1 / 42

420 likes | 590 Vues

Diagnostic Testing. Ethan Cowan, MD, MS Department of Emergency Medicine Jacobi Medical Center Department of Epidemiology and Population Health Albert Einstein College of Medicine. The Provider Dilemma.

Télécharger la présentation
## Diagnostic Testing

**An Image/Link below is provided (as is) to download presentation**
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.
Content is provided to you AS IS for your information and personal use only.
Download presentation by click this link.
While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

**Diagnostic Testing**Ethan Cowan, MD, MS Department of Emergency Medicine Jacobi Medical Center Department of Epidemiology and Population Health Albert Einstein College of Medicine**The Provider Dilemma**• A 26 year old pregnant female presents after twisting her ankle. She has no abdominal or urinary complaints. The nurse sends a UA and uricult dipslide prior to you seeing the patient. What should you do with the results of these tests?**The Provider Dilemma**• Should a provider give antibiotics if either one or both of these tests come back positive?**Why Order a Diagnostic Test?**• When the diagnosis is uncertain • Incorrect diagnosis leads to clinically significant morbidity or mortality • Diagnostic test result changes management • Test is cost effective**Clinician Thought Process**• Clinician derives patient prior prob. of disease: • H & P • Literature • Experience • “Index of Suspicion” • 0% - 100% • “Low, Med., High”**Probability of Disease**0% 100% Testing Zone P(+) P(-) Threshold Approach to Diagnostic Testing • P < P(-) Dx testing & therapy not indicated • P(-) < P < P(+) Dx testing needed prior to therapy • P > P(+) Only intervention needed Pauker and Kassirer, 1980, Gallagher, 1998**Probability of Disease**0% 100% Testing Zone P(+) P(-) Threshold Approach to Diagnostic Testing • Width of testing zone depends on: • Test properties • Risk of excess morbidity/mortality attributable to the test • Risk/benefit ratio of available therapies for the Dx Pauker and Kassirer, 1980, Gallagher, 1998**Reliability**Inter observer Intra observer Correlation B&A Plot Simple Agreement Kappa Statistics Validity Sensitivity Specificity NPV PPV ROC Curves Test Characteristics**Reliability**• The extent to which results obtained with a test are reproducible.**Reliability**Not Reliable Reliable**Intra rater reliability**• Extent to which a measure produces the same result at different times for the same subjects**Inter rater reliability**• Extent to which a measure produces the same result on each subject regardless of who makes the observation**Correlation (r)**• For continuous data • r = 1 perfect • r = 0 none O1 O1 = O2 O2 Bland & Altman, 1986**Correlation (r)**• Measures relation strength, not agreement • Problem: even near perfect correlation may indicate significant differences between observations O1 r = 0.8 O1 = O2 O2 Bland & Altman, 1986**Bland & Altman Plot**O1 – O2 • For continuous data • Plot of observation differences versus the means • Data that are evenly distributed around 0 and are within 2 STDs exhibit good agreement 10 0 -10 [O1 + O2] / 2 Bland & Altman, 1986**a**b c d Simple Agreement Rater 1 Rater 2 • Extent to which two or more raters agree on the classifications of all subjects • % of concordance in the 2 x 2 table (a + d) / N • Not ideal, subjects may fall on diagonal by chance - + total - a + b + c + d total a + c b + d N**a**b c d Kappa Rater 1 Rater 2 • The proportion of the best possible improvement in agreement beyond chance obtained by the observers • K = (pa – p0)/(1-p0) • Pa = (a+d)/N (prop. of subjects along the main diagonal) • Po = [(a + b)(a+c) + (c+d)(b+d)]/N2 (expected prop.) - + total - a + b + c + d total a + c b + d N**K=1**K > 0.80 0.60 < K < 0.80 0.40 < K < 0.60 0 < K < 0.40 K = 0 K < 0 Perfect Excellent Good Fair Poor Chance (pa = p0) Less than chance Interpreting Kappa Values**n11**n12 ... n1C n21 n22 ... n2C . . . . ... ... . . nC1 nC2 ... nCC Weighted Kappa Rater 1 Rater 2 1 2 ... C total • Used for more than 2 observers or categories • Perfect agreement on the main diagonal weighted more than partial agreement off of it. 1 n1. 2 n2. . . . . C nC. total n.1 n.2 ... n.C N**Validity**• The degree to which a test correctly diagnoses people as having or not having a condition • Internal Validity • External Validity**Validity**Valid, not reliable Reliable and Valid**Internal Validity**• Performance Characteristics • Sensitivity • Specificity • NPV • PPV • ROC Curves**2 x 2 Table**Disease Status TP = True Positives FP = False Positives total noncases cases positives Test Result + TP FP negatives - FN TN total cases noncases N TN = True Negatives FN = False Negatives**Gold Standard**• Definitive test used to identify cases • Example: traditional agar culture • The dipstick and dipslide are measured against the gold standard**Sensitivity (SN)**Disease Status • Probability of correctly identifying a true case • TP/(TP + FN) = TP/ cases • High SN, Negative test result rules out Dx (SnNout) total noncases cases positives Test Result + TP FP negatives - FN TN total cases noncases N Sackett & Straus, 1998**Specificity (SP)**Disease Status • Probability of correctly identifying a true noncase • TN/(TN + FP) = TN/ noncases • High SP, Positive test result rules in Dx (SpPin) total noncases cases positives Test Result + TP FP negatives - FN TN total cases noncases N Sackett & Straus, 1998**Problems with Sensitivity and Specificity**• Remain constant over patient populations • But, SN and SP convey how likely a test result is positive or negative given the patient does or does not have disease • Paradoxical inversion of clinical logic • Prior knowledge of disease status obviates need of the diagnostic test Gallagher, 1998**Positive Predictive Value (PPV)**Disease Status • Probability that a labeled (+) is a true case • TP/(TP + FP) = TP/ total positives • High SP corresponds to very high PPV (SpPin) total noncases cases positives Test Result + TP FP negatives - FN TN total cases noncases N Sackett & Straus, 1998**Negative Predictive Value (NPV)**Disease Status • Probability that a labeled (-) is a true noncase • TN/(TN + FN) = TP/ total negatives • High SN corresponds to very high NPV (SnNout) total noncases cases positives Test Result + TP FP negatives - FN TN total cases noncases N Sackett & Straus, 1998**Vulnerable to Disease Prevalence (P) Shifts**Do not remain constant over patient populations As P PPV NPV As P PPV NPV Predictive Value Problems Gallagher, 1998**Flipping a Coin to Dx AMI for People with Chest Pain**ED AMI Prevalence 6% SN = 3 / 6 = 50%SP = 47 / 94 = 50% PPV= 3 / 50 = 6%NPV = 47 / 50 = 94% Worster, 2002**Flipping a Coin to Dx AMI for People with Chest Pain**CCU AMI Prevalence 90% SN = 45 / 90 = 50% SP = 5 / 10 = 50% PPV= 45 / 50 = 90%NPV = 5 / 50 = 10% Worster, 2002**1.0**Sensitivity (TPR) 0.0 0.0 1.0 1-Specificity (FPR) Receiver Operator Curve • Allows consideration of test performance across a range of threshold values • Well suited for continuous variable Dx Tests**Receiver Operator Curve**• Avoids the “single cutoff trap” Sepsis Effect No Effect WBC Count Gallagher, 1998**Area Under the Curve (θ)**1.0 • Measure of test accuracy • (θ) 0.5 – 0.7 no to low discriminatory power • (θ) 0.7 – 0.9 moderate discriminatory power • (θ) > 0.9 high discriminatory power Sensitivity (TPR) 0.0 0.0 1.0 1-Specificity (FPR) Gryzybowski, 1997**Problem with ROC curves**• Same problems as SN and SP “Reverse Logic” • Mainly used to describe Dx test performance**Physical Exam**+ OR CT Scan - - + No Appy Appy Appendicitis Example • Study design: • Prospective cohort • Gold standard: • Pathology report from appendectomy or CT finding (negatives) • Diagnostic Test: • Total WBC Cardall, 2004**Appendicitis Example**SN 76% (65%-84%) SP 52% (45%-60%) PPV 42% (35%-51%) NPV 82% (74%-89%) Cardall, 2004**Physical Exam**+ OR CT Scan - - + No Appy Appy Appendicitis Example • Patient WBC: • 13,000 • Management: • Get CT with PO & IV Contrast Cardall, 2004**Follow UP**• CT result: acute appendicitis • Patient taken to OR for appendectomy**But, was WBC necessary?**Answer given in talk on Likelihood Ratios

More Related