Transcript Diagnosis - Augusta University

Diagnosis:Testing the Test
Verma Walker
Kathy Davies
Journal of Pediatric Gastroenterology & Nutrition.
35(1):39-43, 2002 Jul.
13 C-urea breath test with infrared spectroscopy for
diagnosing helicobacter pylori infection in children and adolescents.
BACKGROUND AND OBJECTIVE:
Studies support the accuracy of 13C-urea breath test for diagnosing
and confirming cure of Helicobacter pylori infection in children.
Three methods are used to assess 13CO2 increment in expired air:
mass spectrometry, infrared spectroscopy, and
laser-assisted ratio analysis. In this study, the
13C-urea breath test performed with infrared
spectroscopy in children and adolescents
was evaluated
METHODS: Seventy-five patients (6 months to 18 years old) were included.
The gold standard for diagnosis was a positive culture or positive histology and
a positive rapid urease test. Tests were performed with 50 mg of 13C-urea
diluted in 100 mL orange juice in subjects weighing up to 30 kg, or with 75 mg
of 13C-urea diluted in 200 mL commercial orange juice for subjects weighing
more than 30 kg. Breath samples were collected just before and at 30 minutes
after tracer ingestion. The 13C-urea breath test was considered positive when
delta over baseline (DOB) was greater than 4.0%
RESULTS: Tests were positive for H. pylori in 31 of 75 patients. Sensitivity
was 96.8%, specificity was 93.2%, positive predictive value was 90.9%, negative
predictive value was 97.6%, and accuracy was 94.7%.
CONCLUSIONS: 13C-urea breath test performed with
infrared spectroscopy is a reliable, accurate, and noninvasive
diagnostic tool for detecting H. pylori infection.
Gold Standard
Investigation
Positive n
Histology
Positive
28
Negative
3
Negative n
0
44
RUT
Positive
Negative
30
1
0
44
Culture
Positive
Negative
22
9
0
44
13C-UBT
Positive
Negative
30
1
3
41
Test Result Positive
Gold Standard
Positive
Gold Standard
Negative
(condition present)
(condition absent)
True Positive
30
False Positive
a
Test Result Negative
1
False Negative
3
b
c d
41
True Negative
Sensitivity
• the proportion of truly diseased persons, as
measured by the gold standard, who are
identified as diseased by the test under
study.
• True Positives/(True Positives + False
Negatives)
• a/(a+c)
• Sensitivity = Snout = Rules Out
Specificity
• The proportion of truly non-diseased
persons, as measured by the gold standard,
who are so identified by the diagnostic test
under study.
• True Negatives/(False Positive + True
Negative)
• d/(b+d)
• Specificity = Spin = Rules In
Predictive Values
• In screening and diagnostic tests, the probability
that a person with a positive test is a true positive
(i.e., does have the disease), or that a person with a
negative test truly does not have the disease. The
predictive value of a screening test is determined
by the sensitivity
and specificity of the test, and by the
prevalence of the condition for which
the test is used.
Positive Predictive Value
•True Positive/(True Positive + False Positive)
•a/(a+b)
Probability that a person with positive test is a true positive
(does have the disease)
Negative Predictive Value
•True Negative/(True Negative + False Negative)
•d/(d+c)
• Probability that a person with a negative test
truly does not have the disease
Using Predictive Values
• Keep clinical significance in mind
– Terminal or rare disease
– Impact of false negative on patient outcome
– Benefit of testing to patient
• Population tested is high or low risk?
• Alternative Tests for screening
Likelihood Ratios
• The likelihood ratio for a test result compares the
likelihood of that result in patients with disease to
the likelihood of that result in patients without
disease:
• Positive LR = (a/a+c)/(b/b+d)
– sensitivity / (1-specificity)
• Negative LR = (c/a+c)/(d/b+d)
– (1-sensitivity) / specificity
Impact on Disease Likelihood
• LR >10 or <0.1 cause large changes
in likelihood
• LR 5-10 or 0.1-0.2 cause moderate changes
• LR 2-5 or 0.2-0.5 cause small changes
• LR between <2 and 0.5 cause
little or no change
Ruling In & Out
• Does patient have disease ?
• Higher Positive LR means disease is likely
to be present if test is positive
• Does patient not have disease?
• Lower Negative LR means that
disease is not likely present or
cause of patient current condition
•Prevalence
• Proportion of persons with a particular disease within a given population at a
given time. Probability that a person selected at random will have disease.
• (a+c) / (a+b+c+d)
•Pre-test odds
• Odds that a person will have the disease; calculated before test is complete.
•prevalence / (1-prevalence)
•Post-test odds
• Measures impact of test result on odds of disease being present
•pre-test odds * LR
•Post-test probability
• Chances of disease after factoring in test results
• post-test odds / (post test odds+1)
Nomogram
Clinical Implications
•
•
•
•
One test is not a diagnosis
Implications of false positive
Further testing may be needed
Numbers may be significant but not
clinically relevant
Number Meanings
•
•
•
•
•
•
100,000 men studied for coronary artery disease
Uric Acid Factor in prediction
Developed CA disease uric acid=7.8 mg/L
Did not develop CA disease uric acid= 7.7 mg/L
P Value = 0.05– significant
Problems?
Number Meanings
• Large study found significant difference for
very small difference in values
• Unlikely that uric acid will be useful as
clinical predictor
• When test is performed, difference
is less than any lab error
Purposes of Statistics
• Estimate relationships between variables,
cause & effect and differences in magnitude
• Measure the significance of the results; do
the numbers have any clinical meaning?
• Adjust for the impact of confounding
variables on results
Bibliography
Center for Evidence Based Medicine. Ed. Douglas Badenoch, Olive Goddard,
Bridget Burchell, Sept. 2002. NHS Research and Development. 1 Oct. 2002
<http://www.minervation.com/cebm/docs/likerats.html>
Evidence Based Medicine Tool Kit. Ed. Jeanette Buckingham, Bruce Fisher,
Duncan Saunders. Nov. 2000. University of Alberta. 5 Sept. 2002
<http://www.med.ualberta.ca/ebm/ebm.htm>
Kawakami, Elisabete. 13C-Urea Breath Test with infrared spectroscopoy for
diagnosing Helicobacter pylori infection in children and adolescents. Journal of
Pediatric Gastroenterology and Nutrition 2002; 35(1): 39-43.
Riegelman, Richard. Studying a Study and Testing a Test: How to
read the Medical evidence. 4th Edition: Lippincott,
Williams & Wilkins, 2000
Schwartz, Alan. EBM and Decision Tools: Diagnostic Test
Cutoffs <http://araw.mede.uic.edu/cgi-bin/cutoff.cgi>