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Lecture 2 Screening and diagnostic tests

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Lecture 2 Screening and diagnostic tests Normal and abnormal Validity: gold or criterion standard Sensitivity, specificity, predictive value – PowerPoint PPT presentation

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Title: Lecture 2 Screening and diagnostic tests


1
Lecture 2 Screening and diagnostic tests
  • Normal and abnormal
  • Validity gold or criterion standard
  • Sensitivity, specificity, predictive value
  • Likelihood ratio
  • ROC curves
  • Bias spectrum, verification, information

2
Clinical/public health applications
  • screening for asymptomatic disease (e.g., Pap
    test, mammography)
  • case-finding testing of patients for diseases
    unrelated to their complaint
  • diagnostic to help make diagnosis in symptomatic
    disease or to follow-up on screening test

3
Evaluation of screening and diagnostic tests
  • Performance characteristics
  • test alone
  • Effectiveness (on outcomes of disease)
  • test intervention

4
Criteria for test selection
  • Reproducibility
  • Validity
  • Feasibility
  • Simplicity
  • Cost
  • Acceptability

5
Sources of variation Biological or true
variation
  • between individuals
  • within individuals (e.g., diurnal variation in
    BP)
  • controlled by standardizing time of measurement

6
Sources of variation Measurement error
  • random error vs systematic error (bias)
  • method (measuring instrument)
  • observer

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Quality of measurements
  • Validity (accuracy)
  • Does it measure what it is intended to?
  • Lack of bias
  • Reproducibility (reliability, precision,
    consistency) of measurements

9
Examples of types of reproducibility
  • Between and within observer (inter- and
    intra-observer variation)
  • May be random or systematic
  • Regression toward the mean
  • Systematic error when subjects have extreme
    values (more likely to be in error than typical
    values)

10
Validity (accuracy)
  • Criterion validity
  • concurrent
  • predictive
  • Face validity, content validity judgement of the
    appropriateness of content of measurement
  • Construct validity validity of underlying entity
    or theoretical construct

11
Normal vs abnormal
  • Statistical definition
  • Gaussian or normal distribution
  • Clinical definition
  • using criterion

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16
Selection of criterion
  • Concurrent
  • salivary screening test for HIV
  • history of cough more than 2 weeks (for TB)
  • Predictive
  • APACHE (acute physiology and chronic disease
    evaluation) instrument for ICU patients
  • blood lipid level
  • maternal height

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Sensitivity and specificity
  • Assess correct classification of
  • People with the disease (sensitivity)
  • People without the disease (specificity)

19
Predictive value
  • More relevant to clinicians and patients
  • Affected by prevalence

20
Choice of cut-point
  • If higher score increases probability of disease
  • Lower cut-point
  • increases sensitivity, reduces specificity
  • Higher cut-point
  • reduces sensitivity, increases specificity

21
Considerations in selection of cut-point
  • Implications of false positive results
  • burden on follow-up services
  • labelling effect
  • Implications of false negative results
  • Failure to intervene

22
Likelihood ratio
  • Likelihood ratio (LR) sensitivity

  • 1-specificity
  • Used to compute post-test odds of disease from
    pre-test odds
  • post-test odds pre-test odds x LR
  • pre-test odds derived from prevalence
  • post-test odds can be converted to predictive
    value of positive test

23
Example of LR
  • prevalence of disease in a population is 25
  • sensitivity is 80
  • specificity is 90,
  • pre-test odds 0.25 1/3
  • 1 - 0.25
  • likelihood ratio 0.80 8
  • 1-0.90

24
Example of LR
  • If prevalence of disease in a population is 25
  • pre-test odds 0.25 1/3
  • 1 - 0.25
  • post-test odds 1/3 x 8 8/3
  • predictive value of positive result 8/38
  • 8/11 73

25
Receiver operating characteristic (ROC) curve
  • Evaluates test over range of cut-points
  • Plot of sensitivity against 1-specificity
  • Area under curve (AUC) summarizes performance
  • AUC of 0.5 no better than chance

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Spectrum bias
  • Study population should be representative of
    population in which test will be used
  • Is range of subjects tested adequate?
  • In population with low risk of outcome,
    sensitivity will be lower, specificity higher
  • In population with high risk of outcome,
    sensitivity will be higher, specificity lower
  • Comorbidity may affect sensitivity and
    specificity

28
Verification bias
  • results of test affect intensity of subsequent
    investigation
  • increasing probability of detection of outcome in
    those with positive test result

29
Information bias
  • Diagnosis is not blind to test result
  • Improves test performance

30
Example Screening seniors in the emergency
department (ED) for risk of function decline
  • High risk group
  • Many not adequately evaluated or referred for
    appropriate services
  • Development and validation of a brief screening
    tool to identify those at increased risk of
    functional decline and other adverse outcomes

31
Two multi-site studies in Montreal EDs
  • Study 1 development of ISAR
  • Prospective observational cohort study
  • JAGS (1999) 47 1226-1237.
  • Study 2 evaluation of 2-step intervention
  • randomized controlled trial
  • JAGS (2001) 49 1272-1281.

32
Common features of 2 studies
  • 4 Montreal hospitals (2 participated in both
    studies)
  • Patients aged 65, community dwelling, English or
    French-speaking
  • Exclusions
  • cognitively impaired or severe illness with
    no proxy informant
  • language barrier (no English or French)

33
Differences between 2 studies Study design
  • Study 1
  • Observational study
  • Follow-up at 3 and 6 months after ED visit
  • Study 2
  • Randomized controlled trial 2-step intervention
    vs usual care
  • Randomization by day of visit
  • Follow-up at 1 and 4 months after ED visit

34
RESULTS ISAR development
  • Adverse health outcome defined as any of
    following during 6 months after ED visit
  • gt10 ADL decline
  • Death
  • Institutionalization

35
Scale development
  • Selection of items that predicted all adverse
    health events
  • Multiple logistic regression - best subsets
    analysis
  • Review of candidate scales with clinicians to
    select clinically relevant scale

36
Identification of Seniors At Risk (ISAR)
  • 1. Before the illness or injury that brought
    you to the Emergency, did you need someone to
    help you on a regular basis? (yes)
  • 2. Since the illness or injury that brought you
    to the Emergency, have you needed more help
    than usual to take care of yourself? (yes)
  • 3. Have you been hospitalized for one or more
    nights during the past 6 months (excluding a
    stay in the Emergency Department)? (yes)
  • 4. In general, do you see well? (no)
  • 5. In general, do you have serious problems with
    your memory? (yes)
  • 6. Do you take more than three different
    medications every day? (yes)
  • Scoring 0 - 6 (positive score shown in
    parentheses)

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Other Outcomes Related to ISAR Source
Dendukuri et al, JAGS, in press
  • Does ISAR score identify patients with current
    functional problems?
  • Self-reported premorbid function (OARS)
  • Function at home visit assessed by nurse 1-2
    weeks after ED visit (SMAF)

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Other Outcomes Related to ISAR
  • Does ISAR predict adverse outcomes (other than
    functional decline) during the subsequent 5 or 6
    months?
  • High hospital utilization (11 days/5 months)
  • Frequent ED visits
  • Frequent community health center visits
  • Increase in depressive symptoms

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42
Summary of data on performance
  • Very good detection of patients with current
    functional problems and depression (AUC values
    0.8 - 0.9)
  • Moderate ability to predict future adverse health
    events (functional decline) and health center
    utilization (AUC values around 0.7)
  • Fair ability to predict future hospital and ED
    utilization (AUC values 0.6 - 0.7)

43
Comparison with other screening tools for
patients admitted to hospital Source McCusker
et al, J Gerontol 2002 57A M569-577
  • Systematic literature review
  • Predictors of functional decline (including
    nursing home admission) among hospitalized
    seniors
  • Investigated individual risk factors and
    predictive indices

44
Predictive indices
  • Inouye (1993) FD and NH at 3 mo
  • 4 factors decubitus ulcer, cognitive impairment,
    premorbid functional impairment, low social
    activity
  • Mateev(1998) D/NH at 3 mo.
  • clinical targeting criteria

45
Predictive indices (cont)
  • McCusker (1999) FD/NH/ D at 6 mo.
  • Identification of Seniors At Risk (ISAR) 6-item
    self-report questionnaire
  • Narain (1988) NH at 6 mo
  • hand-developed algorithm based on residence,
    mental status, diagnosis

46
Predictive indices (cont)
  • Rubenstein (1984) FD and NH at 12 mo
  • expected discharge location and diagnosis
  • Sager (1996) FD at 3mo
  • Hospital Admission Risk Profile (HARP) (age, MMSE
    and IADL)
  • Zureik (1997) NH at discharge
  • 6-item index

47
Performance of 7 predictive indices for
functional decline
48
Performance of predictive indices
  • Moderate performance (AUC 0.65 - 0.66)
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