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Prevention of Depressive Disorders: Overview of a Developing Field

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Title: Prevention of Depressive Disorders: Overview of a Developing Field


1
Prevention of Depressive Disorders Overview of
a Developing Field
Charles F. Reynolds III, M.D.
CDC Prevention Research Center University of
Pittsburgh Graduate School of Public
Health September 10, 2010
2
Acknowledgments
Pittsburgh Conference on Prevention of Depressive
Disorders June 25-27, 2009
List of Participants Aartjan Beekman , M.D.,
Ph.D. David Mohr, Ph.D. Terry Brugha,
M.D. Ricardo F. Muñoz, Ph.D. Pim Cuijpers,
Ph.D. Charles F. Reynolds III, M.D. Mary Amanda
Dew, Ph.D. Robert G. Robinson, M.D. Linda
Garand, Ph.D., RN, CS Barry Rovner, M.D. Judy
Garber, Ph.D. Filip Smit, Ph.D. Ulrich Hegerl,
M.D. Geesje Thomassen, M.S. Amy M. Kilbourne,
Ph.D., M.P.H. Annemieke van Straten, Ph.D. Eric
Lenze, M.D. Benjamin Van Voorhees, M.D.,
M.P.H. Cathy Mihalopoulos, Ph.D.
3
Disclosures
National Institute of Mental Health National
Institute on Aging National Center for Minority
Health and Health Disparities National Heart,
Lung, and Blood Institute John A. Hartford
Foundation American Foundation for Suicide
Prevention Commonwealth of Pennsylvania UPMC
endowment in geriatric psychiatry Forest,
Pfizer, Lilly, Bristol Myers Squibb, Wyeth,
GlaxoSmithKline (provide pharmaceuticals for
NIH-sponsored research)
4
Overview
  • Why is prevention of depressive disorders
    important?
  • Is prevention of depression possible?
  • Challenges for the future

5
Prevention encompasses
  • Preemption of incident and recurrent episodes of
    depression
  • Protection from developmental complications of
    depression

6
Complications of depression
  • Interpersonal problems
  • Increase in medical comorbidity and increase in
    medical risk factors over time
  • Worsening of cognitive impairment
  • Impairment of mobility
  • Excess disability
  • Increased mortality
  • Diminished healthspan

7
Interrelation of prevention and treatment
Universal prevention General population
Selective prevention Vulnerable people
Indicated prevention People with symptoms
Treatment / therapy Diagnosed patients
Relapse prevention Patients in remission
Maintenance therapy Recovered patients
Courtesy Filip Smit
8
Mental health intervention spectrum
From Preventing Mental, Emotional, and
Behavioral Disorders Among Young People Progress
and Possibilities. Washington, DC The National
Academies Press, 2009.
9
Why indicated or selective prevention?
  • Need to maximize efficiency of depression
    prevention via attributable fraction (proportion
    of cases prevented if toxic effects of a risk
    factor could be completely eliminated) and effort
    (NNT/NNP)
  • Subthreshold symptoms present potential for
    highest attributable fraction and lowest number
    needed to treat/prevent (NNT/NNP)

10
Why is prevention of depressive disorders
important?
11
Why is prevention important?
  • Prevalence, persistence, and substantial
    morbidity/mortality of depression
  • Treatment is only partially satisfactory in
    reducing disability
  • Limited access to treatment, especially
    minorities social inequalities of risk widen
    with age?socioeconomic gradient in treatment
    access, utilization, and response
  • Mental health workforce issues need models of
    large-scale depression prevention that could be
    carried out by general medical clinicians using
    cost-effective, stepped care approaches

12
The disease burden of depression
  • Fourth disorder worldwide (DALYs)
  • Highest burden of disease in 2030 in developed
    countries
  • High prevalence
  • High incidence (almost 50 of prevalence)
  • Huge economic costs (130 million euros per
    million inhabitants for MDD alone)

Courtesy Pim Cuijpers
13
Averted Years Lived with Disabilities (current
coverage and with Evidence-Based Mental Health)
  • Disorder Current EBMH
    Max
  • Any mood disorder 15 23 35
  • Major depression 16 23 34
  • Any anxiety disorder 13 20 49
  • Any alcohol rel. dis. 2 5 34
  • Schizophrenia 13 22 22
  • Any disorder 13 20 40

Courtesy Gavin Andrews
14
Implications
  • Currently avoided in MDD 16, maximum 34
  • Needed
  • Better treatments
  • Dissemination (low-income countries!)
  • Prevention!

15
Is prevention of depression possible?
16
Preventing depression in at-risk youth
  • Hazard of depression onset was significantly
    lower in CB than UC
  • (X24.90, p0.03 Hazard Ratio (HR)0.63,
    95 CI 0.400.98)
  • 32.7 in UC control diagnosed with a probable or
    definite MDE
  • 21.4 in CBP had a MDE
  • NNT 9

Garber et al., JAMA, 301(21)2215-2224, 2009
17
Moderation by baseline parental depression
  • CBP superior to UC if parents not currently
    depressed
  • 11.7 MDE in CBP
  • 40.5 in UC
  • No significant difference between CBP and UC
    conditions if parent was depressed at baseline
  • Within CBP, effects were diminished
    significantly
  • 11.7 if parent not currently depressed
  • 31.2 if parent currently depressed

(HR5.53, Wald X2(3)13.30 p0.001)
18
Prevention of incidence of new cases of depression
  • Meta-analytic review
  • 19 trials
  • Results
  • IRR 0.78 (95 CI 0.650.93)
  • No significant subgroups (type, target
    population)
  • IPT may be somewhat more effective than CBT

Cuijpers et al., Am J Psychiatry, 2008
19
Meta-analysis of studies examining prevention of
depressive disorders
IRR (95 CI)
Study IRR 95 CI
Munoz, 1995 0.54 0.102.90
Clarke, 1995 0.53 0.241.20
Seligman, 1999 0.78 0.531.16
Brugha, 2000 0.50 0.131.95
Elliott, 2000 0.44 0.230.86
Clarke, 2001 0.28 0.090.84
Zlotnick, 2001 0.07 0.001.12
Allart, 2003 1.13 0.522.49
Priest, 2003 1.02 0.821.27
Spence, 2003 1.06 0.661.68
Hagan, 2004 1.15 0.691.92
Willemse, 2004 0.64 0.321.27
Gilham, 2006 1.00 0.571.76
Martinovic, 2006 0.13 0.012.42
Munoz, 2006 0.54 0.132.17
Sheffield, 2006 I 1.05 0.611.82
Sheffield, 2006 U 0.71 0.391.28
Sheffield, 2006 UI 0.85 0.471.54
Young, 2006 0.11 0.010.96
Zlotnick, 2006 0.20 0.050.88
Rovner, 2007 0.74 0.431.28
Pooled 0.78 0.650.93
20
Prevention of depression in post-stroke patients
Robinson et al. JAMA, 2008
21
Depression incidence in macular degeneration at
months and 6 months by treatment assignment
27.4
30
23.2
25
21.1
20
PST
11.6
Percent
15
UC
10
5
0
6 Months
2 Months
N 190 OR .65 .33, 1.39 P .29
N 194 OR .43 .20, .95 P .033
Rovner et al, AGP, 2006
22
(No Transcript)
23
Screening and informed consent
n 325
Watchful waiting
3 months
Randomisation
n 170
n86
Guided self-help
3 months
CAU
n84
3 months
n77
PST
CAU
n66
Referral GP
3 months
CAU
Primary outcome
n76
n 138
n62
24
Effect of the intervention
  • Crude risk of developing either anxiety- or
    depressive disorder in EXP was less than 50
  • RR 0,42 (0,18-0,96)
  • After multiple imputation
  • RR 0,34 (0,20-0,61)
  • Worst case scenario drop out
  • RR 0,37 (0,16-0,88)
  • Poison regression (based on person-time)
  • IRR 0,47 (0,22-0,99)

Courtesy Aartjan Beekman
25
Efficiency of intervention
  • NNT 8,2

Courtesy Aartjan Beekman
26
Conclusion
  • Step-up prevention of anxiety and depressive
    disorders in old people is both feasible and
    effective
  • Effect is impressive (more than 50 RR)
  • This is more than most treatments can do
  • Provisional analyses effect remains at 2 years

27
Reducing Suicidal Ideation and Depressive
Symptoms in Depressed Older Primary Care Patients
  • A Randomized Controlled Trial Utilizing
    Citalopram and Depression Care Management (n
    598)
  • Rates of suicidal ideation declined faster (p
    .01) in intervention patients compared with usual
    care patients.
  • Differences peaked at 8 months (70.7 versus
    43.9 resolution p .005)
  • PROSPECT (Prevention of Suicide in Primary Care
    Elderly Collaborative Trial).

Bruce M, Tenhave T, Reynolds CF et al JAMA,
291(9)1081-1091, 2004
28
The Effect of a Primary Care Practice-Based
Intervention on Mortality in Older Adults
PROSPECT
  • After a median follow-up of 52.8 months, patients
    with major depressive disorder in intervention
    practices were less likely to have died than
    patients in usual care practices
  • adjusted hazard ratio 0.55 (CI, 0.36-0.84)
  • No effect was seen in patients with clinically
    significant minor depression.
  • The benefit seemed to be almost entirely
    attributable to a reduction in deaths due to
    cancer.
  • The mechanism for such an effect is unclear and
    warrants further investigation.
  • Gallo JJ, Bogner HR, Morales K, Post EP, and Lin
    JY. Ann Intern Med, 2007

29
Challenges for the Future
30
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31
Limitations of current approaches
  • Different target groups and interventions
  • The majority of participants do not develop MDD,
    in control and treatment groups
  • NNT20
  • Almost no dissemination in routine care

32
We need
  • More effective interventions
  • Aimed at those who need it most
  • With high impact on public health
  • At low costs

33
More efficacy trials in specific target groups
  • General medical patients
  • Primary care
  • Adolescents and young adults
  • Postpartum depression
  • Low SES groups and ethnic minorities
  • Family caregivers
  • Other target groups

34
Can prevention be personalized?
Since most adults are resilient to depression
after a disabling medical event or other negative
life events such as bereavement, how can one
improve the cost benefit ratio of prevention
efforts? Example genetic contributions to (1)
likelihood of onset (2) time period of risk and
(3) likelihood of risk reduction using
psychosocial and pshchopharmacologic
strategies Need to understand architecture of
both risk and resilience to depression in old age
Courtesy Eric Lenze
35
Targets for prevention of emergent MDD during
interferon-alpha therapy
Courtesy Frank Lotrich
36
Can suicide be prevented by remediating specific
cognitive deficits?
Specific cognitive impairments
Aging
Decision-making
Ideation
Attempt
Specific Cognitive impairments
Depression
Life-long vulnerability To suicide (e.g., genes,
early life experiences
Courtesy Katalin Szanto and Alexandre Dombrovski
37
New types of interventions
  • Internet-based approaches
  • Stepped-care approaches
  • Community-based interventions

38
Dissemination of effective prevention
  • How should we disseminate preventive
    interventions?
  • How can we improve participation rates?
  • Which models are economically feasible?

39
What is Cost Effectiveness of Depression
Prevention in Old Age?
40
Cost-effectiveness plane
More costs, Less health More costs More health
Less Costs Less Health Less costs, More health
Courtesy Filip Smit Smit et al., British Journal
of Psychiatry, 2006
41
Stepped-care approach toward preventing depression
3
96
3
0
't Veer et al. (in prep.) Cost-effectiveness of a
stepped-care intervention to prevent onset of
depression and anxiety in late life.
Courtesy Filip Smit
42
Preventive online PST v WL
6
0
93
1
Warmerdam et al. (in prep) Cost-utility and
cost-effectiveness of internet-based treatments
for adults with depressive symptoms
Courtesy Filip Smit
43
Conclusions
  • 'Cost effective' target groups can be identified
  • Similar approaches need to be developed for
    preventing relapse and recurrence
  • Some of these interventions can be embedded in a
    disease-management approach with outcome
    monitoring

Courtesy Filip Smit
44
We must go beyond traditional health care Using
the internet
  • Interventions that can be used again and again.
  • Reducing health disparities
  • especially when the local health care system
    cannot provide care to people who need it.
  • Interventions that can be shared globally
  • without taking anything away from local
    populations

Courtesy Ricardo Muñoz
45
Ethics of consent in internet-based prevention
  • Participants can be expected to become
  • Clinically depressed
  • Suicidal
  • Assuring that users know the expectations of a
    research vs. a therapeutic contract?
  • Practicing via the Web?
  • Assuring that users know that Website cannot
    provide crisis intervention
  • Need guidelines for reasonable expectations for
    ethical Internet research on depression

Courtesy Ricardo Muñoz
46
The problem Reaching the target populations
  • About 7.5 of population suffers from minor
    depression (Cuijpers et al., 2004)
  • About 750,000 people
  • Participation in preventive interventions
  • 2,000 to 4,000 participants
  • 250 to 500 preventive courses
  • not more than about 0.5 percent

Courtesy Pim Cuijpers
47
Possible causes Participants
  • People with sD are not willing to participate
  • do not consider themselves as having sD / in
    need of a preventive intervention
  • Stigma
  • Prevention is not effective
  • Not willing to participate in a group
  • Scheduling problems

Courtesy Pim Cuijpers
48
Possibilities to increase participation rates
  • Aimed at potential participants
  • Media campaigns to reduce the stigma
  • Media campaigns stressing possibility to prevent
    depression
  • Organisational solutions
  • Offer the CWD through the Internet
  • Offer the CWD as individual intervention
  • Increase resources for organising CWD courses
  • Position preventive services in primary care
  • Embedd CWD courses in broader community
    interventions
  • Communication
  • Increase awareness in health professionals about
    the preventive services
  • Increase resources for recruitment
  • Systematic screening of potential participants

Courtesy Pim Cuijpers
49
Prevention of Depression in Older African
Americans
Primary Care Elderly Patients N306 CESD gt 11 no
MDD in past 12 months
Problem Solving Therapy N153
Attention-Only Contact Dietary Education N153
  • Subjects age 50 and older
  • 153 AA, 153 white
  • Stratified by site and previous history of
    depression

Assessment Point (time from T1)
T1 baseline T2 3 months Follows
completion of intervention T3 6
months T4 9 months T5 12
months T6 15 months T7 18
months T8 21 months T9 24 months
Primary Outcomes Incident major depressive
episodes (SCID) Level of depressive symptoms
(HRSD) Health-related quality of life (MOS
SF-12)
Booster sessions of PSTPC and DIET after
assessments are completed
C.F. Reynolds, PI
50
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51
With thanks to the leadership of the ACISR/LLMD
and ACISR/LLDP (P30 MH052247, P30 MH071944, and
P30 MH090333)
  • Stewart Anderson
  • Howard Aizenstein
  • Carmen Andreescu
  • Robert Bies
  • Charlotte Brown
  • Meryl Butters
  • Kyaien Conner
  • Mario Cruz
  • Ellen Detlefsen
  • Mary Amanda Dew
  • Deborah Dobransky-Fasiska
  • Alex Dombrovski
  • Julie Donohue
  • Ellen Frank
  • Ari Gildengers
  • Victoria Grochocinski

Joan Rogers Bruce Rollman Richard Schulz Etienne
Sibille Beth Skidmore Kathy Slomka Jeannette
South-Paul Jacqueline Stack Robert Sweet Kati
Szanto Carrie Farmer Teh James D. Tew Wes
Thompson Deb Weiner Ellen Whyte Allan Zuckoff
  • Margo Holm
  • Patricia R. Houck
  • Jill Houle
  • Jordan Karp
  • John W. Kasckow
  • David Kupfer
  • Eric Lenze
  • Frank Lotrich
  • Lynn Martire
  • Sati Mazumdar
  • Mark Miller
  • Jennifer Morse
  • Benoit H. Mulsant
  • Lisa Parker
  • Paul Pilkonis
  • Harold Alan Pincus
  • Bruce G. Pollock
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