[Workshop] Implementation of screening (Oct10)

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Workshop from day 2 at the IX Congresso Portugues de Psico-Oncologia in Porto (Oporto) Portugal 21-Oct-2010.

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[Workshop] Implementation of screening (Oct10)

  1. 1. Alex Mitchell www.psycho-oncology.info/workshop Department of Cancer & Molecular Medicine, Leicester Royal Infirmary Department of Liaison Psychiatry, Leicester General Hospital IPOS 2010IPOS 2010 WORKSHOP Day 2 Implementation of Screening: Screening studies, Short methods, HADS and longer methods, implementation, future of screening WORKSHOP Day 2 Implementation of Screening: Screening studies, Short methods, HADS and longer methods, implementation, future of screening
  2. 2. Schedule Day 2Schedule Day 2 930-10.00 – Introduction to research task 1. design 2. evaluation 10.00-11.00 – T3 Screening in Cancer: Instruments & Validity Break 11.30 – 12.30 – Group work #2 Lunch 1.30-2.30 – T4 Screening in Cancer: Implementation and future Break 3.00 – 4.00 – Presentation of Research task
  3. 3. Group Work #2Group Work #2 930-10.00 – Introduction, groups and issues 10.00-11.00 – T1 Basic science of screening Break 11.30 – 12.30 – Group task #1 Lunch 1.30-2.30 – T2 Symptoms, Burden, Help, Needs in Cancer Break 3.00 – 4.00 – Evaluation of a screening paper
  4. 4. Group Work #2Group Work #2 Read paper in your group…….. 1.What is being tested? 2.What is the comparison? 3.Is the tool effective? 4.Is the tool acceptable? 5.Did the tool make a difference?
  5. 5. T1. Are We Looking for Distress?T1. Are We Looking for Distress? How Often What method?
  6. 6. n=226 Comment: Frequency of cancer specialists enquiry about depression/distress from Mitchell et al (2008)
  7. 7. 1,2 or 3 Simple QQ 15% Clinical Skills Alone 73% ICD10/DSMIV 0% Short QQ 3% Other/Uncertain 9% Other/Uncertain 2% Use a QQ 15% ICD10/DSMIV 13% Clinical Skills Alone 55% 1,2 or 3 Simple QQ 15% Cancer Staff Current Method (n=226) Psychiatrists Comment: Current preferred method of eliciting symptoms of distress/depression
  8. 8. 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
  9. 9. T2. Are We finding it?T2. Are We finding it? How successful are we (routinely)?
  10. 10. 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
  11. 11. 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 CHEMO+ CHEMO- Baseline Probability COMMU+ COMMU- Detection sensitivity = 50.6% Detection specificity = 79.4% Overall accuracy = 65.4%. Comment: Slide illustrates performance of chemotherapy vs community nurses in oncology T125 – Sat am
  12. 12. 0 10 20 30 40 50 60 70 80 90 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 GP Accuracy – Detection of Distress by GHQ ScoreGP Accuracy – Detection of Distress by GHQ Score McCall et al (2007) Primary Care Psychiatry - Recognition by Severity Comment: Slide illustrates raw number of people identified by severity on the GHQ. Although the % detection increases with severity, the absolute number decreased due to falling prevalence
  13. 13. 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
  14. 14. Testing Clinicians: A Meta-AnalysisTesting Clinicians: A Meta-Analysis Methods (currently unpublished) 12 studies reported in 7 publications. 2 studies examined detection of anxiety, 8 broadly defined depression (includes HADS-T) 3 strictly defined depression and 7 broadly defined distress. 9 studies involved medical staff and 2 studies nursing staff. Gold standard tools including GHQ60, GHQ12 HADS-T, HADS-D, Zung and SCID. The total sample size was 4786 (median 171).
  15. 15. 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
  16. 16. GPs vs Oncologists vs NursesGPs vs Oncologists vs Nurses Who is better? Bayesian analysis
  17. 17. 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 GP+ GP- Baseline Probability Nurse+ Nurse- Oncologist+ Oncologists- Comment: Doctors appear to be more successful at ruling-in or giving a diagnosis, nurses more successful at ruling out
  18. 18. 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
  19. 19. T3. Screening Tools in CancerT3. Screening Tools in Cancer Clinician Opinion Patient Opinion
  20. 20. 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
  21. 21. Clinicians Methods to Evaluate Depression Unassisted Clinician Conventional Scales Ultra-Short (<5) Short (5-10) Long (10+)Untrained Trained Routine Implementation Acceptability ? Accuracy? Accuracy? vs Comment: schematic overview of methods to evaluate depression example
  22. 22. Clinicians Methods to Evaluate Depression Conventional Scales Short (5-10) Long (10+) HADS-D BDI example example
  23. 23. Comment: This is a reminder of the structure of the HADS scale, this version adapter for cancer.
  24. 24. HADS – Pros vs ConsHADS – Pros vs Cons ADVANTAGES DISADVANTAGES
  25. 25. HADS – Pros vs ConsHADS – Pros vs Cons ADVANTAGES Well known Short (7 items) Well tested Depression & anxiety covered Self-report DISADVANTAGES Can be too long Validation stats not good Which version? Distress, anger, needs not covered Scoring complex HADS-t not recommended Royalty fee
  26. 26. 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)
  27. 27. 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%
  28. 28. 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)
  29. 29. 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)
  30. 30. British Journal of Cancer (2007) 96, 868 – 874
  31. 31. 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
  32. 32. 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
  33. 33. 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
  34. 34. T4. How Valid Are the ToolsT4. How Valid Are the Tools
  35. 35. Validity of Methods to Evaluate Depression Unassisted Clinician Conventional Scales Ultra-Short (<5) Short (5-10) Long (10+)Untrained Trained
  36. 36. 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
  37. 37. 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
  38. 38. 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
  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 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
  40. 40. Validity of DT vs depression (DSMIV)Validity of DT vs depression (DSMIV) SE 80% SP 60% PPV 32% NPV 93%
  41. 41. 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
  42. 42. T5. How to Choose A Cut-OffT5. How to Choose A Cut-Off
  43. 43. Distress ThermometerDistress Thermometer
  44. 44. Distress Thermometer – Pooled TableDistress 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%
  45. 45. 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%
  46. 46. British Journal of Cancer (2007) 96, 868 – 874
  47. 47. 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”
  48. 48. 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
  49. 49. 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
  50. 50. 18% DepT 23% Distress 69% Dysfunction 76% 0.3% 3% 2% 26%28% 22% Of the 293 Non-Nil Dysfunction Distress DepT
  51. 51. Mean DT Scores?Mean DT Scores? Unimpaired Mild Moderate Severe Mean DT Score 2.1 4.1 5.9 6.5 Std Deviation 2.54 3.0 2.56 3.59 Sample Size 296 182 39 14 Simplified DT Range* 0-3 4-5 6-7 8-10
  52. 52. 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
  53. 53. Typically severely impared Typically mod impared Typically mildly impared Typically unimpared None at all
  54. 54. 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
  55. 55. Dt vs DysfunctionDt vs Dysfunction ROC plot from Book 1 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 Sensitivity 1-Specificity Distress Thermometer(+ve), M(-ve)
  56. 56. Optimal Cut to Define Distress on DTOptimal Cut to Define Distress on DT At a cut-off of 2v3 (>=3) Sensitivity =67.8%; PPV =60.3%; UI+ = 0.409 Specificity = 68.9%; NPV = 70.3%; UI- = 0.484 At a cut-off of 3v4 (>=4) Sensitivity =58.9%; PPV =65.6%; UI+ = 0.386 Specificity = 75.9%; NPV = 70.3%; UI- = 0.534 At a cut-off of 4v5 (>=5) Sensitivity =50.9%; PPV =67.85; UI+ = 0.345 Specificity = 81.1%; NPV = 67.9%; UI- = 0.55
  57. 57. T6. Screening in Cancer: ImplementationT6. Screening in Cancer: Implementation Clinician Opinion Patient Opinion
  58. 58. Comment: Slide illustrates actual gain in meta-analysis of screening implementation in primary care
  59. 59. Screen Routine vs At-Risk vs Identified Low High Follow-up Care ?? Desire for Help Meetable Unmet Needs
  60. 60. 800 Patients Approached 100 Not Willing (13%) 700 Patients Willing (87%) 500 Staff Willing (71%)TAU 402 Data Collected (80%)Screen Data Leicester: DT/ET ImplementationLeicester: DT/ET Implementation T177 t680
  61. 61. 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).
  62. 62. Qualitative Aspects: CommunicationQualitative Aspects: Communication 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
  63. 63. 2x2 Clinician Help Table : ACTUAL HELP2x2 Clinician Help Table : ACTUAL HELP Clinician thinks: Unmet Needs Clinician thinks no Unmet Needs Patient Says: Help Wanted => Intervention => Low grade Patient Distressed => Intervention =>?? Patient Not distressed or Help Not Wanted => Monitor? => discharge?
  64. 64. 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%)
  65. 65. 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
  66. 66. 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]
  67. 67. Advanced AspectsAdvanced Aspects Algorithms Structured interviews Computerized testing Item-banking Screening in subgroups p643 p454
  68. 68. T7. ExtrasT7. Extras Unfiled
  69. 69. Cancer Population CNS Assessment Possible case Depression Screen #1 +ve n = 200 No Depression Sp 55% Se 70% n = 800 N = 1000 TP = 140 FP = 360 Probable Non-Case TN =440 FN = 60 PPV 28% NPV 88% Screen #1 -ve Yield TP = 140 TN = 440 FN = 60 FP = 360 NPV 88% PPV 28% Sp 55% Se 70%
  70. 70. Cancer Population CNS Assessment Possible case Depression Screen #1 +ve n = 200 No Depression Sp 55% Se 70% n = 800 N = 1000 TP = 140 FP = 360 Probable Non-Case TN =440 FN = 60 PPV 28% Oncologist Assessment Sp 80% Sp 40% NPV 88% Probable Depression TP = 56 FP = 72 Probable Non-Case TN =288 FN = 84 PPV 44% NPV 77% Screen #1 -ve Screen #2 +ve Screen #2 +ve Cumulative Yield TP = 56 TN = 728 FN = 144 FP = 72 NPV 83% PPV 44% Sp 91% Se 28%
  71. 71. Credits & Acknowledgments Elena Baker-Glenn University of Nottingham Paul Symonds Leicester Royal Infirmary Chris Coggan Leicester General Hospital Burt Park University of Nottingham Lorraine Granger Leicester Royal Infirmary Mark Zimmerman Brown University, Rhode Island Brett Thombs McGill University Canada James Coyne University of Pennsylvania Nadia Husain University of Leicester For more information www.psycho-oncology.info
  72. 72. 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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