Modelling therapeutic strategies in the treatment of osteoarthritis: an economic evaluation of meloxicam versus diclofenac and piroxicam

Thermosensitive Polyurethane-Based Hydrogels as Potential Vehicles for Meloxicam Delivery

Meloxicam (MX) is a nonsteroidal anti-inflammatory drug (NSAID) used mainly to reduce pain, inflammation, and fever. In the present study, thermosensitive polyurethane (PU)-based hydrogels with various excipients (PEG, PVP, HPC, and essential oil) were prepared and loaded with MX. Rheological investigations were carried out on the PU-based formulations in various shear regimes, and their viscoelastic characteristics were determined. The average size of the PU micelles was 35.8 nm at 37 °C and slightly increased at 37 nm in the presence of MX. The zeta potential values of the hydrogels were between -10 mV and -11.5 mV. At pH = 6 and temperature of 37 °C, the formulated PU-based hydrogels loaded with MX could deliver significant amounts of the active substance, between 60% and 80% over 24-48 h and more than 90% within 2 weeks. It was found that anomalous transport phenomena dominated MX's release mechanism from the PU-based networks. The results are encouraging for further studies aiming to design alternative carriers to commercial dosage forms of nonsteroidal anti-inflammatory drugs.

Cost-effectiveness analyses of osteoarthritis oral therapies: a systematic review

BACKGROUND

Cost-effectiveness analyses (CEAs) have been performed for oral non-disease-altering osteoarthritis (OA) treatments for well over a decade. During that period the methods for performing these analyses have evolved as pharmacoeconomic methods have advanced, new treatments have been introduced, and the knowledge of associated adverse events (AEs) has improved.

OBJECTIVE

The objective of this systematic review was to trace the development of CEAs for oral non-disease-altering treatments in OA.

METHODS

A systematic search for CEAs of OA oral treatments was performed of the English-language medical literature using the following databases: PubMed, EMBASE, MEDLINE In-Process, EconLit, and Cochrane. Key requirements for inclusion were that the population described patients with OA or arthritis and that the analysis reported at least one incremental cost-effectiveness ratio. Each identified publication was assessed for inclusion. Thirteen characteristics and all AEs appearing in each included CEA were extracted and organized. Reference lists from these CEAs were also searched. A chronology of key CEAs in the field was compiled, noting the characteristics that advanced the state of the art in modeling oral OA treatments.

RESULTS

Thirty publications of 28 CEAs were identified and evaluated. Developments in CEAs included an expanded set of comparators that broadened from non-steroidal anti-inflammatory drugs (NSAIDs) only to NSAIDs plus gastroprotective agents, cyclooxygenase-2 inhibitors, and opioids. In turn, AEs expanded from gastrointestinal (GI) events to also include cardiovascular (CV) and neurological events. Efficacy, which initially was presumed to be equivalent for all treatments, evolved to treatment-specific efficacies. Decision-tree analyses were generally replaced by Markov models or, occasionally, stochastic or discrete event simulation. Finally, outcomes have progressed from GI-centric measures to also include quality-adjusted life-years.

CONCLUSION

Methods used by CEAs of oral non-disease-altering OA treatments have evolved in response to changing treatments with different safety profiles and efficacies as well as technical advances in the application of decision science to health care.

Cardiovascular and gastrointestinal safety of NSAIDs: a systematic review of meta-analyses of randomized clinical trials

As part of the Safety of Non-Steroidal Anti-Inflammatory Drugs (SOS) Project, we reviewed the incidence of cardiovascular (CV) and gastrointestinal (GI) events associated with the use of this category of drugs. We collected data from published meta-analyses (MAs) of clinical trials of nonsteroidal anti-inflammatory drugs (NSAIDs). The Medline, Cochrane, ISI, and SCOPUS databases were systematically searched for MAs of NSAID clinical trials that could potentially contain data on adverse incidents such as myocardial infarction (MI), cerebrovascular events (CeVs), stroke, thromboembolic events (ThEs), heart failure (HF), gastrointestinal bleeding (GIB), and perforation, ulcer, and bleeding (PUB). From 1,733 identified references, 29 MAs were selected for the review. This allowed 109 estimations of incidence rates of CV adverse events and 26 estimations of incidence rates for GI adverse events. No data were found on hemorrhagic stroke or LGIB. Coxibs were studied in more MAs than traditional NSAIDs were (21 MAs for coxibs vs. 7 for traditional NSAIDs; one meta-analysis studied both). Many NSAIDs were not considered in any of the MAs. Our systematic review of MAs included information on the incidence of CV and GI events and identified important knowledge gaps regarding, in particular, the CV safety of traditional NSAIDs.

Impact of chondroitin sulphate on health utility in patients with knee osteoarthritis: towards economic analysis

OBJECTIVES

The first objective was to assess the effect of the chondroitin 4 and 6 sulphate (CS) on health-related quality of life using utility values in patients with knee osteoarthritis (OA) during a 24-month treatment course. The second objective was, using these data, to conduct economic analyses.

METHODS

Data from the STOPP study was used. This study was a randomised, double-blind, placebo (PL) -controlled trial of 2-year duration. In the STOPP study, authors assessed quality of life using the Western Ontario and McMaster Osteoarthritis Index (WOMAC). WOMAC scores were translated into Health Utility Index (HUI) scores using a specific formula. Incremental cost effectiveness ratio (ICER) was calculated taking into account the cost of CS and its effect on HUI scores, compared to PL.

RESULTS

At baseline, the mean (SD) HUI scores were 0.59 (0.17), and 0.59 (0.18) for the PL and CS groups, respectively (p=0.31 between the two groups). The mean (SD) HUI scores changes from baseline to 6 months were 0.02 (0.02), and 0.05 (0.01) for the PL and CS groups, respectively (p=0.03). After 24 months of follow-up, HUI score increases by 0.04 (0.02) in the PL group and by 0.05 (0.02) in the CS group (p=0.37). Using the price bracket of CS in Europe, ICER assessment always resulted in a cost below €30,000 per QALY gained, after 6, 12 and 24 months of treatment.

CONCLUSION

CS treatment increases health utilities in patients with knee OA compared to PL over the first 6 months of treatment. Economic evaluation based on these data suggests that CS treatment could be considered as cost-effective in patients with knee OA up to a period of 24 months. A limitation in this study is the absence of direct utility assessment as well as the absence of effective treatment as comparator.

Principles of good practice for budget impact analysis: report of the ISPOR Task Force on good research practices--budget impact analysis

OBJECTIVES

There is growing recognition that a comprehensive economic assessment of a new health-care intervention at the time of launch requires both a cost-effectiveness analysis (CEA) and a budget impact analysis (BIA). National regulatory agencies such as the National Institute for Health and Clinical Excellence in England and Wales and the Pharmaceutical Benefits Advisory Committee in Australia, as well as managed care organizations in the United States, now require that companies submit estimates of both the cost-effectiveness and the likely impact of the new health-care interventions on national, regional, or local health plan budgets. Although standard methods for performing and presenting the results of CEAs are well accepted, the same progress has not been made for BIAs. The objective of this report is to present guidance on methodologies for those undertaking such analyses or for those reviewing the results of such analyses.

METHODS

The Task Force was appointed with the advice and consent of the Board of Directors of ISPOR. Members were experienced developers or users of budget impact models, worked in academia, industry, and as advisors to governments, and came from several countries in North America, Oceana, Asia, and Europe. The Task Force met to develop core assumptions and an outline before preparing a draft report. They solicited comments on the outline and two drafts from a core group of external reviewers and more broadly from the membership of ISPOR at two ISPOR meetings and via the ISPOR web site.

RESULTS

The Task Force recommends that the budget impact of a new health technology should consider the perspective of the specific health-care decision-maker. As such, the BIA should be performed using data that reflect, for a specific health condition, the size and characteristics of the population, the current and new treatment mix, the efficacy and safety of the new and current treatments, and the resource use and costs for the treatments and symptoms as would apply to the population of interest. The Task Force recommends that budget impact analyses be generated as a series of scenario analyses in the same manner that sensitivity analyses would be provided for CEAs. In particular, the input values for the calculation and the specific cost outcomes presented (a scenario) should be specific to a particular decision-maker's population and information needs. Sensitivity analysis should also be in the form of alternative scenarios chosen from the perspective of the decision-maker. The primary data sources for estimating the budget impact should be published clinical trial estimates and comparator studies for efficacy and safety of current and new technologies as well as, where possible, the decision-maker's own population for the other parameter estimates. Suggested default data sources also are recommended. These include the use of published data, well-recognized local or national statistical information and in special circumstances, expert opinion. Finally, the Task Force recommends that the analyst use the simplest design that will generate credible and transparent estimates. If a health condition model is needed for the BIA, it should reflect health outcomes and their related costs in the total affected population for each year after the new intervention is introduced into clinical practice. The model should be consistent with that used for the CEA with regard to clinical and economic assumptions.

CONCLUSIONS

The BIA is important, along with the CEA, as part of a comprehensive economic evaluation of a new health technology. We propose a framework for creating budget impact models, guidance about the acquisition and use of data to make budget projections and a common reporting format that will promote standardization and transparency. Adherence to these proposed good research practice principles would not necessarily supersede jurisdiction-specific budget impact guidelines, but may support and enhance local recommendations or serve as a starting point for payers wishing to promulgate methodology guidelines.