The cost-utility of maintenance treatment with venlafaxine in patients with recurrent major depressive disorder

Estimation of Input Costs for a Markov Model in a German Health Economic Evaluation of Newer Antidepressants

Background: Estimating input costs for Markov models in health economic evaluations requires health state–specific costing. This is a challenge in mental illnesses such as depression, as interventions are not clearly related to health states. We present a hybrid approach to health state–specific cost estimation for a German health economic evaluation of antidepressants. Methods: Costs were determined from the perspective of the community of persons insured by statutory health insurance (“SHI insuree perspective”) and included costs for outpatient care, inpatient care, drugs, and psychotherapy. In an additional step, costs for rehabilitation and productivity losses were calculated from the societal perspective. We collected resource use data in a stepwise hierarchical approach using SHI claims data, where available, followed by data from clinical guidelines and expert surveys. Bottom-up and top-down costing approaches were combined. Results: Depending on the drug strategy and health state, the average input costs varied per patient per 8-week Markov cycle. The highest costs occurred for agomelatine in the health state first-line treatment (FT) (“FT relapse”) with €506 from the SHI insuree perspective and €724 from the societal perspective. From both perspectives, the lowest costs (excluding placebo) were €55 for selective serotonin reuptake inhibitors in the health state “FT remission.” Conclusion: To estimate costs in health economic evaluations of treatments for depression, it can be necessary to link different data sources and costing approaches systematically to meet the requirements of the decision-analytic model. As this can increase complexity, the corresponding calculations should be presented transparently. The approach presented could provide useful input for future models.

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.

[How to assess curative and/or preventive effects of psychotropic drugs?]

Proving the efficacy of a psychotropic drug is a medical, scientific and ethical need. Psychotropic drug development is now a highly complex process, which takes several years and which is very expensive. It involves multiple steps of preclinical and clinical pharmacological refinement and testing. Methodology of studies to prove curative or preventive effect of psychotropic drugs is well codified. Preclinical studies include pharmacokinetic data, toxicology and performance in various animal models of pathology. Clinical phases are centered on randomized controlled double blind trials for demonstrating efficacy and safety/tolerability. This methodology follows strict criteria to avoid bias and to prove internal and external validity of the results. All the results from randomized controlled trials or RCTs lead to different levels of evidence of Evidence-Based Medicine (EBM): gold standard is RCTs while the lowest reference is clinical case or expert opinion. However, it is possible to level criticism at these data issued from RCTs. The main matter is that studies do not reflect the healthcare reality in daily life. For these reasons, a real debate between evaluation of efficacy and effectiveness is acute. Effectiveness refers to the overall effects of psychotropic drugs in naturalistic conditions. Furthermore, analysis of costs and financial benefits are more and more important from social and economic points of view. Official agencies and health insurances look after them very carefully. This article deals with these issues and provides examples using data from the international literature. These examples are drawn from RCTs, naturalistic studies, meta-analysis, pharmaco-economic studies and concern neuroleptics, antipsychotics, antidepressants, and mood-stabilizers.

[Unsatisfactory response: definition and involvement]

In the treatment of unipolar depression, treatment response is a key issue in terms of evolution and prognosis. Within this concept, the inadequate response includes the worsening, the lack of response, partial response and poor tolerance. This lack of response may be related to intrinsic factors to the individual, but also to more extrinsic environmental factors. In this review, we explore this concept through its links with adherence and treatment duration. In this field, the concept of early response can be a powerful indicator of therapeutic response, which conditions the prescription of antidepressants beyond the strict framework of the sufficient period of 4 to 6 weeks. In addition to its impact on prognosis, the literature data show that the insufficient response is a significant burden in terms of medical and economic cost, and somatic comorbidity; and justifies a systematic identification of this dimension. Therefore self-reports (QIDS; BDI) will be preferred to the clinician-rated depression symptom rating scales (MADRS, HAMD) that require a specific training. Identifying predictors of non-response would be an attractive target for prescribers but the results to date are not operative.

Quality-adjusted life-years gain and health status in patients with OSAS after one year of continuous positive airway pressure use

STUDY OBJECTIVES

To estimate the health utility score and quality-adjusted life-years (QALY) index of obstructive sleep apnea syndrome (OSAS) in patients over 1 y of continuous positive airway pressure (CPAP) treatment.

DESIGN

Longitudinal interventional study.

SETTING

The study was carried out in Sao Paulo Sleep Institute, Brazil.

PATIENTS AND PARTICIPANTS

Ninety-five patients with OSAS and with apnea-hypopnea index (AHI) > 20 of either sex, body mass index < 40 kg/m(2), and no previous contact with CPAP were included.

INTERVENTIONS

The participants underwent baseline and titration polysomnographies, clinical evaluation, and ambulatory blood pressure (BP) measurement, completed Short-Form 6 Dimension Health Survey (SF-6D) and Epworth Sleepiness Scale (ESS) questionnaires, and implementation of CPAP. The patients were followed for 1 y.

MEASUREMENTS AND RESULTS

The mean AHI and age were 57.6 ± 29.2 events/h and 53.3 ± 9.3 y, respectively. One year of CPAP treatment increased the health utility score from 0.611 ± 0.112 to 0.710 ± 0.121 (P < 0.01). Therefore, CPAP resulted in a mean gain of 0.092 QALY/patient. The improvements in utility scores were associated with decreases in the ESS after 1 mo, in systolic BP after 1 y, and in diastolic BP at 6 mo. BP normalization group (≤ 130/85 mmHg) showed higher QALY than that of the non-normalization group (0.10 ± 0.09 versus 0.05 ± 0.10; P = 0.03). One-year ESS score (P = 0.03), diastolic BP reduction P = 0.01) and baseline utility scores (P < 0.01) were significantly associated with QALY gain.

CONCLUSION

This study showed a significant QALY/patient gain after 1 y of regular CPAP use. In addition, BP normalization was associated with higher QALY gain. Thus, utility studies can provide more complete analyses of the total benefits of CPAP treatment in patients with OSAS and should be encouraged.

Practice nurse involvement in primary care depression management: an observational cost-effectiveness analysis

Background

Most evidence on the effect of collaborative care for depression is derived in the selective environment of randomised controlled trials. In collaborative care, practice nurses may act as case managers. The Primary Care Services Improvement Project (PCSIP) aimed to assess the cost-effectiveness of alternative models of practice nurse involvement in a real world Australian setting. Previous analyses have demonstrated the value of high level practice nurse involvement in the management of diabetes and obesity. This paper reports on their value in the management of depression.

Methods

General practices were assigned to a low or high model of care based on observed levels of practice nurse involvement in clinical-based activities for the management of depression (i.e. percentage of depression patients seen, percentage of consultation time spent on clinical-based activities). Linked, routinely collected data was used to determine patient level depression outcomes (proportion of depression-free days) and health service usage costs. Standardised depression assessment tools were not routinely used, therefore a classification framework to determine the patient’s depressive state was developed using proxy measures (e.g. symptoms, medications, referrals, hospitalisations and suicide attempts). Regression analyses of costs and depression outcomes were conducted, using propensity weighting to control for potential confounders.

Results

Capacity to determine depressive state using the classification framework was dependent upon the level of detail provided in medical records. While antidepressant medication prescriptions were a strong indicator of depressive state, they could not be relied upon as the sole measure. Propensity score weighted analyses of total depression-related costs and depression outcomes, found that the high level model of care cost more (95% CI: -$314.76 to $584) and resulted in 5% less depression-free days (95% CI: -0.15 to 0.05), compared to the low level model. However, this result was highly uncertain, as shown by the confidence intervals.

Conclusions

Classification of patients’ depressive state was feasible, but time consuming, using the classification framework proposed. Further validation of the framework is required. Unlike the analyses of diabetes and obesity management, no significant differences in the proportion of depression-free days or health service costs were found between the alternative levels of practice nurse involvement.

The estimation of utility weights in cost-utility analysis for mental disorders: a systematic review

OBJECTIVE

To systematically review approaches and instruments used to derive utility weights in cost-utility analyses (CUAs) within the field of mental disorders and to identify factors that may have influenced the choice of the approach.

METHODS

We searched the databases DARE (Database of Abstracts of Reviews of Effects), NHS EED (National Health Service Economic Evaluation Database), HTA (Health Technology Assessment), and PubMed for CUAs. Studies were included if they were full economic evaluations and reported quality-adjusted life-years as the health outcome. Study characteristics and instruments used to estimate utility weights were described and a logistic regression analysis was conducted to identify factors associated with the choice of either the direct (e.g. standard gamble) or the preference-based measure (PBM) approach (e.g. EQ-5D).

RESULTS

We identified 227 CUAs with a maximum in 2009, 2010, and 2012. Most CUAs were conducted in depression, dementia, or psychosis, and came from the US or the UK, with the EQ-5D being the most frequently used instrument. The application of the direct approach was significantly associated with depression, psychosis, and model-based studies. The PBM approach was more likely to be used in recent studies, dementia, Europe, and empirical studies. Utility weights used in model-based studies were derived from only a small number of studies.

LIMITATIONS

We only searched four databases and did not evaluate the quality of the included studies.

CONCLUSIONS

Direct instruments and PBMs are used to elicit utility weights in CUAs with different frequencies regarding study type, mental disorder, and country.

Testing the McSad depression specific classification system in patients with somatic conditions: validity and performance

Background

Valuations of depression are useful to evaluate depression interventions offered to patients with chronic somatic conditions. The only classification system to describe depression developed specifically for valuation purposes is the McSad, but it has not been used among somatic patients. The aim of this study was to test the construct validity of the McSad among diabetes and cancer patients and then to compare the McSad to the commonly used EuroQol – 5 Dimensions (EQ-5D^TM) classification system. The comparison was expected to shed light on their capacity to reflect the range of depression states experienced by somatic patients.

Methods

Cross-sectional data were collected online from 114 diabetes and 195 cancer patients; additionally, 241 cancer patients completed part of the survey on paper. Correlational analyses were performed to test the construct validity. Specifically, we hypothesized high correlations of the McSad domains with depression (Center for Epidemiological Studies Depression Scale (CES-D) and the Patient Health Questionnaire (PHQ-9)). We also expected low/moderate correlations with self-esteem (Rosenberg Self-Esteem scale - RSE) and extraversion (Eysenck Personality Questionnaire Extraversion scale - EPQ-e). Multiple linear regression analyses were run so that the proportion of variance in depression scores (CES-D, PHQ-9) explained by the McSad could be compared to the proportion explained by the EQ-5D classification system.

Results

As expected, among all patients groups, we found moderate to high correlations for the McSad domains with the CES-D (.41 to .70) and the PHQ-9 (.52 to .76); we also found low to moderate correlations with the RSE (-.21 to .-48) and the EPQ-e (.18 to .31). Linear regression analyses showed that the McSad explained a greater proportion of variance in depression (CES-D, PHQ-9) (Diabetes: 73%, 82%; Cancer: 72%, 72%) than the EQ-5D classification system (Diabetes: 47%, 59%; Cancer: 51%, 47%).

Conclusions

Findings support the construct validity of the McSad among patients with somatic conditions and demonstrate that it performs better than the EQ-5D classification system to reflect the range of depression states. For future valuation purposes, the McSad classification system could therefore be recommended to describe depression as experienced by patients with a chronic medical condition.

Economic evaluation of agomelatine relative to other antidepressants for treatment of major depressive disorders in Greece

Background

Major depressive disorder (MDD) constitutes an important public health problem, as it is highly prevalent in the industrialized world and it is associated with substantial economic consequences for patients, health care providers, insurance and social security organizations and employers. To conduct an economic evaluation comparing agomelatine with other commonly used alternatives for treating patients with major depressive disorder (MDD) in Greece.

Methods

An existing international Markov model designed to evaluate the cost-effectiveness of agomelatine was adapted to the Greek setting. It reflects six different health states, in which patients may move on a monthly basis. The analysis was undertaken from a societal perspective. Transition probabilities, utilities and costs assigned to each health state were extracted from the published literature, government sources and expert opinion. Data reflects the year 2012 and was discounted using a rate of 3.5%. Probabilistic analysis was undertaken to deal with uncertainty.

Results

Base case analyses revealed that agomelatine is a dominant therapy for MDD relative to escitalopram, fluoxetine and sertraline, and it appeared to be cost-effective compared to venlafaxine (ICER: €547/QALY). Agomelatine remained a dominant treatment against generic sertraline and fluoxetine, and it appeared to be a cost-effective alternative compared to generic venlafaxine and escitalopram (ICER: €1,446/QALY and €3,303/QALY, respectively). Excluding the indirect cost from the analysis, agomelatine remained a cost-effective alternative over all comparators. In the probabilistic sensitivity analysis agomelatine was dominant in 44.5%, 89.6%, 70.6% and 84.6% of simulated samples against branded venlafaxine, escitalopram, fluoxetine and sertraline, respectively.

Conclusion

The present evaluation indicates that agomelatine is either a dominant or a cost-effective alternative relative to branded or generic alternatives, in Greece.

A decision analysis of long-term lithium treatment and the risk of renal failure

OBJECTIVE

To establish whether lithium or anticonvulsant should be used for maintenance treatment for bipolar affective disorder (BPAD) if the risks of suicide and relapse were traded off against the risk of end-stage renal disease (ESRD).

METHOD

Decision analysis based on a systematic literature review with two main decisions: (1) use of lithium or at treatment initiation and (2) the potential discontinuation of lithium in patients with chronic kidney disease (CKD) after 20 years of lithium treatment. The final endpoint was 30 years of treatment with five outcomes to consider: death from suicide, alive with stable or unstable BPAD, alive with or without ESRD.

RESULTS

At the start of treatment, the model identified lithium as the treatment of choice. The risks of developing CKD or ESRD were not relevant at the starting point. Twenty years into treatment, lithium still remained treatment of choice. If CKD had occurred at this point, stopping lithium would only be an option if the likelihood of progression to ESRD exceeded 41.3% or if anticonvulsants always outperformed lithium regarding relapse prevention.

CONCLUSION

At the current state of knowledge, lithium initiation and continuation even in the presence of long-term adverse renal effects should be recommended in most cases.

A proposed model for economic evaluations of major depressive disorder

In countries like UK and Australia, the comparability of model-based analyses is an essential aspect of reimbursement decisions for new pharmaceuticals, medical services and technologies. Within disease areas, the use of models with alternative structures, type of modelling techniques and/or data sources for common parameters reduces the comparability of evaluations of alternative technologies for the same condition. The aim of this paper is to propose a decision analytic model to evaluate long-term costs and benefits of alternative management options in patients with depression. The structure of the proposed model is based on the natural history of depression and includes clinical events that are important from both clinical and economic perspectives. Considering its greater flexibility with respect to handling time, discrete event simulation (DES) is an appropriate simulation platform for modelling studies of depression. We argue that the proposed model can be used as a reference model in model-based studies of depression improving the quality and comparability of studies.

A critical review of model-based economic studies of depression: modelling techniques, model structure and data sources

Depression is the most common mental health disorder and is recognized as a chronic disease characterized by multiple acute episodes/relapses. Although modelling techniques play an increasingly important role in the economic evaluation of depression interventions, comparatively little attention has been paid to issues around modelling studies with a focus on potential biases. This, however, is important as different modelling approaches, variations in model structure and input parameters may produce different results, and hence different policy decisions. This paper presents a critical review of literature on recently published model-based cost-utility studies of depression. Taking depression as an illustrative example, through this review, we discuss a number of specific issues in relation to the use of decision-analytic models including the type of modelling techniques, structure of models and data sources. The potential benefits and limitations of each modelling technique are discussed and factors influencing the choice of modelling techniques are addressed. This review found that model-based studies of depression used various simulation techniques. We note that a discrete-event simulation may be the preferred technique for the economic evaluation of depression due to the greater flexibility with respect to handling time compared with other individual-based modelling techniques. Considering prognosis and management of depression, the structure of the reviewed models are discussed. We argue that a few reviewed models did not include some important structural aspects such as the possibility of relapse or the increased risk of suicide in patients with depression. Finally, the appropriateness of data sources used to estimate input parameters with a focus on transition probabilities is addressed. We argue that the above issues can potentially bias results and reduce the comparability of economic evaluations.

Methodologies used in cost-effectiveness models for evaluating treatments in major depressive disorder: a systematic review

BACKGROUND

Decision makers in many jurisdictions use cost-effectiveness estimates as an aid for selecting interventions with an appropriate balance between health benefits and costs. This systematic literature review aims to provide an overview of published cost-effectiveness models in major depressive disorder (MDD) with a focus on the methods employed. Key components of the identified models are discussed and any challenges in developing models are highlighted.

METHODS

A systematic literature search was performed to identify all primary model-based economic evaluations of MDD interventions indexed in MEDLINE, the Cochrane Library, EMBASE, EconLit, and PsycINFO between January 2000 and May 2010.

RESULTS

A total of 37 studies were included in the review. These studies predominantly evaluated antidepressant medications. The analyses were performed across a broad set of countries. The majority of models were decision-trees; eight were Markov models. Most models had a time horizon of less than 1 year. The majority of analyses took a payer perspective. Clinical input data were obtained from pooled placebo-controlled comparative trials, single head-to-head trials, or meta-analyses. The majority of studies (24 of 37) used treatment success or symptom-free days as main outcomes, 14 studies incorporated health state utilities, and 2 used disability-adjusted life-years. A few models (14 of 37) incorporated probabilities and costs associated with suicide and/or suicide attempts. Two models examined the cost-effectiveness of second-line treatment in patients who had failed to respond to initial therapy. Resource use data used in the models were obtained mostly from expert opinion. All studies, with the exception of one, explored parameter uncertainty.

CONCLUSIONS

The review identified several model input data gaps, including utility values in partial responders, efficacy of second-line treatments, and resource utilisation estimates obtained from relevant, high-quality studies. It highlighted the differences in outcome measures among the trials of MDD interventions, which can lead to difficulty in performing indirect comparisons, and the inconsistencies in definitions of health states used in the clinical trials and those used in utility studies. Clinical outcomes contributed to the uncertainty in cost-effectiveness estimates to a greater degree than costs or utility weights.

Change in formulation and its potential clinical and pharmacoeconomic value: example of extended release venlafaxine

INTRODUCTION

The 505(b)(2) route of a New Drug Application (NDA) allows published literature or previous FDA findings of safety and effectiveness to be used for approval. Such drugs are not therapeutic equivalents (i.e., generics); instead, the FDA calls them pharmaceutical alternatives. A recent example is the approval of venlafaxine extended-release (ER) tablets, developed as an alternative to the widely used ER venlafaxine capsules. The smaller size of the tablets makes them available in a 225-mg strength, which is the approved maximum dose in major depressive disorder after up-titration but currently unavailable in the capsule formulation, requiring patients on this dose to take two or three capsules; in addition, the tablets are priced at a discount compared to the capsules.

METHODS

The objective of this review was to investigate how the change in formulation of ER venlafaxine from capsules to tablets, as an example of such a change in formulation, can potentially offer value to patients and society, with a specific focus on pill burden, drug cost, and adherence. Based on a MEDLINE literature search, the pertinent literature was reviewed in a qualitative manner.

REVIEW OF THE LITERATURE

Simplifying treatment regimens, reducing pill burden, and reducing drug costs are recognized strategies for improving adherence. This can be of particular benefit in psychiatric illness because of high rates of nonadherence to treatment. Lack of adherence may negatively impact treatment outcomes and increase disease cost. As such, the ER venlafaxine tablets have the potential to reduce pill burden, improve adherence and outcomes, and reduce cost to patients and society. These preliminary findings need to be corroborated with more primary research and a systematic review of formulation changes.

CONCLUSION

A change in formulation of established therapies such as ER venlafaxine has the potential to offer clinical and pharmacoeconomic benefits to patients and society.

Escitalopram versus other antidepressive agents for depression

BACKGROUND

Although pharmacological and psychological interventions are both effective for major depression, antidepressant drugs remain the mainstay of treatment in primary and secondary care settings. During the last 20 years, antidepressant prescribing has risen dramatically in western countries, mainly because of the increasing consumption of selective serotonin reuptake inhibitors (SSRIs) and newer antidepressants, which have progressively become the most commonly prescribed antidepressants. Escitalopram is the pure S-enantiomer of the racemic citalopram.

OBJECTIVES

To assess the evidence for the efficacy, acceptability and tolerability of escitalopram in comparison with tricyclics, other SSRIs, heterocyclics and newer agents in the acute-phase treatment of major depression.

SEARCH STRATEGY

Electronic databases were searched up to July 2008. Trial databases of drug-approving agencies were hand-searched for published, unpublished and ongoing controlled trials.

SELECTION CRITERIA

All randomised controlled trials comparing escitalopram against any other antidepressant (including non-conventional agents such as hypericum) for patients with major depressive disorder (regardless of the diagnostic criteria used).

DATA COLLECTION AND ANALYSIS

Data were entered by two review authors (double data entry). Responders and remitters to treatment were calculated on an intention-to-treat basis. For dichotomous data, odds ratios (ORs) were calculated with 95% confidence intervals (CI). Continuous data were analysed using standardised mean differences (with 95% CI) using the random effects model.

MAIN RESULTS

Fourteen trials compared escitalopram with another SSRI and eight compared escitalopram with a newer antidepressive agent (venlafaxine, bupropion and duloxetine). Escitalopram was shown to be significantly more effective than citalopram in achieving acute response (OR 0.67, 95% CI 0.50 to 0.87). Escitalopram was also more effective than citalopram in terms of remission (OR 0.53, 95% CI 0.30 to 0.93). Significantly fewer patients allocated to escitalopram withdrew from trials compared with patients allocated to duloxetine, for discontinuation due to any cause (OR 0.62, 95% CI 0.38 to 0.99).

AUTHORS' CONCLUSIONS

Some statistically significant differences favouring escitalopram over other antidepressive agents for the acute phase treatment of major depression were found, in terms of efficacy (citalopram and fluoxetine) and acceptability (duloxetine). There is insufficient evidence to detect a difference between escitalopram and other antidepressants in early response to treatment (after two weeks of treatment). Cost-effectiveness information is also needed in the field of antidepressant trials. Furthermore, as with most standard systematic reviews, the findings rely on evidence from direct comparisons. The potential for overestimation of treatment effect due to sponsorship bias should also be borne in mind.