Keynote - How Do Investigations in Psycho-oncology Inform Clinical Practice? (Oct01

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This is the opening keynote lecture from the IX Congresso Portugues de Psico-Oncologia in Porto (Oporto) Portugal 22-oct-2010.

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Keynote - How Do Investigations in Psycho-oncology Inform Clinical Practice? (Oct01

  1. 1. Alex Mitchell www.psycho-oncology.info Department of Cancer & Molecular Medicine, Leicester Royal Infirmary Department of Liaison Psychiatry, Leicester General Hospital Portugal 2010Portugal 2010 IX Congresso Portugues de Psico-Oncologia How do investigations inform clinical practice? IX Congresso Portugues de Psico-Oncologia How do investigations inform clinical practice?
  2. 2. T1. BackgroundT1. Background Survivorship Treatment rates
  3. 3. 10.9million incident cases (1mi breast, lung colorectal); 25mi prevalent cases
  4. 4. 0 10 20 30 40 50 60 70 80 90 100 M elanom aBreast(fem ale)U rinary bladder Prostate C olon Allsites R ectum N on-H odgkin lym phom a O vary Leukem ia Lung and bronchus Pancreas 1975-1977 1984-1986 1996-2004 Change 5 Year Survival in US Cancers
  5. 5. Suicidal ThoughtsSuicidal Thoughts Studied 554 (411 BW 143 BSA). We measured suicidal thoughts : not at all 0; several days 1; more than half the days 2; nearly every day 3. We report here, the proportion of people with any suicidal thoughts (non zero scores). All = 8% Of major or minor depression. 22% had suicidal thoughts Of major depression 36% had suicidal thoughts (45% BW) Of those with distress 18.0%
  6. 6. % Receiving Any treatment for Depression% Receiving Any treatment for Depression 10.9 11.3 8.1 8.8 4.3 5.6 10.9 13.8 6.8 17.9 3.4 5.5 15.4 7.2 0 2 4 6 8 10 12 14 16 18 20 H igh Incom e B elgium France G erm any Israel Italy JapanN etherlandsN ew Zealand Spain U SALow Incom e C hina C olom biaSouth A frica U kraine Wang P et al (2007) Lancet 2007; 370: 841–50 n=84,850 face-to-face interviews
  7. 7. % Receiving Any treatment for Mental Health% Receiving Any treatment for Mental Health 7.2 34.6 5.7 6.3 6.4 11.7 19.1 14 8.9 3.9 3.2 5.7 32.7 5 5 7.7 11 16.1 6.5 6.2 2.3 1.8 0 5 10 15 20 25 30 35 40 AllPatients MentalIllHealth NoMentalIllHealth Nochronicmedicalconditions 1chronicmedicalcondition 2chronicmedicalconditions 3chronicmedicalconditions 18-44years 45-64years 65-74years 75+ Cancer n=4878 No Cancer n=90,737 Maria Hewitt, Julia H. Rowland Mental Health Service Use Among Adult Cancer Survivors: Analyses of the National Health Interview Survey Journal of Clinical Oncology, Vol 20, Issue 23 (December), 2002: 4581-4590
  8. 8. Q. Why Low Treatment Rates?Q. Why Low Treatment Rates? Clinicians? Patients?
  9. 9. 94.2% 37.4% 8 yrs N= 9282 NCS‐R
  10. 10. n=226 Comment: Frequency of cancer specialists enquiry about depression/distress from Mitchell et al (2008)
  11. 11. Comment: Slide illustrates diagnostic accuracy according to score on DT 11.8 15.4 30.4 28.9 41.9 42.9 40.7 57.1 82.4 66.7 71.4 15.8 25.0 26.1 24.4 19.4 19.0 33.3 21.4 11.8 22.2 14.3 72.4 59.6 43.5 46.7 38.7 38.1 25.9 21.4 5.9 11.1 14.3 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 Zero One Two Three Four Five Six Seven Eight Nine Ten Judgement = Non-distressed Judgement = Unclear Judgement = Distressed
  12. 12. 0 0.05 0.1 0.15 0.2 0.25 0.3 Eight N ine Ten Eleven Tw elve Thirteen Fourteen Fifteen Sixteen Seventeen Eighteen N ineteen Tw entyTw enty-one Proportion Missed Proportion Recognized HADS-D
  13. 13. Testing Clinicians: A Meta-AnalysisTesting Clinicians: A Meta-Analysis All cancer professionals SE =39.5% and SP =77.3%. Oncologists SE =38.1% and SP = 78.6%; a fraction correct of 65.4%. By comparison nurses SE = 73% and SP = 55.4%; FC = of 60.0%. When attempting to detect anxiety oncologists managed SE = 35.7%, SP = 89.0%, FC 81.3%. Presented at IPOS2009
  14. 14. 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Pre-test Probability Post-testProbability 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 p180
  15. 15. 462 (42%) Meetable Needs 1093 (100%) Population 388 (84%) Aware of Need 172 (44%) Requested Help 80 (47%) Needs Met 462 needs 17.3% 322 DSMIV 25%
  16. 16. Can tools (investigations) help?Can tools (investigations) help?
  17. 17. Q. How Common is the Problem?Q. How Common is the Problem? Depression Distress Anxiety
  18. 18. Requires depressed mood for most of the day, for most days (by subjective account or observation) for at least 2 years The symptoms cause clinically significant distress OR impairment in social, occupational, or other important areas of functioning. Requires persistently low mood two (or more) of the following six symptoms: (1) poor appetite or overeating (2) Insomnia or hypersomnia (3) low energy or fatigue (4) low self-esteem (5) poor concentration or difficulty making decisions (6) feelings of hopelessness DSM-IV Dysthymic disorder Acute: if the disturbance lasts less than 6 months Chronic: if the disturbance lasts for 6 months These symptoms cause marked distress that is in excess of what would be expected from exposure to the stressor OR significant impairment in social or occupational (academic) functioning Requires the development of emotional or behavioral symptoms in response to an identifiable stressor(s) occurring within 3 months of the onset of the stressor(s). Once the stressor has terminated, the symptoms do not persist for more than an additional 6 months. DSM-IV Adjustment disorder 2 weeksThese symptoms cause clinically important distress OR impair work, social or personal functioning. Requires two to four out of nine symptoms with at least at least one from the first two (depressed mood and loss of interest). DSM-IV Minor Depressive Disorder 2 weeksThese symptoms cause clinically important distress OR impair work, social or personal functioning. Requires five or more out of nine symptoms with at least at least one from the first two (depressed mood and loss of interest). DSM-IV Major Depressive Disorder 2 weeks unless symptoms are unusually severe or of rapid onset). At least some difficulty in continuing with ordinary work and social activities Requires two of the first three symptoms (depressed mood, loss of interest in everyday activities, reduction in energy) plus at least two of the remaining seven symptoms (minimum of four symptoms) ICD-10 Depressive Episode DurationClinical SignificanceSymptoms
  19. 19. Depression 13% 20% 57% 48% 38% 18% Anxiety Adjustment Disorder N=11 N=4 N=10 Comment: Slide illustrates meta-analytic rates of mood disorder
  20. 20. Prevalence of depression in Palliative settings 20 studies involving 2655 individuals 16.9% (95% CI = 13.2% to 21.0%) 13.0% (95% CI = 11.6% to 14.5%) for MDD p572 Proportion meta-analysis plot [random effects] 0.0 0.2 0.4 0.6 combined 0.17 (0.13, 0.21) Maguire et al (1999) 0.05 (0.01, 0.14) Akechi et al (2004) 0.07 (0.04, 0.11) Kadan-Lottich et al (2005) 0.07 (0.04, 0.11) Love et al (2004) 0.07 (0.04, 0.11) Wilson et al (2004) 0.12 (0.05, 0.22) Chochinov et al (1997) 0.12 (0.08, 0.18) Wilson et al (2007) 0.13 (0.10, 0.17) Kelly et al (2004) 0.14 (0.06, 0.26) Chochinov et al (1994) 0.17 (0.11, 0.24) Le Fevre et al (1999) 0.18 (0.10, 0.28) Breitbart et al (2000) 0.18 (0.11, 0.28) Meyer et al (2003) 0.20 (0.10, 0.35) Minagawa et al (1996) 0.20 (0.11, 0.34) Lloyd-Williams et al (2001) 0.22 (0.14, 0.31) Hopwood et al (1991) 0.25 (0.16, 0.36) Desai et al (1999) [late] 0.25 (0.10, 0.47) Payne et al (2007) 0.26 (0.19, 0.33) Lloyd-Williams et al (2003) 0.27 (0.17, 0.39) Jen et al (2006) 0.27 (0.19, 0.36) Lloyd-Williams et al (2007) 0.30 (0.24, 0.36) proportion (95% confidence interval)
  21. 21. Prevalence of depression in Oncology settings 57 studies involving 9195 individuals across 12 countries. The prevalence of depression was 17.3% (95% CI = 13.8% to 21.2%), 13.0% (95% CI = 11.6% to 14.5%) for MDD p572 Proportion meta-analysis plot [random effects] 0.0 0.3 0.6 0.9 combined 0.1730 (0.1375, 0.2116) Colon et al (1991) 0.0100 (0.0003, 0.0545) Massie and Holland (1987) 0.0147 (0.0063, 0.0287) Hardman et al (1989) 0.0317 (0.0087, 0.0793) Derogatis et al (1983) 0.0372 (0.0162, 0.0720) Lansky et al (1985) 0.0455 (0.0291, 0.0676) Mehnert et al (2007) 0.0472 (0.0175, 0.1000) Katz et al (2004) 0.0500 (0.0104, 0.1392) Singer et al (2008) 0.0519 (0.0300, 0.0830) Sneeuw et al (1994) 0.0540 (0.0367, 0.0761) Pasacreta et al (1997) 0.0633 (0.0209, 0.1416) Lee et al (1992) 0.0660 (0.0356, 0.1102) Reuter and Hart (2001) 0.0761 (0.0422, 0.1244) Grassi et al (2009) 0.0826 (0.0385, 0.1510) Grassi et al (1993) 0.0828 (0.0448, 0.1374) Walker et al (2007) 0.0831 (0.0568, 0.1165) Kawase et al (2006) 0.0851 (0.0553, 0.1240) Coyne et al (2004) 0.0885 (0.0433, 0.1567) Alexander et al (2010) 0.0900 (0.0542, 0.1385) Love et al (2002) 0.0957 (0.0650, 0.1346) Ozalp et al (2008) 0.0971 (0.0576, 0.1510) Morasso et al (2001) 0.0985 (0.0535, 0.1625) Costantini et al (1999) 0.0985 (0.0535, 0.1625) Silberfarb et al (1980) 0.1027 (0.0587, 0.1638) Desai et al (1999) [early] 0.1111 (0.0371, 0.2405) Morasso et al (1996) 0.1121 (0.0593, 0.1877) Prieto et al (2002) 0.1227 (0.0825, 0.1735) Ibbotson et al (1994) 0.1242 (0.0776, 0.1853) Payne et al (1999) 0.1290 (0.0363, 0.2983) Kugaya et al (1998) 0.1328 (0.0793, 0.2041) Alexander et al (1993) 0.1333 (0.0594, 0.2459) Gandubert et al (2009) 0.1597 (0.1040, 0.2300) Razavi et al (1990) 0.1667 (0.1189, 0.2241) Akizuki et al (2005) 0.1797 (0.1376, 0.2283) Leopold et al (1998) 0.1887 (0.0944, 0.3197) Devlen et al (1987) 0.1889 (0.1141, 0.2851) Berard et al (1998) 0.1900 (0.1184, 0.2807) Joffe et al (1986) 0.1905 (0.0545, 0.4191) Berard et al (1998) 0.2100 (0.1349, 0.3029) Maunsell et al (1992) 0.2146 (0.1605, 0.2772) Grandi et al (1987) 0.2222 (0.0641, 0.4764) Evans et al (1986) 0.2289 (0.1438, 0.3342) Spiegel et al (1984) 0.2292 (0.1495, 0.3261) Golden et al (1991) 0.2308 (0.1353, 0.3519) Fallowfield et al (1990) 0.2565 (0.2054, 0.3131) Hosaka and Aoki (1996) 0.2800 (0.1623, 0.4249) Kathol et al (1990) 0.2961 (0.2248, 0.3754) Green et al (1998) 0.3125 (0.2417, 0.3904) Jenkins et al (1991) 0.3182 (0.1386, 0.5487) Burgess et al (2005) 0.3317 (0.2672, 0.4012) Hall et al (1999) 0.3722 (0.3139, 0.4333) Morton et al (1984) 0.3958 (0.2577, 0.5473) Baile et al (1992) 0.4000 (0.2570, 0.5567) Passik et al (2001) 0.4167 (0.2907, 0.5512) Bukberg et al (1984) 0.4194 (0.2951, 0.5515) Massie et al (1979) 0.4850 (0.4303, 0.5401) Ciaramella and Poli (2001) 0.4900 (0.3886, 0.5920) Levine et al (1978) 0.5600 (0.4572, 0.6592) Plumb & Holland (1981) 0.7750 (0.6679, 0.8609) proportion (95% confidence interval)
  22. 22. Distress Thermometer
  23. 23. Distress Thermometer – Pooled Table Score Ransom 2006 Tuinman 2008 Mitchell 2009 Lord 2010 Hoffman 2004 Gessler 2009 Clover 2009 Jacobsen 2005 Sum Proporti on Zero 68 38 61 123 14 27 65 71 467 18.4% One 72 31 42 68 5 26 39 46 329 12.9% Two 77 22 35 44 5 18 30 54 285 11.2% Three 65 37 42 46 8 23 45 46 312 12.3% Four 51 29 29 30 8 7 21 31 206 8.1% Five 41 46 62 40 11 13 41 48 302 11.9% Six 38 32 23 28 2 16 26 31 196 7.7% Seven 36 21 23 38 2 15 32 16 183 7.2% Eight 18 12 18 29 6 9 19 15 126 5.0% Nine 16 5 8 14 3 3 13 9 71 2.8% Ten 9 4 7 20 4 0 9 13 66 2.6% Sum 491 277 350 480 68 157 340 380 2543 Proportion 19.3% 10.9% 13.8% 18.9% 2.7% 6.2% 13.4% 14.9%
  24. 24. Proportion 18 .4 % 12 .9 % 11.2 % 12 .3 % 8 .1% 11.9 % 5.0 % 2 .8 % 2 .6 % 7.7% 7.2 % 0.0% 2.0% 4.0% 6.0% 8.0% 10.0% 12.0% 14.0% 16.0% 18.0% 20.0% Zero One Two Three Four Five Six Seven Eight Nine Ten Insignificant SevereModerateMildMinimal p124 50%
  25. 25. ET - Table of Cut-PointsET - Table of Cut-Points Distress Thermometer Anxiety thermometer Depression Thermometer Anger Thermometer Help Thermometer Cut-point Insignificant 39.0 25.6 50.1 55.7 54.3 0,1 Minimal 20.1 22.5 18.3 13.6 15.4 2,3 Mild 16.9 16.5 12.2 10.5 12.2 4,5 Moderate 12.0 14.5 9.8 6.6 6.6 6,7 Severe 11.9 20.8 9.5 13.6 11.2 8,9,10 p130
  26. 26. 8% DT 37% DepT 23% AngT 18% AnxT 47% 4% 7% 1% 1% 9% 3% 0% 2% 4% 15% 3% 2% Nil 41% Non-Nil 59% DT AnxT AngT DepT
  27. 27. Q. Investigations => ScreeningQ. Investigations => Screening What is available?
  28. 28. Observation Interview Visual Self-Report Depression Screening DISCS VA-SES ET/DT HAMD-D 17 PhysicalGeneral Signs of DS 6 CDSS#10 MADRAS 10 Trained Confident Skilled Clinician Alone YALE SMILEY
  29. 29. Comment: This is a reminder of the structure of the HADS scale, this version adapter for cancer.
  30. 30. Inadequate Data (n=11) No data (n= 250) No reference standard (n= 293) Accuracy or Validity Analyses (n= 210) HADS Validity Analyses (n=50) HADS in Cancer Initial Search (n= 768) Scale Types Sample Size (cases) HADS-T (n=26) HADS-D (n=14) HADS-A (n=10) Less than 30 (n=22) More than 100 (n=8) 30 to 100 (n=20) Review articles (n= 16) Depression (n=22) Any Mental Ill Health (n=24) Anxiety (n=4) Outcome Measure No interview standard (n=149)
  31. 31. Validity of HADS vs depression (DSMIV)Validity of HADS vs depression (DSMIV) SE 71.6% (68.3) SP 82.6% (85.7) Prev 13% PPV 38% NPV 95%
  32. 32. 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Pre-test Probability Post-testProbability HADS+ HADS- Baseline Probability HADS7v8+ HADS7v8- Depression_HADS-d (7v8)
  33. 33. Q. Why only depression / anxiety?Q. Why only depression / anxiety? ?
  34. 34. 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 Distress Thermometer Anxiety Thermometer Depression Thermometer Anger Thermometer Ten Nine Eight Seven Six Five Four Three Two One Zero Comment: Slide illustrates scores on ET tool
  35. 35. DT DepTVs HADS-A AnxT AngT AUC: DT=0.82 DepT=0.84 AnxT=0.87 AngT=0.685
  36. 36. 6. How Valid Are the Tools6. How Valid Are the Tools
  37. 37. DT vs HADS-T Validity (n=660)DT vs HADS-T Validity (n=660) SE SP AUC CUT DT – 71.9% 78.4% 0.814 cut point >=4 AnxT – 75.7% 73.4% 0.821 cut point >=5 DepT – 77.6% 82.2% 0.855 cut point >=3 AngT – 77.5% 77.6% 0.823 cut point >=2 HelpT - 69.1% 80.8% 0.809 cut point >=3
  38. 38. 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Pre-test Probability Post-testProbability Baseline Probability HADSd+ HADSd- HADS-T+ HADS-T- HADS-A+ HASD-A- Depression_HADS
  39. 39. 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Pre-test Probability Post-testProbability 1Q+ 1Q- Baseline Probability DT+ DT- 2Q+ 2Q- HADSd+ HADSd- HADS-T+ HADS-T- BDI+ BDI- EPDS+ EPDS- HADS-A+ HASD-A- Depression_all
  40. 40. 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Pre-test Probability Post-testProbability DT+ [N=4] DT+ [N=4] Baseline Probability 1Q+ [N=4] 1Q- [N=4] 2Q+ 2Q- DT/IT+ DT/IT- HADST+ [N=13] HADST+ [N=13] PDI+ PDI- Mitchell AJ. Short Screening Tools for Cancer Related Distress A Review and Diagnostic Validity Meta-analysis JNCI (2010) in press Distress
  41. 41. Validity of DT vs depression (DSMIV)Validity of DT vs depression (DSMIV) SE 80% SP 60% PPV 32% NPV 93%
  42. 42. DT vs DSMIV DepressionDT vs DSMIV Depression SE SP PPV NPV DTma 80.9% 60.2% 32.8% 92.9% DTLeicesterBW 82.4% 68.6% 28.0% 98.3% DTLeicesterBSA 100% 59.6% 26.8% 100% BSA = British South Asian BW= British White
  43. 43. Q. Problem with somatic symptoms?Q. Problem with somatic symptoms?
  44. 44. 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
  45. 45. Medically Unwell Alone Primary Depression Alone Secondary Depression Comment: Slide illustrates concept of phenomenology of depressions in medical disease Fatigue Anorexia Insomnia Concentration
  46. 46. Study: Coyne Thombs Mitchell N= 4500; Pooled database study; All comparative studies Physical illness+comorbid depression Vs Physical illness alone Vs Primary depression alone
  47. 47. Co-morbid Depression vs Primary Depression 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 A gitation (C om orbid) A gitation (Prim ary) A nxiety (C om orbid) A nxiety (Prim ary) A ppetite (C om orbid) A ppetite (Prim ary) C oncentration (Com orbid) C oncentration (Prim ary) Fatigue (C om orbid) Fatigue (Prim ary) G uilt(C om orbid) G uilt(Prim ary) H opelessness (C om orbid) H opelessness (Prim ary) Insom nia (C om orbid) Insom nia (Prim ary) Loss Interest(C om orbid) Loss Interest(P rim ary) Low M ood (C om orbid) Low M ood (P rim ary) R etardation (C om orbid) R etardation (Prim ary) Suicide (C om orbid) Suicide (Prim ary) W eightLoss (C om orbid) W eightLoss (P rim ary) * * * * * * * * * Comorbid Depression Primary Depression n=4069 vs 4982 Comment: Slide illustrates similar symptoms profile in comorbid vs primary depression
  48. 48. Co-morbid Depression vs Medical Illness Alone n= 4069 vs 1217 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 A nxiety (C om orbid) A nxiety (M edical) C oncentration (Com orbid) C oncentration (M edical) Fatigue (C om orbid) Fatigue (M edical) H opelessness (C om orbid) H opelessness (M edical) Insom nia (any type)(C om orbid) Insom nia (any type)(M edical) Loss Interest(C om orbid) Loss Interest(M edical) Low M ood (C om orbid) Low M ood (M edical) R etardation (C om orbid) R etardation (M edical) Suicide (C om orbid) Suicide (M edical) W eightLoss (C om orbid) W eightLoss (M edical) W orthlessness (C om orbid) W orthlessness (M edical) Medical Illness Alone Comorbid Depression * * * * * * * * * Comment: Slide illustrates distinct symptoms profile in comorbid depression vs medical illness alone
  49. 49. Medically Unwell Alone Primary Depression Alone Secondary Depression Comment: Slide illustrates concept of phenomenology of depressions in medical disease Fatigue Anorexia Insomnia Concentration
  50. 50. Medically Unwell Primary Depression Secondary Depression Comment: Slide illustrates actual phenomenology of depressions in medical disease Weight loss Agitation Retardation
  51. 51. Q. How to Choose A Cut-OffQ. How to Choose A Cut-Off
  52. 52. British Journal of Cancer (2007) 96, 868 – 874
  53. 53. Distress Thermometer
  54. 54. Distress Thermometer – Pooled Proportion 18 .4 % 12 .9 % 11.2 % 12 .3 % 8 .1% 11.9 % 5.0 % 2 .8 % 2 .6 % 7.7% 7.2 % 0.0% 2.0% 4.0% 6.0% 8.0% 10.0% 12.0% 14.0% 16.0% 18.0% 20.0% Zero One Two Three Four Five Six Seven Eight Nine Ten Insignificant SevereModerateMildMinimal p124 50%
  55. 55. PHQ9 Linear distribution 0 5 10 15 20 25 30 35 Zero O ne Two Three Four Five Six Seven Eight Nine Ten Eleven Twelve Thirteen Fourteen Fifteen Sixteen Seventeen Eighteen PHQ9 (Major Depression) PHQ9 (Minor Depression) PHQ9 (Non-Depressed) Baker-Glen, Mitchell et al (2008)
  56. 56. SampleSample We analysed data collected from Leicester Cancer Centre from 2008-2010 involving 531 people approached by a research nurse and two therapeutic radiographers. We examined distress using the DT and daily function using the question: “How difficult have these problems made it for you to do your work, take care of things at home, or get along with other people?” “Not difficult at all =0; Somewhat Difficult =1; Very Difficult =2; and Extremely Difficult =3”
  57. 57. Dysfunction in 531 cancer patientsDysfunction in 531 cancer patients 55.7% 34.3% 7.3% 2.6% 0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% Unimpaired Mild Moderate Severe
  58. 58. Unimpaired by DT ScoreUnimpaired by DT Score 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% 1 2 3 4 5 6 7 8 9 10 11
  59. 59. 18% DepT 23% Distress 69% Dysfunction 76% 0.3% 3% 2% 26%28% 22% Of the 293 Non-Nil Dysfunction Distress DepT
  60. 60. DT distribution by ImpairmentDT distribution by Impairment 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0 1 2 3 4 5 6 7 8 9 10
  61. 61. Extreme and incapacitating Very Severe and very disabling Moderately Severe and disabling Moderate and quite disabling Moderate and somewhat disabling Mild-Moderate and slight disabling Mild but not particularly disabling Very mild and not disabling Minimal but bearable Minimal and not problematic None at all
  62. 62. T4. Screening in Cancer: ImplementationT4. Screening in Cancer: Implementation Clinician Opinion Patient Opinion
  63. 63. 1,2 or 3 Simple QQ 24% Clinical Skills Alone 20% ICD10/DSMIV 24% Short QQ 24% Long QQ 8% Algorithm 26% Short QQ 23% ICD10/DSMIV 0% Clinical Skills Alone 17% 1,2 or 3 Simple QQ 34% Cancer Staff Ideal Method (n=226) Psychiatrists Effective? Comment: “Ideal” method of eliciting symptoms of distress/depression according to clinician
  64. 64. Comment: Slide illustrates actual gain in meta-analysis of screening implementation in primary care
  65. 65. 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Pre-test Probability Post-testProbability Clinical+ Clinical- Baseline Probability Screen+ 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
  66. 66. 800 Patients Approached 100 Not Willing (13%) 700 Patients Willing (87%) 500 Staff Willing (71%)TAU 402 Data Collected (80%)Screen Data Leicester: UptakeLeicester: Uptake T177 t680
  67. 67. Pre-Post Screen - DistressPre-Post Screen - Distress Before After Sensitivity of 49.7% Specificity of 79.3% PPV was 67.3% NPV was 64.1%
  68. 68. Pre-Post Screen - DistressPre-Post Screen - Distress Before After Sensitivity of 49.7% 55.8% =>+5% Specificity of 79.3% 79.8% =>+1% PPV was 67.3% 70.9% =>+4% NPV was 64.1% 67.2% =>+3% There was a non-significant trend for improve detection sensitivity (Chi² = 1.12 P = 0.29).
  69. 69. Qualitative AspectsQualitative Aspects DISTRESS 43% of CNS reported the tool helped them talk with the patient about psychosocial issues esp in those with distress 28% said it helped inform their clinical judgement DEPRESSION 38% of occasions reported useful in improving communication. 28.6% useful for informing clinical judgement
  70. 70. Next StepNext Step 269 Nurse-patient interactions Helped 65 (24%) Not Helped 204 (76%) Unmet Needs 150 (55.8%) Referred 23 (8.6%) Declined Helped 20 (7.4%) No Unmet Needs 34 (12.6%) p179
  71. 71. 2x2 Clinician Help Table : ACTUAL HELP2x2 Clinician Help Table : ACTUAL HELP Clinician thinks: Unmet Needs Clinician thinks no Unmet Needs Patient Says: Help Wanted (60) Helped 21/35 (60%) Helped 11/23 (48%) Patient Distressed Helped 65/102 (63%) Helped 31/62 (50%) Patient Not distressed or Help Not Wanted Helped 8/35 (23%) Helped 20/117 (17%)
  72. 72. b. Intervention and helpb. Intervention and help PREDICTORS 1. patient desire for help 2. number of unmet needs 3. clinicians confidence 4. patient reported anger p179
  73. 73. RCT using DT Carlson et al 2010RCT using DT Carlson et al 2010 Screening for Distress in lung and breast cancer outpatients: A randomized controlled trial Linda Carlson Tom Baker Cancer Centre, University of Calgary 1) Minimal Screening: the Distress Thermometer (DT) [n=365] 2) Full Screening: DT, Problem Checklist, Psychological Screen for Cancer (PSSCAN) [n=391] a personalized report 3) Triage: Full screening plus optional personalized phone triage [378]
  74. 74. FURTHER READING: Screening for Depression in Clinical Practice An Evidence-Based guide ISBN 0195380193 Paperback, 416 pages Nov 2009 Price: £39.99

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