Cost-effectiveness of escitalopram in major depressive disorder in the Dutch health care setting

The Incidence and Costs of Adverse Events Associated with Antidepressants: Results from a Systematic Review, Network Meta-Analysis and Multi-Country Economic Model

PURPOSE

There is variation in the safety profile of antidepressants. Rates of adverse events along with the costs of treating them can be an important factor influencing the choice of depression treatment. This study sought to estimate the comparative safety of commonly prescribed antidepressants, and how the costs of treating these varied across European countries.

METHODS

A systematic literature review was conducted (in Medline, Embase, PsycINFO and CENTRAL) to identify placebo-controlled trials reporting rates of at least one type of sexual dysfunction, weight change, insomnia, anxiety, and anhedonia. Eight antidepressants were considered: duloxetine, escitalopram, fluoxetine, paroxetine, sertraline, trazodone, venlafaxine, and vortioxetine. This evidence was synthesised via Bayesian random effects network meta-analyses to provide comparative estimates of safety. A systematic search identified country-specific costs of managing depression and adverse events of antidepressants. Evidence on costs and safety was combined in an economic model to provide country-specific costs for Bulgaria, the Czech Republic, Greece, Hungary, Italy, Romania, Slovakia, Portugal, and Poland.

RESULTS

Trazodone had the lowest rates of both insomnia (odds ratio 0.66, 95% credible interval 0.31 to 1.38) and anxiety (0.13, <0.01 to 1.80). All antidepressants were associated with increased rates of sexual dysfunction relative to placebo. Weight change was largest for fluoxetine (kg change -1.01, -1.40 to -0.60) and sertraline (-1.00, -1.36 to -0.65), although heterogeneity was extreme for this outcome. No evidence was identified for anhedonia. Total costs were lowest for trazodone in all nine of the countries evaluated. This was primarily due to reduced rates of treatment discontinuation.

CONCLUSION

Trazodone generally had the best safety profile of the antidepressants evaluated. This led to healthcare costs being lowest for trazodone in all nine European countries, emphasising the importance of considering rates of adverse events when choosing a pharmacological treatment to treat symptoms of depression.

Application of the Delphi Method in the Study of Depressive Disorder

Depressive disorder is a common mental disorder that has a high prevalence and low visiting rate, which caused patients years lived with disability. Due to the complexity of the depressive disorder, the Delphi method is a better choice compared with other commonly used methods, which provides a new perspective for the prevention and treatment of depression. This article will summarize the clinical studies of depressive disorders using the Delphi method from four perspectives, and summarize the advantages and disadvantages of the Delphi method in depressive disorders research, arguing that the Delphi method can cross the gap between clinical research and clinical practice, and is a highly practical part of the research process.

Considering the societal perspective in economic evaluations: a systematic review in the case of depression

BACKGROUND

Depressive disorders are associated with a high burden of disease. However, due to the burden posed by the disease on not only the sufferers, but also on their relatives, there is an ongoing debate about which costs to include and, hence, which perspective should be applied. Therefore, the aim of this paper was to examine whether the change between healthcare payer and societal perspective leads to different conclusions of cost-utility analyses in the case of depression.

METHODS

A systematic literature search was conducted to identify economic evaluations of interventions in depression, launched on Medline and the Cost-Effectiveness Registry of the Tufts University using a ten-year time horizon (2008-2018). In a two-stepped screening process, cost-utility studies were selected by means of specified inclusion and exclusion criteria. Subsequently, relevant findings was extracted and, if not fully stated, calculated by the authors of this work.

RESULTS

Overall, 53 articles with 92 complete economic evaluations, reporting costs from healthcare payer/provider and societal perspective, were identified. More precisely, 22 estimations (24%) changed their results regarding the cost-effectiveness quadrant when the societal perspective was included. Furthermore, 5% of the ICURs resulted in cost-effectiveness regarding the chosen threshold (2% of them became dominant) when societal costs were included. However, another four estimations (4%) showed the opposite result: these interventions were no longer cost-effective after the inclusion of societal costs.

CONCLUSIONS

Summarising the disparities in results and applied methods, the results show that societal costs might alter the conclusions in cost-utility analyses. Hence, the relevance of the perspectives chosen should be taken into account when carrying out an economic evaluation. This systematic review demonstrates that the results of economic evaluations can be affected by different methods available for estimating non-healthcare costs.

Model-Based Economic Evaluation of Treatments for Depression: A Systematic Literature Review

BACKGROUND

An increasing number of model-based studies that evaluate the cost effectiveness of treatments for depression are being published. These studies have different characteristics and use different simulation methods.

OBJECTIVE

We aimed to systematically review model-based studies evaluating the cost effectiveness of treatments for depression and examine which modelling technique is most appropriate for simulating the natural course of depression.

METHODS

The literature search was conducted in the databases PubMed, EMBASE and PsycInfo between 1 January 2002 and 1 October 2016. Studies were eligible if they used a health economic model with quality-adjusted life-years or disability-adjusted life-years as an outcome measure. Data related to various methodological characteristics were extracted from the included studies. The available modelling techniques were evaluated based on 11 predefined criteria.

RESULTS

This methodological review included 41 model-based studies, of which 21 used decision trees (DTs), 15 used cohort-based state-transition Markov models (CMMs), two used individual-based state-transition models (ISMs), and three used discrete-event simulation (DES) models. Just over half of the studies (54%) evaluated antidepressants compared with a control condition. The data sources, time horizons, cycle lengths, perspectives adopted and number of health states/events all varied widely between the included studies. DTs scored positively in four of the 11 criteria, CMMs in five, ISMs in six, and DES models in seven.

CONCLUSION

There were substantial methodological differences between the studies. Since the individual history of each patient is important for the prognosis of depression, DES and ISM simulation methods may be more appropriate than the others for a pragmatic representation of the course of depression. However, direct comparisons between the available modelling techniques are necessary to yield firm conclusions.

Cost-effectiveness analysis of pharmaceutical treatment options in the first-line management of major depressive disorder in Belgium

OBJECTIVE

The objective of this study was to assess the cost effectiveness of commonly used antidepressants as first-line treatment of major depressive disorder (MDD) in Belgium.

METHODS

The model structure was based on a decision tree developed by the Swedish TLV (Tandvårds- och läkemedelsförmånsverket) and adapted to the Belgium healthcare setting, using primary local data on the patterns of treatment and following KCE [Federal Knowledge Center (Federaal Kenniscentrum voor de Gezondheidszorg)] recommendations. Comparators were escitalopram, citalopram, fluoxetine, paroxetine, sertraline, duloxetine, venlafaxine, and mirtazapine. In the model, patients not achieving remission or relapsing after remission on the assessed treatment moved to a second therapeutic step (titration, switch, add-on, or transfer to a specialist). In case of failure in the second step or following a suicide attempt, patients were assumed to be referred to secondary care. The time horizon was 1 year and the analysis was conducted from the National Institute for Health and Disability Insurance (NIHDI; national health insurance) and societal perspectives. Remission rates were obtained from the TLV network meta-analysis and risk of relapse, efficacy following therapeutic change, risk of suicide attempts and related death, utilities, costs (2012), and resources were derived from the published literature and expert opinion. The effect of uncertainty in model parameters was estimated through scenario analyses and a probabilistic sensitivity analysis (PSA).

RESULTS

In the base-case analysis, escitalopram was identified as the optimal strategy: it dominated all other treatments except venlafaxine from the NIHDI perspective, against which it was cost effective with an incremental cost-effectiveness ratio of <euro>6,352 per quality-adjusted life-year (QALY). Escitalopram also dominated all other treatments from the societal perspective. At a threshold of <euro>30,000 per QALY and from the NIHDI perspective, the PSA showed that the probability of escitalopram being identified as the optimal strategy ranged from 61 % (vs. venlafaxine) to 100 % (vs. fluoxetine).

CONCLUSION

Escitalopram was associated with the highest probability of being the optimal treatment from the NIHDI and societal perspectives. This analysis, based on new Belgian clinical practice data and following KCE requirements, provides additional information that may be used to guide the choice of treatments in the management of MDD in Belgium.

C-QUALITY: cost and quality-of-life pharmacoeconomic analysis of antidepressants used in major depressive disorder in the regional Italian settings of Veneto and Sardinia

Background

Major depression is a commonly occurring, seriously impairing, and often recurrent mental disorder. Selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine reuptake inhibitors (SNRIs) are the treatments most commonly used for major depressive disorder. The objective of this study was to assess the cost-effectiveness of SSRIs and SNRIs in the treatment of major depressive disorder in two Italian regional settings, ie, Veneto and Sardinia.

Methods

A decision analytic model was adapted from the Swedish Dental and Pharmaceutical Benefits Agency to reflect current clinical practice in the treatment of major depressive disorder in the most significant Italian regions. This adaptation was possible as a result of collaboration with an expert panel of Italian psychiatrists and health economists. The population comprised patients with a first diagnosis of major depressive disorder and initiating one SSRI or SNRI drug for the first time. The time frame used was 12 months. Efficacy and utility data for the model were retrieved from the literature and validated by the expert panel. Local data were used for resource utilization and for treatment costs based on the perspective of each regional health service. Scenario analyses and probabilistic sensitivity analyses were performed to test the robustness of the model.

Results

Base case analysis showed that escitalopram is associated with the largest health gain (in quality-adjusted life years) and a lower total cost at one year for Sardinia (except for sertraline, against which it was cost-effective) and for Veneto, and therefore dominates the other treatment strategies, given that more quality-adjusted life years are achieved at a lower total cost. Scenario analyses and probabilistic sensitivity analyses support the robustness of the model.

Conclusion

The results indicate that escitalopram is the most cost-effective pharmacologic treatment strategy for both regional health services compared with all SSRIs and all SNRIs used in the first-line treatment of major depressive disorder.

C-QUALITY: cost and quality-of-life pharmacoeconomic analysis of antidepressants in major depressive disorder in Italy

INTRODUCTION

Major depressive disorder (MDD) is a common and disabling condition across the world. Selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine reuptake inhibitors (SNRIs) are the most commonly used antidepressants. The objective of this study was to assess the cost-effectiveness [€ per quality-adjusted life year (QALY)] of all SSRIs and all SNRIs for the treatment of MDD in Italy.

METHODS

A decision analytic model was adapted from the Swedish Dental and Pharmaceutical Benefits agency model to reflect current clinical practice in the treatment of MDD in the largest Italian regions. This adaptation was possible thanks to the collaboration of an expert panel of Italian psychiatrists and health economists. The model evaluated patients with a first diagnosis of MDD and initiating an SSRI or an SNRI for the first time. The time horizon was 12 months. Efficacy and utility data for the model were retrieved from the literature and validated by the expert panel. Local data were considered for resource utilization and for treatment costs based on each regional health service perspective. Population-weighted regional data were used to define a national model. Scenario simulations, one-way sensitivity analyses, and Monte Carlo simulations were performed to test the robustness of the model.

RESULTS

The base case analysis showed that escitalopram was associated with a lower total cost (€ 1,562) and a larger health gain (QALYs) at 1 year (0.732) per patient and dominated the other treatment strategies since more QALYs were achieved at a lower total cost. Sensitivity analyses support the robustness of the model.

CONCLUSION

The results indicate that escitalopram is the most cost-effective pharmacological treatment strategy for the Italian health service compared with other SSRIs and all SNRIs used in the first-line treatment of MDD.

Probability elicitation to inform early health economic evaluations of new medical technologies: a case study in heart failure disease management

OBJECTIVES

Early estimates of the commercial headroom available to a new medical device can assist producers of health technology in making appropriate product investment decisions. The purpose of this study was to illustrate how this quantity can be captured probabilistically by combining probability elicitation with early health economic modeling. The technology considered was a novel point-of-care testing device in heart failure disease management.

METHODS

First, we developed a continuous-time Markov model to represent the patients' disease progression under the current care setting. Next, we identified the model parameters that are likely to change after the introduction of the new device and interviewed three cardiologists to capture the probability distributions of these parameters. Finally, we obtained the probability distribution of the commercial headroom available per measurement by propagating the uncertainty in the model inputs to uncertainty in modeled outcomes.

RESULTS

For a willingness-to-pay value of €10,000 per life-year, the median headroom available per measurement was €1.64 (interquartile range €0.05-€3.16) when the measurement frequency was assumed to be daily. In the subsequently conducted sensitivity analysis, this median value increased to a maximum of €57.70 for different combinations of the willingness-to-pay threshold and the measurement frequency.

CONCLUSIONS

Probability elicitation can successfully be combined with early health economic modeling to obtain the probability distribution of the headroom available to a new medical technology. Subsequently feeding this distribution into a product investment evaluation method enables stakeholders to make more informed decisions regarding to which markets a currently available product prototype should be targeted.

Cost-effectiveness evaluation of escitalopram in major depressive disorder in Italy

Background

Depression has a lifetime prevalence of 10%–25% among women and 5%–12% among men. Selective serotonin reuptake inhibitors (SSRIs) are the most used and the most cost-effective treatment for long-term major depressive disorder. Since the introduction of generic SSRIs, the costs of branded drugs have been questioned. The objective of this study was to assess the cost-effectiveness (€ per quality-adjusted life year [QALY]) of escitalopram (which is still covered by a patent) compared with paroxetine, sertraline, and citalopram, the patents for which have expired.

Methods

A decision analytic model was adapted from the Swedish Dental and Pharmaceutical benefits agency model to reflect current clinical practice in the treatment of depression in Italy in collaboration with an expert panel of Italian psychiatrists and health economists. The population comprised patients with a first diagnosis of major depressive disorder and receiving for the first time one of the following SSRIs: escitalopram, sertraline, paroxetine, and citalopram. The time frame used was 12 months. Efficacy and utility data for the original model were validated by our expert panel. Local data were considered for resource utilization and for treatment costs based on the Lombardy region health service perspective. Several scenario simulations, oneway sensitivity analyses, and Monte Carlo simulations were performed to test the robustness of the model.

Results

The base case scenario showed that escitalopram had an incremental cost-effectiveness ratio (ICER) of €4395 and €1080 per QALY compared with sertraline and paroxetine, respectively. Escitalopram was dominant over citalopram, which was confirmed by most one-way sensitivity analyses. The escitalopram strategy gained 0.011 QALYs more than citalopram, 0.008 more than paroxetine, and around 0.007 more than sertraline. Monte Carlo simulations indicated that ICER values for escitalopram were centered around €1100 and €4400 per QALY compared with paroxetine and sertraline, respectively. Although there is no official cost-effectiveness threshold in Italy, the value of €25,000 per QALY could be acceptable. All ICER values retrieved in all analyses were lower than this threshold.

Conclusion

The findings from this cost-effectiveness analysis indicate that escitalopram could be accepted as a cost-effective strategy for the Lombardy region health service compared with the other SSRIs studied. The present assessment is based on ICER values resulting from this analysis, which are lower than the thresholds proposed by health care authorities in other European Union countries. These benefits are driven by the effectiveness of escitalopram, which result in an improved health-related quality of life, a higher probability of sustained remission, and better utilization of health care resources. The study results are robust and in line with other pharmacoeconomic analyses comparing escitalopram with other SSRIs.