pharmacoeconomic evaluation of antidepressants

Pharmacoeconomics 2005; 23 (6): 595-606REVIEW ARTICLE 1170-7690/05/0006-0595/$34.95/0

© 2005 Adis Data Information BV. All rights reserved.

Pharmacoeconomic Evaluationof AntidepressantsA Critical Appraisal of Methods

Sheikh Usman Iqbal1 and Mark Prashker2,3

1 Health Outcomes Technologies Program, Health Services Department, Boston UniversitySchool of Public Health, and Center for the Assessment of Pharmaceutical Practices (CAPPs),Boston, Massachusetts, USA

2 Health Services Department, Boston University School of Public Health, Boston,Massachusetts, USA

3 Center for Health Quality, Outcomes and Economic Research (CHQOER), VA Health ServicesResearch and Development, Bedford, Massachusetts, USA

ContentsAbstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5951. Literature Search and Selection Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5962. Critical Analysis of Selected Economic Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 597

2.1 Retrospective Database Evaluations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5972.1.1 Study 1 (Hylan et al.) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5982.1.2 Study 2 (Sclar et al.) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5982.1.3 Study 3 (Simon and Fishman) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5992.1.4 Study 4 (Forder et al.) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 599

2.2 Meta-Analyses Followed by Decision-Tree Modelling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5992.2.1 Study 5 (Einarson et al.) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6012.2.2 Study 6 (Jonsson and Bebbington) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6012.2.3 Study 7 (Einarson et al.) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6012.2.4 Study 8 (Doyle et al.) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 602

3. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6024. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 604

In recent years, there has been much debate regarding the real cost effective-Abstractness of new antidepressants. This review is an attempt to identify key contentiousmethodological issues that can impact the reliability, validity and quality of theresearch on this subject. There are inherent complexities between inputs andoutcomes related to depression, and the choice of pharmacoeconomic methodolo-gy requires a crucial balance between the study design and its ability to capturerelevant information. Knowledge of the real efficiency of antidepressants shouldalways be ascertained with reference to the real-world setting. Studies that show acorresponding balance between internal and external validity, coupled with soundmethodology and standardised reporting, have the potential to translatepharmacoeconomics research into real-world, time-relevant decision-making.

The adequacy and acceptability of pharmacoeco- pered by a lack of standardisation regarding studynomic evaluation of antidepressants has been ham- objectives, methodology, assumptions, use of avail-

596 Iqbal & Prashker

able data and outcome measures. One apparent rea- the years 1994–2003. The keywords for the searchson is the intrinsic complexity between inputs and were: ‘depression’, ‘antidepressants’, ‘economics’,outcomes related to depression, and the continuous ‘pharmacoeconomics’, ‘outcomes’, ‘costs’, ‘cost-ef-variability of clinical measures in the patient popula- fectiveness’ and ‘cost-benefit analysis’. Our initialtion over time. In addition, there are weaknesses and search identified about 1000 candidate studies. Aftera lack of consistency in the conduct, methodology the initial search, abstracts of the selected articlesand reporting of depression-related economic stud- were screened by study investigators to ascertain theies that affect the overall credibility and reliability of exact nature of economic analyses and the type ofthis research. pharmacotherapy.

Sound theoretical foundations and standardised We excluded economic studies with cost-utilitymethodological approaches can enhance the credi- analyses, because the issues around reliability, va-bility of pharmacoeconomics in a real-world setting. lidity and specificity of the utility instruments em-Moreover, research practices that serve to minimise ployed in depression studies were outside the scopereal or perceived bias will increase the quality and of the review. We also excluded papers on psycho-usefulness of such studies. Major depression is a therapy and other non-pharmacological interven-disorder with great personal and societal costs. The tions, paediatric and adolescent depression, andtremendous clinical diversity among people with the pharmaceutical comparisons other than tricyclicillness, coupled with the inherent complexities in antidepressants (TCAs), selective serotonintreating depression, reinforces the need to identify reuptake inhibitors (SSRIs) and serotoninvarious aspects of care related to depression and noradrenaline (norepinephrine) reuptake inhibitorsexamine their relevant impact on resource utilisation (SNRIs). After this screening process, 256 articlesand cost assessments. remained. After review, a final set of 118 articles

The purpose of this review is to evaluate the that could be applied expediently to published crite-standards and methodological issues for economic ria/templates for economic analysis of healthcareevaluation of antidepressants that can impact the technology were selected to be part of our database.reliability, validity and sensitivity of the pharma- We conducted extensive auditing and evaluationcoeconomic data. The accuracy and appropriateness of the selected literature on antidepressant use, asso-of results from economic evaluations for allocating ciated costs, healthcare expenditures and respectiveresources in healthcare are points of major concern outcomes. We identified various methodologicalfor decision-makers. The new antidepressants are problems and shortcomings in the articles by em-expensive agents, and any potential advantage of ploying published criteria/templates for economicthese drugs must be weighed against their extra high analysis of healthcare technology.[1] We also select-cost. Lack of credible, research-based data may pre- ed eight of the published articles and carried out avent us from detecting any differences in critical analysis on each. Our selection criterion forpharmacotherapy or from appreciating the subtleties the studies to be included in the critical analysis wasbetween antidepressants in real-world effectiveness. based on the social citation index. Amongst theRecognising this, the present review emphasises the articles with at least ten citations per study, thoseimportance of real-world relevance of study results, studies that represented the earliest efforts in evalu-with the corresponding balance between internal ating the economic aspects of newly introducedand external validity. Without such efforts, concerns antidepressants and benchmarking the methodologi-and reservations will continue to arise, further lead- cal approaches to these assessments were included.ing us into a state of ambiguity regarding the actual Studies published after 2000 were excluded to en-cost effectiveness of newer antidepressants. sure adequate time for citation.

Since 1990, researchers have employed five1. Literature Search andstudy designs for pharmacoeconomic evaluation ofSelection Methodsdepression. These include randomised clinical trials,

Economic studies related to depression were ob- meta-analyses, retrospective database evaluations,tained through a systematic MEDLINE search for decision-analytical modelling and prospective,

© 2005 Adis Data Information BV. All rights reserved. Pharmacoeconomics 2005; 23 (6)

Pharmacoeconomic Evaluation of Antidepressants 597

Table I. Overview of retrospective database evaluations of antidepressants

Authors Study design Population Treatment sample ResultsHylan et al.[3] Retrospective analysis using a FFS private enrollees 2693 new users of Fluoxetine showed lower

two-stage econometric model between 1990 and fluoxetine, sertraline, direct costs compared withDependent variable: natural log 1994 paroxetine or TCAs TCAsof direct healthcare costs Significant differences inIndependent variables: baseline characteristics ofdemographics, co-morbid fluoxetine patients relative toconditions, type of depression, those receiving TCAsprior services, provider No significant differences incharacteristics baseline shown by sertraline

and paroxetine

Sclar et al.[4] Retrospective cohort study HMO enrollees 701 new users of fluoxetine Fluoxetine showed lessMultivariate analysis between 1989 and or TCAs direct costs compared withDependent variable: PPE 1993 Duncan’s Multiple Range TCAsIndependent variables: Test and Chi-squaredemographics, concomitant analyses showed nopharmacotherapy, prior costs, significant differenceMPR, antidepressant therapy, between two groups forinitial prescriber classification dependent variables

Simon and Retrospective cohort study Medicare/Medicaid 5169 new users of No overall differences inFishman[5] Dependent variable: direct HMO enrollees desipramine, fluoxetine or costs

healthcare costs between 1992 and imipramine Fluoxetine showed lowerIndependent variables: age, 1994 Fluoxetine users were older non-antidepressant costssex, chronic disease score with greater disease burden with no statisticalTest of differences based on significancelog transformation for normallydistributed variables and ranktransformation for variablesshowing skewed distribution

Forder et al.[6] Retrospective cohort study UK NHS enrollees 392 continuing users of Sertraline showed 2.3%Dependent variable: healthcare between 1993 and sertraline significantly lower directcosts 1994 Differences in two groups costs than TCAsIndependent variables: based on age, sex, numberdemographics, duration and of previous episodes,severity of depression, co-morbid duration and severity ofconditions depressionOrdinary least square multipleregression followed by cross-predictions

FFS = fee for service; HMO = health maintenance organisation; MPR = medication possession ratio; PPE = post-period expenditure; TCA =tricyclic antidepressant.

randomised, naturalistic enquiry. To accommodate insurers, Medicaid, Medicare programmes and elec-issues relating to ‘efficacy versus effectiveness’ and tronic records that are reliable sources of patientto allow a judicious merger of theory and practice, diagnosis, choice of drug and resource utilisation.[2]

we selected two designs for our analysis: retrospec- A common observation is that they often arrive attive database investigations and meta-analysis fol- differing conclusions, with certain studies showinglowed by decision-tree modelling. favourable outcomes for newer drugs,[3-6] while the

remainder present less certain results.[7-9] However,2. Critical Analysis of Selected when observed from a utilisation and cost perspec-Economic Studies tive, almost all the studies share a common view-

point: that higher acquisition costs of newer drugs2.1 Retrospective Database Evaluations (SSRIs, SNRIs) are more or less offset by a reduc-

tion in overall healthcare resource utilisation.[10]The majority of retrospective evaluations related

The retrospective database evaluations that weto depression rely on administrative databases fromhealth maintenance organisations (HMOs), private subjected to critical analysis are summarised in table



I and discussed in more detail in the remainder of trade-offs that may be posed by the two drug catego-this section. The first three analyses were cost- ries.minimisation studies designed from the outset toexamine costs without taking into account the health 2.1.2 Study 2 (Sclar et al.)outcomes of different antidepressants. The study by A retrospective economic evaluation from HMOForder et al.[6] was a more classic analysis with claims data comparing the 1-year direct medicaldirect costs measured in monetary units, whereas the costs of 701 patients newly prescribed either fluoxe-benefits were in natural units of clinical outcomes. tine or one of the listed TCAs (amitriptyline,All the studies employed different statistical meth- desipramine, nortriptyline) was conducted by Sclarods to adjust for observed and unobserved factors et al.[4] Using a multiple regression model on select-along with sensitivity analyses to evaluate the ro- ed individual patient data, they showed that thebustness of study results. receipt of a TCA compared with fluoxetine was

A major point of concern with the retrospective associated with significant greater healthcare costsevaluations analysed is the lack of health outcomes ($US313 per patient, 1993 values) because of in-discussion. In addition, with the exception of Hylan creased health services utilisation.et al.,[3] none of the studies took into account the The authors did not include patients’ existingpotential effects of suboptimal drug dosage on treat- health status and the degree of severity of depressionment effects and health outcomes. in their regression model, and therefore the compa-

rability between the groups is questionable. Hos-2.1.1 Study 1 (Hylan et al.) pitalisation was shown to be the major driver of theHylan et al.[3] evaluated the 1-year direct health- overall costs in the TCA group, and that might have

care costs associated with newly started treatment been due to case mix differences. In terms of variouswith TCAs and SSRIs (fluoxetine, sertraline and assumptions drawn by the authors, the patient levelparoxetine) by using fee-for-service private insur- archive data (6 months) before the initiation of an-ance claims from 1990 to 1994 for a sample of 2693 tidepressant therapy is not a valid, reliable estimateof 450 000 enrollees with 20 large employers across of health status.[2] Continuation of prescription wasthe US. The authors used a two-stage econometric assumed to be related to higher levels of compliancemodel to adjust for both observed and unobserved and wellness. This assumption may be true withfactors, including demographics, disease variables regard to compliance, but a patient’s wellness de-and suboptimal dosage. The 1-year total healthcare pends on a range of issues including individual(median) cost was found to be significantly lower patient response, physician–patient communication,for fluoxetine-treated patients than for the TCA social support, job satisfaction and concomitant psy-group. For the sertraline and paroxetine groups, the chological interventions, and is not a certain out-costs did not differ significantly from the TCA come of an increased medication possession ratiogroup. (MPR).[11,12]

The study showed no statistical differences be- In terms of selection criteria, patients had totween treatment groups in the univariate analysis of remain exclusively on a single antidepressant. Thistotal mean costs. Even assuming that it was a result has the potential to create overall cost-measurementof skewed distribution, the differences in the median bias. In normal practice, patients do switch from onecosts were not statistically significant. In the mul- therapy to another, and subsequent prescriptions aretivariate analysis, the statistically significant differ- certainly associated with extra expenditures in termsences among the groups (fluoxetine versus TCA) of further consultations and drug acquisition, etc.were mostly driven by lower non-mental healthcare Exclusion of these patients from the analysis iscosts, which may or may not have a linear relation- likely to reduce drug costs, especially for thoseship with mental healthcare costs. The fundamental comparators with a higher degree of intolerance forlimitation of the study was that there were no specif- the initial prescription.[13] Therefore, the estimationic or assumed outcomes that could be related to the of drug costs does not correspond to real-worldcosts, so it is impossible to evaluate the economic clinical practice and patient behaviour.



2.1.3 Study 3 (Simon and Fishman) often confronts challenges including illiteracy, so-cial deprivation and alternative conception of ill-The direct medical costs for 5169 primary careness, etc.,[19] may question the findings of the studypatients newly receiving antidepressant treatmentin terms of its overall representation to the generalduring 1992–1994 with fluoxetine or TCAspopulation.(imipramine or desipramine) were compared by Si-

mon and Fishman.[5] Compared with TCAs, the use2.1.4 Study 4 (Forder et al.)of fluoxetine was associated with $US140 higherForder et al.[6] employed a non-modelling, quasi-mean drug costs and $US300 higher mean costs for

experimental approach by comparing direct medicalall other health services per patient (1995 values).and non-medical costs among 392 patients continu-The cost differences were not statistically signifi-ing to receive sertraline or TCAs. The sertralinecant. However, the costs (non-antidepressant) aftergroup was taken from a previous open-label study,adjusting for age and total costs in the pretreatmentwhereas the TCA group was identified from theperiod were $US75–300 lower per patient in thesame general practices. The patients in the twofluoxetine group than in either of the TCA groups,groups were matched on the basis of age, sex, num-but the differences were not statistically significant.ber of previous episodes of depression, duration and

This study had no disease-specific outcome mea- severity of depression. The sertraline-treated pa-sure that could be linked to costs. Although they tients showed lower mean costs compared withadjusted for co-morbidity by using the chronic dis- TCA-treated patients, but none of the results wereease score, which has no specific relevance to de- statistically significant. In terms of treatment out-pression,[14] they did not take into account the sever- comes, cost per successfully treated patient wasity of depression. There was an intent-to-treat analy- considered, and sertraline was dominant for all defi-sis; therefore, the cost of medication switches was nitions of cost and outcomes except for the cost ofassigned to the initial prescription group. The pa- prescribed antidepressant medication alone.tients in the fluoxetine group were significantly old- This more focused model showed no definitiveer with a higher burden of illness, so it is possible patient outcomes; the treatment effect (success/fail-that many of these patients had already undergone ure) was presented in the form of ‘patients veryTCA therapy in the past and therefore, in the prior much improved’ and ‘patients at least somewhatobservation period or during the study, were less improved’, which is a unique categorisation and notvulnerable to medication switches compared with comparable with others used in the literature. Thethe TCA group. There was no secondary analysis inpatient psychiatric hospitalisation was a majorexcluding those who switched medication to deter- driver of the cost among the TCA group. The au-mine any significant differences. There was no spec- thors acknowledged considerable suboptimal pre-ification of a minimum or defined daily dose. Sever- scribing in the TCA group, but did not account foral studies have demonstrated a greater probability of this with adjustment in their regression model orreceiving antidepressant pharmacotherapy at a de- sensitivity analyses. The suboptimal dosage couldfined daily dose when being treated with an SSRI have a direct relationship with treatment effect[20]

relative to a TCA.[15-18] It is possible that a number and subsequent hospitalisation, thus driving up theof patients treated for depression may have been overall costs. In addition, no blinding was done onprescribed TCAs at subtherapeutic levels, which behalf of the assessors who interviewed patients tocould be linked directly to inadequate treatment ascertain details about medication, co-morbidity,effect and increased health services utilisation. prognosis, service utilisation and outcomes; thus,

The cost data were derived from Medicaid and introducing the possibility of observer bias.Medicare populations that have sociodemographicand health differences from the general population. 2.2 Meta-Analyses Followed byEven though the chronic disease score may adjust Decision-Tree Modellingfor health differences, the variations in soci-odemographic indicators, especially for the Medi- A significant number of depression studies em-caid population, which is inherently vulnerable and ploy decision-analytical modelling to structure



Table II. Summary of simulation studies evaluating the cost effectiveness of antidepressants

Authors Comparators Data sources and study design Outcomes ResultsEinarson et al.[21] SNRIs vs SSRIs, Efficacy data from a meta-analysis of Treatment success and SNRIs showed the highest

TCAs, HCAs 28 randomised trials SFDs cost effectiveness basedMinimum duration of therapy: 4 weeks on brand acquisition costsHRSD scores ≥18Treatment patterns from clinical expertsDirect healthcare costs from privateHMO claims and drug costs from theRed BookTimeframe of the model = 1 yearInclusion of direct costs only

Jonsson and Paroxetine vs Efficacy data from a clinical trial of Treatment success Paroxetine was associatedBebbington[22] imipramine 717 patients with a lower healthcare

Treatment patterns from Delphi panel cost per successfullyInclusion of direct costs only treated patient because ofDuration of clinical trial = 6 weeks a higher success rate andTimeframe assumed in the model = fewer hospitalisations and12 months treatment withdrawalsCosts from private health databaseclaims

Einarson et al.[23] SNRIs vs SSRIs, Efficacy data from a meta-analysis of Treatment success and Venlafaxine was dominantTCAs 36 randomised trials involving 2953 SFDs in all incremental

patients pharmacoeconomicMinimum duration of therapy = 4 weeks analysesHRSD scores ≥15Treatment patterns from Delphi panelCosts from Ontario’s Schedule ofBenefits and hospital statisticsTimeframe of the model = 6 monthsInclusion of direct costs only

Doyle et al.[24] SNRIs vs SSRIs, Efficacy data derived from two meta- Treatment success and Venlafaxine most costTCAs analyses conducted by Einarson et al.[23] SFDs effective in nine of ten

Treatment patterns obtained from local countriesclinical and health economic experts inten countriesCosts obtained from country-specificstandard lists of healthcare resourcevaluationsTimeframe = 6 months

HCA = heterocyclic amine; HMO = health maintenance organisation; HRSD = Hamilton Rating Scale for Depression; SFD = symptom-freeday; SNRI = serotonin noradrenaline (norepinephrine) reuptake inhibitor; SSRI = selective serotonin reuptake inhibitor; TCA = tricyclicantidepressant.

problems and fill in gaps in information.[21-26] With section. The primary concern emerging from therespect to depression, these modelling techniques modelling studies is the direction and magnitude ofhave the potential to offer useful and reliable insight potential bias in their data sources. Scant attentionpertaining to treatment efficacy and resource usage. has been paid to the fact that depression runs aHowever, owing to the complex nature of the dis-

chronic course with many heterogeneous as well asease, decision analysis is subject to a number of

unpredictable outcomes. Model extrapolations rely-methodological issues such as the use of data thating solely on short duration data or a limited numbermay lack external validity, and inadequate attentionof trials cannot account for longer-term outcomesto include all factors that influence the disease pro-

cess and track them over time. such as restoration of normal functioning, treatmentsuccess or prevention of relapse and recurrence ofThe modelling simulation studies that we sub-depression. Multiple data sources are required tojected to critical analysis are summarised in table II

and discussed in more detail in the remainder of this have more reliable and robust results.



2.2.2 Study 6 (Jonsson and Bebbington)All of the studies we analysed were cost-effec-Jonsson and Bebbington[22] evaluated the directtiveness studies and used relevant data from

medical cost of depression by comparing paroxetinerandomised, controlled trials, as well as feedback(an SSRI) with imipramine (a TCA). They firstfrom Delphi panels, to construct decision trees. Inestimated the cost of illness by using a top-downaddition, a number of simplifying assumptions wereapproach and then evaluated cost effectiveness byused by the authors to fill in gaps in the information.developing a simulation model based on clinicalThe studies included all relevant classes of antide-decision-analysis theory. The model used data main-pressants, i.e. TCAs, SSRIs, SNRIs and heterocyclicly from the results of one particular clinical trialamines (HCAs), that are prescribed in daily clinicalcomprising 717 patients. The 1-year total cost (1990practice. With the exception of Jonsson and Beb-values) of depression in the UK was estimated to bebington,[22] SNRIs turned out to be the most cost-£222 million. The expected cost per patient over 1effective drug for the treatment of depression.year was relatively equal for paroxetine (£430) andimipramine (£424). The cost per successfully treated2.2.1 Study 5 (Einarson et al.)patient was lower for paroxetine (£824) than forEinarson et al.[21] compared venlafaxine (animipramine (£1024). The results were stable in theSNRI) with TCAs, SSRIs and trazodone (an HCA)sensitivity analysis that was performed on all theby taking treatment costs from a survey of threevariables in the model.HMOs and then incorporating them in a decision-

The authors used clinical data that were derivedtree model for inpatients and outpatients. Clinicalfrom selected randomised, clinical trials, with re-outcomes were derived from a meta-analysis of thesults taken primarily from a single trial. This non-medical literature for oral treatment of major depres-random selection is itself a source of potential bias.sive disorder. The model showed SNRI therapyThe authors did not include failure to respond todemonstrating the highest level of cost effectivenesstreatment, and therefore the inference is that effec-in inpatient settings, with symptom-free days as ativeness of treatment was based solely on compli-treatment outcome. In terms of outpatient treatment,ance. This creates potential bias on behalf of thethe generic HCAs showed the highest level of costauthors, keeping in mind the 6-week duration of theeffectiveness; when using brand name drug acquisi-trial from which the observations were taken. Rely-tion costs, the SNRIs demonstrated the maximuming solely on compliance rates without adjusting orcost effectiveness.taking into account other factors would typically fail

This was carried out from a cost-based payer to represent recommended or typical practice.[28,29]perspective without an intention-to-treat analysis. Even though the study was heavily criticised byThe outcome was symptom-free days. In terms of Freemantle et al.[30] and other researchers,[31-33] thisthe cost-based payer perspective, health plans and appears to be the most rigorous and comprehensivepatients are most interested in treatment success and analysis, incorporating almost all the standard re-not just in symptom remission.[27] None of the dif- quirements relating to the clarity and completenessferences among the groups were statistically signifi- of an economic evaluation. Unfortunately, the studycant, probably because of small sample sizes. For results suffered heavily due to the limited scope ofinstance, in the outpatient group, the median sample enquiry, as results from a single clinical trial weresize was 29 patients for SSRIs and 36 for TCAs. mostly employed for the study. This was followedSimilarly, inpatient projections were based on data by some questionable assumptions around treatmentfrom 82 patients using SSRIs and 67 patients using effectiveness, as discussed earlier in section 2.2.2.venlafaxine. It is often the case that these studies are

2.2.3 Study 7 (Einarson et al.)specifically powered and designed to ensure ade-quate examination of outcomes and this may not be Einarson et al.[23] conducted a cost-effectivenessappropriate for analysing costs. This leads to analysis from the perspective of the Ontario (Cana-problems interpreting cost differences because of da) Ministry of Health using SNRIs (venlafaxine),the large variability in costs for the chosen sam- SSRIs (fluoxetine, fluvoxamine, sertraline, paroxe-ples.[1] tine) and TCAs (amitriptyline, imipramine,



desipramine, nortriptyline). A decision tree over 6 The rates for efficacy and withdrawal from treat-months was employed using an expert panel, and ment were obtained from the same trials as those ofcosts during that time period (1996) were deter- Einarson et al.[23] and applied to all the countries, butmined from standard lists that included the costs of no information was provided about the possibledrugs as well as the care received for depression. implications of country-specific assumptions em-Success and treatment withdrawal rates were deter- ployed by the authors. An effort was made to estab-mined from a meta-analysis of 36 published lish the generalisability of the results, without takingrandomised, controlled trials. Treatment success and into account the fact that this could only be argued insymptom-free days were treated as study outcomes. the context of effectiveness estimates as opposed toThe expected cost per treatment success in outpa- efficacy estimates. The specialised patient popula-tients and inpatients, respectively, was $Can6044 tions of clinical trials and the results extrapolatedand $Can17 234 for venlafaxine, $Can6634 and from them lack external validity, and pooling secon-$Can20 874 for SSRIs, and $Can9035 and dary data from various study designs would make$Can20 459 for TCAs. In terms of intermediate the analysis more generalisable.outcomes, the respective expected cost per symp-

3. Discussiontom-free day for outpatients and inpatients, respec-tively, was $Can45.92 and $Can127.33 for Most published pharmacoeconomic studies ofvenlafaxine, $Can51.64 and $Can157.04 for SSRIs, depression do not include all of the relevant aspectsand $Can70.71 and $Can152.43 for TCAs. that are essential for a structured, reliable and credi-Venlafaxine was found to be dominant in all incre- ble economic analysis. Because there are no explicitmental pharmacoeconomic analyses. uniform criteria, there is wide variability among

Einarson et al.[23] selected studies with a mini- studies with regard to handling of factors such asmum level of 4 weeks’ duration of drug therapy. compliance, treatment withdrawals, relapses, toxici-Therapeutic responses often lag behind the initiation ty, adverse effects and time horizons. There is alsoof antidepressant therapy by several weeks and, as a wide variability in study set-up and the types ofresult, it is felt that a minimum of 6 weeks is costs (with their subsequent effects) included. Al-required to assess accurately the full impact of medi- though such studies have financial and medical im-cation.[34] Venlafaxine and TCAs were backed up by plications, the lack of application of widely acceptedSSRIs, whereas SSRI failures were treated with guidelines on the conduct and reporting of economicSNRIs, but there was no mention of using an inten- analyses make it difficult to interpret this research.tion-to-treat analysis. For pharmacoeconomic studies of depression, the

choice of methodology requires a crucial balance2.2.4 Study 8 (Doyle et al.) between study design and the overall applicability toWith very similar methodology, modelling tech- various healthcare environments. Marked variations

niques and treatment outcomes to those of Einarson in costs and outcomes have been found in studies ofet al.,[23] Doyle et al.[24] conducted a multinational patients with depression. This stems from differ-pharmacoeconomic evaluation comparing SNRIs ences in inputs, which encompass variations inwith SSRIs and TCAs in ten countries across the US healthcare systems, clinical manifestations and pa-and Europe. Information for the model was obtained tient characteristics. Therefore, it is imperative forthrough a meta-analysis of clinical trials as well as the research community to understand that econom-local clinical and health economic experts in each ic investigations in depression undertaken as part ofmarket. The total expected cost per patient for treat- an informed decision-making process must adhereing major depressive disorder with venlafaxine was to the highest standards and furnish credible, robustthe lowest cost in nine of ten countries studied, data. This will help us to understand the complexresulting in savings to the primary payer in almost interaction and critical interplay among various dis-all markets. Moreover, along with cost savings per ease characteristics and their relevance to choice oftreatment success, venlafaxine was also associated pharmacotherapy, economic costs and treatmentwith a higher number of symptom-free days. outcomes. Randomised clinical trials, even though



regarded as a gold standard for clinical research, are count robust and applicable measurement tech-not a sufficient source of informed decision-making niques, undermines the credibility and effectivenessin terms of economic evaluation of depression. of the results. These studies do not address a specific

question about value for money, and therefore bringDepression is amongst the most difficult areas tointo question the basic rationale behind conductingcost because of the wide range of grades of severity,an economic evaluation. From a policy perspective,its chronic nature with recurrent episodes, potentialthese evaluations do not usually incorporate in theirlack of accurate diagnosis, compliance issues, widediscussions the importance of distribution of costsvariations in therapeutic dosages of antidepressantand outcomes among different patient or populationdrugs, productivity issues, and potential links togroups. Also, there exist system-level differencessuicides and accidents.[35-38] Consequently, the in-among the studies that can directly influence theclusion and exclusion criteria of clinical trials, incost assessments and study results.[2]combination with their strict protocols, limit appli-

cability of studies to real-world use. It is the beha- Health status of the plan members, utilisationviour of patients and providers interacting with vari- management techniques, cost sharing with enroll-ous aspects of drug and healthcare services that ees, and physician reimbursement all affect cost andleads to variability in clinical outcomes and subse- possibly outcomes through several avenues, and arequent expenditures, thus making it difficult to con- central to the discussion of differentials in consumerduct economic analyses. Furthermore, as cost data expenditure across various health plans.[27] Healthare more variable than effect data, there are issues service utilisation is directly affected by health sta-relating to statistical power and inadequate sample tus.[2] Similarly, differences in co-payments and costsizes that limit the ability to demonstrate clinical and sharing for one comparator drug over the other havecost differences simultaneously.[1] the potential to influence access, compliance,

utilisation and outcomes.[2] Fee-for-service provid-When one examines the types of trial, it is possi-ers may have an incentive to maximise utilisation ofble to rate their usefulness for providing data forhealthcare services, whereas capitated providerseconomic analyses.would tend to do otherwise and minimise the burdenProspective, naturalistic clinical trials have beenof documentation. For every study setting, there is asuggested as the preferred study design that canneed to explain the critical interplay among theseprovide the best data for the cost-effectiveness eval-factors and the extent to which they can potentiallyuation of antidepressants.[10,39,40] However, the smallinfluence costs and healthcare resource utilisation.number of studies conducted so far do not furnishSuch factors must be taken into account to make aenough data to support any meaningful trend. More-fair and relevant comparison with other healthcareover, issues like the sample size, duration of theenvironments.follow-up period, and robustness of the inclusion

Decision analysis affords a structured process forand exclusion criteria would continue to be of keypharmacoeconomic comparison. However, in de-concern with these studies. It is also doubtful thatpression, there are complex relationships betweenany single empirical study would be able to exploreinputs and outcomes and the clinical measures thatall of the economic aspects of depression.[10,39]

are continuous variables in the patient populationIn a short-term scenario, retrospective economicover time. Where expert opinion is used in decision-evaluations utilising large administrative databasesanalytical models, the experience of the expert panelfrom HMOs, private insurers, Medicaid, Medicaremay be biased towards patients who are seen moreprogrammes or other electronic records to capturefrequently, and this may reflect inadequate assump-resource utilisation could be a useful strategy totions or limited scope of enquiry. Moreover, expertassess the impact of treatment effects and resourceopinion across practice settings and insurance sys-usage on both costs and outcomes. However, mosttems remains controversial.[41]such studies do not include valid and reliable esti-

mates of health outcomes. Consideration of vague, In studies that use meta-analysis, most of thenonspecific outcomes, or consequences based on efficacy data are derived from clinical trials thathypothetical assumptions without taking into ac- may have internal validity but lack substantial exter-



nal validity. The credibility of adverse effect-related studies,[48-51] have major implications for manywithdrawal rates taken from a 6-week trial is ques- players in society and should be included regardlesstionable. Tolerance to many of the cognitive and of any specific perspective taken. Apart from thepsychomotor deficits induced by TCAs is likely to obvious patient’s perspective, an estimated 200 mil-develop in the continuation and maintenance phase lion work days are lost each year in the US due toof therapy.[42,43] In contrast, the sexual adverse ef- employee depression,[48] with the costs accrued tofects of SSRIs usually occur at a later stage of the employer, through absenteeism and productivitymedication therapy.[44] losses, and to government agencies through transfer

payments in the form of welfare, unemployment,Similarly, most randomised, clinical trials of de-disability, etc. There is no apparent attribution ofpression have employed the Hamilton Rating Scaleindirect costs to health plans, but, from a marketfor Depression (HRSD) scale as their main outcomeperspective, cost-effective improvement (from thefor measurement of depression and response topatient’s viewpoint) of care for depression leads totreatment, with success termed as a 50% reductionbetter patient functioning as well as increased pa-in the scale. This is an arbitrary definition as it maytient satisfaction, which certainly is meaningful toshow a clinically meaningful response, but this re-health plans competing with others in the market.sponse definition does not always depict the whole

picture. For a severely depressed patient with a4. Conclusionsbaseline HRSD score of 30, a reduction to 15 would

be termed a treatment success, but the patient wouldFrom the literature, it is quite evident that thestill be depressed (although not as severely de-

preferred method for pharmacoeconomic evaluationpressed). An HRSD score of <7 or <8 is often usedof antidepressants is cost-effectiveness and cost-as the criteria for remission of depressive epi-utility analysis. A cost-minimisation study can onlysodes.[45,46] Therefore, the magnitude of symptomsbe carried out without ambiguity if it is based onat the endpoint is also an important measure ofexisting equivalent (medical) evidence of effective-remission and should be included in the criteria forness among the comparators.success. Furthermore, HRSD is an unstructured as-

Despite the published guidelines, the existingsessment and is particularly subject to observer bi-standards for conducting economic research in de-as.[47] Even with complete blinding, the adversepression are insufficient. Economic evaluations re-effects of the two comparators (SSRIs and TCAs)lated to depression should focus on increasing ourdiffer significantly, which could influence the wayknowledge of the real efficiency of the drugs andthat the investigator assesses the outcome, especial-related healthcare technologies so as to allow thely when the focus of interest and optimism is to-judicious use of societal resources. Guidelines maywards the new drug. There are now other alterna-not ensure the quality of a study, but they would settives such as structured interviews, especially thosedown standards for research methods and introduceavailable in computerised format (e.g. Revisedsome consistency and reliability to the methods ofClinical Interview Schedule, Diagnostic Intervieweconomic evaluation. Concerns about the compara-Schedule) that should be the preferred method forbility and credibility of analyses will probably per-the measurement of depression.[47]

sist if future improvements are not made in the field.Most pharmacoeconomic studies of depression Sustaining vigilance while preserving the potential

should evaluate the indirect costs of depression, but to improve and innovate will require a cautiousnone of the aforementioned studies did so. Where balance. Methodological rigour, a strong theoreticalboth the direct and indirect costs of depression have basis and standardised reporting will help to main-been evaluated, direct costs comprise only one-third tain that paradigm.of the annual economic costs of depression, whereastwo-thirds of costs were indirect costs, related Acknowledgementspredominantly to absenteeism and lost productivi-ty.[48] Indirect costs related to depression, which Sheikh Usman Iqbal was responsible for the literaturehave been documented extensively in a number of search and review, analyses and manuscript writing. Mark



19. Bruce EL, Haiden AH, Carol T, et al. The evolution of qualityPrashker was responsible for literature review, analyses, man-management in state Medicaid agencies: a national survey ofuscript writing and editing.states with comprehensive managed care programs. Jt Comm J

The authors have no conflicts of interest. The manuscript Qual Improv 2002; 28: 426-36was supported in part by Boston University School of Public 20. Lin EH, Von KM, Katon W, et al. The role of the primary careHealth, Health Services Department, and Center for the As- physician in patients’ adherence to antidepressant therapy.

Med Care 1995; 33: 67-4sessment of Pharmaceutical Practices (CAPPs).21. Einarson TR, Arkian S, Sweeney S, et al. A model to evaluate

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and consequences of small trials in depression: a systematic E-mail: [email protected]


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