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Clinical Epidemiology: Thyroid disease and test results

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Title: Clinical Epidemiology: Thyroid disease and test results


1
Clinical EpidemiologyThyroid disease and test
results
  • Wiley D. Jenkins, PhD, MPH
  • Research Assistant Professor
  • Southern Illinois University School of Medicine
  • Department of Family and Community Medicine

2
Who I am
  • My name is Wiley D. Jenkins and I am currently
    Research Assistant Professor at the SIU-SOM
    Department of Family and Community Medicine.
    Prior to this I spent 13 years in the state
    health department laboratory.
  • I received my MPH-Epidemiology from Tulane
    University in 2002. This was followed by my PhD
    in Health policy from the University of Illinois
    at Chicago in 2007.
  • Much of my research and work experience has
    concerned laboratory testing, STDs and the
    quality of laboratory data.

3
Learning objectives
  • To understand the concepts of test sensitivity,
    specificity, positive predictive value and
    negative predictive value.
  • To understand how these factors effect the
    utility of individual tests when diagnosing a
    condition.
  • To understand how these factors are manipulated
    by targeting screening tests to specific
    populations.

4
Performance objectives
  • To be able to calculate the sensitivity,
    specificity, positive predictive value and
    negative predictive value for a given test.
  • To be able to determine if a tests result is
    useful given its calculated values.
  • To be able to show how screening guidelines
    should be adjusted to increase positive and
    negative predictive values to maximize result
    usefulness.

5
There is always uncertainty
  • Our common language incorporates uncertainty.
  • Usually implies error bars
  • Physics tells us that in an infinite universe,
    anything is possible. Some things are just more
    or less likely.
  • Heisenberg uncertainty principle
  • statement that locating a particle in a small
    region of space makes the momentum of the
    particle uncertain and conversely, that
    measuring the momentum of a particle precisely
    makes the position uncertain
  • As a matter of practicality, some things are
    essentially 100 or always something.
    HOWEVER, its important to know when this is not
    the case, and that is not always obvious.

6
Quick review of terms
  • Sensitivity the ability of a test to correctly
    identify those who have a condition
  • Specificity the ability of a test to correctly
    identify those who do not have a condition
  • Positive predictive value the number of
    individuals who have a condition from all those
    who test positive
  • Negative predictive value - the number of
    individuals who do not have a condition from all
    those who test negative

7
The 2 x 2 table
  • Youll use this a lot later in life

8
Sensitivity
  • 90 sensitivity implies that of all those who
    have the disease, 10 will not be identified by
    the test. If prevalence is 20 of the population

9
Specificity
  • 75 specificity implies that of all those who do
    not have the disease, 25 will not be identified
    by the test. If prevalence is 20 of the
    population

10
Positive/negative predictive value
  • We complete the remaining marginals and find
  • PPV for our example test is 180/380 47
  • NPV is 600/620 97.
  • What do we draw from this about the usefulness of
    the test?

11
Time for a clinical example
  • 27-year-old woman
  • 10 lb weight loss in past two months, not trying
  • Some difficulty sleeping
  • Never had anything like this before
  • No signs/symptoms of depression
  • Meds Oral contraceptive pills
  • 1-cm, firm, smooth nodule in right lobe of
    thyroid
  • BMI 20
  • Skin slightly dry
  • Remainder of physical examination normal
  • What do you think?
  • What should we do?

12
Lab tests and results
13
What next?
  • Order more tests?
  • Schedule for surgery?
  • Prescribe medication, therapy, hamburgers?
  • 1st, lets see what the tests are really telling
    us.

14
Thyroid stimulating hormone
  • Our patient has a (low) normal TSH
  • Sensitivity 92
  • Specificity 94
  • Are these good values?
  • Assume prevalence for thyroid disease of 4 in
    large populations
  • Calculate PPV and NPV for TSH
  • Do we care more about the PPV or NPV for this
    scenario?

15
TSH 2 x 2 table
  • Complete the table and calculate the PPV and NPV
    assuming sens 92, spec 94 and prevalence
    4

16
TSH 2 x 2 table - completed
  • We find
  • PPV 37/95 31
  • NPV 902/905 100
  • Which do we care about and what conclusions do we
    draw?

17
Free T4
  • Our patient has an elevated Free T4
  • Sensitivity 82
  • Specificity 94
  • Assume prevalence for thyroid disease of 4 in
    large populations
  • Calculate PPV and NPV for Free T4
  • Do we care more about the PPV or NPV for this
    scenario?

18
Free T4 table
  • Complete the table and calculate the PPV and NPV
    assuming sens 82, spec 94 and prevalence
    4

19
Free T4 table - completed
  • We find
  • PPV 33/91 36
  • NPV 902/909 99
  • Which do we care about and what conclusions do we
    draw?

20
So
  • We have
  • A symptomatic woman on OCPs with a thyroid nodule
  • A normal TSH
  • An elevated Total T4
  • An elevated Free T4
  • What next?
  • Scintigraphy?
  • Fine Needle Aspiration Biopsy?
  • Excisional Biopsy?

21
Fine needle aspiration biopsy
  • Indeterminate result
  • 15-20 false positive rate (assume 20 for
    calculations to follow)
  • 3 false negative rate
  • If we assume a 4 prevalence of thyroid cancer,
    calculate the sensitivity and specificity of the
    biopsy.
  • Calculate the positive and negative predictive
    value.

22
The FNAB 2 x 2 table
  • What do we know?
  • Prevalence 4
  • False positive rate 20
  • False negative rate 3

23
The FNAB 2 x 2 table
  • False positives FP rate x all negatives 0.20
    x 960 192
  • False negatives FN rate x all positives .03 x
    40 1

24
The FNAB 2 x 2 table - completed
  • We find
  • PPV 39/231 17
  • NPV 768/769 100
  • Which do we care about and what conclusions do we
    draw?

25
Clinical course
  • The patient was referred to a surgeon for
    excisional biopsy.
  • Nodule was removed, was a benign colloid goiter,
    no malignancy and no evidence of Hashimotos or
    other disease.

26
Lab results
27
How do laboratory tests contribute to medical
errors?
  • Are not always right
  • May result in unnecessary further testing
  • May result in unnecessary surgery
  • With attendant complications
  • If we assume that tests are correct 95 of the
    time, what is the likelihood that, in a battery
    of 20 tests, one will be a false result?
  • So, for every Chem 20 you order (or other battery
    of 20 tests), 1 will be either a FALSE POSITIVE
    or a FALSE NEGATIVE.
  • Need to know how to work with sensitivity and
    specificity in order to know what to believe.

28
Time for a population example
  • Why, because we like you! (M I C)
  • Seriously though, population-level studies are
    translated into clinical guidelines.
  • In 2006, the number of reported cases of
    Chlamydia trachomatis (Ct) in the US exceeded
    1,000,000 for the 1st time.
  • The great majority of cases (70 in women) are
    entirely asymptomatic.
  • Upwards of 40 of untreated Ct progress to PID
    followed by chronic pelvic pain, ectopic
    pregnancy and infertility.
  • How do we address this?

29
Chlamydia trachomatis screening
  • Diagnostic companies have spent considerable
    money developing rapid and accurate tests for the
    detection of Ct.
  • Current tests offer
  • 95 sensitivity
  • 98 specificity
  • So, do we just test everyone? Lets see.
    (150,000,000 women) x (10/test) need for
    other alternative.
  • Who has Ct?
  • 0.35 all Americans
  • 0.52 women
  • 0.17 men
  • 1.76 Black women
  • 0.24 White women
  • 2.9 women aged 15-19
  • 2.8 women aged 20-24

30
The Ct 2 x 2 table - completed
  • For the general population (0.35) we find
  • PPV 33/233 14
  • NPV 9765/9767 100

31
The Ct 2 x 2 table - completed
  • For all women (0.52) we find
  • PPV 49/248 20
  • NPV 9749/9752 100

32
The Ct 2 x 2 table - completed
  • For all women aged 16-24 (2.9) we find
  • PPV 276/470 59
  • NPV 9516/9530 100

33
Utility of targeted testing
  • By purposefully targeting our testing to at-risk
    populations, we increase the PPV of the test and
    better allocate resources.
  • General population
  • Prevalence 0.35 PPV 14
  • All women
  • Prevalence 0.52 PPV 20
  • Women aged 16-24
  • Prevalence 2.9 PPV 59
  • Females admitted into juvenile detention
    centers??
  • Prevalence 12-20 PPV gt90!
  • Other risk factors important.
  • This works for clinical guidelines for screening,
    such as mammography, prostate exams, cholesterol

34
Take away items
  • Not a good practice to order tests just because
    we can or for fishing expeditions.
  • Costs can quickly become quite significant (e.g.
    compare HC expenditure for US versus other
    industrialized countries and resultant health
    outcomes).
  • Utility of the results is directly impacted by
    the population/person to which they are given.
  • Multiple tests increase the likelihood of a
    correct diagnosis.
  • E.g. Ct in 16-24, PPV 59
  • Additional test on just these positives (e.g. 59
    prevalence) with same sens/spec results in PPV of
    99!
  • In the absence (always) of the ultimate test,
    use multiple results to arrive at the best
    conclusion.

35
Questions or comments?? Contact info Wiley D.
Jenkins, PhD, MPH wjenkins_at_siumed.edu 217-545-8717
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