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4/20/2015 Clinical Epidemiology Jeffrey A. Summers, MD FACP Professor, Department of Medicine Quillen College of Medicine ETSU Definition Causes, distribution, and effects of health and disease in populations The Investigation and control of the distribution and determinants of disease The science of making predictions about individual patients by counting clinical events in similar patients, using strong scientific methods for studies of groups of patients to ensure that the predictions are accurate Easy Definition All That Statistics Stuff 1 4/20/2015 Outline Testing in Populations Risk - Relative, absolute Kinds of Clinical Research Studies P Values Populations True False TP FP TN FN + - Populations Spin and Snout 2 4/20/2015 Populations Sensitivity, Specificity, Positive and Negative Predictive Values all reflect ACCURACY in a PARTICULAR POPULATION Populations Sensitivity - Accuracy in SICK Specificity - Accuracy in WELL PPV - Accuracy in those with a POSITIVE TEST NPV - Accuracy in those with a NEGATIVE TEST Sensitivity Accuracy in Sick = How many sick people have a positive test Specificity Accuracy in Well = How many well people have a negative test 3 4/20/2015 Positive Predictive Value Accuracy in Positive Test = How many people with positive test are sick Negative Predictive Value Accuracy in Negative Test = How many people with a negative test are well Predictive Value is Dependent on Prevalence Calculate Sensitivity and Specificity You do a study of PET scanning for CAD. 1000 patients are tested, with 400 positive tests. Of those with positive tests, 390 had abnormal angiograms. Of the 600 with negative tests, 20 had abnormal angiograms. What is the sensitivity, specificity, and positive and negative predictive values? Calculate S/S and Predictive values Sens: There were 410 patients with disease, 390 had positive tests. Sensitivity = 95% Spec: There were 590 patients without disease, 580 had negative tests. Specificity = 98% PPV: There were 400 positive tests, 390 with disease. PPV = 97.5 NPV: There were 600 negative tests, 580 without disease. NPV = 96.7% Prevalence of CAD is 410/1000 or 41% 4 4/20/2015 Bismarck Problem You are the Director of the Health Department in Bismarck, ND, lucky you. The City Council has heard that HIV testing is 99% sensitive and 99% specific and would like to require HIV testing for all couples about to marry. The prevalence of HIV in Bismarck is 1 in 1000. What is the likelihood that a screened person with a positive test actually has HIV? Solution Assume 10,000 screened. In that group, there will be 10 with HIV. With 99% sensitivity, 9.9 of those will test positive (99% of 10). Of the 9990 that do not have HIV, 99% will have negative tests (99% specific). 1% will have positive tests, or 99.9 people (1% of 9990). Rounding, 110 positive tests, 10 true positives. Positive Predictive Value is then 10/110 or 9%. There is a 9% probability that a person in that population with a positive test actually has HIV Risk/Risk Reduction Absolute Risk Reduction Relative Risk Reduction 5 4/20/2015 Absolute Risk Reduction There is a risk of something happening. You do something to modify the risk. The difference (subtraction) between the original risk and new risk is the absolute risk reduction. Relative Risk Reduction There is a risk of something happening. You do something to reduce the risk. The difference between the old and new risk (subtraction) DIVIDED by the old risk is the relative risk reduction Clopidogrel Early study of clopidogrel showed a reduction in mortality in MI with the med from 3% to 2%. Absolute risk reduction = 3-2 = 1% Relative risk reduction = (3-2)/3 = 33% Which was used in ads, and pushed to change guidelines??? 6 4/20/2015 Number Needed to Treat Number Needed to Treat (NNT) is the reciprocal of the Absolute Risk Reduction (1/ARR) 1% ARR means number needed to treat to benefit one patient is 100. Cost Benefit Cost Benefit is the NNT times the cost, or the cost to benefit one patient. In our clopidogrel example, cost is 100*cost of treating with clopidogrel for 1 year, which at $3.50 per pill was $127,750 to benefit one patient. Clinical Research Studies Cohort - start with a group that gets an intervention, follow outcomes. Can be prospective or retrospective. Case Control - start with group with the outcome, match controls, and look at differences. Better for rare conditions. Cross-sectional (survey, prevalence) 7 4/20/2015 Question In an "outcomes" analysis of coronary bypass surgery, health services researchers identify charts of all patients diagnosed with three vessel disease at three major clinical centers during the past ten years. These patients are separated into those who initially were treated surgically and those who were initially treated medically, with surgery used if medical treatment was unsuccessful. Aggregate results for mortality and a variety of other outcome variables were compiled for each group, to produce prognostic profiles for those initially treated medically vs. those who received immediate surgery. This study was a: A. B. C. D. E. prospective cohort study retrospective cohort study cross-sectional survey hospital-based case-control study controlled clinical trial Question In a study examining the relationship between oral contraceptives and bacteriuria, you follow women who do and do not use oral contraceptives over a three-year period, and find that 70 of the 500 individuals who use OC acquired bacteriuria, while 150 of 3000 individuals who don’t use OC acquired bacteriuria. Is this a cohort or case-control study? What is the absolute risk conferred by the OCs? What is the relative risk conferred by the OCs? Answers It is a cohort study. Risk of bacteriuria with OCs is 70/500= 0.14 Risk without OCs is 150/3000= 0.05 Absolute risk conferred is 0.14-0.05= 0.09 (9%) Relative risk conferred is 0.14/0.05= 2.8 8 4/20/2015 P Values Lots of incorrect definitions NOT the probability the conclusion is wrong NOT the probability that the null hypothesis is true P Value P value is the Probability, given the null hypothesis is true, that you would have gotten the results you did. In other words, if the null hypothesis is true, there is only a n% chance that the study would have come out the way it did P Value p<0.05 Cutoff is historical. Story behind it is hysterical. 9