jiwa3

Drugs Aging (2012) 29:793-806DOI 10.1007/S40266-012-0012-5

F SYSTEMATIC REVIEW

Effect of Selective Serotonin Reuptake Inhibitors in Alzheimer'sDisease with Comorbid DepressionA Meta-Analysis of Depression and Cognitive Outcomes

Amir A. Sepehry Philip E. Lee Ging Yuek R. Hsiung B. Lynn Beattie Claudia Jacova

Published online: 11 October 2012 Springer International Publishing Switzerland 2012

AbstractBackground Comorbid depression is a leading neuro-psychiatrie complication in the Alzheimer's disease (AD)syndrome. In 2011, diagnostic criteria for AD were revisedto include neuropsychiatrie symptoms. It has been pro-posed that adding an antidepressant to existing treatmentfor AD could provide relief for not only depressive but alsocognitive symptoms.Objective The aim was to quantitatively review publishedstudies to examine the efficacy of selective serotoninreuptake inhibitor (SSRI)/serotonin-noradrenaline (norepi-nephrine) reuptake inhibitor (SNRI) therapy for alleviation ofcomorbid, diagnosed depression as well as cognitive declinein AD.Methods A search of electronic databases was performed.Studies were retained for analysis if SSRI/SNRI antide-pressant therapy was compared with placebo among ADpatients with comorbid depression. Effect-size (ES)

estimates (Hedges' g) were calculated using Comprehen-sive Meta-Analysis software.Results From 598 examined studies, 12 SSRI studies metthe inclusion criteria, and from these, only six met all cri-teria, among which five reported sufficient and consistentdata to be included in the meta-analysis. Within a randomeffect model, ES estimates of the first and second nestedglobal analyses were non-significant, non-heterogeneousand small to null at the endpoint for depression, favouringSSRIs, -0.06 and -0.10, respectively {p > 0.05). The ESfor global cognition as measured by the Mini-Mental StateExamination was negligible (ES = 0.001).Conclusions Current evidence does not support the effi-cacy of SSRI treatment for symptoms of comorbiddepression in AD. However, studies differed in terms ofcriteria for diagnosis of depression, the compound testedand outcome measures for depression. These factors couldaccount for the lack of a clear benefit for depression.

A. A. Sepehry G. Y. R. Hsiung C. JacovaUniversity of British Columbia (UBC),College for Interdisciplinary Studies, Graduate Programin Neuroscience, Vancouver, BC, Canada

A. A. Sepehry P. E. Lee G. Y. R. Hsiung C. Jacova (E3)UBC Division of Neurology, Department of Medicine,UBC Hospital, 2211 Wesbrook Mall, Rm 152,Vancouver, BC V6T 2B5, Canadae-mail: [email protected]

A. A. Sepehry P. E. Lee G. Y. R. Hsiung B. L. Beattie C. JacovaClinic for Alzheimer Disease and Related Disorders,UBC Hospital, Vancouver, BC, Canada

P. E. Lee B. L. BeattieUBC Division of Geriatric Medicine, Department of Medicine,Vancouver, BC, Canada

1 Introduction

Alzheimer's Disease (AD) is one of the leading publichealth concerns in the 21st century, and has been estimatedto account for 63 % of all dementias [1, 2]. Alzheimer'sDisease International, the international federation ofAlzheimer associations, estimated that 36 million peopleworldwide are living with dementia, with numbers dou-bling every 20 years, leading to 66 million by 2030 and115 million by 2050 [3]. These estimates are consistentwith current projections for AD provided in Canadian andUS reports, in which the number of individuals affected byAD is projected to increase dramatically in the next twodecades, when there will be 1 million affected individualsby 2038 in Canada [1] and 7.7 million by 2030 in the USA

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794 A. A. Sepehry et al.

[4]. In this setting, any therapeutic intervention capable ofproviding some benefit warrants close scrutiny.

1.1 Alzheimer's Disease (AD) and ComorbidDepression

Depression in AD is a disabling condition that is under-recognized and highly correlated with increased healthcareutilization, risk of suicide, and greater severity and accel-eration of cognitive impairment [5-10]. The reportedprevalence of comorbid depression or depressive symp-toms in individuals with AD has been quite variable,ranging from 3 to 50 % [11], likely due to differences inmethods of assessment, diagnostic criteria, stages ofdementia, and other factors. Comorbid depression com-plicates diagnosis, affects treatment approaches and out-comes, and decreases the quality of life of affectedindividuals as well as their caregivers.

1.2 Pharmacotherapy for AD and Depression

Pharmacological treatment of AD is currently based on twointernationally approved types of medications: cholines-terase inhibitors (ChEIs) and the A^-methyl-D-aspartate(NMDA) receptor agonist (memantine). These classes ofmedications are prescribed either alone or in combination[12]. Pharmacotherapeutic guidelines for treating depres-sion in AD recommend that a pharmacological treatmentwith minimal and least severe adverse effects be used as afirst-line approach [13, 14]. The treatments of choice areselective serotonin reuptake inhibitors (SSRIs), includingfiuoxetine, paroxetine and sertraline; serotonin-noradren-aline (norepinephrine) reuptake inhibitors (SNRIs),including venlafaxine; or other newer agents, includingmirtazapine. The recommendation issued by the CanadianConsensus Conference on Dementia (3rd CCCDTD) [15] isthat if a person with dementia and depression has aninadequate response to non-pharmacological interventions,a trial of antidepressant treatment should be considered,with preference given to an SSRI. Additionally, a recentEuropean guideline by the British Psychological Societyand The Royal College of Psychiatrists, commissioned bythe National Institute for Health and Clinical Excellence(NICE) and the Social Care Institute for Excellence (SCIE)(NICE-SCIE), recommends that people with dementia whoalso have major depressive disorder should be offeredantidepressant medication, and that compounds with anti-cholinergic effects should be avoided. They recommendthat treatment should be started by clinicians with specialisttraining, who should follow the NICE-SCIE clinicalguideline 'Depression: Management of Depression in Pri-mary and Secondary Care' after a careful risk-benefitassessment [16].

Evidence has accrued since the 1980s [17-19] thatsuggests that when individuals experiencing cognitiveimpairment and comorbid depression are treated withantidepressant medication, depressive symptoms mayimprove while cognitive symptoms may not. Currently, theprimary treatment goal in AD is to improve function byalleviating cognitive and behavioural symptoms. A sec-ondary treatment goal is to minimize factors exacerbatingcognitive impairment and hindering the efficacy ofantidementia drugs and other interventions. Thus, recognizingand treating depression symptoms in order to maximizefunction appears an important step. There may be also aneurobiological rationale. Emerging evidence from animalstudies suggests that antidepressant treatment may have neu-roprotective and anti-infiammatory properties [20-22].

No review or meta-analysis focused specifically on ADwith comorbid depression; nor did any explicitly focus onboth depression and cognition as pre-specified outcomes ofthe meta-analysis. Hence, using a meta-analytic approach onstudy-level data, we intended to (1) systematically reviewthe currently available evidence examining the use of SSRIor SNRI mono-therapy to alleviate comorbid depression aswell as cognitive symptoms in patients with AD with aconcurrent diagnosis of depression; and (2) highlight gaps inthe literature, which warrant further research into evidence-based pharmaco-therapeutic approaches in AD.

2 Methods

2.1 Data Sources, Searches and Selection

We conducted a search of the electronic search engines[PubMed, EMBASE, Cumulative Index to Nursing andAllied Health Literature (CINHAL), Cochrane CentralRegister of Controlled Trials (CENTRAL) and PsycINFO]on 30 January 2011, without any language restrictions.PubMed was searched using the terms (a) "second andthird generation antidepressants OR citalopram OR dul-oxetine OR escitalopram OR fiuoxetine OR fiuvoxamineOR nefazodone OR paroxetine OR sertraline OR venla-faxine" AND (b) "cognitive OR cognition OR neuropsy-chology OR neuropsychological" AND (c) "Alzheimer'sOR Alzheimer's disease OR AD OR Alzheimer". Psy-cINFO on the OVID platform was searched differently inorder to collect the maximum number of studies. Searchterms were "second and third generation antidepressant" asmajor word or major subject headings OR "citalopram ORduloxetine OR escitalopram OR fluoxetine OR fiuvox-amine OR nefazodone OR paroxetine OR sertraline ORvenlafaxine" AND "Alzheimer". Cross-referencing wascarried out with the aid of several reviews and an earliermeta-analysis of the efficacy and safety of antidepressant

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SSRIs in AD for Depression and Gognition 795

use for depression in AD [23]. The search was updated on30 July 2011, with one new study emerging that met ourcriteria. Agents not classifiable as an SSRI or SNRI wereexcluded from our investigation. Additionally, the searchwas substantiated a posteriori on April 2012 by examiningweb addresses with clinical trials registrations (http://clinicaltrials.gov/) and ALOIS (http://www.medicine.ox.ac.uk/alois/). Using the antidepressant intervention with ADas the health status/diagnosis provided only one ongoingstudy (ESAD/NCT00702780) that partially met our selec-tion criteria. In this trial, diagnosis of depression at onsetwas not specified; hence, the trial was not added to thesearch results.

Studies were evaluated based on a set of selected a prioriinclusion and exclusion criteria. Initially abstracts wereexamined for explicit inclusion criteria. Subsequently, inorder to achieve a high standard and minimum heteroge-neity, studies were examined on the basis of a set ofexclusion criteria (Table 1). After two authors (A.A.S. andP.E.L.) had independently coded the studies, the kappameasure of agreement was calculated to ensure consistencyin coding (k = 1.00 [100 % consistency was reached]).Furthermore, where appropriate, the authors of the studieswere contacted for raw or continuous data.

Power analysis with G*Power (Version 3; Faul, Erdf-elder, Lang and Buchner, Dsseldorf, Germany) [24] wascarried out a priori in order to have an estimate of thenumber of studies needed to calculate an omnibus Hedges'g effect-size (ES) estimate. Several sets of analyses wereperformed. For all analyses, the alpha level was set to 0.05,two tails. One analysis was done for medium-small ES andone for small ES. After setting the power to 0.8 and ES to0.4, the estimated unequal sample size ratio of 1.3:1 was 88for the control group and 114 for the treatment group.Alternatively, when setting the power level to 0.8 and ES to0.2, the estimated unequal sample size (1.3:1) was 349 forthe control group and 453 for the treatment group.

Comprehensive Meta-Analysis (CMA) (Version 2;Biostat Inc., Englewood, NJ, USA) [25] was used to cal-culate ES estimates and examine for publication bias.Where appropriate, within a random effect model, omnibusES estimates were derived with Hedges' g [26], providingan unbiased ES adjusted for sample size. Expecting vari-ability in ES estimates, a random effect model that toler-ated population level inferences and is more stringent thana fixed effect model was prominently used across our meta-analytic examination [27].

In the presence of heterogeneity, examination of themoderating factors using Cochran's Q Chi-square test and fwas accomplished [28]. A significant Q-test value suggestsrejection of the homogeneity hypothesis of the effect set; thef statistic [= 100 % X (g - df)/Q] that shows quantifica-tion of heterogeneity in the degree of inconsistency (total

Table 1 Selection criteria for studies

Inclusion criteria1. Presence of individuals suffering from AD2. Presence of depression as a comorbid condition3. Prescription of any novel antidepressantExclusion criteria1. Did not report on geriatric population with AD2. Reported on mild cognitive impairment3. Did not investigate pharmacological treatment (was not a

clinical trial) or was a head-to-head study without a placeboarm

4. Depression was an exclusion criterion, there was no diagnosisfor depression, or depression was non-concomitant to AD

5. Failed to include cognitive assessment as an outcome measure6. The study design was of low quality according to Jadad et al.

[72], such as a case report, case series, case study, letter orcommentary or editorial without data

7. Was a review or meta-analysis8. Exclusively investigated pharmacological markers or genetic

markers, or was an animal study9. Included research participants with other diagnosis such as

OCD, or comorbid alcoholism, and third diagnosis, ordiagnosis was mixed with medical illnesses

10. Investigated antidepressant treatment approach for smokingcessation

AD Alzheimer's disease, OCD obsessive-compulsive disorder

variation across studies that is due to heterogeneity ratherthan chance) was used. Values for this statistic range from 0and 100 %, where low, moderate and high f values are 25,50 and 75 %, respectively. A value of 0 % denotes theabsence of heterogeneity, and larger values show increasedheterogeneity [28].

Calculation of the post hoc fixed ES estimate for endpointbaseline difference was accomplished using the DSTAT(Version 1; Lawrence Erlbaum Associates Inc., Hillsdale,NJ, USA) [29]. In the absence of continuous descriptivemeasures (mean, SD), study authors were contacted toretrieve the appropriate statistics. Alternatively, given dis-tributional assumptions, in the absence of the mean and SD,data from the median and inter-quartile ranges were trans-formed to mean and SD. Overall, our meta-analysis wasconsistent with the Preferred Reporting Items for SystematicReviews and Meta-Analyses (PRISMA) statement [30].

3 Results

3.1 Characteristics of the Included Trials

After removing duplicates, we identified 598 studies, col-lected from search engine hits (Fig. 1). After evaluation forinclusion and exclusion criterion, 12 studies were included

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598 abstracts identified through database

12 studies matched inclusion andexclusion criteria

5 were investigating mixed dementia

168 were reviews, meta-analyses and surveys

6 were commentaries, guidelines, letters or bookchapters

10 were experimental non-human studies (animal, post-mortem and molecular investigation)

39 were case studies

3 were missing cognitive testing as an outcome measure

4 were missing a placebo arm

93 failed to show diagnosis of depression or adepression scale, or depression was excluded

258 were studying a diagnosis other than AD

1 was investigating benzodiazepines

1

5 studies were explicitlyreporting on the same

study (DIADS-1); onlythe most recent study

was included

1

3 studies explicitlyreported on the same

study (DIADS-2); only1 was included in the

examination

V1

6 studies included in meta-analytic examination

298 patients enrolledwith SSRI

antidepressant

323 patientsenrolled for

placebo treatment

A total of 621 enrolledindividuals in trials

Fig. 1 Flowchart showing study exclusion and inclusion. AD Alzheimer's disease, SSRI selective serotonin reuptake inhibitor

in this preliminary investigation of SSRI antidepressant usefor treatment of depression complicating AD. No studies ofSNRI antidepressant treatment met our criteria. Hence, welimit our meta-analysis and discussion to SSRIs in theremainder of this paper. There were no studies in non-English language that met our criteria. Certain studiesexplicitly reported on the same trials, e.g. Depression inAlzheimer's Disease Study 1 (DIADS-1) and DIADS-2[31-36]. Hence, only the most recent studies with the mostcomprehensive outcome data were included [31, 34, 36].However, other DIADS-1 and DIADS-2 publishedmanuscripts were used for additional information ondemographics and methods when needed. Accordingly, weidentified six studies (A'= 4 + 1 + 1) for our meta-analysis:

four studies excluding DIADS-1 or -2, one describingDIADS-1 and one describing DIADS-2 (Fig. 1). The totalnumber of patients enrolled in SSRI treatment arms fromthose studies was 297, and the total number of patientsenrolled in placebo arms was 318. These sample sizessupport the minimum 1.3:1 ratio needed to run a meta-analysis and calculate an omnibus estimate for a medium-small ES.

Study sample sizes (treatment and placebo) ranged from31 to 228 patients. The majority of the patients enrolled inthe studies were female (67 %), and one study includedonly females for both arms of the study [37]. The largestattrition was observed in the Health Technology Assess-ment Study of the use of Antidepressants for Depression in

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SSRIs in AD for Depression and Cognition 797

Table 2 Descriptive representation of the

Study, year

Magai et al., 2000 [37]Petracca et al., 2001 [44]DIADS-1 [31-33, 35]Rozzini et al., 2010 [45]DIADS-2 [34, 36]''Banerjee et al., 2011 [38]

Patients

TX

1717246667

107

studies for ag

(n)PL

1424209064

111

;e, sex, study attrition and

Female (%)TX

10047838159.768

PL

10071507148.464

sample included

Age [y, mean

TX

88.4(6.1)70.2 (6.3)75.5 (9.5)75.7 (7.6)76.5 (8.0)80 (8.4)

(SD)]PL

90.1 (6.5)71.3 (6.9)79.9 (5.2)75.9 (7.2)78.2 (8.0)79 (8.8)

Attrition (iTX

121725"NR10.926

PL

141212.5"NR7.536.5

NR not reported, PL placebo, TX treatment^ Based on the attrition reported on page 493 of the Munro et al. [74]'' Attrition is calculated based on the CSDD data as provided by the authors

Dementia (HTA-SADD) in the treatment arm with sertra-line [38]. The average age for treatment arms ranged from70.2 to 88.4 years, and for placebo arms it ranged from71.3 to 90.1 years. Overall, patients enrolled in the placeboarms of the studies were older than those in the treatmentarms (Table 2).

As shown in Table 3, the included studies reported bothlongitudinal change scores and endpoint data. Five studieswere double-blind, placebo-controlled trials. Four of thesewere randomized. One trial was observational. The averageduration of the trials was 21.3 weeks when we included theMini-Mental State Examination (MMSB) data from theDIADS-2 at 24 weeks, and 19.3 weeks when we includedCornell Scale for Depression in Dementia (CSDD) datafrom the DIADS-2 at 12 weeks, with a range between6 weeks and approximately 9 months. Five of six studiesexplicitly report a diagnosis of probable AD according tothe National Institute of Neurological and CommunicativeDisorders and Stroke and the Alzheimer's Disease andRelated Disorders Association (NINCDS-ADRDA) criteria[39]. Three of the six included studies explicitly reporteddiagnoses of depression based upon Diagnostic and Sta-tistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria, whereas others used different, yet inconsistentapproaches, where the method utilized was not explicitlyreported or, for example, the provisional diagnostic criteriafor depression in AD were utilized [40]. All studiesincluded mixed types of depression (e.g. minor and majordepression). Sertraline was the most frequently prescribedSSRI antidepressant (N = 4 studies, plus an additionalstudy with mixed SSRIs). Other SSRIs included fluoxetine,or a mix including citalopram, escitalopram and paroxe-tine. All studies incorporated a dose titration. Concurrenttreatment, allowing multiple and existing pharmacologicaltreatments, was reported by three studies. One non-randomized trial and two randomized controlled trialsexplicitly stated that they allowed the use of ChEIs with

SSRIs, and two studies explicitly reported excludingpatients with other concomitant treatment; however, onestudy did not report on allowing poly pharmacy. MMSE[41] was the most administered tool to assess cognition(A' = 5). The CSDD (also abbreviated as CS) [42] andHamilton Depression Scale (HAM-D) [43] were the mostfrequently utilized depression scales, used in four and twotrials, respectively (Table 4). The presence of a minimumof three studies using the same cognitive scale (MMSE) ordepression scale (CSDD) allowed us to run a meta-analyticexamination of the evidence and to maintain high homo-geneity with respect to outcome measures between studies.

3.2 Analysis of the Studies via Comprehensive Meta-Analysis

3.2.1 Depression

An initial global nested analysis using CMA was per-formed including all depression scales and counting eachstudy once. Given that the DIADS-1 study reported on twodepression scales (CSDD and HAM-D), two global nestedanalyses including each scale once were performed. Thefirst global nested analysis included DIADS-1 (Lyketsoset al. [31] 2003) with only the HAM-D results, and gen-erated an ES estimate for global depression of 0.06(p = 0.54; A^ = 5; = 4.94; df=4;p = 0.29; f = 19.08)(Fig. 2). Then the second global nested analysis was carriedout, replacing the CSDD with the HAM-D from the samestudy, resulting in ES = -0.10; p ^ 0.40; A^ = 5;Q = 3.n;df= A;p = 0.53;/^ = 0.01 (Fig. 3). The samplesizes for the global nested analysis were treatment = 184, andplacebo =191. Both effects were small, non-significant andhomogeneous.

Subsequent efficacy analyses were carried out separatelyfor studies reporting on CSDD (A^ = 4) (Fig. 4) and thosereporting on HAM-D (A' = 2) (Fig. 5). Analysis of CSDD

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og

60

o

Ii

M

Q

2^ i; _

B' Q.2


Table 4 Cognitive and depression outcome measurement

Study, year BIC (AD severity) Cognition Depression

Magai et al., 2000 [37]Petracca et al., 2001 [44]DIADS-I [31-33, 35]

Rozzini et al., 2010 [45]DIADS-2 [34, 36]''' 'Banetjee et al., 2011 [38]''

NR (late-stage)MMSE >10 (NR)MMSE >10 (NR)

NR (mild to moderate)MMSE 10-26 (mild to moderate)NR (NR)

Knit-brow face; sad faceMMSEMMSE; EOWPVT-R; HVLT-R;

Rivermead; WISC-RMMSE; ADAS-CogMMSEMMSE

CS;GSHAM-DCSDD; HAM-D

MMSE mean change GDSCSDDCSDD

AD Alzheimer's disease, ADAS-Cog Alzheimer's Disease Assessment Scale-Cognitive subscale, BIC Baseline Inclusion Cognitive Criteria, CSCornell Scale for Depression, CSDD Cornell Scale for Depression in Dementia, EOWPVT-R Expressive One-Word Picture Vocabulary Test-Revised, GDS Geriatric Depression Scale, GS Gestalt Depression Scale, HAM-D Hamilton Depression Scale, HVLT-R Hopkins Verbal LearningTest-Revised, MMSE Mini-Mental State Examination, NR not reported, WISC-R Wechsler Intelligence Scale for Children-Revised^ Authors were contacted in order to obtain relevant continuous data (P. Rosenberg and L.T. Drye, personal communication)'' CSDD data is from 12 weeks, MMSE data is from 24 weeks'^ Authors were contacted in order to obtain relevant continuous data (S. Banetjee and J. Hellier, personal commutiication)

Hedges' g and 95 % Cl

Fiuoxetine

Sertraline

Sertraline

Sertraline

Sertraline

Model

Random

Study name

Petracca et al. 2001

Lyketsos et ai. 2003

Banerjee et ai. 2011Magai et al. 2000

Rosenberg et al. 2010

Outcome

HAM-D

HAM-D

CSDD

CSDD

CSDD

Timepoint

End

End

End

End

End

Statistics for each studyHedges'

9

-0.126

-0.498

0.000

-0.257

0.083

-0.062

Variance

0.112

0.091

0.027

0.142

0.033

0.011

Loweriimit

-0.781

-1.090

-0.320

-0.996

-0.274

-0.264

Upperlimit

0.529

0.094

0.320

0.482

0.441

0.139

p vaiue

0.706

0.099

1.000

0.496

0.648

0.544

Sample size

Treatment

15

24

68

15

62

Piacebo

20

20

82

12

57

-2.00 -1.00 0.00 1.00 2.00

Fig. 2 First nested analysis; effect-size estimate for depression [Hamilton Depression Scale (HAM-D) and Cornell Scale for Depression inDementia (CSDD)] for endpoints; each study was considered once (N = 5) [31, 34, 37, 38, 44]

Model Study name


Lyketsos et al. 2003

Banerjee et ai. 2011Magai et ai. 2000

Rosenberg et al. 2010Random

Outcome

HAM-D

CSDD

CSDD

CSDD

CSDD

Timepoint

End

End

End

End

End

StatisticsHedges'

g

-0.126

-0.665

0.000

-0.257

0.083

-0.102

for each studyLower

Variance iimit

0.112

0.093

0.027

0.142

0.033

0.014

-0.781

-1.264

-0.320

-0.996

-0.274

-0.337

Upperlimit

0.529

-0.066

0.320

0.482

0.441

0.133

p value

0.706

0.030

1.000

0.496

0.648

0.396

Sampie size

Treatmeni

15

24

68

15

62

: Piacebo

20

20

82

12

57

Hedges' g and 95 % CI

Fiuoxetine

Sertraiine

Sertraiine

Sertraiine

Sertraiine

-2.00-1.00 0.00 1.00

Fig. 3 Second nested analysis; effect-size estimate for depression [Hamilton Depression Scale (HAM-D) and Cornell Scale for Depression inDementia (CSDD)] for endpoints; each study was considered once (Af = 5) [31, 34, 37, 38, 44]

data, comparing treatment arm with placebo arm at end-point, yielded an unbiased non-significant Hedges' g [42]favouring treatment, using a random effect model (ES =-0.12; p = 0.42; N = 4: placebo n = 171, treatmentn 169). These results were mildly heterogeneous(Q = 4.94; df=3;p = 0.18; f = 39.05), and the largestincluded study [38] accounted for 44 % of the fixed

relative weight in the ES estimate. For HAM-D data, usingthe fixed effect model, a non-significant Hedges' g of 0.33favouring treatment with SSRIs was found for the limitednumber of studies using the HAM-D {N 2: placebon = 40, treatment n 39). There was no differencebetween fixed and random effect models. This estimatefalls between small and medium size according to Cohen's

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Model

Fixed

Random

Fixed

Random

Group bytime point

Baseline

Baseline

Baseiine

Baseiine

Baseiine

Baseiine

End

End

End

End

End

End

Study name

Banerjee et al. 2011Lyketsos et ai. 2003

Magai et ai. 2000

Rosenberg et ai. 2010

Banerjee et ai. 2011Lyketsos et ai. 2003

Magai et ai. 2000

Rosenberg et al. 2010

Outcome

CSDDCSDD

CSDD

CSDD

CSDD

CSDD

CSDD

CSDD


g

-0.178

0.428

-0.184

0.053

-0.043

-0.021

0.000

-0.665

^0.257

0.083

-0.075

-0.121

Variance

0.018

0.090

0.142

0.030

0.009

0.014

0.027

0.093

0.142

0.033

0.012

0.022

Lowerlimit

-0.443

-0.161

-0.921

-0.288

-0233

-0.254

-0.320

-1.264

-0.996

-0.274

-0.287

-0.414

Upperlin i^t

0.087

1.018

0.554

0.393

0.148

0.213

0.320

-0.006

0.482

0.441

0.137

0.172

p value

0.189

0.155

0.625

0.762

0.659

0.862

1.000

0.030

0.496

0.648

0.487

0.417

Sample size

Treatment

107

24

15

67

68

24

15

62

Piacebo

111

20

12

64

82

20

12

57

Hedges' g and 95 % Gl

-1.00 -0.50 0.00 0.50 1.00

Fig. 4 Gross-sectional comparison of treatment arm and placebo (depression): favours treatment with selective serotonin reuptake inhibitors[Cornell Scale for Depression in Dementia (CSDD)] (/V = 4) [31, 34, 37, 38]

Hedges' g and 95 % CIModel

Fixed

Random

Fixed

Random

Group bytime point

Baseline

Baseline

Baseline

Baseline

End

End

End

End

Study name





Outcome

HAM-D

HAM-D

HAM-D

HAM-D

Time point

Baseline

Baseline

End

End


9

-0.447

0.307

-0.050

-0.063

-0.126

-0.498

-0.331

-0.331

Variance

0.099

0.089

0.047

0.142

0.112

0.091

0.050

0.050

Loweriimit

-1.063

-0.279

-0.475

-0.802

-0.781

-1.090

-0.770

-0.770

Upperlimit

0.170

0.894

0.375

0.676

0.529

0.094

0.108

0.108

p vaiue

0.156

0.304

0.816

0.867

0.706

0.099

0.140

0.140

-2.00 -1.00 0.00 1.00 2.00

Fig. s Cross-sectional comparison of treatment arm and placebo (depression), favours treatment with selective serotonin reuptake inhibitors[Hamilton Depression Scale (HAM-D)] (A^ = 2) [31, 44]

guidelines, and it was homogeneous (Q 0.68; df\;p = 0.41; f = 0.01) (Figs. 4 and 5).

3.2.2 Cognition

An analysis of the studies reporting assessment of globalcognition with MMSE (JV = 5) [31, 36, 38, 44, 45] andassessment of depression with HAM-D (N = 2) [31, 44]was conducted. A non-significant Hedges' g (ES 0.001;p = 0.99) was found for MMSE completers (treatment = 196; placebo n = 222; z = O.Ol; p = 0.99, two-tail)(Fig. 6), and the largest study accounted for 36.58 % ofthe fixed relative weight [38]. The -statistic value forMMSE was non-significant (Q = 1.58; df = 4; p = O.Sl;f 0.01). There was no difference in ES estimatesbetween fixed and random effect models, suggesting verylittle variability among the included studies. However,because of the small number of studies included in each

analysis, ranging from two to five studies, Q-statistics maynot have had sufficient power to detect significant hetero-geneity, even if this was present. Examination of the funnelplot (not shown) of studies included in the cognitionanalysis suggests possible study bias given that the studiesare distributed asymmetrically and that the smaller studiesare at the bottom of the plot on only one side of the mean.Complying with the PRISMA statement, further examina-tion with classic fail-safe N (which addresses the concernthat the observed significance may be spurious) was carriedout. Data from five studies reporting MMSE results yieldeda z value of 0.05 with the corresponding two-tailedp value of 0.96. Given that the combined result was notstatistically significant, the fail-safe N was not consideredto be relevant (Fig. 6).

Of the studies with CSDD data, only two also reportedMMSE results. Our ES estimate based on a random effectmodel at the endpoint was non-significant and favouring

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Model Group by Study name Outcome Time point Statistics for each study

Fixed

Random

Fixed

Random

time point

Baseiine

Baseline

Baseline

Baseline

Baseline

Baseline

Baseline

End

End

End

End

End

End

End

Petraccaetal.2001


Rozzini et al. 2010

Banerjee et al. 2011Weintraubetal. 2010



Rozzini et al. 2010

Banerjee et al. 2011Weintraubetal. 2010

MMSEMMSE

MMSE

MMSE

MMSE

MMSE

MMSE

MMSE

MMSE

MMSE

Baseline

Baseline

Baseline

Baseline

Baseline

End

End

End

End

End

Hedges'9

0.000

0.180

0.000

0.039

0.248

0.088

0.088

-0.044

-0.087

0.079

-0.166

0.159

0.001

0.001

Variance

0.097

0.089

0.026

0.025

0.030

0.007

0.007

0.111

0.088

0.026

0.036

0.053

0.010

0.010

, Lowerlimit

-0.609

-0.404

-0.316

-0.268

-0.094

-0.081

-0.081

-0.698

-0.670

-0.237

-0.540

-0.293

-0.191

-0.191

Upperlimit0.609

0.764

0.316

0.347

0.590

0.258

0.258

0.610

0.496

0.395

0.207

0.611

0.192

0.192

p value

1.000

0.545

1.000

0.802

0.156

0.308

0.308

0.895

0.770

0.625

0.383

0.490

0.995

0.995

Hedges' g and 95 % CI

-1.00-0.50 0.00 0.50

Fig. 6 Effect-size estimate comparing treatment arm of the studies to placebo (cognition), favouring placebo (N = 5). [31, 36, 38, 44, 45]MMSE Mini-Mental State Examination

placebo (ES = -0.14; p = 0.37; 95 % CI = -0.46, 0.17)(refer to Table 4 for included studies).

3.2.3 Post Hoc Analysis

Given the lack of significant ES estimates for depressionand cognition, moderating factors were not fully examined.However, we conducted further analyses (a) on the baselinedata, examining for sampling bias; (b) on the possibility ofgenerating a global neurocognitive index and on factorsspecific to the clinical validity of treatment, such as globalfunctional outcome and quality of life; (c) on the differencefrom baseline to endpoint for the placebo group; and (d) onadverse events.

The ES estimate obtained from comparing treatment andplacebo groups at baseline suggests that there were nosampling biases in the included studies; the ESs were smallin size (HAM-D: ES = -0.06; CSDD: ES = -0.02;MMSE: ES = 0.09). The comparison of baseline to theendpoint for the placebo arm showed no significantdifference for MMSE (ES = -0.03; p = 0.76; 95 % CI-0.24, 0.18; r= -0.02) but a significant difference forCSDD (ES = 0.98; /? = 0.001; 9 5 % CI 0.77, 1.19;r = 0.44).

A global neurocognitive ES index based on all thereported neuropsychological tests with the exclusion ofMMSE or functional outcome measures (e.g. Activities ofDaily Living) was not feasible given that only one studyreported on neuropsychological tests at endpoint: DIADS-1[31, 33].

The examination of the endpoint global functional out-come from the DIADS-1 study with the PsychogeriatricDependency Rating Scale-Activities of Daily Living(PGDRS-ADL), the DIADS-2 study with the Alzheimer'sDisease Cooperative Study (ADCS)-Activity of DailyLiving Scale, and the HTA-SADD study with BristolActivities of Daily Living-Activity Limitation (BADL-AL)showed that globally either there was no significant dif-ference or very little difference exists between sertralinegroups and placebo at the end of the trials. As to quality oflife, HTA-SADD and DIADS-2 were the only studies toreport on such outcome measures, and both investigatinggroups reported non-significant differences between treat-ment and placebo arms.

The number of patients in the placebo arm administeredthe MMSE at baseline was 194, and at the endpoint, thenumber was 166, which is a 14 % loss. The number ofpatients in the placebo arm administered the CSDD atbaseline was 207, and at the endpoint, the number was 171,which is roughly a 17 % loss. In the treatment arm, thepercentage loss was higher: MMSE (baseline = 253;endpoint = 196) 22.5 % loss; CSDD (baseline = 213;endpoint = 169) 20.7 % loss. Non-parametric examinationfor this variation was not possible given that the emergingsample for MMSE differed from that for CSDD.

An overview of the adverse events for the includedstudies with a single SSRI (fluoxetine or sertraline), but notmixed SSRIs, showed that fluoxetine was better tolerated,with few drop-outs and few reported adverse events (e.g.mild confusional state in only one patient) [44], in contrast

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to sertraline, for which adverse events were frequent [31,36-38]. Banerjee et al. [38] reported the largest list ofadverse events for both SSRI and placebo treatment (86 vs.58, respectively). As for the only non-controlled study(Rozzini et al. [45]), since multiple SSRIs were used andthe study was observational, no conclusion can be drawnwith regard to adverse events. This notwithstanding, weincluded every eligible study to avoid the file-drawer effect[46].

4 Discussion

Using a systematic meta-analytic approach, we evaluatedthe currently available evidence regarding SSRI and SNRImono-therapy for the treatment of depressive and cognitivesymptoms in AD patients with concurrent depression. Wedid not find any SNRI trials meeting our selection criteriaand limited our analysis to SSRIs. Notwithstanding powerlimitations, we found non-significant effects in twodepression nested analyses including CSDD and HAM-D,and found no effects on a measure of global cognition, theMMSE. There was a suggestion that the size of the effectfor CSDD (very small) and HAM-D (small to medium) wasdifferent. Compared with previous work, the externalvalidity of our analysis is stronger because we have(a) included the largest clinical trial published to date onthe topic and (b) we have included trials from the UK, Italyand the USA. Based on these findings, support for the useof SSRIs as a class of medications for the treatment of ADwith concurrent depression appears quite weak. However,several caveats are in order. Firstly, we cannot rule out thatwithin the class, different SSRI compounds may havedifferent effects in AD given their unique pharmacologicalproperties. For example, fiuoxetine has antagonistic prop-erties at serotonin 5-HT2c receptors, which could increasenorepinephrine and dopamine neurotransmission [47]. Themajority of trials to date, including HTT-SADD, haveexamined sertraline, and only a few have addressed otherantidepressants. Secondly, there is no gold standard diag-nostic approach to depression in AD. The studies includedin these analyses have either utilized DSM-IV criteria orother approaches such as the Olin provisional approach,which requires fewer symptoms for a diagnosis ofdepression [10]. Because of statistical constraints, and thelack of a significant ES estimate, we have not conductedanalyses on moderating factors but cannot exclude thepossibility that outcomes may be moderated by howdepression is diagnosed in AD. Finally, there is no goldstandard outcome measure for depression in AD. In thestudies included in this work, two scales have been uti-lized: the CSDD and the HAM-D. It is possible, and in factsomewhat supported by our data, that the effect of SSRI

treatment is scale dependent. The HAM-D places strongemphasis on neurovgtative signs, and it is possible thatthese rather than mood symptoms benefit from SSRItreatment. However, we cannot further assess this possi-bility without patient-level data on specific neurovgtativesymptoms, such as sleep impairment.

4.1 Comparison to Other Meta-analyses and Reviews

There have been previous meta-analytic studies that haveeither examined the efficacy and safety of a variety ofantidepressants for treatment of depression in AD, includ-ing tricyclic antidepressants, despite recent guidelinesdiscouraging their use [14], or the effect of antidepressantsfrom a limited number of placebo-controlled trials inpeople with depression in dementia, with inconclusiveresults [23, 48]. In these studies, broad inclusion criteriawere used for the diagnosis of depression. Additionally,reviews of treatment of depression in AD showed limita-tions [49, 50], particularly in the methodological approach,such that no clear conclusion can be drawn. For example, a2010 review of the pathophysiology, diagnosis and treat-ment approach for depression in AD included seven ran-domized placebo-controlled trials, from which data fromDIADS-1 were utilized twice, with inclusion of both datafrom an earlier paper and the final trial paper [49]. How-ever, the authors concluded that the data were too sparse tofully assess the benefit-risk ratio of antidepressants formanaging depression in AD or other dementias. Anotherreview examined the full spectrum of antidepressants andconcluded that further data are needed to assess the benefitsand risks of antidepressant therapy in patients withdementia [50]. In this study, no degree of cognitive benefitwas assessed in relation to the improvement in symptomsor signs of depression. Furthermore, this study was notspecific to AD. Thus the cumulative evidence on efficacyof SSRI treatment in AD for depressive and cognitivesymptoms remains inconclusive.

In contrast to the conclusions of reviews, a meta-analysisof ten studies on the effect of second-generation (SSRIs,SNRIs and other classes but not tricyclics) antidepressanttherapy for late-life depression found that antidepressantswere more effective than placebo in elderly depressedindividuals, with methodological and statistical heteroge-neity [51]. We did not find evidence of such treatmentbenefits in subjects with AD. However, we also encounteredheterogeneity, both in the depression outcomes that wereused and in the ES estimate for one outcome (CSDD). Incontrast to other meta-analyses and reviews, following thePRISMA statement, we used very specific inclusion criteria,and focused only on studies addressing SSRI therapy fordepression in AD, and not on the entire dementia spectrum.Additionally, we were able to include the largest and most

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recently published (2011) antidepressant trial, thus reachingsignificant sample size and power to systematically exam-ine treatment effects. We also found that there is no ran-domized placebo-controlled clinical trial explicitlyinvestigating the effect of a ChEI with concomitant SSRI orSNRI on cognitive symptoms and diagnosed comorbiddepression as per our selection criteria.

4.2 Measurement Scales in AD with ConcurrentDepression

We noted dissimilarities in the outcome scales that havebeen utilized. The CSDD is an interview-based assessmenttool that collects information about the signs and symptomsof depression in dementia from informants and patientsduring the past week. In contrast, the patient-based HAM-D rates change, frequency and intensity of diagnoseddepression with regard to treatment outcome. It is possiblethat the latter scale is more sensitive to small changes indepressive symptoms. It is beyond the scope of our work toevaluate these scales, but it should be kept in mind thatinterpretation of scores on scales relying on self-report insubjects with AD, comorbid depression and MMSE scoresof


sub-analysis considering depression subtypes as a moder-ating factor given the lack of significant heterogeneity andthe limitations of the data reported in the individual trials.

4.5 The Big Picture and Areas for Future Investigation

This meta-analysis uncovered factors that necessitate fur-ther investigation in relation to depression in AD. Whatappears to matter is how depressive symptoms are diag-nosed and assessed. From the neurobiological perspective,depression could be a symptom of AD, a disorder in itsown right, or both. Clinical presentation of depressionoverlaps with AD, and this is reflected in the DSM-IVcriteria for major depression (mood, psychomotor activity,cognition and vegetative symptoms). For now, cliniciansneed to adopt an in-depth phenomenological approach toascertain a diagnosis of depressive disorder.

A point of importance is the significant improvement ondepression scales in the placebo arm as assessed by CSDD.It is possible, though not proven, that being in an antide-pressant trial may be by itself an effective approach. Thisspeculation, of course, will need careful study to gathersupport for this hypothesis. We concur with the conclusionby the HTA-SADD group [38] that sertraline may not be agood fit as a first-line antidepressant, and that psychosocialapproaches may be more effective for treating depressionin AD. However, we noted in our meta-analysis that ser-traline was the compound most frequently studied andother compounds utilized in clinical care did not undergothe same amount of scrutiny. Therefore, conclusions can-not be drawn at present specifically on the efficacy of thelatter. Furthermore, other classes of antidepressants, suchas SNRIs, are commonly prescribed to persons with AD,yet the efficacy and safety of these medications have notbeen formally assessed.

We agree that depression in dementia is likely differentfrom depression in aging, and that its treatment or assess-ment cannot be extrapolated from treatment approaches innormal elderly. Furthermore, consistent with a recentreview for management of neuropsychiatrie symptomsassociated with AD by Gauthier et al. [64], the literatureremains very limited, such that no clear inferences can bedrawn or suggestions made to change the current clinicalguideline for treating comorbid depression in AD usingSSRIs. Hence, we conclude that depression in AD is stillnot a well-understood phenomenon. Until more is knownand given the revised criteria for AD dementia [62], whichinclude behavioural changes, there are myriad opportuni-ties to explore this important clinical phenomenon withregard to treatment effectiveness and the components ofdiagnosis.

5 Conclusions

Current evidence does not support the efficacy of SSRItreatment for symptoms of comorbid depression in AD.However, there is substantial variation in individuals'clinical response and tolerance even within the same classof medication. A real necessity for antidepressant treatmentmust be established, and criteria for application should bedeveloped at an individual patient level [65]. There is alack of consensus with regard to the diagnostic approachand outcomes in trials of antidepressants in AD. When aharmonized diagnostic approach exists, trials adopting thisapproach may yield more reliable outcomes. Additionally,clinicians, in evaluating the benefits of antidepressanttreatment, should consider the possibility of improvedquality of life and increased functional independence [66-68]. Potential risks, including injurious falls [69], exacer-bation of suicidal ideation and possible abnormal changesin the electrical activity of the heart [70], should not beunderestimated. In addition, follow-up monitoring forpossible metabolic abnormalities (e.g. hyponatraemia)should be taken into consideration [71 ]. In summary, SSRIsfor AD patients with coexisting depression should be pre-scribed with caution.

Acknowledgments The authors wish to express their gratitude forthe provision of unpublished trial data upon request from Dr. SubeBanerjee and Jennifer Hellier on behalf of the HTA-SADD group, andfrom Drs. Paul B. Rosenberg and Lea T. Drye on behalf of theDIADS-2 group.

Funding and Conflicts of Interest The author have no conflicts ofinterest to report. Amir A. Sepehry, PhD candidate, is funded by theCanadian Institutes of Health Research (CIHR) (Frederick Bantingand Charles Best Canada Graduate ScholarshipsDoctoral Awards).Dr. Lee has received funding from the Cullen Family, St. Paul'sHospital Foundation and has received honoraria for speaking andparticipating in advisory boards for Janssen-Ortho, Novartis andPfizer. Dr. Lee is a co-investigator in the Alzheimer Drug TherapyInitiative (ADTI) project, funded by the British Columbia (BC)Ministry of Health Services, and is a co-investigator for the clinicaltrials at the University of British Columbia Hospital (UBCH) Clinicfor Alzheimer's Disease and Related Disorders (CARD), funded byBaxter, Bristol-Myers-Squibb, Elan, Janssen, Pfizer, Hoffman-LaRoche, and Genentech. Dr. Hsiung is supported by a ClinicalGenetics Investigatorship award from the CIHR, and has receivedresearch support from Baxter, Bristol-Myers-Squibb, Elan, Janssen,Pfizer, Hoffman-La Roche, and Genentech at the UBCH-CARD.Dr. Beanie is a co-investigator for the clinical trials at the UBCH-CARD, funded by Baxter, Bristol-Myers-Squibb, Elan, Janssen,Pfizer, Hoffman-La Roche, and Genentech. She is also receiving grantfunding from the CIHR and from the ADTI, which is funded by theBC Ministry of Health Services. Dr. Jacova receives funding from theCIHR and the BC Ministry of Health Services through the ADTI.Drs. Lee, Hsiung and Jacova gratefully acknowledge support from theRalph Fisher Professorship in Alzheimer's (Alzheimer Society ofBritish Columbia).

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Individual Contributions to the Manuscript Amir A. Sepehrydesigned and conducted data collection, coding, statistical analysisand interpretation of the data, and was involved in writing ofthe various drafts of the manuscript. Dr. Lee was the second rater inthe evaluation of studies for inclusion in the meta-analysis; wrote thediscussion section; and revised the manuscript. Dr. Hsiung had inputinto various sections of the manuscript and was involved in overallrevisions. Dr. Beaitie had input into various sections of the manu-script and was involved in overall revisions and editing for content.Dr. Jacova supervised the project and interpretation of the data,revised the manuscript and edited for content.

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