clinical epidemiology thyroid disease and test results l.
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Clinical Epidemiology: Thyroid disease and test results. Wiley D. Jenkins, PhD, MPH Research Assistant Professor Southern Illinois University School of Medicine Department of Family and Community Medicine. Who I am.

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clinical epidemiology thyroid disease and test results

Clinical Epidemiology:Thyroid disease and test results

Wiley D. Jenkins, PhD, MPH

Research Assistant Professor

Southern Illinois University School of Medicine

Department of Family and Community Medicine

who i am
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.
learning objectives
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.
performance objectives
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 test’s 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.
there is always uncertainty
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.
quick review of terms
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
the 2 x 2 table
The 2 x 2 table
  • You’ll use this a lot later in life…
sensitivity
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…
specificity
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…
positive negative predictive value
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?
time for a clinical example
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?
what next
What next?
  • Order more tests?
  • Schedule for surgery?
  • Prescribe medication, therapy, hamburgers…?
  • 1st, let’s see what the tests are really telling us.
thyroid stimulating hormone
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?
tsh 2 x 2 table
TSH 2 x 2 table
  • Complete the table and calculate the PPV and NPV assuming: sens = 92%, spec = 94% and prevalence = 4%
tsh 2 x 2 table completed
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?
free t4
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?
free t4 table
Free T4 table
  • Complete the table and calculate the PPV and NPV assuming: sens = 82%, spec = 94% and prevalence = 4%
free t4 table completed
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?
slide20
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?
fine needle aspiration biopsy
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.
the fnab 2 x 2 table
The FNAB 2 x 2 table
  • What do we know?
    • Prevalence – 4%
    • False positive rate – 20%
    • False negative rate – 3%
the fnab 2 x 2 table23
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
the fnab 2 x 2 table completed
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?
clinical course
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 Hashimoto’s or other disease.
how do laboratory tests contribute to medical errors
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.
time for a population example
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?
chlamydia trachomatis screening
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
the ct 2 x 2 table completed
The Ct 2 x 2 table - completed
  • For the general population (0.35%) we find:
    • PPV = 33/233 = 14%
    • NPV = 9765/9767 = 100%
the ct 2 x 2 table completed31
The Ct 2 x 2 table - completed
  • For all women (0.52%) we find:
    • PPV = 49/248 = 20%
    • NPV = 9749/9752 = 100%
the ct 2 x 2 table completed32
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%
utility of targeted testing
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 = >90%!
    • Other risk factors important.
  • This works for clinical guidelines for screening, such as mammography, prostate exams, cholesterol…
take away items
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.
slide35

Questions or comments??

Contact info:

Wiley D. Jenkins, PhD, MPH

wjenkins@siumed.edu

217-545-8717