Invited talk for the 2009 Suffolk conference (Bury St Edmonds) on No Physical Health without Mental Health.

1. Detecting Depression in Primary & Secondary Care
Evidence Based Comparison
Alex Mitchell alex.mitchell@leicspart.nhs.uk
Consultant in Liaison Psychiatry
Bury St Edmonds - No Physical Health Without Mental Health 2009

2. Introduction to Physical/Mental Comorbidity

3. No Physical Health Without Mental Health
• Awareness of the link between
physical and mental health
• Liaison Mental Health Services
• Engaging Patients and Carers
• Re-organisation, Quality &
Commissioning
• Training and Education

4. Quality of preventive care
Quality of medical care
Quality of cardiac care

5. Quality of Care MI vs No MI
27 examined receipt of medical care in those with and
without mental illness
19/27 showed deficits in care
10 examined medical care in those with and without
substance use disorder (or dual-diagnosis
10/10 showed deficits in care

6. Quality of Medical Treatment i Procedures
HR =0.89 p<0.004 Summary meta-analysis plot [random effects]
Petersen 2003 [Angiography] 0.90 (0.83, 0.98)
Jones 2005 [CABG] 0.91 (0.75, 1.09)
Plomondon 2007 [CABG] 1.02 (0.99, 1.06)
Druss 2000 [CABG] 0.90 (0.85, 0.96)
Plomondon 2007 [Cath] 1.05 (0.98, 1.13)
Druss 2000 [Cath] 0.74 (0.70, 0.78)
Jones 2005 [PTCA] 1.04 (0.98, 1.10)
Druss 2000 [PTCA] 0.96 (0.91, 1.02)
Plomondon 2007 [PCI] 1.06 (0.97, 1.15)
Druss 2001 [Revascularisation] 0.74 (0.56, 0.95)
Lawrence 2003 [Revascularisation Men] 0.31 (0.21, 0.45)
Lawrence 2003 [Revascularisation Women] 0.34 (0.18, 0.64)
Petersen 2003 [Revascularisation] 0.89 (0.79, 0.98)
Kisely 2007 [Revascularisation] 0.92 (0.86, 1.07)
combined 0.89 (0.82, 0.96)
0.1 0.2 0.5 1 2
relative risk (95% confidence interval)

7. Quality of Medical Treatment ii Medication
OR =0.92 OR =0.79 OR =0.72
Summary meta-analysis plot [random effects] Summary meta-analysis plot [random effects] Summary meta-analysis plot [random effects]
ACE (Kreyenbuhl) 0.23 (0.12, 0.44)
ACE (Druss2001) 0.81 (0.65, 0.98) ACE (Kreyenbuhl) 0.46 (0.18, 1.19)
ACE-I or ARBb (Weiss) 0.83 (0.61, 1.14)
ACE (Petersen) 0.92 (0.79, 1.09) Arthritis (Redelmeier) 0.59 (0.57, 0.62)
Aspirin (Desai) 0.75 (0.39, 1.43)
ACE-I or ARBb (Plomondon) 0.93 (0.84, 1.01) Aspirin (Desai) 1.07 (0.49, 2.30) Bblocker (Desai) 0.70 (0.48, 1.03)
Aspirin (Hippisley-Cox) 1.00 (0.97, 1.04)
Aspirin (Druss2001) 0.81 (0.65, 0.98) Bblocker (Hippisley-Cox) 1.18 (0.94, 1.56)
Aspirin (Weiss) 0.89 (0.64, 1.24)
Aspirin (Petersen) 0.96 (0.81, 1.15) Bblocker (Wang) 0.55 (0.45, 0.55)
Bblocker (Desai) 0.70 (0.43, 1.15)
Aspirin (Plomondon) 0.93 (0.83, 1.04) Bblocker (Hippisley-Cox) 0.96 (0.88, 1.06) Chemotherapy (Goodwin) 0.65 (0.43, 1.00)
Bblocker (Weiss) 0.96 (0.54, 1.71) Cholesterol (Desai) 1.31 (0.57, 3.00)
Bblocker (Druss2001) 0.85 (0.72, 0.98)
Cholesterol (Desai) 1.01 (0.37, 2.77)
Bblocker (Plomondon) 1.11 (0.97, 1.28) Cholesterol (Hippisley-Cox) 0.86 (0.70, 12.30)
Cholesterol (Weiss) 1.85 (1.11, 3.09)
HAART (Tegger) 0.36 (0.25, 0.50)
BBlockers (Petersen) 0.78 (0.69, 0.92) Insulin (Weiss) 1.44 (0.96, 2.16)
Osteoporosis (Bishop) 0.38 (0.15, 0.97) HAART (Yun) 1.43 (1.18, 1.74)
HAART (Mijch) 1.28 (1.04, 1.57)
Statin (Hippisley-Cox) 0.85 (0.80, 0.91) Statin (Hippisley-Cox) 1.15 (0.80, 1.95)
HAART (Himelhoch2004) 2.28 (1.24, 32.50)
Statin (Kreyenbuhl) 0.29 (0.11, 0.77)
Statin (Kreyenbuhl) 0.14 (0.05, 0.44)
HAART (Himelhoch2007) 0.85 (0.71, 1.23)
Statin (Weiss) 0.54 (0.36, 0.51)
combined 0.72 (0.51, 1.00)
combined 0.92 (0.85, 1.00) combined 0.79 (0.66, 0.95)
0.1 0.2 0.5 1 2 5 0.01 0.1 0.2 0.5 1 2 5 10 100
0.5 1 2 5 10 100
odds ratio (95% confidence interval) odds ratio (95% confidence interval)
odds ratio (95% confidence interval)
SMI Schz Affective

8. Detecting Depression in Primary & Secondary Care
Evidence Based Update
2/3rds 1/3rd
Primary Care
10% 25%
cg42 cg90 Medical Psychiatry

9. Comment: Slide illustrates added proportion of all
depression treated in each setting. Most depression
is treated in primary care
1.20
1.00
1.00
0.80
0.64
0.60
0.40
0.26
0.20
0.10
0.00
All visits (N =14,372) Primary care (N =3,605) Psychiatrists (N =293) Medical specialists (N
=10,474)

10. Clinical Questions Evidence
Detecting depression Routinely
PC vs SC; International Differences?
Symptoms of Depression
Too complex? Distress?
Depression in medical settings
Special? Somatic symptoms?
Depression in late-life
Different?
Enhanced Detection
Which tool?
Do they work?

11. Recognition in Routine Care
Is “diagnosis as usual” sufficient?

12. Audience
Which method do you prefer?
Your own skills (first assessment)
Start with 1 or
2 questions
Limit to 7 or
9 questions
20 questions
Phone a friend!

13. Audience
Which method do you prefer?
Your own skills (first assessment) 50%‫‏‬
Start with 1 or 32%
2 questions 73%
Limit to 7 or 75%
9 questions 80%
20 questions 85%
Phone a friend!

14. Cancer Staff Psychiatrists
Current Method (n=226)‫‏‬
Other/Uncertain
9% Other/Uncertain
ICD10/DSMIV 2%
0% ICD10/DSMIV
13%
Short QQ
3%
1,2 or 3 Sim ple
QQ
15%
Clinical Skills
Use a QQ Alone
15% 55%
Clinical Skills
Alone
73% 1,2 or 3 Sim ple
QQ
15%
Comment: Slide illustrates preferences of cancer
clinicians for detecting depression in a national
survey

15. Cancer Staff Psychiatrists
Other/Uncertain
9% Other/Uncertain
ICD10/DSMIV 2%
0% ICD10/DSMIV
13%
Short QQ
3%
1,2 or 3 Sim ple
QQ
15%
Clinical Skills
Use a QQ Alone
15% 55%
Clinical Skills
Alone
73% 1,2 or 3 Sim ple
QQ
15%
Comment: Slide illustrates preferences of cancer
clinicians vs psychiatrists for detecting
Current Method
depression

16. Methods to Evaluate Depression
Unassisted Clinician Conventional Scales
Untrained Trained Short (5-10)‫ ‏‬Long (10+)‫‏‬
Other/Uncertain
Ultra-Short (<5)‫‏‬
9%
ICD10/DSMIV
0%
Short QQ
3% Other/Uncertain Other/Uncertain
9% 9%
ICD10/DSMIV ICD10/DSMIV
0% 0%
Short QQ Short QQ
1,2 or 3 Simple
3% 3%
QQ
15%
Clinical Skills 1,2 or 3 Sim ple 1,2 or 3 Sim ple
Alone QQ QQ
73% 15% 15%
Clinical Skills Clinical Skills
Alone Alone
73% 73%
Verbal Questions Visual-Analogue Test
PHQ2 Distress Thermometer
WHO-5 Depression Thermometer
Whooley/NICE

17. GP Detection of Depression – Meta-analysis
Methods
– 140 studies of GP recognition
rate =>
– 90 depression
– 40 interview
– 19 se sp (+2)
– 10 countries

18. Accuracy 2x2 Table
Depression Depression
PRESENT ABSENT
Test +ve True +ve False +ve PPV
Test -ve False -Ve True -Ve NPV
Sensitivity Specificity Prevalence

19. N=35 studies
Accuracy of GP’s Diagnoses
Depression Depression
PRESENT ABSENT
GP +ve 2503 2515 5018
PPV 42.8%
GP -ve 4050 25,125 6678
NPV 85.1%
6553 27,640 9559
Sensitivity Specificity
Prevalence 19%
48% 80.1%

20. Unassisted Accuracy
Cut-off value
Non-Depressed
Depressed
#
of
Individuals True -ve True +ve
False -ve False +ve
Test
Result

21. Unassisted Accuracy - Prospective
Comment: Slide illustrates detection of
depression (incl false + false –) for each
100 consecutive patients in primary care
if prospective cases are recorded
Cut-off value
Non-Depressed
n=80
Depressed
#
n=20
of
Individuals True -ve True +ve
64 10
False -ve False +ve
10 16 Test
Result

22. Unassisted Accuracy – Medical Notes
Comment: Slide illustrates detection of
depression (incl false + false –) for each
100 consecutive patients in primary care
if GPs opinions are gathers from notes
Cut-off value
Non-Depressed
n=80
Depressed
#
n=20
of
Individuals True -ve True +ve
73 7
False -ve False +ve
13 7 Test
Result

23. % Receiving Any treatment for Depression
20
17.9
18 n=84,850 face-to-face interviews
16 15.4
13.8
14
12 11.3
10.9 10.9
10
8.8
8.1
8 7.2
6.8
6 5.6 5.5
4.3
4 3.4
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Wang P et al (2007) Lancet 2007; 370: 841–50

24. Sl e
ep
di s
turb
an
Los ces
so ; in
fa som
ppe ni a
De tite ; ea
; ov rly
0
10
20
30
40
50
60
70
80
90
pre ere wa 100
sse a tin ke n
dm g; w ing
ood e ig
; ho ht c
pe han 86.8
Los Ap les
so a th sne ges
f in y; l ss;
ter eth sad
est arg
;w y; t ; gl
oom
ithd
raw
ired
nes y
al; s; l
55.6 54.4
Los in d ass
so iffe i tud
fe ren e
ner ce;
Los gy; lo n
43.3
so l os eli n
f lib so ess
ido f dr
; lo i ve
36
ss ; bu
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xio ex ou
us; d ri v t
ag e; i
mp
29.8
itat
ed; Te ote
irri t ars nce
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ma eli n e; r eep
tic; est ing
ve g gw les ; cr
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tive hl e
ss; ens g
sym gui e; s
pt o l ty; t res
ms lac sed
;m ko
ala f se
i se
26.2 25.6 25.2
Su ;m lf e
i ci d ste
Los ulti
ple em
so e th
GP Asks about:
f co ou con
23.8
nce ght sul
ntr s; t ta t
hou ion
atio
n; p ght s
24
oor of s
Dim me el f
ini s mo inj u
hed ry, ry
per poo
f or r th
ma i nk
nce ing
Em ; in
Los otio abi
21.4 21.2
na lity
so
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cop
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t; f
bil i
ty; e
avi so lat mo
our fe a ff od
al p njo ect sw
rob ym ; lo ing
lem ent ss s
s; a or of e
13.9 12.8
ggr pl e mo
ess asu tion
ive re ;
nes lac
9.5
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ssi eh um
mis avi or
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7.2
gat han
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ych atti
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eec i on
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5.9
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use a gu ss
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l co ss,
De hol etc
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i on bac
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s; h
act allu or
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to p atio gs
rob ns;
2.6
abl con
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yo es
or l
1.8
r pa ife
st h
looking for depression
i sto eve
ry n ts
Ob of d
1.8
ses epr
siv ess
e id i on
eat
1.3
i on
; ph
ob
ias
Comment: Slide illustrates which
Lac
symptoms are asked about by GPS
0.9
Pe ko
ri o f in
do sig
f lif ht
e(
0.4
me
no
pau
se )
0.4

25. GP Recognizes:
Proportion of Individual Symptoms Recognised by GPs
80.0 76.1
70.0
60.0
50.0
40.0 36.4
34.6
31.6
30.0
21.6
20.0 16.7
13.3
9.1 8.3 8.3
10.0
0.0
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ng
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ar
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of
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No
of
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ch
ss
ss
po
Lo
Lo
Hy
O’Conner et al (2001) Depression in primary care.
Int Psychogeriatr 13(3) 367-374.

26. Predictors of Recognition
Prevalence
10% rural 15% mean 20% urban 20% (oncology 25%)
Severity
70% mild 20% moderate 10% severe
International
Low in developing but in Western:
Italy > Netherlands >Australia > UK > US
Cumulative
77% single 89% 3-6 months

27. 1
Post-test Probability
0.9 Comment: Slide illustrates Bayesian
curve – pre-test post test probability for
every possible prevalence
0.8
0.7
0.6
0.5
PPV
0.4
0.3 Baseline Probability
Depression+
0.2
NPV
Depression-
0.1
Pre-test Probability
0
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

28. 80
74
70 69.6
70
61.5
59.6
60 56.7 56.7 55.6 54.2
50 45.7
43.9
39.7
40
30 28.4
22.2 21
19.3
20
10
0
s
L
ris
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ch
g
Ja
n
Sa
n
Na
ro
Sh
an
Ba
de
G
M
o
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Recognition from WHO PPGHC Study (Ustun, Goldberg et al)

29. Symptoms of Depression…usual suspects
Reminder of DSMIV and ICD

30. Which are Criteria for Depression?
Loss of confidence Psychic anxiety
Low motivation / drive Somatic anxiety
Withdrawal Anger
Avoidance Irritability
Social isolation Lack of reactive mood
Worry Cognitive Change
Feelings of dread Memory complaints
Helplessness Perceptual distortion
Hopelessness
=> None are official criteria!

31. Core Symptoms ICD10 DSMIV
Persistent sadness or low mood Yes (core)‫‏‬ Yes (core)‫‏‬
Loss of interests or pleasure Yes (core)‫‏‬ Yes (core)‫‏‬
Fatigue or low energy Yes (core)‫‏‬ Yes
Disturbed sleep Yes Yes
Poor concentration or Yes Yes
indecisiveness
Low self-confidence Yes No
Poor or increased appetite Yes No
Suicidal thoughts or acts Yes Yes
Agitation or slowing of Yes Yes
movements
Guilt or self-blame Yes Yes
Significant change in weight No Yes

32. Symptom Significance in Depression
Depression ICD10 DSMIV HADs D Score
Severity
Healthy 0 or 1 0 symptom 0-3
symptom
Sub-syndromal 2 or 3 1 or No core 4-7
symptoms symptoms
Mild 4 symptoms 2-4 symptoms 8 -11
(2+2)‫‏‬ (minor)‫‏‬
Moderate (5 or )6 5 symptoms 12 - 15
symptoms (Mj)‫‏‬
Severe (7 or) 8 Unspecified 16 - 21
symptoms
(3+4)‫‏‬
=> HADS

33. Graphical – single discriminating symptom
Comment: Slide illustrates the concept of
discrimination using one symptom severity of “low
mood”
Non-Depressed
Depressed
#
of
Individuals
With symptom Point of Rarity
Severity of Low Mood

34. Graphical – single symptom
Non-Depressed
Depressed
# ?Point of Rarity
of
Individuals
With symptom
Severity of
Low Mood

35. Pooled
Comment: Slide illustrates added hypothetical
distribution of mood scores in a population with
hidden depression
Non-Depressed
Depressed
#
of
Individuals
With symptom
Severity of Low Mood

36. Comment: Slide illustrates added actual distribution
of mood scores on the HADS in a cancer
population with hidden depression from the
Edinburgh cancer centre

37. 0
1000
1500
2000
2500
3000
500
Ze
r o
O
ne
Tw
o
Th
re
e
Fo
ur
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ei
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irt
ee
Fo n
ur
te
en
Fi
ft e
en
Si
xt
ee
Se n
ve
nt
ee
Ei n
gh
te
en

38. 0.05
0.15
0.25
0
0.1
0.2
0.3
Ei
gh
t
N
in
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n
El
ev
en
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el
ve
Th
irt
ee
n
Fo
ur
te
en
Fi
fte
en
Si
xt
ee
n
Se
ve
nt
Proportion Missed
ee
n
Proportion Recognized
Ei
gh
te
en
N
in
et
ee
n
Tw
en
Tw ty
en
ty
-o
ne

39. Symptoms of Depression…time for change
Are the classical symptoms evidence based?

40. “Common” Symptoms of Depression
Item Depressed Frq Non-Depressed Frq
Depressed mood 0.93 0.18
Diminished drive 0.88 0.30
Loss of energy 0.87 0.32
Concentration/indecision 0.87 0.27
Sleep disturbance 0.83 0.32
Diminished concentration 0.82 0.24
Diminished interest/pleasure 0.81 0.12
Insomnia 0.70 0.27
Anxiety 0.69 0.42
Worthlessness 0.61 0.12
Psychic anxiety 0.59 0.33
Thoughts of death 0.56 0.12
Mitchell, Zimmerman et al n=2300

41. “Uncommon” Symptoms
Non-Depressed
Item Depressed Proportion Proportion
Somatic anxiety 0.46 0.25
Decreased appetite 0.45 0.11
Anger 0.44 0.26
Psychomotor agitation 0.34 0.09
Psychomotor retardation 0.28 0.04
Decreased weight 0.23 0.06
Lack of reactive mood 0.22 0.06
Increased appetite 0.19 0.07
Hypersomnia 0.19 0.06
Increased weight 0.16 0.06
Mitchell, Zimmerman et al MIDAS Database. Psychol Med 2009

42. -0.10
0.00
0.10
0.20
0.30
0.40
0.50
A nge
r
A nxie
ty
Decr
ea s e
d app
eti te
Decr
eas e
d weig
ht
Depr
es sed
m ood
Dimin
is hed
c onc
entr a
t io n
identifying non-depressed
Dimin
is hed
dr ive
Dimin
is hed
int er
est /p
leasu
re
Exc e
ss ive
guilt
Help
less n
Comment: Slide illustrates added value of each
ess
symptom when diagnosing depression and when
Hope
le s snes
s
Hy pe
rsom
ni a
Inc re
a sed a
ppet
ite
Inc re
a sed w
eight
Indec
isiv enes
s
Ins om
nia
L ac k
of re
act iv
e mo
od
L os s
of en
erg y
Ps ych
i c a nx
iety
Ps ych
o mot o
r agi ta
tion
Ps ych
o mot o
r c han
ge
Ps ych
o mot o
r ret ar
da tion
Sl eep
dis tu
rban
ce
Soma
ti c a
nx iet
y
Rule-In Added Value (PPV-Prev)
Thou
g hts
Rule-Out Added Value (NPV-Prev)
of de
ath
Wor t
hles s
ness

43. 1 Depressed Mood
S Diminished interest/pleasure
e
0.9 Diminished drive
n
s Loss of energy
i Sleep disturbance
0.8
t Diminished concentration
i
0.7 v
i
t
0.6 y
0.5
0.4
0.3 Comment: Slide illustrates summary ROC curve
sensitivity/1-specficity plot for each mood
symptom
0.2
0.1
1 - Specificity
0
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
n=1523

44. Depression in Medical Settings
Are the symptoms (phenomenology) unique?
Is it harder to detect?

45. Approaches to Somatic Symptoms of Depression
Inclusive
Uses all of the symptoms of depression, regardless of whether they may or
may not be secondary to a physical illness. This approach is used in the
Schedule for Affective Disorders and Schizophrenia (SADS) and the Research
Diagnostic Criteria.
Exclusive
Eliminates somatic symptoms but without substitution. There is concern that
this might lower sensitivity. with an increased likelihood of missed cases (false
negatives)‫‏‬
Etiologic
Assesses the origin of each symptom and only counts a symptom of
depression if it is clearly not the result of the physical illness. This is proposed
by the Structured Clinical Interview for DSM and Diagnostic Interview Schedule
(DIS), as well as the DSM-III-R/IV).
Substitutive
Assumes somatic symptoms are a contaminant and replaces these additional
cognitive symptoms. However it is not clear what specific symptoms should be
substituted

46. Somatic Bias in Mood Scales

47. Comment: Slide illustrates concept of
phenomenology of depressions in
medical disease
Primary Depression
Medically Unwell Secondary
Depression

48. Study: Coyne Thombs Mitchell
N= 1200 – 4500
Pooled database study
All comparative studies

49. A
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(C
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pp (P
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om
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n=4069 vs 4982
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so or
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ss ni d)
In a
te (P
ri
re
st m
Lo ar
(C y)
ss om
In
*
te or
re bi
st d)
Lo
w (P
M rim
oo ar
d y)
(C
Lo om
w
*
M or
R oo bi
d)
et d
ar
da (P
rim
t io
n ar
(C y)
R
et om
ar or
da bi
t io d)
n
Su (P
ic ri
id m
primary depression
e ar
y)
(C
om
*
Su or
W ic bi
ei id d)
gh e
tL (P
ri
os m
s ar
W (C y)
ei om
gh
symptoms profile in comorbid vs
tL or
Comment: Slide illustrates similar
os bi
Co-morbid Depression vs Primary Depression
d)
s
(P
rim
ar
y)
Prim ary Depression
Com orbid Depression
*