Alex Mitchell www.psycho-oncology.info/workshop Department of Cancer & Molecular Medicine, Leicester Royal Infirmary Department of Liaison Psychiatry, Leicester General Hospital IPOS 2010 IPOS 2010 WORKSHOP Day 2 Implementation of Screening: Screening studies, Short methods, HADS and longer methods, implementation, future of screening
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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
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
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
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?
T1. Are We Looking for Distress?T1. Are We Looking for Distress?
How Often
What method?
n=226Comment: Frequency of cancer specialists enquiry about depression/distress from Mitchell et al (2008)
1,2 or 3 Simple QQ15%
Clinical Skills Alone73%
ICD10/DSMIV0%
Short QQ3%
Other/Uncertain9% Other/Uncertain
2%
Use a QQ15%
ICD10/DSMIV13%
Clinical Skills Alone55%
1,2 or 3 Simple QQ15%
Cancer StaffCurrent Method (n=226)
Psychiatrists
Comment: Current preferred method of eliciting symptoms of distress/depression
1,2 or 3 Simple QQ24%
Clinical Skills Alone20%
ICD10/DSMIV24%
Short QQ24%
Long QQ8%
Algorithm26%
Short QQ23%
ICD10/DSMIV0%
Clinical Skills Alone17%
1,2 or 3 Simple QQ34%
Cancer StaffIdeal Method (n=226)
Psychiatrists
Effective?
Comment: “Ideal” method of eliciting symptoms of distress/depression according to clinician
T2. Are We finding it?T2. Are We finding it?
How successful are we (routinely)?
Comment: Slide illustrates diagnostic accuracy according to score on DT
11.815.4
30.4 28.9
41.9 42.9 40.7
57.1
82.4
66.771.4
15.8
25.0
26.124.4
19.4 19.0
33.3
21.4
11.8
22.2 14.3
72.4
59.6
43.546.7
38.7 38.1
25.921.4
5.911.1
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
GP Accuracy – Detection of Distress by GHQ ScoreGP Accuracy – Detection of Distress by GHQ ScoreMcCall 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
0
0.05
0.1
0.15
0.2
0.25
0.3
Eight
Nine Ten
Eleven
Twelv
eTh
irtee
nFo
urtee
n
Fiftee
nSixt
een
Seven
teen
Eighteen
Ninetee
n
Twen
tyTw
enty-
one
Proportion MissedProportion Recognized
HADS-D
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).
Testing Clinicians: A Meta-AnalysisTesting Clinicians: A Meta-Analysis
All cancer professionalsSE =39.5% and SP =77.3%.
OncologistsSE =38.1% and SP = 78.6%; a fraction correct of 65.4%.
By comparison nursesSE = 73% and SP = 55.4%; FC = of 60.0%.
When attempting to detect anxiety oncologists managedSE = 35.7%, SP = 89.0%, FC 81.3%.
Presented at IPOS2009
GPs vs Oncologists vs NursesGPs vs Oncologists vs Nurses
Zero One Two Three Four Five Six Seven Eight Nine Ten
Insignificant SevereModerateMildMinimal
p124
50%
British Journal of Cancer (2007) 96, 868 – 874
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”
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
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
18%
DepT23%
Distress69%
Dysfunction76%
0.3%
3% 2%
26%28% 22%
Of the 293 Non-Nil
DysfunctionDistress
DepT
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
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
Typically severely impared
Typically mod impared
Typically mildly impared
Typically unimpared
None at all
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
Dt vs DysfunctionDt vs Dysfunction
ROC plot from Book 1
0.00 0.25 0.50 0.75 1.000.00
0.25
0.50
0.75
1.00Sensitivity
1-Specificity
Distress Thermometer(+ve), M(-ve)
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+ = 0.409Specificity = 68.9%; NPV = 70.3%; UI- = 0.484
At a cut-off of 3v4 (>=4)Sensitivity =58.9%; PPV =65.6%; UI+ = 0.386Specificity = 75.9%; NPV = 70.3%; UI- = 0.534
At a cut-off of 4v5 (>=5)Sensitivity =50.9%; PPV =67.85; UI+ = 0.345Specificity = 81.1%; NPV = 67.9%; UI- = 0.55
T6. Screening in Cancer: ImplementationT6. Screening in Cancer: Implementation
Clinician Opinion
Patient Opinion
Comment: Slide illustrates actual gain in meta-analysis of screening implementation in primary care
There was a non-significant trend for improve detection sensitivity (Chi² = 1.12 P = 0.29).
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
2x2 Clinician Help Table : ACTUAL HELP2x2 Clinician Help Table : ACTUAL HELPClinician thinks:Unmet Needs
Clinician thinks no Unmet Needs
Patient Says:Help Wanted
=> Intervention => Low grade
Patient Distressed => Intervention =>??
Patient Not distressed orHelp Not Wanted
=> Monitor? => discharge?
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 orHelp Not Wanted
Helped 8/35(23%)
Helped 20/117(17%)
b. Intervention and helpb. Intervention and helpPREDICTORS
1. patient desire for help
2. number of unmet needs
3. clinicians confidence
4. patient reported anger
p179
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]
Advanced AspectsAdvanced Aspects
Algorithms
Structured interviews
Computerized testing
Item-banking
Screening in subgroups
p643
p454
T7. ExtrasT7. Extras
Unfiled
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 = 360Probable Non-Case TN =440
FN = 60
PPV 28% NPV 88%
Screen #1-ve
YieldTP = 140
TN = 440
FN = 60
FP = 360
NPV 88%
PPV 28%
Sp 55%
Se 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 = 360Probable Non-Case TN =440
FN = 60
PPV 28%
Oncologist Assessment Sp 80%
Sp 40%
NPV 88%
Probable Depression TP = 56
FP = 72Probable Non-Case TN =288
FN = 84
PPV 44% NPV 77%
Screen #1-ve
Screen #2+ve
Screen #2+ve
Cumulative YieldTP = 56
TN = 728
FN = 144
FP = 72
NPV 83%
PPV 44%
Sp 91%
Se 28%
Credits & Acknowledgments
Elena Baker-Glenn University of NottinghamPaul Symonds Leicester Royal InfirmaryChris Coggan Leicester General HospitalBurt Park University of NottinghamLorraine Granger Leicester Royal InfirmaryMark Zimmerman Brown University, Rhode IslandBrett Thombs McGill University CanadaJames Coyne University of PennsylvaniaNadia Husain University of Leicester
For more information www.psycho-oncology.info
FURTHER READING:
Screening for Depression in Clinical Practice An Evidence-Based guide
ISBN 0195380193 Paperback, 416 pagesNov 2009Price: £39.99