reducing diagnostic uncertainty: what the evidence …...evidence-based neuropsychological practice...
TRANSCRIPT
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Gordon J. Chelune, PhD, ABPP(Cn)Professor Emeritus, Department of Neurology
University of Utah School of Medicine
Reducing Diagnostic Uncertainty: What the Evidence-based Researcher
Can Do for Clinical Practitioners
Kessler Foundation, November 2019
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This presentation will have 2 parts:
• General background on EBP and what researchers can do facilitate clinicians’ use of their research findings
• Specific methods for using data derived from research based on populations to inform clinical decisions about individuals
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Evidence-based PracticeThe purpose of any evaluation is to reduce uncertainty about a patient’s diagnosis, management, or care.
EBP provides a framework for doing this in an empirical and systematic way that incorporates published data from critically appraised research to inform decisions about individual patients.
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Every Patient Evaluation
➢Represents a Clinical Outcome➢Every Test Score is part of the Outcome➢Can/Should be interpreted within
context of Evidence-based Research
From “Description” to “Outcomes”
The Outcomes Movement of the 80s and 90s
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What is Evidence-based Practice?
What vs. How
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What is Evidence-Based Clinical
Neuropsychological Practice?
Evidence-based clinical neuropsychological practice (EBCNP)
is value-driven pattern of clinical practice that attempts to
integrate the “best research” derived from the study of
populations to inform clinical decisions about individuals
within the context of the provider’s expertise and individual
patient values with the goal of maximizing clinical outcomes
and quality of life for the patient in a cost-effective manner
while addressing the concerns and needs of the provider’s
referral sources.(Chelune, 2017, p 160)
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Seven Components of Evidence-based Neuropsychological Practice
1. Value-driven pattern of clinical practice
2. Integrates “best research”
3. Derived from the study of populations to inform clinical
decisions about individuals
4. Within the context of the provider’s expertise and
individual patient values
5. Goal of maximizing clinical outcomes and quality of life for
the patient
6. In a cost-effective manner
7. Addressing the concerns and needs of the provider’s
referral sources
Adapted from Chelune, 2017
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The “Value” or Clinical Significance of Evaluations
Patients “deserve decisions and recommendations that are founded increasingly upon empirical validation. The instruments chosen to produce data to resolve questions in a valid fashion should be selected for their power to reduce uncertainty with respect to those questions…”
Costa, JCN, 1983, p. 7.
Our ability “to reduce uncertainty” provides value to patient care
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That’s the “What”
Now for the “How”
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Evidence-based Practice
Evidence-based practice begins with asking appropriate and answerable questions, which define the parameters of our search, what to evaluate, and how to apply research findings.
Asking appropriate and answerable questions
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Type of Question Type of Evidence
Etiology: Disease causes and modes of operation Case-control or cohort studies
Diagnostic: Signs, symptoms, or tests for diagnosis a disorder
Diagnostic validations studies
Prognosis: The probable course of disease over time Inception cohort studies
Therapy: Selection of effective treatments which meet patient values
Randomized controlled trials
Cost-effectiveness: Comparison of efficacy/cost ofinterventions
Economic evaluation
Quality of Life: What will QoL of the patient be Qualitative study
The Question dictates what to look for, where to look, and what to expect
Adapted from Heneghan & Badenoch, 2006
What is the Question
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• Patient• Intervention• Comparison• Outcome
Asking:Well-Built Clinical Questions (PICO)
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• Background: Do patients with AD and FTD have different patterns of semantic and phonemic fluency?
• Foreground: In patients with
Patient: Frontotemporal dementia
Intervention: patterns of phonemic and semantic fluency
Comparison: compared to Alzheimer’s dementia
Outcome: are different (sensitive/specific)?
Asking:Well-Built Clinical Questions (PICO):
Diagnosis
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Acquire Relevant Data:Informatics skills in finding answers
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Acquire Relevant Data:Informatics skills in finding answers
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Database ContentMedline/PubMed General medical database; many journals not
referencedPsychINFO General psychological literature, including book
chaptersCINAHL Nursing/Allied Health
Embase Pharmacologic and biomedical database including international entries
BIOSIS Biological and biomedical sciences; journal articles, conference proceedings, books, and patents
HSTAT Health Sciences Technology and Assessment; clinical guidelines, AHRQ and NIH publications
CCRCT Cochrane Central Register of Controlled Trials
CDSR Cochrane Database of Systematic Reviews
DARE Database of Abstracts and Reviews of Effects; critically appraised systematic reviews
Campbell Collaboration
Systematic reviews in education, criminal justice, and social welfare
Common Web-based electronic research databases
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Supports Boolean Operators:AND, OR, NOT, Nesting
https://www.ncbi.nlm.nih.gov/pubmed
PubMed
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Knowing what is good, bad, acceptable, etc.
Appraisal Skills:
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➢ Meta-analyses, Systematic Reviews, and Critically Appraised Topics
➢ Randomized Cohort Studies➢ Cohort Studies➢ Case Controlled Studies➢ Case Series and Case Reports➢ Book Chapters & Expert Opinions
Common “Types” of Evidence:Some are better than others
The Evidence Pyramid
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Case Control StudiesNote reverse directionality, health outcome occurs before study begins.
Note forward directionality; health outcome occurs after study beginsCohort Studies
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Identifying “Best Research” is not easy
Incomplete and inadequate reporting of research hampers the assessment of the strengths and weaknesses of the studies reported in the medical and neuropsychological literature. Readers need to know what was planned (and what was not), what was done, what was found, and what the results mean.
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Reporting Guidelines:Moving toward greater transparency
❖ STROBE
❖ CONSORT
❖ STARD
Consolidated Standards of Reporting Trials.Website: http://www.consort-statement.org/
STrengthening the Reporting of OBservational studies in Epidemiology.Website: http://www.strobe-statement.org/
STAndards for the Reporting of Diagnostic accuracy studies.Website: http://www.stard-statement.org/
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Composite of the two PET groups
Results: The SI ratio was significantly different between PET groups (p< .000), with patients with AD PET patterns showing lower SI scores. A 2x2 Group x Fluency repeated measures ANOVA was calculated and there was a significant non-orthogonal interaction (p < .000) showing a marked difference between fluency measures among the AD PET group. ROC analysis of SI yielded an AUC of .742 (p < .000).
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Flowchart of Data Selection: Data collected from January 2006 – June 15, 2011
3092 cases in the patient registry
1245 patients with Neuropsychological evaluations
928 cases meeting inclusion criteria: MMSE ≥18 Age ≥ 55 yrs. Education > 8 yrs. English as primary language
180 patients with both PET imaging and neuropsychological
testing meeting inclusion criteria
351 patients with PET imaging
Patients are rank ordered by SSP hypometabolic (z-score) differences
between AD vs. FTD regions
Upper and lower quartiles labeled prototypic AD and FTD groups
(n=45 in each group)
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✓ Asked the Relevant Question
✓ Acquired the Relevant Clinical Research
✓ Appraised the Research
Now …
Recap of the 5 A’s:
✓ To Apply the Information to a given Patient
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One of the defining features of evidence-based practice is the use of data derived from research based on populations to inform clinical decisions about individuals…
…how do we move from group data to data that is applicable at the level of the individual?
Evidence-based Practice and Research
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Ask Yourself:
If my patient, with his/her specific test score(s), had participated in this study, in which group would they most likely have been ???
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COI RP
Do Patients with a Condition of InterestDiffer from Reference Population?
How Much vs. How Many
How Much How Many
Using Clinical Research
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Is the difference between groups statistically reliable?
p < .05
Performance
COI RP
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Performance
Reference
Population (RP)Healthy Controls
B C
True Positives True Negatives
FalsePositives
FalseNegatives
Condition of
Interest (COI)Alzheimer’s Dementia
A
Sensitivity = % True Positives
Specificity = % True Negatives
AD HC
Test Operating Characteristics
“How Many”
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TruePositive
FalsePositive
FalseNegative
TrueNegative
Condition of Interest
Yes (COI) No (RP)
Factor(event)
Yes+
No-
A B
C D
The Basic 2x2 Table
Sensitivity
Specificity
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Test Operating Characteristics
% Prevalence Odds
% Overall Correct Hit Rate Odds Ratio
Sensitivity Relative Risk Ratio
Specificity Likelihood Ratio
Positive Predictive Power Pre – Post Test Odds
Negative Predictive Power Pre – Post Test Probabilities
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Bayesian approach:
Analyses of Changes in Base Rates
Bayes’ Theorem: What we know after giving a test in equal to what we knew before doing the test times a modifier (based on the test results). Test results are used to adjust a prior distribution to form a new posterior distribution of scores.
Value Driven Pattern of Practice
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Nomogram for using Likelihood Ratios
(LR) to determine Post-test
Probabalities of a COI if the Pre-test
Probability and LR are known
E.g. Prevalence of COI = 20%
LR+ = 10
LR- = 0.1
Does Testing Matter
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p.24
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http://araw.mede.uic.edu/cgi-bin/testcalc.pl
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Condition of Interest
FTD AD Totals
SI > .524 12 6 18
SI Cutoff A B
SI < .524 4 26 30
C D
Totals 16 32 48
Test Operating Characteristics for FTD
% Prevalence (Baserate) of COI 33.33
% Positive Test Result 37.50
% Negative Test Result 62.50
% Overall Correct Hit Rate 79.17
Sensitivity (% True Positives) 0.7500
Specificity (% True Negatives) 0.8125
Positive Predictive Power 0.667
Negative Predictive Power 0.867
Odds having COI w. Pos. Test 2.000
Odds having COI w. Neg. Test 0.154
Odds Ratio 13.0000
Likelihood Ratio (LR+) 4.0000
Pre-Test Odds 0.5000
Post-Test Odds 2.0000
Pre-test Probabality 0.3333
Post-Test Probabality 0.6667
Risk Ratio (cohort studies) 5.0000
Test Operating Characteristics for AD
% Prevalence (Baserate) of COI 66.67
% Positive Test Result 62.50
% Negative Test Result 37.50
% Overall Correct Hit Rate 79.17
Sensitivity (% True Positives) 0.8125
Specificity (% True Negatives) 0.7500
Positive Predictive Power 0.867
Negative Predictive Power 0.667
Odds having COI w. Pos. Test 6.500
Odds having COI w. Neg. Test 0.500
Odds Ratio 13.0000
Likelihood Ratio (LR+) 3.2500
Pre-Test Odds 2.0000
Post-Test Odds 6.5000
Pre-test Probabality 0.6667
Post-Test Probabality 0.8667
Risk Ratio (cohort studies) 2.6000
Condition of Interest
AD FTD Totals
SI < .524 26 4 30
SI Cutoff A B
SI > .524 6 12 18
C D
Totals 32 16 48
FTD AD
Likelihood FTD when SI is > .524 Likelihood AD when SI is < .524
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My Patient’s SI Score is 0.65
How likely is my patient FTD?
Hey –What about my Patient??
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Two Challenges:
• Investigators do not always provide information about base rates and cutoff scores.
• When provided, the cutoff scores are not specific to the patient’s actual observed scores
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1. Z-score = (X – M)/ SD and tells us the area under the curve –percentile rank
2. If you know the sample size (N), you can estimate the actual number of cases above and below that z-score.
Given N=500 and a z-score of -1.533a. 500 x .94 = 469 aboveb. 500 x .06 = 31 below
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True Positive False Positive
False Negative True Negative
Condition of Interest
Yes (AD) No (HC)
Factor(Test Score)
Yes< 77
No> 77
A B
C D
The Basic 2x2 Table
31
469
Specificity
??
??
Sensitivity
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Ask Yourself:
If my patient, with his/her specific test score of 77, had participated in this study, in which group would they most likely have been ???
Likelihood Ratio
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True Positive False Positive
False Negative True Negative
Condition of Interest
Yes (COI) No (RP)
Factor(Test Score)
Yes< 77
No> 77
A B
C D
The Basic 2x2 Table
31
469
Specificity
37
11
Sensitivity
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If one has the Means, Standard Deviations, and Sample Sizes for the groups in question it is possible to estimate the number of cases in each group that would fall above or below a patient’s observed score and to calculate the TOC characteristics for that score
Caveat
**IMPORTANT** Calculations assume normal distribution of scores.Use only within the scope of this assumption
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The Next Challenge:
What to do about “non-normal” distributions
The Problem of Skew
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Pearson Coefficient of Skewness for grouped data
If the Mean, SD, and Skew Coefficient are known, one can algebraically solve for the Median (Md) which represents the score at which the 50th percentile occurs.
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What If …
An Investigator provides:
Mean, SD, N, and Skew Coefficient …AND…
… a transformation formula used to successfully normalized the data, can you use the Mean and SD of the transformed scores to generate base rates for observed scores?
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How to program a Feigan Nomogram in Excel?
How to deal with variables that are skewed?
If variables with skewed distributions can be normalized, can the Mean and SD of the normalized scores then be used to determine the number of cases above and below a patient’s score ?
Open to Suggestions/Comments/Help:
Johannes Moreelse
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