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Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)
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Cardiff09 - Detecting Depression in Primary & Secondary Care (May2009)

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Lecture for the University of Cardiff Psychiatry programme 2009. Topic is detecting depression - an evidence based approach. 86 slides; most self-explanatory but some slide labels added. Warning! can …

Lecture for the University of Cardiff Psychiatry programme 2009. Topic is detecting depression - an evidence based approach. 86 slides; most self-explanatory but some slide labels added. Warning! can be a bit statistically heavy!

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  • 1. Detecting Depression in Primary & Secondary Care Evidence Based At Last? Alex Mitchell alex.mitchell@leicspart.nhs.uk Consultant in Liaison Psychiatry Cardiff May 2009
  • 2. Detecting Depression in Primary & Secondary Care Evidence Based At Last? 2/3rds 1/3rd 10% 25% Medical Psychiatry
  • 3. 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)
  • 4. % 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 2 0 SA in n ly na m ca e a l y ne ce e nd e s m bi pa an m It a a nd ra u hi i an U ai la Sp fr co om co gi Ja m Is C kr rla A a Fr el In er In Ze ol U h B he G w ut h C ew et ig Lo So H N N Wang P et al (2007) Lancet 2007; 370: 841–50
  • 5. Clinical Questions Evidence What are the symptoms of depression? Are we looking for depression? If we look, do we detect depression? What tools are available? Do the tools really make a difference? What about acceptability (Ultra-Short Screening)‫‏‬ Depression in medical settings - special? Depression in late-life – special? Implementation of screening - how
  • 6. Clinical Questions Evidence What are the symptoms of depression? Are we looking for depression? If we look, do we detect depression? What tools are available? Do the tools really make a difference? What about acceptability (Ultra-Short Screening)‫‏‬ Depression in medical settings - special? Depression in late-life – special? Implementation of screening - how
  • 7. 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!
  • 8. 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
  • 9. 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
  • 10. Useful Symptoms of Depression? Audience – How useful would the following be? Depressed Non-Depressed Low mood 100% 0% Insomnia 50% 25% Weight gain 5% 8% Diagnosis => Occurrence (se) & discrimination (ppv)‫‏‬ => illustration
  • 11. 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
  • 12. Graphical – single symptom Non-Depressed Depressed # ?Point of Rarity of Individuals With symptom Severity of Low Mood
  • 13. 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
  • 14. Comment: Slide illustrates added actual distribution of mood scores on the HADS in a cancer population with hidden depression from the Edinburgh cancer centre
  • 15. “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 MIDAS Database. Psychol Med 2009
  • 16. “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
  • 17. 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 L os s of ene rg y Dim inis he dd r ive Sl e ep dis t C on urb anc c en tr at e ion /i n dec n=1523 is io n D ep res sed mo od Dim A nx inis iet y hed c onc ent r at ion Dim Ins o inis he m nia d in t er est /p l e asu re Ps y chi ca nx i e ty Hel p less ss ne Wo r th les s nes s Hop e les s nes s Som ati c anx iety Tho ug hts of dea th specificity of each mood symptom A ng er Exc ess Comment: Slide illustrates sensitivity and ive guil Ps y t cho mo t or c ha ng e Ind ec i siv e nes D ec s rea s ed app eti t Ps y cho e mo t or agi Ps y tati cho on mo t or ret ard atio n D ec rea s ed wei Lac g ht ko f re act ive mo od Inc rea sed app et it e Hy p erso mn ia All Case Proportion Inc rea Depressed Proportion sed we ight Non-Depressed Proportion
  • 18. -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 ea s e d we ig ht Depr es sed m ood Dimin is hed c onc entr a t ion 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 ased appe t ite Inc re ased w eig ht Indec isiv e ne ss Ins om nia L ac k of re act iv e mo od L os s o f en erg y Ps ych i c anx 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 datio n Sl eep dis tu rban ce Soma ti c a n x iety Rule-In Added Value (PPV-Prev) Thou gh Rule-Out Added Value (NPV-Prev) ts of deat h Wor t hle s snes s
  • 19. 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 Comment: Slide illustrates summary ROC curve 0.3 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
  • 20. Clinical Questions Evidence What are the symptoms of depression? Are we looking for depression? If we look, do we detect depression? What tools are available? Do the tools really make a difference? What about acceptability (Ultra-Short Screening)‫‏‬ Depression in medical settings - special? Depression in late-life – special? Implementation of screening - how
  • 21. Audience Which method do you prefer? Your own skills (no assistance)‫‏‬ Start with 1 or 2 questions Limit to 7 questions 20 questions! Phone a friend!
  • 22. 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
  • 23. Cancer Staff Psychiatrists Ideal Method (n=226)‫‏‬ Effective? Long QQ 8% Clinical Skills Clinical Skills Alone Alone Algorithm 20% 17% 26% ICD10/DSMIV 24% ICD10/DSMIV 1,2 or 3 Sim ple 0% 1,2 or 3 Sim ple QQ QQ 24% Short QQ 34% 23% Short QQ 24% Comment: Slide illustrates “ideal” preferences of cancer clinicians for detecting depression in a national survey
  • 24. 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
  • 25. Cancer Staff Psychiatrists Long QQ 8% Clinical Skills Clinical Skills Alone Alone Algorithm 20% 17% 26% ICD10/DSMIV 24% CD10/DSMIV 1,2 or 3 Sim ple 0% 1,2 or 3 Sim ple QQ QQ 24% Short QQ 34% 23% Short QQ 24% Comment: Slide illustrates “ideal” preferences of cancer clinicians vs psychiatrists for detecting Ideal Method depression
  • 26. Do Clinicians Look for Depression Often?
  • 27. Methods to Evaluate Depression Unassisted Clinician Conventional Scales Untrained Trained Short (5-10)‫ ‏‬Long (10+)‫‏‬ Othe r/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 Sim ple 3% 3% QQ 15% Clinical Sk ills 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
  • 28. Clinical Questions Evidence What are the symptoms of depression? Are we looking for depression? If we look, do we detect depression? What tools are available? Do the tools really make a difference? What about acceptability (Ultra-Short Screening)‫‏‬ Depression in medical settings - special? Depression in late-life – special? Implementation of screening - how
  • 29. GP Detection of Depression – Meta-analysis Mitchell, Vaze, Rao Methods 100 studies of GP recognition rate => 35 with Se Sp 9x DSM 7x ICD10 9x HADS 4x CES-D; 4x PHQ 2x BDI Mitchell, Vaze, Rao (2009) in press Lancet
  • 30. Accuracy 2x2 Table Depression Depression PRESENT ABSENT Test +ve True +ve False +ve PPV Test -ve False -Ve True -Ve NPV Sensitivity Specificity Prevalence
  • 31. 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% Mitchell, Vaze, Rao Lancet in Press
  • 32. Unassisted Accuracy Cut-off value Non-Depressed Depressed # of Individuals True -ve True +ve False -ve False +ve Test Result
  • 33. 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
  • 34. Unassisted Accuracy - Retrospective 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
  • 35. Some Predictors of Detection Giving sufficient time Asking about depression Looking for symptoms Recognizing symptoms High and low risk samples Mild Moderate Severe
  • 36. GP Recognition of Individual symptom 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 s ng a d gy s ia st ty ism es oo si ni ex re xie pi er ia m ln m m te Co or en dr An so fu in i An w ss on ar In t of Lo No of Pe Te ch ss ss po Lo Lo Hy O’Conner et al (2001) Depression in primary care. Int Psychogeriatr 13(3) 367-374.
  • 37. Sl e ep di s tur ban Los ces so ; in fa s om ppe ni a De ti te ; ea 0 10 20 30 40 50 60 70 80 90 100 pre ; ov s se ere r ly dm a tin wa g; w ke n ood e ig ing ; ho 86.8 Los pe ht c Apa les han so thy sne ges f in ; le s s; ter tha s ad es t r gy ;w ; tir ; gl ithd edn oom raw al ; es s y 55.6 54.4 Los in d ; la so iffe s si fe ren tud Los ner c e; e 43.3 so gy; lo n f lib l os eli n ido so ess ; lo f dr 36 ss i ve Anx of s ; bu io u ex rnt ou s; a d ri v e; i t 29.8 g ita mp ted Te ote ; irr ars Som Fe i tab ;w nce atic eli n l e; eep ; ve gw res ing get orth tl es ; cr yi n ativ es l es s; g s, t ens g ym uil t e; s pt o y; l t re ms ac k s se ;m of s d ala 26.2 25.6 25.2 Sui i se el f Los ci d ;m est ee m so e th ulti f co ou ple 23.8 nc e ght con ntr a s; t s ul tio n hou ta t ion ght s 24 Dim ; po of s or el f ini s me inj u hed mo ry per ry , f or poo ma r th nce i nk Em ; in i ng 21.4 21.2 Los otio abi so na li ty f af l la to Be fec bil i cop h av Los so t; f lat ty ; mo e i ou fe a ff od ral njo ect sw pro ym ; lo ing bl e ms ent ss s 13.9 12.8 or of e ; ag pl e mo gr e as u tion ss iv re ; 9.5 ene lac Pe s s; ko s si be f hu mi s hav mo m; i ou r 7.2 ne ral gat c ha Ps iv e yc h atti nge s 7 App om tud ear oto es , anc r re wo e; tar r ry ing 7 spe dat ec h i on ; sl ; ex He ada ow ces nes si v c he s 5.9 He es s; d av y mi l iz zi i ng nes us e ; va s 4.8 of a gue l co nes De hol s, e l us , to tc . i on bac 4.1 Re s; h co ac t all u or ion ci n dru to p atio gs 2.6 r ob ns; abl c on Fa ec fus mil aus ion yo es 1.8 r pa or life looking for depression st h eve i sto ry n ts 1.8 Ob of d ses epr si ve es s i de i on 1.3 ati o n; p ho bia Comment: Slide illustrates which s symptoms are asked about by GPS 0.9 Per Lac i od ko f in of l s ig ife ht 0.4 (me no p aus e) 0.4
  • 38. Effect of Prevalence
  • 39. 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 0.4 0.3 Baseline Probability Depression+ 0.2 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
  • 40. 1 Post-test Probability 0.9 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
  • 41. Effect of Severity
  • 42. 1.00 Post-test Probability 0.90 Comment: Slide illustrates GP diagnosis of depression is more successful than their diagnosis of milder “distress” 0.80 0.70 0.60 0.50 0.40 Distress+ 0.30 Distress- Baseline Probability 0.20 Depression+ Depression- 0.10 Pre-test Probability 0.00 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
  • 43. GPs vs Oncologists vs Nurses Who is better? Bayesian analysis
  • 44. 1.00 Post-test Probability GP+ GP- 0.90 Baseline Probability Nurse+ Nurse- 0.80 Oncologist+ Oncologists- 0.70 0.60 0.50 0.40 0.30 0.20 0.10 Pre-test Probability 0.00 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
  • 45. Clinical Questions Evidence What are the symptoms of depression? Are we looking for depression? If we look, do we detect depression? What tools are available? Do the tools really make a difference? What about acceptability (Ultra-Short Screening)‫‏‬ Depression in medical settings - special? Depression in late-life – special? Implementation of screening - how
  • 46. 20 Instruments for Depression Ultra-short <6 Short > 5 < 11 Long > 10 PHQ1 HADS (7)‫‏‬ HAM-D (21)‫‏‬ PHQ2 (2)‫‏‬ BDI (7)‫‏‬ BDI (21,13)‫‏‬ WHO-5 (5)‫‏‬ MOS-D (8)‫‏‬ BSI (53)‫‏‬ Distress Therm (1)‫‏‬ PHQ9 (9)‫‏‬ CES-D (20,10)‫‏‬ DSMIV (9)‫‏‬ Zung (20)‫‏‬ MADRAS (10)‫‏‬ GDS (30,15)‫‏‬ EPDS (10)‫‏‬ SDS (20)‫‏‬ DADS (7)‫‏‬ DEPS (10)‫‏‬
  • 47. Severity1 IDS-C30 IDS-SR30 QIDS-C16 QIDS-SR16 HRSD17 HRSD21 HRSD24 MADRS BDI Addition: Comparison of Scale Scores 0 (None)‫‏‬ 0 0-3 4-5 0–3 4–5 0 1 0 1 0 1–2 0–1 2 0–1 2 0 0 0 6 6 2 2 3 3 3–4 0 7-8 7–8 3 3 4 4 5 0 9-10 9–11 4 4 5–6 5–6 6–7 0 11 12–13 5 5 7 7–8 8–9 6 9 1 (Mild)‫‏‬ 12-15 14–16 6 6 8 9 10–11 7 10 1 16-17 17–18 7 7 9–10 10 12 1 18-20 19–21 8 8 11 11–12 13–14 1 21-22 22–23 9 9 12 13 15–16 1 23 24–25 10 10 13 14–15 17–18 19 18 2 (Moderate)‫‏‬ 24-27 26–28 11 11 14–15 16 19 20 19 2 28-29 29–30 12 12 16 17 20–21 2 30-32 31–33 13 13 17 18–19 22–23 2 33-35 34–36 14 14 18–19 20–21 24–25 2 36 37–38 15 15 18–19 22 26 34 29 3 (severe)‫‏‬ 37-39 39–40 16 16 20 23 27–28 35 30 3 40-41 41–43 17 17 21–22 24–25 29–30 3 42-43 44–45 18 18 23 26 31–32 3 44-45 46–47 19 19 24 27 33 3 46 48 20 20 25 28 34 4 (v Severe)‫‏‬ 47-51 49–53 21 21 26–27 29–31 35–38 4 52-53 54–55 22 22 28 32 39 4 54-56 56–58 23 23 29 33–34 40–41 4 57-59 59–61 24 24 30–31 35–36 42–44 4 60-62 62–24 25 25 32 37–38 45–46 4 63-65 65–67 26 26 33–35 39–41 47–49
  • 48. => Symptoms
  • 49. Clinical Questions Evidence What are the symptoms of depression? Are we looking for depression? If we look, do we detect depression? What tools are available? Do the tools really make a difference? What about acceptability (Ultra-Short Screening)‫‏‬ Depression in medical settings - special? Depression in late-life – special? Implementation of screening - how
  • 50. Screening Evidence - Yes USPSTF good evidence that screening improves the accurate identification of depressed patients in primary care settings and that treatment of depressed adults identified in primary care settings decreases clinical morbidity. Small benefits have been observed in studies that simply feed back screening results to clinicians. Larger benefits have been observed in studies in which the communication of screening results is coordinated with effective follow-up and treatment. Pignone, M. P., Gaynes, B. N., Rushton, J. L., et al (2002) Screening for depression in adults: a summary of the evidence for the U.S. Preventive Services Task Force. Annals of Internal Medicine, 136, 765-776. => Gilbody
  • 51. Screening Evidence - No Gilbody, S. M., House, A. O. & Sheldon, T. A. (2001) Routinely administered questionnaires for depression and anxiety: systematic review. BMJ, 322 (7283), 406-409. => NICE
  • 52. Do Tools Work? Clinician rate vs tool rate (both against SCID)‫‏‬ Clinician with vs without tool Tool vs SCID
  • 53. 1.00 Comment: Slide illustrates Bayesian Post-test Probability curve comparison from indirect studies of clinician and HADS 0.90 This illustrates POTENTIAL gain from screening 0.80 0.70 0.60 0.50 0.40 Clinician Positive (Fallowfield et al, 2001) 0.30 Clinician Negative (Fallowfield et al, 2001) Baseline Probability 0.20 HADS-D Positive (Mata-analysis) HADS-D Negative (Meta-analysis) 0.10 Pre-test Probability 0.00 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
  • 54. Comment: Slide illustrates actual gain in meta-analysis of screening implementation in primary care
  • 55. 1.00 Post-test Probability Clinical+ Clinical- 0.90 Baseline Probability Screen+ Screen- 0.80 0.70 0.60 0.50 0.40 Comment: Slide illustrates Bayesian 0.30 curve comparison from RCT studies of clinician with and without screening 0.20 This illustrates ACTUAL gain from screening 0.10 Pre-test Probability 0.00 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
  • 56. HADS Validity vs Structured Interview METHODS Against depression 9x studies of the HADS-D; 5x of the HADS-T and 2x of the HADS-A were identified. RESULTS HADS-T = HADS-D = HADS-A The clinical utility index (UI+, UI-) was 0.214 and 0.789 for the HADS-D. Sensitivity Specificity PPV NPV FC HADS-D 51.4% 86.9% 41.6% 90.8% 81.4% HADS-A 82.4% 81.7% 35.9% 97.4% 81.8% HADS-T 77.7% 84.3% 44.5% 95.9% 83.4%
  • 57. 1.00 Comment: Slide illustrates Bayesian Post-test Probability curve comparison of HADS in detection of depression in cancer settings. 0.90 Against expectations HADS-A was most successful 0.80 0.70 0.60 0.50 0.40 HADS-T Positive (N=5) HADS-T Negative (N=5) 0.30 Baseline Probability HADS-A Positive (N=2) HADS-A Negative (N=2) 0.20 HADS-D Positive (N=9) HADS-D Negative (N=9) 0.10 Pre-test Probability 0.00 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
  • 58. Clinical Questions Evidence What are the symptoms of depression? Are we looking for depression? If we look, do we detect depression? What tools are available? Do the tools really make a difference? What about acceptability (Ultra-Short Screening)‫‏‬ Depression in medical settings - special? Depression in late-life – special? Implementation of screening - how
  • 59. Test Duration Ultra-short screening tools were defined as those with 1-4 items taking less than 2 minutes to complete. Short screening tools were defined as those with 5-14 items, taking between 2 and five minutes to complete. Standard screening tools were defined as those with 15 or more items, taking more than five minutes to complete. => Tools table
  • 60. NICE Screening: How? Step 1: Recognition • Use two screening questions, such as: – “During the last month, have you often been bothered by feeling down, depressed or hopeless?” – “During the last month, have you often been bothered by having little interest or pleasure in doing things?”
  • 61. Distribution of DT Scores Ransom (2006) PO (n=491) 18.0 15.7 16.0 14.7 13.8 14.0 13.2 12.0 10.4 10.0 8.4 7.7 8.0 7.3 6.0 3.7 4.0 3.3 1.8 2.0 0.0 Score 0 Score 1 Score 2 Score 3 Score 4 Score 5 Score 6 Score 7 Score 8 Score 9 Score 10 Gessler, Lowe Psycho-oncology (in press 2008)‫‏‬
  • 62. SCAN, SCID, PSE, CIDI, MINI LONG BDI, MADRAS, Hamilton High NPV MEDIUM High PPV SHORT High NPV HADS, EPDS, PHQ9, CES-D Med PPV High NPV PHQ2, NICE, DT Low PPV
  • 63. Clinical Questions Evidence What are the symptoms of depression? Are we looking for depression? If we look, do we detect depression? What tools are available? Do the tools really make a difference? What about acceptability (Ultra-Short Screening)‫‏‬ Depression in medical settings - special? Depression in late-life – special? Implementation of screening - how
  • 64. 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
  • 65. Somatic Bias in Mood Scales
  • 66. Comment: Slide illustrates concept of phenomenology of depressions in medical disease Primary Depression Medically Unwell Secondary Depression
  • 67. Study: Coyne Thombs Mitchell N= 1200 – 4500 Pooled database study All comparative studies
  • 68. A gi ta tio n (C A om 0 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 gi or ta bi tio d) n A (P nx ri m ie ty ar (C y) om * A or nx bi ie d) A ty pp (P et ri m it e ar (C y) om C A pp or * n=4069 vs 4982 on et bi ce it e d) nt (P ra ri tio m C n ar on (C y) ce om nt or ra bi tio n d) Fa (P t ig rim ue ar y) (C om Fa or t ig bi ue d) (P G ri ui m lt ar (C y) om * H or op el G bi es ui d) lt sn (P es ri H s m op (C ar el om y) es * sn or bi es d) In s so (P ri m m ni ar a y) (C In om * so or Lo m bi 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 ri m oo ar d y) (C Lo om w * M or R oo bi d) et d ar da (P ri m 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 *
  • 69. A nx ie ty (C om 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 A or C nx bi on ie d) ce ty nt (M ra ed tio ic C n al on (C ) om * ce nt or ra bi tio d) n (M Fa ed t ig ic ue al (C ) * om or H Fa bi n= 4069 vs 1217 op t ig d) el ue es sn (M es ed H s ic al op (C ) In om * so el es or m sn bi ni d) a es (a s ny (M In ty ed so pe ic m )( al ) ni C a om * (a ny or ty bi Lo pe d) ss )( In M te ed r es ic al Lo t( C ) om * ss In or te bi r es d) Lo t( w M M ed ic oo al d ) (C om * Lo w or M bi d) R oo et d ar (M da ed t io ic n al ) (C R * et om ar or da bi t io d) n (M Su ed ic ic id e al ) (C * om Su or bi W ic id d) ei gh e (M t Lo ed ss ic al W (C ) om * ei gh or W t bi or Lo d) th ss le (M ss ne ed ss ic W (C al ) or th om le or ss bi ne d ) ss symptoms profile in comorbid (M ed ic Medical Illness Alone al ) Com orbid Depression Comment: Slide illustrates distinct depression vs medical illness alone Co-morbid Depression vs Medical Illness Alone
  • 70. Comment: Slide illustrates actual phenomenology of depressions in medical disease Primary Depression Secondary Depression Medically Unwell
  • 71. Clinical Questions Evidence What are the symptoms of depression? Are we looking for depression? If we look, do we detect depression? What tools are available? Do the tools really make a difference? What about acceptability (Ultra-Short Screening)‫‏‬ Depression in medical settings - special? Depression in late-life – special? Implementation of screening - how
  • 72. Are Certain Symptoms Common in Older People
  • 73. -0.25 -0.2 -0.15 -0.1 -0.05 0 0.05 0.1 Helplessness Ho pelessness Worthlessn ess An xiety (Som atic anxiety) Ang er Indecisiveness Thou ghts of Death Dim inished Con centration Anxiety (Com b in ed ) Increased Appetite Sleep Disturb ance (Hyp ersom n ia) Sleep Distu rbance (Co m bined) Increased Weight Loss of Energy More common in early-life depression More common in late-life depression Psychom otor Agitatio n An xiety (Psychic anxiety) Excessive G u ilt Dim in ished Interest mid-life depression Sleep Disturban ce (Insom nia) Decreased Appetite Comment: Slide illustrates simple Depressed Mo od frequency of symptoms in late life vs Psych om oto r Retardation Decreased Weight
  • 74. Accuracy - Comparative Depression Depression PRESENT ABSENT Younger % % Accuracy Y Older % % Accuracy O Accuracy Old vs Young
  • 75. A 0.000 0.100 0.200 0.300 0.400 0.500 0.600 0.700 0.800 nx ie A A ty ng nx (C er ie om ty (P bi ne A sy d) nx ch ie ic ty an (S xi om et >64 >59 >54 <55 at y) D ic ec an re xi as et ed y) A D pp ec et re ite as ed D W D ep ei im re gh in ss t is ed he M d C oo on d ce D nt im ra in tio is n he d * In te * Ex re ce st ss iv e G H ui el lt pl es sn H es op s el In es cr sn ea es se s d Ap In pe cr tit ea e se d W In ei de gh ci t si ve ne Lo ss Ps ss yc of ho E Ps m ne ot rg yc or y ho A Sl m gi * ee ta p ot tio D or n Sl is R ee tu et p rb ar D an da is ce tio tu n rb (C an om Sl ce bi ee (H ne p D yp d) is er tu so rb m an ni ce a) (In so Th m ou ni gh a) ts of symptoms in late life vs mid-life of W D ea or th th * le depression – few have special significance ss * Comment: Slide illustrates diagnostic value ne ss * * *
  • 76. Clinicians Detection Is it Influenced by differences?
  • 77. 1.00 Post-test Probability Routine Case-Finding Late-Life Routine Exclusion Late-life 0.90 Baseline Probability Routine Case-Finding Mixed Routine Exclusion Mixed 0.80 Routine Case-Finding Younger Routine Exclusion Younger 0.70 0.60 0.50 0.40 0.30 0.20 0.10 Pre-test Probability 0.00 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Comment: Slide illustrates detection of late life vs mid-life depression in primary care – GPs are least successful with late-life depression
  • 78. Clinical Questions Evidence What are the symptoms of depression? Are we looking for depression? If we look, do we detect depression? What tools are available? Do the tools really make a difference? What about acceptability (Ultra-Short Screening)‫‏‬ Depression in medical settings - special? Depression in late-life – special? Implementation of screening - how
  • 79. FURTHER READING: Screening for Depression in Clinical Practice An Evidence-Based guide Alex J Mitchell & James C Coyne ISBN13: 9780195380194ISBN10: 0195380193 Paperback, 416 pages Nov 2009 Price:$49.95 / £39.99

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