Cost-effectiveness of azithromycin for preventing Mycobacterium avium complex infection in HIV-positive patients in the era of highly active antiretroviral therapy. The Swiss HIV Cohort Study

A Bayesian Approach to Net Health Benefits: An Illustration and Application to Modeling HIV Prevention

Purpose. To conduct a cost-effectiveness analysis of HIV prevention when costs and effects cannot be measured directly. To quantify the total estimation of uncertainty due to sampling variability as well as inexact knowledge of HIV transmission parameters. Methods. The authors focus on estimating the incremental net health benefit (INHB) in a randomized trial of HIV prevention with intervention and control conditions. Using a Bernoulli model of HIV transmission, changes in the participants’ risk behaviors are converted into the number of HIV infections averted. A sampling model is used to account for variation in the behavior measurements. Bayes’s theorem and Monte Carlo methods are used to attain the stated objectives. Results. The authors obtained a positive mean INHB of 0.0008, indicating that advocacy training is just slightly favored over the control condition for men, assuming a $50,000 per quality-adjusted life year (QALY) threshold. To be confident of a positive INHB, the decision maker would need to spend more than $100,000 per QALY.

Parameterization of treatment effects for meta-analysis in multi-state Markov models

Standard approaches to analysis of randomized controlled trials (RCTs) using Markov models make it difficult to generalize treatment effects to new patient groups and synthesize evidence across trials. This paper demonstrates how pair-wise and mixed treatment comparison meta-analysis can be applied to event history data for disease progression reported by RCTs. The data, in the form of aggregated discrete time transitions, have a multi-nomial likelihood. In order for evidence synthesis to be performed a structured approach to modelling the differences in the effects of the different treatments must be taken. A multi-state continuous-time Markov model similar to others used in published economic evaluations of asthma treatments is developed, with transition rates related to the likelihood via Kolmogorov's forward equations. The formulation in terms of rates allows a flexible characterization of summary treatment effects. These ideas are applied to an illustrative data set consisting of a set of five trials comparing eight different treatments for asthma. A range of models is developed in which the relative treatment effects act on forward, backward transitions, or both, and models are compared using the DIC. Bayesian inferential techniques are used and the parameters are estimated using MCMC simulation in WinBUGS. An intuitively appealing mechanism of action involving a single parameter acting on all backward transitions was identified for the relative effects of the treatments, which allowed the estimation of a pooled treatment effect, allowing us to rank the different treatment options within each connected evidence network to ascertain which were the most clinically effective.

Incremental cost-effectiveness ratio and incremental net-health benefit: two sides of the same coin

In recent years, an alternative framework for cost-effectiveness analyses has been growing in popularity. Instead of the incremental cost-effectiveness ratio for which statistical inference is often difficult, the incremental net-health benefit (INHB), a linear transformation of incremental costs and effectiveness, has been utilized. The linear structure of this statistic allows easy computation and interpretation of confidence intervals, hypothesis tests and acceptability curves. It is often difficult, however, to switch decision-making procedures without first verifying the appropriateness of the new methods. In this paper, we demonstrate the decision-making similarities between the INHB and the incremental cost-effectiveness ratio and describe how the INHB can be used to clarify inference of the incremental cost-effectiveness ratio. We also describe the two statistics in terms of the DeltaE-DeltaC plane, thus allowing both a mathematical and graphical comparison of these similarities. We conclude with a general discussion of cost-effectiveness analyses and advocate Bayesian, rather than frequentist inference as the more intuitive and powerful decision-making framework.

Current treatment of atypical mycobacteriosis

BACKGROUND

Atypical mycobacteria are a heterogeneous group of organisms that are of increasing importance because of the growing number of infections they cause. This rising rate of infection is due mainly to the increase in the number of susceptible (and especially immunosuppressed) patients.

OBJECTIVE

To revise the currently used treatment schemes of the most commonly isolated atypical mycobacteria.

METHODS

Literature review using reference books and PubMed with specific keywords for each mycobacteria.

RESULTS/CONCLUSION

The first important step in the management of atypical mycobacteria is to recognize the true infections caused by these organisms. The treatment required varies according to species. Well-characterized combinations exist for most common isolates, with the use of first-line antituberculous drugs (isoniazid, rifampin, ethambutol), clarithromycin, aminoglycosides and/or quinolones for slowly growing species (Mycobacterium avium complex, Mycobacterium kansasii, Mycobacterium xenopi, Mycobacterium ulcerans, Mycobacterium marinum, Mycobacterium lentiflavum, Mycobacterium malmoense) and macrolides, quinolones, amikacin and other antibiotics for rapidly growing mycobacteria (Mycobacterium abscessus, Mycobacterium chelonae, Mycobacterium fortuitum). Surgical therapy is also important for some species (Mycobacterium ulcerans, Mycobacterium scrofulaceum) and for localized infections. The treatment of uncommon species is not well defined and is determined by the results of in vitro tests of individual strains. Because of the increasing number of resistant strains, new antibiotics need to be used for the treatment of these strains.

An opportunity cost approach to sample size calculation in cost-effectiveness analysis

The inclusion of economic evaluations as part of clinical trials has led to concerns about the adequacy of trial sample size to support such analysis. The analytical tool of cost-effectiveness analysis is the incremental cost-effectiveness ratio (ICER), which is compared with a threshold value (lambda) as a method to determine the efficiency of a health-care intervention. Accordingly, many of the methods suggested to calculating the sample size requirements for the economic component of clinical trials are based on the properties of the ICER. However, use of the ICER and a threshold value as a basis for determining efficiency has been shown to be inconsistent with the economic concept of opportunity cost. As a result, the validity of the ICER-based approaches to sample size calculations can be challenged. Alternative methods for determining improvements in efficiency have been presented in the literature that does not depend upon ICER values. In this paper, we develop an opportunity cost approach to calculating sample size for economic evaluations alongside clinical trials, and illustrate the approach using a numerical example. We compare the sample size requirement of the opportunity cost method with the ICER threshold method. In general, either method may yield the larger required sample size. However, the opportunity cost approach, although simple to use, has additional data requirements. We believe that the additional data requirements represent a small price to pay for being able to perform an analysis consistent with both concept of opportunity cost and the problem faced by decision makers.

Cost-effectiveness of genotypic antiretroviral resistance testing in HIV-infected patients with treatment failure

Background

Genotypic antiretroviral resistance testing (GRT) in HIV infection with drug resistant virus is recommended to optimize antiretroviral therapy, in particular in patients with virological failure. We estimated the clinical effect, cost and cost-effectiveness of using GRT as compared to expert opinion in patients with antiretroviral treatment failure.

Methods

We developed a mathematical model of HIV disease to describe disease progression in HIV-infected patients with treatment failure and compared the incremental impact of GRT versus expert opinion to guide antiretroviral therapy. The analysis was conducted from the health care (discount rate 4%) and societal (discount rate 2%) perspective. Outcome measures included life-expectancy, quality-adjusted life-expectancy, health care costs, productivity costs and cost-effectiveness in US Dollars per quality-adjusted life-year (QALY) gained. Clinical and economic data were extracted from the large Swiss HIV Cohort Study and clinical trials.

Results

Patients whose treatment was optimized with GRT versus expert opinion had an increase in discounted life-expectancy and quality-adjusted life-expectancy of three and two weeks, respectively. Health care costs with and without GRT were $US 421,000 and $US 419,000, leading to an incremental cost-effectiveness ratio of $US 35,000 per QALY gained. In the analysis from the societal perspective, GRT versus expert opinion led to an increase in discounted life-expectancy and quality-adjusted life-expectancy of three and four weeks, respectively. Health care costs with and without GRT were $US 551,000 and $US 549,000, respectively. When productivity changes were included in the analysis, GRT was cost-saving.

Conclusions

GRT for treatment optimization in HIV-infected patients with treatment failure is a cost-effective use of scarce health care resources and beneficial to the society at large.

The contrast and convergence of Bayesian and frequentist statistical approaches in pharmacoeconomic analysis

The application of Bayesian statistical analyses has been facilitated in recent years by methodological advances and an increasing complexity necessitated within research. Substantial debate has historically accompanied this analytic approach relative to the frequentist method, which is the predominant statistical ideology employed in clinical studies. While the essence of the debate between the two branches of statistics centres on differences in the use of prior information and the definition of probability, the ramifications involve the breadth of research design, analysis and interpretation. The purpose of this paper is to discuss the application of frequentist and Bayesian statistics in the pharmacoeconomic assessment of healthcare technology. A description of both paradigms is offered in the context of potential advantages and disadvantages, and applications within pharmacoeconomics are briefly addressed. Additional considerations are presented to stimulate further development and to direct appropriate applications of each method such that the integrity and robustness of scientific inference be strengthened.

Disseminated mycobacterium avium-intracellulare complex (MAC) infection in the era of effective antiretroviral therapy: is prophylaxis still indicated?

Before highly active antiretroviral therapies (HAART) were available for the treatment of persons with HIV infection, disseminated Mycobacterium avium-intracellulare complex (MAC) infection was one of the most common opportunistic infections that affected people living with AIDS. Routine use of chemoprophylaxis with a macrolide has been advocated in guidelines for the treatment of HIV-infected individuals if they have a circulating CD4+ cell count of < or =50 cells/microL. In addition, lifelong prophylaxis for disease recurrence has been recommended for those with a history of disseminated MAC infection. The introduction of HAART has resulted in a remarkable decline in the incidence of opportunistic infections and death among persons living with AIDS. Considerable reconstitution of functional immune responses against opportunistic infections can be achieved with HAART. In the case of infection with MAC, there has been a substantial reduction in the incidence of disseminated infections in the HAART era, even in countries where the use of MAC prophylaxis was never widely accepted. Moreover, the clinical picture of MAC infections in patients treated with potent antiretroviral therapies has shifted from a disseminated disease with bacteraemia to a localised infection, presenting most often with lymphadenopathy and osteomyelitis. Data from several recently conducted randomised, double-blind, placebo-controlled trials led to the current practice of discontinuing primary and secondary prophylaxis against disseminated MAC infections at stable CD4+ cell counts >100 cells/microL. These recommendations are still conservative as primary or secondary disseminated MAC infections are only rarely seen in patients who respond to HAART, despite treatment initiation at very low CD4+ cell counts. Potential adverse effects of macrolide therapy and drug interactions with antiretrovirals also metabolised via the cytochrome P450 enzyme system must be critically weighed against the marginal benefit that MAC prophylaxis may provide in addition to treatment with HAART. These authors feel that, unless patients who initiate HAART at low CD4+ cell counts do not respond to HIV-treatment, routine MAC prophylaxis should not be recommended. Nevertheless, the patient population for whom MAC prophylaxis may still be indicated in the era of HAART needs to be identified in prospectively designed clinical trials.

Bayesian approaches to multiple sources of evidence and uncertainty in complex cost-effectiveness modelling

Increasingly complex models are being used to evaluate the cost-effectiveness of medical interventions. We describe the multiple sources of uncertainty that are relevant to such models, and their relation to either probabilistic or deterministic sensitivity analysis. A Bayesian approach appears natural in this context. We explore how sensitivity analysis to patient heterogeneity and parameter uncertainty can be simultaneously investigated, and illustrate the necessary computation when expected costs and benefits can be calculated in closed form, such as in discrete-time discrete-state Markov models. Information about parameters can either be expressed as a prior distribution, or derived as a posterior distribution given a generalized synthesis of available data in which multiple sources of evidence can be differentially weighted according to their assumed quality. The resulting joint posterior distributions on costs and benefits can then provide inferences on incremental cost-effectiveness, best presented as posterior distributions over net-benefit and cost-effectiveness acceptability curves. These ideas are illustrated with a detailed running example concerning the cost-effectiveness of hip prostheses in different age-sex subgroups. All computations are carried out using freely available software for conducting Markov chain Monte Carlo analysis.

Optimizing a portfolio of health care programs in the presence of uncertainty and constrained resources

Much research has been devoted to handling uncertainty in cost-effectiveness analysis. The current literature suggests summarizing uncertainty in cost-effectiveness analysis using acceptability curves or net health benefits. These approaches, however, focus only on uncertainty associated with costs and effects of the programs under consideration. In the real world, most decision-makers have to fund a portfolio of health care programs. Therefore, a more comprehensive approach would include in the analysis the uncertainty of costs and effects of all programs supported by the fixed budget. This paper extends the decision rule described by Birch and Gafni (J. Health Econ. 11(3) (1992) 279) within the context of a portfolio of programs when costs and effects are uncertain and resources constrained.

Probabilistic sensitivity analysis for decision trees with multiple branches: use of the Dirichlet distribution in a Bayesian framework

In structuring decision models of medical interventions, it is commonly recommended that only 2 branches be used for each chance node to avoid logical inconsistencies that can arise during sensitivity analyses if the branching probabilities do not sum to 1. However, information may be naturally available in an unconditional form, and structuring a tree in conditional form may complicate rather than simplify the sensitivity analysis of the unconditional probabilities. Current guidance emphasizes using probabilistic sensitivity analysis, and a method is required to provide probabilistic probabilities over multiple branches that appropriately represents uncertainty while satisfying the requirement that mutually exclusive event probabilities should sum to 1. The authors argue that the Dirichlet distribution, the multivariate equivalent of the beta distribution, is appropriate for this purpose and illustrate its use for generating a fully probabilistic transition matrix for a Markov model. Furthermore, they demonstrate that by adopting a Bayesian approach, the problem of observing zero counts for transitions of interest can be overcome.

Prevention of human immunodeficiency virus-related opportunistic infections in France: a cost-effectiveness analysis

A simulation model of human immunodeficiency virus (HIV) disease, which incorporated French data on the progression of HIV disease in the absence of antiretroviral therapy and on cost, was used to determine the clinical impact and cost-effectiveness of different strategies for the prevention of opportunistic infections in French patients who receive highly active antiretroviral therapy (HAART). Compared with use of no prophylaxis, use of trimethoprim-sulfamethoxazole (TMP-SMZ) increased per-person lifetime costs from euro 185,600 to euro 187,900 and quality-adjusted life expectancy from 112.2 to 113.7 months, for an incremental cost-effectiveness ratio of euro 18,700 per quality-adjusted life-year (euro/QALY) gained. Compared with use of TMP-SMZ alone, use of TMP-SMZ plus azithromycin cost euro 23,900/QALY gained; adding fluconazole cost an additional euro 54,500/QALY gained. All strategies that included oral ganciclovir had cost-effectiveness ratios that exceeded euro 100,000/QALY gained. In the era of HAART, on the basis of French data, prophylaxis against Pneumocystis carinii pneumonia, toxoplasmic encephalitis, and Mycobacterium avium complex bacteremia is cost-effective. Prophylaxis against fungal and cytomegalovirus infections is less cost-effective than are other therapeutic options for HIV disease and should remain of lower priority.

Decision analytical economic modelling within a Bayesian framework: application to prophylactic antibiotics use for caesarean section

Economic evaluation of health care interventions based on decision analytic modelling can generate valuable information for health policy decision makers. However, the usefulness of the results obtained depends on the quality of the data input into the model; that is, the accuracy of the estimates for the costs, effectiveness, and transition probabilities between the different health states of the model. The aim of this paper is to review the use of Bayesian decision models in economic evaluation and to demonstrate how the individual components required for decision analytical modelling (i.e., systematic review incorporating meta-analyses, estimation of transition probabilities, evaluation of the model, and sensitivity analysis) may be addressed simultaneously in one coherent Bayesian model evaluated using Markov Chain Monte Carlo simulation implemented in the specialist Bayesian statistics software WinBUGS. To illustrate the method described, a simple probabilistic decision model is developed to evaluate the cost implications of using prophylactic antibiotics in caesarean section to reduce the incidence of wound infection. The advantages of using the Bayesian statistical approach outlined compared to the conventional classical approaches to decision analysis include the ability to: (i) perform all necessary analyses, including all intermediate analyses (e.g., meta-analyses) required to derive model parameters, in a single coherent model; (ii) incorporate expert opinion either directly or regarding the relative credibility of different data sources; (iii) use the actual posterior distributions for parameters of interest (opposed to making distributional assumptions necessary for the classical formulation); and (iv) incorporate uncertainty for all model parameters.

Evaluation of the safety of macrolides

The safety of all drugs is established by animal studies, administration to healthy volunteers and the observations during clinical studies to confirm efficacy. During these studies, patients are questioned about side-effects and extensive laboratory testing of blood and urine samples is performed. Despite these extensive studies, new problems may arise during post marketing surveillance which is designed to identify any rare side-effects. Today, all studies suggest that macrolides, and especially the more recently developed agents, are well tolerated. Some variations in tolerability may be due to the size of the macrocyclic ring and the presence of different esters. There are very few instances of irreversible organ damage.

Opportunity costs and uncertainty in the economic evaluation of health care interventions

Considerable methodological research has been conducted on handling uncertainty in cost-effectiveness analysis. The current literature suggests the concepts of net health benefits and cost-effectiveness acceptability curves to circumvent the technical shortcomings of cost-effectiveness ratio statistics. However, these approaches do not provide a solution for the inherent problem that the threshold cost-effectiveness ratio itself is unknown. The authors suggest analysing uncertainty in cost-effectiveness analysis by directly addressing the concept of opportunity costs using the decision rule described by Birch and Gafni (1992) and introduce a new graphical framework (the "decision making plane") for communicating with policy makers.

Affordability and cost-effectiveness: decision-making on the cost-effectiveness plane

Much recent research interest has focused on handling uncertainty in cost-effectiveness analysis and in particular the calculation of confidence intervals for incremental cost-effectiveness ratios (ICERs). Problems of interpretation when ICERs are negative have led to two important and related developments: the use of the net-benefit statistic and the presentation of uncertainty in cost-effectiveness analysis using acceptability curves. However, neither of these developments directly addresses the problem that decision-makers are constrained by a fixed-budget and may not be able to fund new, more expensive interventions, even if they have been shown to represent good value for money. In response to this limitation, the authors introduce the 'affordability curve' which reflects the probability that a programme is affordable for a wide range of threshold budgets. The authors argue that the joint probability an intervention is affordable and cost-effective is more useful for decision-making since it captures both dimensions of the decision problem faced by those responsible for health service budgets.

Use of a recombinant strain of Mycobacterium avium expressing beta-galactosidase to evaluate the activities of antimycobacterial agents inside macrophages

A reliable and low-cost method that enables rapid screening of the activity exerted by new antimicrobial agents on intracellularly growing Mycobacterium avium has been developed. To this aim, a recombinant (lacZ) strain of M. avium expressing the Escherichia coli beta-galactosidase gene was used to evaluate, in murine macrophages, the susceptibility of M. avium to common antimycobacterial agents. beta-Galactosidase levels, measured in the presence of each of the antibiotics tested, were closely correlated with the number of CFU recovered from the M. avium lacZ strain-infected macrophages.