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EBM Basics Using an Article on Diagnosis: Making (Specific) Sense of It All. Alex Djuricich, MD Department of Medicine Indiana University School of Medicine Ambulatory Rotation 2005-2006. Case 1.
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EBM BasicsUsing an Article on Diagnosis:Making (Specific) Sense of It All Alex Djuricich, MD Department of Medicine Indiana University School of Medicine Ambulatory Rotation 2005-2006
Case 1 • A 54 year old white male, newly diagnosed Type II DM (as of 6 weeks ago), comes to office with foot complaints in December. His neighbor, a long-time diabetic, just had a BKA 1 week ago, after a long bout with PVD. The patient just learned about diabetic complications in his DM class, and is quite concerned about his feet. He has had “pale” feet x 6 months. His feet seem “cool” to him. He admits to foot pain with exercise. He gets back pain when he walks more than 2 blocks. Meds: Glucotrol XL 5 mg qd. On PE, he indeed has pale, cool, hairless feet bilaterally. BP 134/82. His PT, DP, and popliteal pulses seem normal. He has dependent rubor, and atrophic skin changes. His ABI is 0.97.
Case 1 • You are concerned that this patient may have peripheral vascular disease. You know that it takes forever to get an arterial Doppler ordered, and would rather know sooner than later. • Given your physical examination findings, does he have peripheral vascular disease (ischemia) or not? Asked another way: • In patients with risk factors for PVD, what physical exam findings are useful diagnostic tools for PVD?
Case 2 • A 65 year old men with no cardiac history comes to the ER because of shortness of breath. He has had gradual dyspnea over the past 3 weeks. He now cannot even go upstairs to sleep without having severe dyspnea. He uses 3 pillows, which he previously did not do. He has woken up at night, sometimes from dyspnea, sometimes from increasing urination. He denies chest pain. PMH: BPH, treated with doxazosin PSH: none. Rest of history, unremarkable • Meds: aspirin 325 mg qday, doxazosin 2 mg qhs • On physical: RR 24 P 104 BP 178/98. No JVD. Lungs: crackles in bases, o/w clear. Cor: RRR S1S2 no S3, +S4, PMI laterally displaced Abd: normal Ext: no edema, O2 sat 94%. CXR: ? Haziness, borderline cardiomegaly EKG: borderline LVH, NSSTTW changes
Case 2 • You are seeing this patient at 5 pm the Wednesday before Thanksgiving. You are concerned about CHF, and feel he should be admitted. However, you realize the echo lab is closed until Monday morning, and you have no documentation that this is systolic dysfunction, although you are concerned about this. You realize that you can’t truly diagnose him as having “CHF”, or at least systolic dysfunction, until later on Monday. You are going into a cardiology fellowship soon, and recently read an article on B-natriuretic peptide. You want to order this test.
Case 2 clinical question • In patients with suspected CHF referred for echocardiography, what are the diagnostic properties of B-natriuretic peptide (BNP) levels for detecting abnormal ventricular function?
Case 3 • You admit a 75 year old woman with community-acquired pneumonia. She responds nicely to appropriate antibiotics but her hemoglobin remains at 10 g/dl with a mean cell volume of 80. Her peripheral blood smear shows hypochromia, she is otherwise well, and is on no incriminating medications. You search her old labs and find out that her hemoglobin was 10.5 g/dl 6 months ago. She has never been investigated for anemia. You discuss this patient on rounds and debate the use of ferritin in the diagnosis of iron deficiency anemia. You admit to yourself that you are unsure how to interpret a ferritin result and how precise and accurate a serum ferritin is for diagnosing iron deficiency anemia. You therefore form the question, "In an elderly woman with hypochromic, microcytic anemia, can a low ferritin diagnose iron deficiency anemia? "
Question • You perform a MEDLINE search using the MeSH terms "ferritin" and "sensitivity and specificity" and find an article on diagnosing iron deficiency anemia in the elderly published in a journal that your library has • Am J Med 1990;88:205-9.
Goals • Given a clinical scenario with a defined question, to be able to critically appraise an article on diagnosis by answering three important questions • Is is valid? • Is it important? • Can we use it for our patient?
Goals • To understand definitions: sensitivity, specificity, positive predictive value, negative predictive value, likelihood ratio • Make sensitivity and specificity more useful • Distinguish between tests that rule in and rule out disease • Interpret likelihood ratios in the care of patients
Valid? • Was there an independent, blind comparison with a reference standard of diagnosis? • Was the test evaluated in an appropriate spectrum of patients (like those we actually see)? • Was the reference standard applied regardless of the diagnostic test result? • Was the test validated in a second group of patients?
Was there an independent, blind comparison with a reference standard of diagnosis? • Patients in study needed to have both the diagnostic test in question AND the reference standard • Results of one should not be known to those who are applying and interpreting the other
Was the diagnostic test evaluated in an appropriate spectrum of patients? • Did the report include patients having all the common presentations of the target disorder (early and late manifestations, mild and severe) • Did the report apply the test to patients with different disorders that are commonly confused with the target disorder?
Was the reference standard applied regardless of the diagnostic test result? • Investigators are tempted to forego applying the reference standard when patients have a negative diagnostic test result • When the reference standard is risky or invasive, it may be wrong to carry it out on patients with negative test results
Was the test validated in a second, independent group of patients? • Diagnostic tests are predictors, not explainers, of diagnoses • If a test performs well in a “test” set of patients, we are assured about its accuracy
Important? • Sensitivity • Specificity • Likelihood Ratios
What do we want when we diagnose something using a test? • To know what the probability of a disease is given a positive or a negative test • Rearranged: “given a positive test result, what is the new probability of disease?”
Tests can be anything • A lab • a positive ANA for “diagnosing” lupus • A radiology result • CXR rib notching for diagnosing coarcation • temporal lobe abnormality on MRI for HSV encephalitis • A specialty test • echo showing aortic stenosis
Tests can be anything • A physical finding • heliotrope rash for dermatomyositis • goiter for diagnosing Graves’ disease • fixed, split S2 for atrial septal defect • An element of the history • fever for endocarditis • forgetfulness for dementia
How do we get sensitivities and specificities? • Start with the grid • Disease • Test • 2 x 2 table of these
Sensitivity probability of a positive test among patients with disease On the graph: Specificity probability of a negative test among patients without disease Sensitivity and Specificity
Sensitivity a/(a + c) Specificity d/(b + d) Sensitivity and Specificity
Sensitivity and Specificity • They do not give us the information we need • What we need is for the test to help us diagnose a disease • That’s why we order the test • this helps us “confirm” (rule in) or “refute” (rule out) the diagnosis
Sensitivity SnNout in a highly Sensitive test, a Negative test rules out the disease Specificity SpPin in a highly Specific test, a Positive test rules in the disease Sensitivity and Specificity
Predictive Values • Positive Predictive Value: • probability of a disease among patients with a positive test • Negative Predictive Value: • probability of no disease among patients with a negative test
Positive Predictive Value a/(a + b) Negative Predictive Value d/(c + d) Predictive Values
Statistics Grid - Alex does it Sensitivity Specificity Positive Predictive Value Negative Predictive Value 0.8 0.6 0.67 0.75 .
Statistics Grid Sensitivity Specificity Positive Predictive Value Negative Predictive Value .
Practice 1 Negative Predictive Value Specificity Positive Predictive Value Sensitivity .
Practice 2 Specificity = Positive Predictive Value = Negative Predictive Value = Sensitivity = 60 / 60 + 40 = 0.6 80 / 80 + 40 = 0.67 60 / 60 + 20 = 0.75 80 / 80 + 20 = 0.8 .
Likelihood Ratio • When ordering a test, which tests will best help us rule in or rule out disease? • Initial assessment of likelihood of disease = pre-test probability • Final assessment of likelihood of disease = post-test probability
Likelihood Ratio • Pre-Test Probability • Post-Test Probability Do test
Likelihood Ratio Probability of strep throat
Likelihood Ratio • Probability of patient with disease having a given test result • Probability of patient without disease having a given test result
Positive Likelihood Ratio (LR+) • Probability of patient with disease having a positive test result • Probability of patient without disease having a positive test result
Negative Likelihood Ratio (LR-) • Probability of patient with disease having a negative test result • Probability of patient without disease having a negative test result
Likelihood Ratios • If ratio > 1: increases likelihood of disease • If ratio < 1: decreases likelihood of disease • If ratio is 1, the test did nothing to help rule in or rule out disease • by definition, this is anything a surgeon orders
LR+ sensitivity 1 - specificity LR- 1-sensitivity specificity Likelihood Ratios
LRs - Example LR+ = LR- =
Summary • Sensitivity SnNout • Specificity SpPin • Positive Predictive Value • Negative Predictive Value • Positive Likelihood Ratio • Negative Likelihood Ratio
Can I apply this test to my patient? • Is the diagnostic test available, affordable, accurate, and precise in our setting? • Can we generate a clinically sensible estimate of our patient’s pre-test probability? • Will the resulting post-test probabilities affect our management and help our patient?
Is test available, affordable, accurate and precise in our setting? • Available: if no, don’t order, or find out how to order • Some diagnostic tests based on symptoms or signs lose power as patients move from primary care to secondary and tertiary care • Only refer the positives, not the negatives
Can we generate a clinically sensible estimate of patient’s pre-test probability? • From personal experience, prevalence statistics, practice databases, or primary studies • Are study patients similar to our own? • Is it unlikely that the disease possibilities or probabilities have changed since this evidence was gathered?