaluating the cost-effectiveness of diagnostic tests used in combination. In our example, assuming the diagnostic performance of the two tests to be independent resulted in the strategy "Wells score moderate/high risk treated for DVT and Wells score low risk tested further with Ddimer" being identified as the most cost-effective at the £20,000 willingness-to-pay threshold (probability cost-effective 0.8). However, when performance dependency is modeled, the most cost-effective strategies were "Ddimer alone" and "Wells score low/moderate risk discharged and Wells score high risk further tested with Ddimer" (probability cost-effective 0.4). CONCLUSIONS: When evaluating the effectiveness and cost-effectiveness of diagnostic tests used in combination, failure to account for diagnostic performance dependency may lead to erroneous results and nonoptimal decision making.

How is evidence on test performance synthesized for economic decision models of diagnostic tests? A systematic appraisal of Health Technology Assessments in the UK since 1997.

OBJECTIVES: The study aims to assess how evidence on diagnostic test accuracy is synthesized and used to inform economic decision modeling for HTA. METHODS: All reports evaluating diagnostic test via an economic decision model published by the NHS Research and Development Health Technology Assessment (HTA) program since 1997 were identified. The methods for evidence synthesis of diagnostic test accuracy data and its use in economic decision modeling in this sample were reviewed. RESULTS: Forty-four HTA reports out of 474 concerned diagnostic accuracy, of which 11 did not do any economic evaluation. Of the remaining 33 HTAs, 14 conducted meta-analyses of diagnostic accuracy in the clinical review but only 8 used such pooled estimates to inform the decision model. A number of meta-analysis methods ranging in complexity were applied to estimate diagnostic accuracy. Nevertheless, when it came to informing the economic decision model, the majority of reviews used independent meta-analytic estimates of sensitivity and specificity. CONCLUSIONS: Often, very simplistic methods to estimate diagnostic test accuracy were used for purposes of informing an economic decision model. The assumptions made by the simplistic methods are usually invalid which may lead to suboptimal decisions being made. It is desirable that decision modelers become aware of the rapid evolution of meta-analysis methods in this area; however, further research is still required to identify how the pooled results obtained from the different meta-analysis models should best be used to inform economic decision models.

Cost-effectiveness of the implantable HeartMate II left ventricular assist device for patients awaiting heart transplantation.

BACKGROUND: Left ventricular assist devices (LVADs) are being proposed as a life-saving therapeutic alternative to conventional medical management for people with end-stage heart failure awaiting transplantation. However, cost-effectiveness assessments of first-generation LVADs have not been encouraging. The cost-effectiveness of the enhanced second-generation LVAD HeartMate II (Thoratec, Pleasanton, CA) is estimated here. METHODS: A probabilistic Markov model was developed to extrapolate survival, utility, and resource use over the total lifetime of a hypothetic cohort of patients with end-stage heart failure under the 2 competing therapeutic strategies, using the most robust and recently published evidence about their performance. Cost data are based on UK activity to consider reimbursement in the UK National Health Service setting. RESULTS: HeartMate II had a mean cost per quality-adjusted life-year (QALY) of £258,922 ($414,275). The sensitivity analysis showed that 2 factors mainly explain why HeartMate II is not a cost-effectiveness strategy as a bridge-to-transplant: (1) the survival of heart transplant candidates treated conventionally while on the waiting list has significantly improved in recent years, and (2) the high acquisition cost of the device, £94,200 ($150,720). CONCLUSIONS: Although HeartMate II LVAD implantation significantly increases survival compared with conventional medical management, it does not provide good value for the money spent according to established thresholds of cost-effectiveness in the UK. HeartMate II is unlikely to become cost-effective unless the additional survival gained by its use raises and/or the device is given free of charge. Therefore, its implantation to transplant candidates lacks justification in terms of cost-effectiveness.

Evaluation of a predevelopment service delivery intervention: an application to improve clinical handovers.

BACKGROUND: We developed a method to estimate the expected cost-effectiveness of a service intervention at the design stage and 'road-tested' the method on an intervention to improve patient handover of care between hospital and community. METHOD: The development of a nine-step evaluation framework: 1. Identification of multiple endpoints and arranging them into manageable groups; 2. Estimation of baseline overall and preventable risk; 3. Bayesian elicitation of expected effectiveness of the planned intervention; 4. Assigning utilities to groups of endpoints; 5. Costing the intervention; 6. Estimating health service costs associated with preventable adverse events; 7. Calculating health benefits; 8. Cost-effectiveness calculation; 9. Sensitivity and headroom analysis. RESULTS: Literature review suggested that adverse events follow 19% of patient discharges, and that one-third are preventable by improved handover (ie, 6.3% of all discharges). The intervention to improve handover would reduce the incidence of adverse events by 21% (ie, from 6.3% to 4.7%) according to the elicitation exercise. Potentially preventable adverse events were classified by severity and duration. Utilities were assigned to each category of adverse event. The costs associated with each category of event were obtained from the literature. The unit cost of the intervention was €16.6, which would yield a Quality Adjusted Life Year (QALY) gain per discharge of 0.010. The resulting cost saving was €14.3 per discharge. The intervention is cost-effective at approximately €214 per QALY under the base case, and remains cost-effective while the effectiveness is greater than 1.6%. CONCLUSIONS: We offer a usable framework to assist in ex ante health economic evaluations of health service interventions.

Pharmacological treatments for neovascular age-related macular degeneration: can mixed treatment comparison meta-analysis be useful?

OBJECTIVE: To investigated the use of mixed treatment comparison (MTC) meta-analysis models to summarize results from randomized clinical trials (RCTs) on approved pharmacological treatments for neovascular age-related macular degeneration (AMD). METHODS: The number of patients with visual loss or visual gain of 3 or more lines of visual acuity (15 ETDRS letters) at 1 year was extracted from 10 RCTs including patients with neovascular AMD and comparing at least one of the following drugs to sham treatment (1080 control patients, 8 studies) or to each other: verteporfin photodynamic therapy (PDT, 1124 patients, 4 studies), pegaptanib (904 patients, 2 twin studies), ranibizumab (984 patients, 4 studies). Both frequentist and Bayesian methods were used to conduct MTCs. RESULTS: Direct and indirect evidence was available and found to be overall in good agreement for the comparisons: PDT vs. control, ranibizumab vs. control, ranibizumab vs. PDT. Bayesian model fit was better for a model including a covariate coding for the PIER study ranibizumab regimen, i.e. quarterly injections after three initial monthly doses. In the MTC model, monthly ranibizumab was superior to PDT and pegaptanib, and could not be shown to be better than PIER ranibizumab regarding visual loss, being estimates imprecise. Ranibizumab PIER retreatment regimen was better than PDT and pegaptanib regarding visual loss, whereas an advantage over them regarding visual gain was suggested by a frequentist MTC approach, but not by a Bayesian approach, which was more conservative. A limitation of our MTC model was that only two twin studies connected pegaptanib to the treatment network, and only one study was available for the PIER ranibizumab regimen. CONCLUSION: The clinically heterogeneous and sparse typology of the evidence is a limitation to carry out MTC meta-analyses of approved pharmacological treatments for neovascular AMD. Ranibizumab was found to be the most effective treatment compared to PDT and pegaptanib, although this superiority cannot be demonstrated regarding visual gain for the PIER ranibizumab regimen in a Bayesian analytic setting. We did not find RCTs which investigated the current ranibizumab as needed retreatment regimen approved in Europe.

Bayesian model selection for meta-analysis of diagnostic test accuracy data: Application to Ddimer for deep vein thrombosis.

A number of statistical models have been developed for meta-analysis (MA) of diagnostic test (DT) accuracy data. Here we consider these alternative MA models, explore the relationships between them, and consider the use of the deviance information criteria (DIC) to decide which is the most appropriate model for a given dataset. A Bayesian statistical approach is adopted throughout. The alternative MA models are applied to a dataset of 198 assays of Ddimer to diagnose deep vein thrombosis. In this example, based on the DIC, a bivariate random effects model for sensitivity and specificity fitted the data best. When considering the inclusion of study level covariates, allowing sensitivity to vary by study setting further improved the fit of the model. The model fitting approach is then repeated for a subset of the data, which highlights the less decisive results obtained when using the DIC with a more limited dataset. Formal approaches to model selection are often overlooked in an MA context; however, they offer sensible rationale to the analysis, particularly for complex models such as those proposed for DT accuracy. Specifically, the use of the DIC statistic appears to be well suited for deciding between potentially complex mixed-effect MA models, possibly including covariates. Copyright © 2010 John Wiley & Sons, Ltd.