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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.

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

    • IX Congresso Portugues de Psico-Oncologia IX Congresso Portugues de Psico-Oncologia How do investigations inform clinical practice? How do investigations inform clinical practice? Alex Mitchell www.psycho-oncology.info Department of Cancer & Molecular Medicine, Leicester Royal Infirmary Department of Liaison Psychiatry, Leicester General Hospital Portugal 2010 Portugal 2010
    • T1. Background Survivorship Treatment rates
    • 10.9million incident cases (1mi breast, lung colorectal); 25mi prevalent cases
    • M 0 10 20 30 40 50 60 70 80 90 100 el an om Br a ea st (fe m al e) U rin ar y bl ad de r Pr os ta te C ol on Al ls i te 5 Year Survival in US Cancers s N R on ec -H tu od m gk in lym ph om a O va ry Le uk Lu em ng ia Change an d 1996-2004 1984-1986 1975-1977 br on ch us Pa nc re as
    • Suicidal 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%
    • % 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 ca m l e a 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
    • % Receiving Any treatment for Mental Health 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 40 34.6 35 32.7 Cancer n=4878 No Cancer n=90,737 30 25 19.1 20 16.1 14 15 11.7 11 8.9 10 7.7 7.2 6.5 5.7 5.7 5 6.3 6.4 6.2 5 5 3.9 3.2 2.3 1.8 0 l th th ons n ns ns nt s 75+ rs rs rs diti o eal Hea diti o diti o y ea y ea y ea atie d iti Il l H con l Il l con con con 44 64 74 P l Al l n ta nt a 18- 45- 65- l di ca cal l l di ca di ca Me Me edi me me me No cm nic nic nic o ni hro hro hro c hr 1c 2c 3c No
    • Q. Why Low Treatment Rates? Clinicians? Patients?
    • 94.2% 37.4% 8 yrs N= 9282 NCS‐R
    • Comment: Frequency of cancer specialists n=226 enquiry about depression/distress from Mitchell et al (2008)
    • 100.0 5.9 11.1 14.3 90.0 Comment: Slide illustrates diagnostic 21.4 accuracy according to score on DT 11.8 25.9 80.0 38.7 38.1 43.5 22.2 14.3 46.7 70.0 59.6 21.4 72.4 60.0 Judgement = Non-distressed 33.3 Judgement = Unclear 19.4 19.0 Judgement = Distressed 50.0 26.1 24.4 82.4 40.0 71.4 66.7 30.0 25.0 57.1 41.9 42.9 40.7 20.0 15.8 30.4 28.9 10.0 15.4 11.8 0.0 Zero One Two Three Four Five Six Seven Eight Nine Ten
    • 0.05 0.15 0.25 0 0.1 0.2 0.3 Ei gh t N in e Te n El ev en Tw el ve Th irt ee HADS-D 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
    • Testing 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
    • Low confidence = more cautious, fewer false positives, more false negatives p180 1.00 Post-test Probability 0.90 0.80 0.70 0.60 Ave Confidence+ 0.50 Ave Confidence- 0.40 Baseline Probability Above Ave Confidence+ 0.30 Above Ave Confidence- High Confidence+ 0.20 High Confidence- 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 High confidence = less cautious, more false positives, low false negatives
    • 1093 (100%) Population 462 needs 462 (42%) 322 DSMIV Meetable Needs 17.3% 25% 388 (84%) Aware of Need 172 (44%) Requested Help 80 (47%) Needs Met
    • Can tools (investigations) help?
    • Q. How Common is the Problem? Depression Distress Anxiety
    • Symptoms Clinical Significance Duration ICD-10 Depressive Episode Requires two of the first three At least some difficulty in 2 weeks unless symptoms are symptoms (depressed mood, loss of continuing with ordinary work unusually severe or of rapid interest in everyday activities, and social activities onset). reduction in energy) plus at least two of the remaining seven symptoms (minimum of four symptoms) DSM-IV Major Depressive Disorder Requires five or more out of nine These symptoms cause 2 weeks symptoms with at least at least one clinically important distress OR from the first two (depressed mood impair work, social or personal and loss of interest). functioning. DSM-IV Minor Depressive Disorder Requires two to four out of nine These symptoms cause 2 weeks symptoms with at least at least one clinically important distress OR from the first two (depressed mood impair work, social or personal and loss of interest). functioning. DSM-IV Adjustment disorder Requires the development of These symptoms cause marked Acute: if the disturbance lasts emotional or behavioral symptoms in distress that is in excess of less than 6 months response to an identifiable stressor(s) what would be expected from Chronic: if the disturbance occurring within 3 months of the exposure to the stressor OR lasts for 6 months onset of the stressor(s). Once the significant impairment in social stressor has terminated, the or occupational (academic) symptoms do not persist for more functioning than an additional 6 months. DSM-IV Dysthymic disorder Requires persistently low mood two The symptoms cause clinically Requires depressed mood for (or more) of the following six significant distress OR most of the day, for most days symptoms: impairment in social, (by subjective account or (1) poor appetite or overeating occupational, or other observation) for at least 2 years (2) Insomnia or hypersomnia important areas of functioning. (3) low energy or fatigue (4) low self-esteem (5) poor concentration or difficulty making decisions (6) feelings of hopelessness
    • 48% Adjustment Disorder N=10 57% 38% 20% 18% 13% Anxiety N=4 Depression N=11 Comment: Slide illustrates meta-analytic rates of mood disorder
    • Prevalence of depression in Palliative settings 20 studies involving 2655 individuals 16.9% (95% CI = 13.2% to 21.0%) Proportion meta-analysis plot [random effects] 13.0% (95% CI = 11.6% to 14.5%) for MDD Lloyd-Williams et al (2007) 0.30 (0.24, 0.36) Jen et al (2006) 0.27 (0.19, 0.36) Lloyd-Williams et al (2003) 0.27 (0.17, 0.39) Payne et al (2007) 0.26 (0.19, 0.33) Desai et al (1999) [late] 0.25 (0.10, 0.47) Hopwood et al (1991) 0.25 (0.16, 0.36) Lloyd-Williams et al (2001) 0.22 (0.14, 0.31) Minagawa et al (1996) 0.20 (0.11, 0.34) Meyer et al (2003) 0.20 (0.10, 0.35) Breitbart et al (2000) 0.18 (0.11, 0.28) Le Fevre et al (1999) 0.18 (0.10, 0.28) Chochinov et al (1994) 0.17 (0.11, 0.24) Kelly et al (2004) 0.14 (0.06, 0.26) Wilson et al (2007) 0.13 (0.10, 0.17) Chochinov et al (1997) 0.12 (0.08, 0.18) Wilson et al (2004) 0.12 (0.05, 0.22) Love et al (2004) 0.07 (0.04, 0.11) Kadan-Lottich et al (2005) 0.07 (0.04, 0.11) Akechi et al (2004) 0.07 (0.04, 0.11) Maguire et al (1999) 0.05 (0.01, 0.14) combined 0.17 (0.13, 0.21) p572 0.0 0.2 0.4 0.6 proportion (95% confidence interval)
    • Prevalence of depression in Oncology settings Plumb & Holland (1981) Proportion meta-analysis plot [random effects] 0.7750 (0.6679, 0.8609) Levine et al (1978) 0.5600 (0.4572, 0.6592) Ciaramella and Poli (2001) 0.4900 (0.3886, 0.5920) Massie et al (1979) 0.4850 (0.4303, 0.5401) 57 studies involving 9195 individuals across 12 Bukberg et al (1984) Passik et al (2001) 0.4194 (0.2951, 0.5515) 0.4167 (0.2907, 0.5512) countries. Baile et al (1992) Morton et al (1984) Hall et al (1999) 0.4000 (0.2570, 0.5567) 0.3958 (0.2577, 0.5473) 0.3722 (0.3139, 0.4333) Burgess et al (2005) 0.3317 (0.2672, 0.4012) Jenkins et al (1991) 0.3182 (0.1386, 0.5487) The prevalence of depression was 17.3% (95% CI = Green et al (1998) 0.3125 (0.2417, 0.3904) Kathol et al (1990) 0.2961 (0.2248, 0.3754) Hosaka and Aoki (1996) 0.2800 (0.1623, 0.4249) 13.8% to 21.2%), Fallowfield et al (1990) Golden et al (1991) 0.2565 (0.2054, 0.3131) 0.2308 (0.1353, 0.3519) Spiegel et al (1984) 0.2292 (0.1495, 0.3261) Evans et al (1986) 0.2289 (0.1438, 0.3342) Grandi et al (1987) 0.2222 (0.0641, 0.4764) Maunsell et al (1992) 0.2146 (0.1605, 0.2772) Berard et al (1998) 0.2100 (0.1349, 0.3029) Joffe et al (1986) 0.1905 (0.0545, 0.4191) 13.0% (95% CI = 11.6% to 14.5%) for MDD Berard et al (1998) Devlen et al (1987) 0.1900 (0.1184, 0.2807) 0.1889 (0.1141, 0.2851) Leopold et al (1998) 0.1887 (0.0944, 0.3197) Akizuki et al (2005) 0.1797 (0.1376, 0.2283) Razavi et al (1990) 0.1667 (0.1189, 0.2241) Gandubert et al (2009) 0.1597 (0.1040, 0.2300) Alexander et al (1993) 0.1333 (0.0594, 0.2459) Kugaya et al (1998) 0.1328 (0.0793, 0.2041) Payne et al (1999) 0.1290 (0.0363, 0.2983) Ibbotson et al (1994) 0.1242 (0.0776, 0.1853) Prieto et al (2002) 0.1227 (0.0825, 0.1735) Morasso et al (1996) 0.1121 (0.0593, 0.1877) Desai et al (1999) [early] 0.1111 (0.0371, 0.2405) Silberfarb et al (1980) 0.1027 (0.0587, 0.1638) Costantini et al (1999) 0.0985 (0.0535, 0.1625) Morasso et al (2001) 0.0985 (0.0535, 0.1625) Ozalp et al (2008) 0.0971 (0.0576, 0.1510) Love et al (2002) 0.0957 (0.0650, 0.1346) Alexander et al (2010) 0.0900 (0.0542, 0.1385) Coyne et al (2004) 0.0885 (0.0433, 0.1567) Kawase et al (2006) 0.0851 (0.0553, 0.1240) Walker et al (2007) 0.0831 (0.0568, 0.1165) Grassi et al (1993) 0.0828 (0.0448, 0.1374) Grassi et al (2009) 0.0826 (0.0385, 0.1510) Reuter and Hart (2001) 0.0761 (0.0422, 0.1244) Lee et al (1992) 0.0660 (0.0356, 0.1102) Pasacreta et al (1997) 0.0633 (0.0209, 0.1416) Sneeuw et al (1994) 0.0540 (0.0367, 0.0761) Singer et al (2008) 0.0519 (0.0300, 0.0830) Katz et al (2004) 0.0500 (0.0104, 0.1392) Mehnert et al (2007) 0.0472 (0.0175, 0.1000) Lansky et al (1985) 0.0455 (0.0291, 0.0676) Derogatis et al (1983) 0.0372 (0.0162, 0.0720) Hardman et al (1989) 0.0317 (0.0087, 0.0793) Massie and Holland (1987) 0.0147 (0.0063, 0.0287) p572 Colon et al (1991) combined 0.0100 (0.0003, 0.0545) 0.1730 (0.1375, 0.2116) 0.0 0.3 0.6 0.9 proportion (95% confidence interval)
    • Distress Thermometer
    • Distress Thermometer – Pooled Table Ransom Tuinman Mitchell Lord Hoffman Gessler Clover Jacobsen Proporti Score 2006 2008 2009 2010 2004 2009 2009 2005 Sum 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%
    • Proportion 20.0% Insignificant Minim al Mild Moderate Severe 18.0% 16.0% 14.0% 12.0% 10.0% 18 .4 % 8.0% 12 .9 % 6.0% 12 .3 % 11.9 % 11.2 % p124 4.0% 8 .1% 7.7% 7.2 % 5.0 % 2.0% 2 .8 % 2 .6 % 0.0% Zero One Tw o Three Four Five Six Seven Eight Nine Ten 50%
    • ET - Table of Cut-Points Distress Anxiety Depression Anger Help Thermometer thermometer Thermometer Thermometer 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
    • DepT DT 23% 37% 4% 3% 3% DT DepT 7% 1% Non-Nil 8% 0% Nil 9% 59% 41% 4% 1% AnxT 2% AngT 15% 2% AnxT AngT 47% 18%
    • Q. Investigations => Screening What is available?
    • General Physical Trained Self-Report Confident Skilled Clinician Alone Signs of DS 6 Depression DISCS Observation Screening Visual CDSS#10 VA-SES SMILEY ET/DT YALE Interview HAMD-D 17 MADRAS 10
    • Comment: This is a reminder of the structure of the HADS scale, this version adapter for cancer.
    • HADS in Cancer Initial Search (n= 768) Review articles (n= 16) No data (n= 250) No reference standard (n= 293) Accuracy or Validity Analyses (n= 210) No interview standard (n=149) Inadequate Data (n=11) HADS Validity Analyses (n=50) Scale Sample Size Outcome Types (cases) Measure HADS-D Less than 30 Depression (n=14) (n=22) (n=22) HADS-T 30 to 100 Anxiety (n=26) (n=20) (n=4) HADS-A More than 100 Any Mental Ill Health (n=10) (n=8) (n=24)
    • Validity of HADS vs depression (DSMIV) SE 71.6% (68.3) SP 82.6% (85.7) Prev 13% PPV 38% NPV 95%
    • Depression_HADS-d (7v8) 1.00 Post-test Probability 0.90 0.80 0.70 0.60 0.50 HADS+ HADS- 0.40 Baseline Probability 0.30 HADS7v8+ 0.20 HADS7v8- 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
    • Q. Why only depression / anxiety? ?
    • 1.00 0.90 0.80 Ten 0.70 Nine Eight 0.60 Seven Six 0.50 Five Four 0.40 Three Two 0.30 One 0.20 Zero Comment: Slide illustrates scores on ET 0.10 tool 0.00 Distress Anxiety Depression Anger Thermometer Thermometer Thermometer Thermometer
    • Vs DT DepT HADS-A AUC: DT=0.82 DepT=0.84 AnxT=0.87 AnxT AngT AngT=0.685
    • 6. How Valid Are the Tools
    • 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
    • Depression_HADS 1 Post-test Probability 0.9 0.8 0.7 0.6 Baseline Probability 0.5 HADSd+ 0.4 HADSd- HADS-T+ 0.3 HADS-T- HADS-A+ 0.2 HASD-A- 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
    • Depression_all 1.00 Post-test Probability 0.90 0.80 0.70 0.60 1Q+ 1Q- 0.50 Baseline Probability DT+ DT- 2Q+ 0.40 2Q- HADSd+ HADSd- HADS-T+ HADS-T- 0.30 BDI+ BDI- EPDS+ EPDS- HADS-A+ 0.20 HASD-A- 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
    • 1.00 Distress Post-test Probability 0.90 0.80 0.70 0.60 DT+ [N=4] 0.50 DT+ [N=4] Baseline Probability 1Q+ [N=4] 1Q- [N=4] 0.40 2Q+ 2Q- DT/IT+ DT/IT- 0.30 HADST+ [N=13] HADST+ [N=13] PDI+ 0.20 PDI- 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 Mitchell AJ. Short Screening Tools for Cancer Related Distress A Review and Diagnostic Validity Meta-analysis JNCI (2010) in press
    • Validity of DT vs depression (DSMIV) SE 80% SP 60% PPV 32% NPV 93%
    • DT 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
    • Q. Problem with somatic symptoms?
    • 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
    • Comment: Slide illustrates concept of phenomenology of depressions in medical disease Primary Depression Alone Fatigue Anorexia Insomnia Concentration Secondary Medically Unwell Alone Depression
    • Study: Coyne Thombs Mitchell N= 4500; Pooled database study; All comparative studies Physical illness+comorbid depression Vs Physical illness alone Vs Primary depression alone
    • A gi ta tio n (C A om 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 gi or ta bi tio d) n A (P nx rim ie ty ar (C y) om * A or nx bi ie d) A ty pp (P et rim it e ar (C y) om A * C 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 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 Co-morbid Depression vs Primary Depression 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 d) s (P rim ar y) Prim ary Depression Com orbid Depression *
    • A nx ie t y (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 r at ed io 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 i d) ei de gh (M t Lo ed ss ic al W (C ) om * ei gh or W t bi or Lo d) th Co-morbid Depression vs Medical Illness Alone 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
    • Comment: Slide illustrates concept of phenomenology of depressions in medical disease Primary Depression Alone Fatigue Anorexia Insomnia Concentration Secondary Medically Unwell Alone Depression
    • Comment: Slide illustrates actual phenomenology of depressions in medical disease Primary Depression Secondary Depression Weight loss Agitation Retardation Medically Unwell
    • Q. How to Choose A Cut-Off
    • British Journal of Cancer (2007) 96, 868 – 874
    • Distress Thermometer
    • Distress Thermometer – Pooled Proportion 20.0% Insignificant Minim al Mild Moderate Severe 18.0% 16.0% 14.0% 12.0% 10.0% 18 .4 % 8.0% 6.0% 12 .9 % 12 .3 % 11.9 % p124 11.2 % 4.0% 8 .1% 7.7% 7.2 % 5.0 % 2.0% 2 .8 % 2 .6 % 0.0% Zero One Tw o Three Four Five Six Seven Eight Nine Ten 50%
    • PHQ9 Linear distribution 35 30 PHQ9 (Major Depression) 25 PHQ9 (Minor Depression) PHQ9 (Non-Depressed) 20 15 10 5 0 ve n en n ro e e o ve n en n ur en en ne x t n gh ee Tw re Te ve n ee Si ee Ze Fo el Fi ev Ni te te O fte Th Ei nt Se Tw irt xt ur gh El Fi ve Th Si Fo Ei Se Baker-Glen, Mitchell et al (2008)
    • Sample 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”
    • Dysfunction in 531 cancer patients 60.0% 55.7% 50.0% 40.0% 34.3% 30.0% 20.0% 10.0% 7.3% 2.6% 0.0% Unimpaired Mild Moderate Severe
    • Unimpaired by DT Score 90.00% 80.00% 70.00% 60.00% 50.00% 40.00% 30.00% 20.00% 10.00% 0.00% 1 2 3 4 5 6 7 8 9 10 11
    • Of the 293 Non-Nil DepT 23% 0.3% DepT 3% 2% 18% Dysfunction Distress 28% 26% 22% Dysfunction Distress 76% 69%
    • DT distribution by Impairment 0.18 0.16 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0 0 1 2 3 4 5 6 7 8 9 10
    • 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
    • T4. Screening in Cancer: Implementation Clinician Opinion Patient Opinion
    • 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: “Ideal” method of eliciting symptoms of distress/depression according to clinician
    • Comment: Slide illustrates actual gain in meta-analysis of screening implementation in primary care
    • 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 in Study from Christensen 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
    • Leicester: Uptake T177 t680 800 Patients Approached 100 Not Willing (13%) 700 Patients Willing (87%) TAU 500 Staff Willing (71%) Screen Data 402 Data Collected (80%)
    • Pre-Post Screen - Distress Before After Sensitivity of 49.7% Specificity of 79.3% PPV was 67.3% NPV was 64.1%
    • Pre-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).
    • Qualitative 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
    • Next Step 269 Nurse-patient interactions Helped 65 (24%) Not Helped 204 (76%) Referred 23 (8.6%) Declined Helped 20 (7.4%) No Unmet Needs 34 (12.6%) Unmet Needs 150 (55.8%) p179
    • 2x2 Clinician Help Table : ACTUAL HELP Clinician thinks: Clinician thinks Unmet Needs no Unmet Needs Patient Says: Helped 21/35 Helped 11/23 Help Wanted (60) (60%) (48%) Patient Helped 65/102 Helped 31/62 Distressed (63%) (50%) Patient Not Helped 8/35 Helped 20/117 distressed or (23%) (17%) Help Not Wanted
    • b. Intervention and help PREDICTORS 1. patient desire for help 2. number of unmet needs 3. clinicians confidence 4. patient reported anger p179
    • RCT 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]
    • FURTHER READING: Screening for Depression in Clinical Practice An Evidence-Based guide ISBN 0195380193 Paperback, 416 pages Nov 2009 Price: £39.99