RCPsych AGM10 - Diagnosing depression in primary care and hospital settings new evidence (v3)

transcript

Alex Mitchell ajm80@le.ac.uk

Consultant in Liaison Psychiatry & Psycho-oncology

Diagnosing Depression in Primary Care and Hospital

Settings - Towards a change in clinical practice

RCPsych Workshop 2010 – 9.45 – 11am

Loss of confidenceLow motivation / driveWithdrawalAvoidanceSocial isolationWorryFeelings of dreadHelplessnessHopelessnessPsychic anxietySomatic anxietyAngerLack of reactive moodCognitive Change (=> memory complaints)Perceptual distortion

Which Are Recognized Symptoms of MDD?

=> plan

UNSURE

DSMVICD11

Symptoms

Under-served

Distress

Monitoring

Scales

Screening

Qualityof care

Older people

PhysicalIllness

DepressionDetection

Prescribing

Follow-up

Culturaleffects

Se Change

PhysiciansSpecialSymptoms

PrimaryCare

Impairment

Help Seeking

Introduction – What’s Going Wrong?

BackgroundContents

% Receiving Any treatment for Depression (CIDI)

10.911.3

8.18.8

High Inc

omeBelg

France

German

Spain USALow

ChinaColom

biaSouth

caUkra

Wang P et al (2007) Lancet 2007; 370: 841–50

n=84,850 face-to-face interviews

=> USA

17.7 20.515.6

21.717.5 20.3

t or a

Depression Alone (=883)

Anixety Alone (n=314)

Depression and Anxiety (n = 439)

Young et al (2001) The Quality of Care for Depressive and Anxiety Disorders in the United States. Arch Gen Psychiatry. 2001;58:55-61

462 (42%)Meetable Needs

1093 (100%)Population

388 (84%)Aware of Need

172 (44%)Requested Help

80 (47%)Needs Met

462 needs

322 DSMIV

Patient & provider factors=> DUD

8 yrs N= 9282 NCS‐R

N=23 studies; 50% some treatment 33% minimal treatment N=19 studies; 30% 1 in 1/12; 10% 3 in 3 months

5 Steps to Improve QoC….and change clinical practice

1. Re-look at concept / criteria /symptoms

2. Understand Detection Problems

3. Understand special populations

4. Consider Enhanced Detection

5. Tie Detection to Clear Action

Depression Care: Who Provides it?

2/3rds 1/3rd

25%Psychiatry

10%Medical

Primary Care

cg90cg42

Percentage of U.S. retail psychotropic prescriptions written from August 2006 to jul07

Mark et al. PSYCHIATRIC SERVICES September 2009 Vol. 60 No. 9

All visits (N =14,372) Primary care (N =3,605) Psychiatrists (N =293) Medical specialists (N=10,474)

Comment: Slide illustrates added proportion of all depression treated in each setting. Most depression is treated in primary care

J Gen Intern Med. 2006 September; 21(9): 926–930.

1a. Re-examination of Depression

Is depression a disease; disorder (syndrome) or normally distributed

Graphical – two diseases

Healthy

Stroke# ofIndividualsWith symptom

Severity of Infarct

Point of Rarity

Comment: Slide illustrates the concept of discrimination using one symptom severity of “low mood”

Graphical – two disorders

Healthy

Diabetes

# ofIndividualsWith symptom

?Point of Rarity

Optimal cut

Graphical - Dimension

Non-Depressed

Depressed# ofIndividualsWith symptom

Severity of Low Mood

Comment: Slide illustrates added hypothetical distribution of mood scores in a population with hidden depression

Do We Have Good Data in Psychiatry?

Zero One

TwoThree Fo

SixSeve

htNine Ten

Eleven

Fiftee

eenSeve

Eighteen

HADS-D N=18,414

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

Distress Ratings (n=2,200) clinical significance criterion

Proportion

18 .4 %

12 .9 %

11.2 %12 .3 %

11.9 %

2 .8 % 2 .6 %

7.7% 7.2 %

Zero One Two Three Four Five Six Seven Eight Nine Ten

Insignificant SevereModerateMildMinimal

Depression is on a continuum using current scales……..There will always be a trade-off of sensitivity vs specificty

Back to Basics Lessons

=> Categorial

1b. Re-examination of Criteria of Depression

=> ICD10

YesYesGuilt or self-blame

DSMIVICD10Core Symptoms

YesNoSignificant change in weight

YesYesAgitation or slowing of movements

YesYesSuicidal thoughts or acts

NoYesPoor or increased appetite

NoYesLow self-confidence

YesYesPoor concentration or indecisiveness

YesYesDisturbed sleep

YesYes (core)‏Fatigue or low energy

Yes (core)‏Yes (core)‏Loss of interests or pleasure

Yes (core)‏Yes (core)‏Persistent sadness or low mood

Symptom Significance in Depression

(7 or) 8 symptoms ‏(3+4)

(5 or )6 symptoms

4 symptoms ‏(2+2)

2 or 3 symptoms

0 or 1 symptom

16 - 21UnspecifiedSevere

12 - 155 symptoms (Mj)‏

Moderate

8 -112-4 symptoms (minor) ‏

4 - 71 or No core symptoms

Sub-syndromal

0 - 30 symptomHealthy

HADs D ScoreDSMIVDepression Severity

Change in practice – ICD10 2/4/6/8 + CS

“Common” Symptoms of Depression

0.120.56Thoughts of death

0.330.59Psychic anxiety

0.120.61Worthlessness

0.420.69Anxiety

0.270.70Insomnia

0.120.81Diminished interest/pleasure

0.240.82Diminished concentration

0.320.83Sleep disturbance

0.270.87Concentration/indecision

0.320.87Loss of energy

0.300.88Diminished drive

0.180.93Depressed mood

Non-Depressed FrqDepressed FrqItem

Mitchell, Zimmerman et al n=2300

“Uncommon” Symptoms

0.060.16Increased weight

0.060.19Hypersomnia

0.070.19Increased appetite

0.060.22Lack of reactive mood

0.060.23Decreased weight

0.040.28Psychomotor retardation

0.090.34Psychomotor agitation

0.260.44Anger

0.110.45Decreased appetite

0.250.46Somatic anxiety

Non-Depressed ProportionDepressed ProportionItem

Mitchell, Zimmerman et al MIDAS Database. Psychol Med 2009

Rule-In Added Value (PPV-Prev)Rule-Out Added Value (NPV-Prev)

Comment: Slide illustrates added value of each symptom when diagnosing depression and when identifying non-depressed

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Depressed Mood

Diminished drive

Diminished interest/pleasure

Loss of energy

Sleep disturbanceDiminished concentration

Sensitivity

1 - Specificity

n=1523

Comment: Slide illustrates summary ROC curve sensitivity/1-specficity plot for each mood symptom

Symptoms of depression are not necessarily optimalFurther research is required against course and burden

2. Recognition in Routine Care

Is “diagnosis as usual” sufficient?

1,2 or 3 Simple QQ15%

Clinical Skills Alone73%

ICD10/DSMIV0%

Short QQ3%

Other/Uncertain9% Other/Uncertain

Use a QQ15%

ICD10/DSMIV13%

Cancer StaffCurrent Method (n=226)

Psychiatrists

=> Psychiatrists

ICD10/DSMIV0%

Short QQ3%

Other/Uncertain9% Other/Uncertain

Use a QQ15%

ICD10/DSMIV13%

Cancer Staff Psychiatrists

Current MethodComment: Slide illustrates preferences of cancer clinicians vs psychiatrists for detecting depression

55.6 54.4

29.826.2 25.6 25.2 23.8 24

21.4 21.2

13.9 12.89.5

7.2 7 7 5.9 4.8 4.1 2.6 1.8 1.8 1.3 0.9 0.4 0.40

ite; o

f driv

; stre

lty; l

ltatio

lity to

l labi

t affe

t or p

r life

Comment: Slide illustrates which symptoms are asked about by GPS looking for depression

What do GPs Ask about:Sleep

AppetiteLow

Energy

GP Recognizes:Proportion of Individual Symptoms Recognised by GPs

36.4 34.631.6

21.616.7

13.39.1 8.3 8.3

Insomnia

hondri

terest

Tearfu

Anxiety

Pessim

Anorex

Not Copin

O’Conner et al (2001) Depression in primary care.Int Psychogeriatr 13(3) 367-374.

GP Detection of Depression – Meta-analysis

Methods– 140 studies of GP recognition

rate =>

– 90 depression– 40 interview– 19 se sp (+2)– 10 countries

Accuracy 2x2 Table

PrevalenceSpecificitySensitivity

NPVTrue -VeFalse -VeTest -ve

PPVFalse +veTrue +veTest +ve

DepressionABSENT

DepressionPRESENT

Accuracy of GP’s Diagnoses

955927,6406553

667825,1254050GP -ve

501825152503GP +ve

DepressionABSENT

DepressionPRESENT

Sensitivity48%

PPV 42.8%

Specificity80.1%

NPV 85.1%

Prevalence 19%

N=35 studies

100 weekly referrals

GP Assessment

10TP 10FN

Screen #1+ve

n = 20 80 ND

Sp 80%

Se 50%

n = 80

N = 100

TP = 10

FP = 1664TN 16FP TN =64

FN = 10

PPV 28% NPV 88%

Screen #1-ve

GP Opinion

50% TP and 25% FP Offered Treatment

50‐80% accept initial treatment

100 weekly referrals

GP Assessment

7TP 13FN

Screen #1+ve

n = 20 80 ND

Sp 90%

Se 30%

n = 80

N = 100

TP = 10

FP = 1672TN 8FP TN =64

FN = 10

PPV 50% NPV 80%

Screen #1-ve

50% TP and 25% FP Offered Treatment

50‐80% accept initial treatment

1/3 of screen positive patients with no treatment well at follow‐up

GP Notation

3/20TP Offered Rx => appropriate treatment rate of 5-20%

2/80FP Offered Rx => inappropriate treatment rate of 1-2%

Weekly Population

GP Assessment

Possible case

Depression

Screen #1+ve

n = 20 No Depression

Sp 80%

Se 50%

n = 80

N = 100

TP = 10

FP = 16Probable Non-Case TN =64

FN = 10

PPV 28%

2nd Assessment Sp 80%

Se 50%

NPV 88%

Probable Depression TP = 56

FP = 72Probable Non-Case TN =288

FN = 84

PPV 44% NPV 77%

Screen #1-ve

Screen #2+ve

Cumulative YieldTP = 56

TN = 728

FN = 144

FP = 72

NPV 83%

PPV 44%

Sp 91%

Se 28%

Single assessment inadequateFalse +ve’s are more of a problem than expected

3. Predictors of Recognition

0.210.22

0.02 0.020.01 0.01

0.010.01 0.01 0.01

10mins

15mins

20mins

25mins

30mins

35mins

40mins

45mins

50mins

55mins

60mins

65mins

70mins

Geraghty JGIM 2007

Is 10‐15 minutes enough?

Severity

Zero One

TwoThree Fo

SixSeve

htNine Ten

Eleven

Fiftee

eenSeve

Eighteen

HADS-D

Nine Ten

Eleven

Fiftee

Eighteen

Ninetee

Proportion MissedProportion Recognized

HADS-D

Comment: Slide illustrates diagnostic accuracy according to score on DT

11.815.4

30.4 28.9

41.9 42.9 40.7

66.771.4

26.124.4

19.4 19.0

22.2 14.3

43.546.7

38.7 38.1

25.921.4

5.911.1

Zero One Two Three Four Five Six Seven Eight Nine Ten

Judgement = Non-distressedJudgement = UnclearJudgement = Distressed

CNS in Oncology N=401

Recognition from WHO PPGHC Study (Ustun, Goldberg et al)

7470 69.6

61.5 59.656.7 56.7 55.6 54.2

45.7 43.939.7

22.2 21 19.3

Santia

Verona

Groningen

Berlin

Seattle

TOTALBangalo

reRio de J

Ibadan

Ankara

ghaiNagas

Clinician traits eg confidence

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Pre-test Probability

Ave Confidence+

Ave Confidence-

Baseline Probability

Above Ave Confidence+

Above Ave Confidence-

High Confidence+

High Confidence-

Low confidence = more cautious, fewer false positives, more false negatives

High confidence = less cautious, more false positives, low false negatives

Predictors of Recognition

Prevalence10% rural 15% mean 20% urban 20% (oncology 25%)

Severity70% mild 20% moderate 10% severe

InternationalLow in developing but in Western:Italy > Netherlands >Australia > UK > US

ContactCummulative: 77% single 89% 3-6 monthsAppointment Duration

Confidence &trust

4. Comorbid Depression

Back to Basics

Approaches to Somatic Symptoms of DepressionInclusiveUses 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.

ExclusiveEliminates somatic symptoms but without substitution. There is concern that this might lower sensitivity. with an increased likelihood of missed cases (false negatives)‏

EtiologicAssesses the origin of each symptom and only counts a symptom ofdepression 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).

SubstitutiveAssumes somatic symptoms are a contaminant and replaces these additional cognitive symptoms. However it is not clear what specific symptoms should be substituted

Who Uses Specific Non-Somatic scales?

Medically Unwell Alone

Primary Depression Alone

Secondary Depression

Comment: Slide illustrates concept of phenomenology of depressions in medical disease

FatigueAnorexiaInsomnia

Concentration

Study: Coyne Thombs Mitchell

N= 4500; Pooled database study; All comparative studies

Physical illness+comorbid depressionVsPhysical illness aloneVs

Primary depression alone

Co-morbid Depression vs Primary Depression

Agitatio

n (Com

orbid)

Agitatio

n (Prim

Anxiety

orbid)

Anxiety

Appetite

(Comorb

Appetite

Concen

tratio

n (Comorb

Concen

tratio

n (Prim

Fatigu

e (Comorb

Fatigu

e (Prim

Guilt (

Comorbid)

Guilt (

Primar

Hopeles

s (Comorb

Hopeles

s (Prim

Insomnia

(Comor

Insomnia

Loss In

t (Comorb

Loss In

t (Prim

Low Mood (C

omorbid)

Low Mood (P

rimary

Retard

ation (

Comorbid)

Retard

ation (

Primary)

Suicide (

Comorbid)

Suicide (

Primar

Weight L

oss (C

omorbid)

Weight L

oss (P

rimary

Comorbid Depression

Primary Depression

n=4069 vs 4982Comment: Slide illustrates similar symptoms profile in comorbid vsprimary depression

Concentration

BEFORE

AgitationRetardation

Co-morbid Depression vs Medical Illness Alone

n= 4069 vs 1217

Anxiety

orbid)

Anxiety

Concen

tratio

n (Comorb

Concen

tratio

n (Med

Fatigu

e (Comorb

id)Fati

Medica

Hopeles

s (Comorb

Hopeles

s (Med

Insomnia

(any t

(Comorb

Insomnia

(any t

Loss In

t (Comorb

Loss In

t (Med

Low Mood (C

omorbid)

Low Mood (M

edical)

Retard

ation (

Comorbid)

Retard

ation (

Medica

Suicide (

Comorbid)

Suicide (

Medica

Weight L

oss (C

omorbid)

Weight L

oss (M

edical)

Worthles

s (Comor

Worthles

s (Med

Medical Illness Alone

Comorbid Depression

Comment: Slide illustrates distinct symptoms profile in comorbid depression vs medical illness alone

Concentration

Medically Unwell

Primary Depression

Comment: Slide illustrates actual phenomenology of depressions in medical disease

Weight loss

AgitationRetardation

Comorbid depression scales need to be reexaminedAgainst alternatives

5. Enhanced Detection Strategies

Does Screening Work?

ICD10/DSMIV0%

Short QQ3%

Other/Uncertain9%

Methods to Evaluate Depression

Unassisted Clinician Conventional Scales

Verbal Questions Visual-Analogue Test

Whooley/NICE

Distress Thermometer

Depression Thermometer

Ultra-Short (<5)‏Short (5-10)‏ Long (10+)‏Untrained Trained

ICD10/DSMIV0%

Short QQ3%

Other/Uncertain9%

ICD10/DSMIV0%

Short QQ3%

Other/Uncertain9%

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Clinician Positive (Fallowfield et al, 2001)

Clinician Negative (Fallowfield et al, 2001)

HADS-D Positive (Mata-analysis)

HADS-D Negative (Meta-analysis)

Comment: Slide illustrates Bayesian curve comparison from indirect studies of clinician and HADS

This illustrates POTENTIAL gain from screening

Benefit

All scales side-by-side

Meader et alNational Collaborative Centre for Mental Health

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

lity HADS+

GDS30+

GDS30-

GDS15+

GHQ28+

GDS15-

GHQ28-

WHOOLEY2Q+

WHOOLEY2Q-

BDI-SF+

BDI-SF-

GHQ12+

GHQ12-

PHQ2 = HIGH NPV

What is the actual added value?

Is there a circularity?

8 RCTs of screening vs no-screening in PC

Comment: Slide illustrates actual gain in meta-analysis of screening implementation in primary care

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Clinical+Clinical-Baseline ProbabilityScreen+Screen-

Comment: Slide illustrates Bayesian curve comparison from RCT studies of clinician with and without screening

This illustrates ACTUAL gain from screening in Study from Christensen

Depression screening can work……..Under favourable conditions

5. Depression in Older People

Does it go unrecognized?

Are Somatic Symptoms Common in Older People?

QuestionsMore or less difficult to detect late-life depression?

More or less

Low moodAgitation InsomniaPoor concentration

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Routine Case-Finding Late-LifeRoutine Exclusion Late-lifeBaseline ProbabilityRoutine Case-Finding MixedRoutine Exclusion MixedRoutine Case-Finding YoungerRoutine Exclusion Younger

Comment: Slide illustrates detection of late life vs mid-life depression in primary care – GPs are least successful with late-life depression

More common in late-life depression

More common in early-life depression

Comment: Slide illustrates simple frequency of symptoms in late life vsmid-life depression

Anxiety

bined)

Anxiety

(Somatic

anxiet

Depres

Diminish

oncentra

Diminish

e Guilt

Helples

Increas

ppetite

Increas

Indecisi

of Ene

omotor Agita

omotor Retar

Sleep D

isturban

ombined)

Sleep D

isturban

omnia)

Sleep D

isturban

ce (In

somnia)

Thoughts

of Dea

thWorth

<55>54>59>64

Comment: Slide illustrates diagnostic value of symptoms in late life vs mid-life depression – few have special significance

Mid-life Depression

Late-life Depression

Comment: Slide illustrates actual phenomenology of late life depression

Poor concworthlessness

Tools and criteria for late-life dep……..May need to be re-examined

=> Future?

=86.4% =82.2%

=57.6%Beals AGP 2004

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Help-Seeking Any+

Help-Seeking Any-

Help-Seeking Medical+

Help-Seeking Medical-

Impairment+

Impairment-

Distress+

Distress-

Beals - Challenges in Operationalizing the DSM-IV - Clinical Significance Criterion Arch Gen Psychiatry. 2004;61:1197-1207

SummaryQuestions

Quick Summary

Depression is modestly common & easily missed5% have depression as their main reason for presentation

Most depression is comorbid50% adults 80% elderly have physical illness

All health professionals struggle with diagnosisSymptom approach

Routine screening modestly effectiveHigh risk, targeted and algorithm approaches

Dimensional approach developingTrials in cardiac care and oncology and neurology of ET

RCPsych AGM10 - Diagnosing depression in primary care and hospital settings new evidence (v3)

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