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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>