DIAGNOSTIC & SCREENING

DIAGNOSTIC & SCREENING Evidence-based Medicine

Masalah experience-based medicine Pengalaman/Data Empiric Nilai-nilai kebenaran Nilai-nilai pembenaran Appendisitis akut McBurney sign (+) McBurney sign (+) Appendisitis akut

Negative appendectomy: 20-40% Use of USG vs. CT Scan in diagnosing acute appendicitis Sensitivity Specificity USG 8798 CT Scan 92 100 Sensitivity Specificity USG 7696 CT Scan 8393 Styrud et al, , Intl J for Quality in Health Care, 2000

Foreground Question Clinical Question P I C O Patient Or Problem Intervention Comparison Outcomes More sensitive & specific CT scan USG Appendicitis

Natural History of Disease Preclinical Clinical Outcome A B C D E F • Biologic onset of the condition • Pathologic evidence of disease detectable by screening • Signs and symptoms of disease • Health care sought • Diagnosis of disease • Treatment of disease

Issues in Screening Definition Improve outcomes of illness • Improve morbidity: example • Improve mortality: example Early detection of preclinical disease in asymptomatic persons Purpose of screening

DEFINITION: Screening The assessment or evaluation of people, who have no symptoms of disease, in order to classify them as to likelihood of having a particular disease

Difference Between Diagnostic and Screening Test Diagnostic testing is used to confirm diagnosis in a patient who is sick Screening test is offered to subjects who are free of symptoms or signs of disease

Objectives diagnostic screening detect disease at all stage detect early stage of disease However, in clinical practice diagnostic results may be in error

Blood pressure Scoliosis Vision/Glaucoma Mammography Pap smears Cholesterol Diabetes Depression Nutrition screening Drug/alcohol use Lead Abuse Fall risk Examples Of Screening Tests

WHY WE NEED A GOOD DIAGNOSTIC TEST

Widal agglutination test Thypoid

109 years after its invention (1896 – 2005) Causes of negative Widal agglutination tests • absence of infection by S typhi • the carrier state • an inadequate inoculum of bacterial antigen in the host to induce antibody production • technical difficulty or errors in the performance of the test • previous antibiotic treatment • variability in the preparation of commercial antigens Postgrad Med J 2000;76:80–84

Causes of positive Widal agglutination tests • the patient being tested has typhoid fever • previous immunisation with Salmonella antigen. • cross-reaction with non-typhoidal Salmonella. • variability and poorly standardised commercial antigen preparation • infection with malaria or other enterobacteriaceae • other diseases such as dengue

Diagnostic tool Sensitivity Specificity (%) (%) • Multi-Test Dip-S-Ticks • for Serotype Typhi 89 50 • TyphiDot 79 89 • TUBEX 78 94 • Widal testing in • the hospitalb 64 76 • Widal testing at the • Pasteur Institute 61 100

Characteristics of Validity the ability of a test to correctly identify those who have the disease or condition Sensitivity the ability of a test to determine those who do not have the disease Specificity

test result negatif Test result positive No treatment might be given Wrong treatment (medical error)

False positive/negative Highly sensitive/specific Diagnostic/screening Diagnostic/screening Misleading Accurate Best diagnostic tools

Pneumonia No Pneumonia Respiratory rate DIAGNOSTIC TEST PROCEDURE GOLD STANDARD Pneumonia No Pneumonia Pneumonia No Pneumonia

Gold Standard for Dx Disease (+) No Disease T E S T Disease(+) No Disease False positive True positive False negative True negative

Sensitivity& Specificity How to calculate these using a 2 X 2 table

Gold Standard for Dx Disease (+) No Disease T E S T Disease(+) No Disease a b c d a + c b + d Sensitivity = a / (a+c) x 100% is the proportion of patients with disease who test positive Sensitivity is the ability of the test to detect the presence of disease

Diagnostic test for anemia using ferritin Sensitivity = 90% of those who have anemia, 90% will test positive It also means that in those that have anemia, 10% will test negative (i.e. there is a 10% false negative rate in those with anemia) Positive = 90% anemia Dx test Negative = 10%

Gold Standard for Dx Disease (+) No Disease T E S T Disease(+) No Disease a b c d a + c b + d Specificity = d / (b+d) x 100% is the proportion of patients without disease who test negative Specificity is the ability of the test to detect the absence of disease

Diagnostic test for anemia using ferritin Spesificity = 85% of those who do not have anemia, 85% will test negative It also means that in those that do not have anemia, 15% will test positive (i.e. there is a 15% false positive rate in those without anemia) Positive = 15 % Non anemia Dx test Negative = 85%

Pretest Probability • is the estimated likelihood of disease before the test is done • = prior probability If a defined population of patients is being evaluated, the pretest probability is equal to the prevalence of disease in the population. It is the proportion of total patients who have the disease.

Note that ……………………….. Sensitivity is calculated based only on those who have disease, and specificity is calculated only on those who do not have disease Therefore, neither sensitivity nor specificity are affected by the prevalence of the target condition

The trade off between sensitivity and specificity In most cases as sensitivity increases, specificity decreases, and vice versa (i.e they are inversely related to each other

The Sensitivity/specificity trade off An example of when you might want a high sensitivity is a screen for neonatal hypothyroidism (you wouldn’t want many false negatives which might lead to irreversible cognitive damage

The Sensitivity/specificity trade off An example of when you might want a high specificity is a screen for HIV (you wouldn’t want many false positives due to the emotional trauma)

True positive: “ . . . individuals with the condition who are correctly identified as diseased by the new test” False positive: . . . individuals without the condition who are falsely identified as diseased by the new test”. This is also referred to as a mis-diagnosis. (Knapp and Miller, 1992)

True negative “ . . . individuals without the condition who are correctly identified as diseased-free by the new test” False negative: “ . . . individuals with the condition who are falsely identified as disease-free by the new test”. This is also referred to as a missed diagnosis.

Predictive Value Positive (PVP) • “ . . . probability that an individual with a positive test result has the disease. • PVP is also known as the posterior probability, positive predictive value or posttest probability or disease” Predictive Value Negative • “ . . . probability that an individual with a negative test result does not have the disease. • PVN is also known as negative predictive value”

Predictive value of a positive test is the proportion of patients with positive tests who have disease. • This is the same thing as posttest probability of disease given a positive test. It measures how well the test rules in disease.

Gold Standard for Dx Disease (+) No Disease T E S T Disease(+) No Disease + PV = a/ (a+b) a b c d Positive Predictive Value (PV+) = (a/a+b) X 100 (%) • = Posttest probability • = the proportion of patients with positive tests who have disease

Gold Standard for Dx Disease (+) No Disease T E S T Disease(+) No Disease a b c d - PV = d/ (c+d) Negative Predictive Value (PV-) = (d/c+d) X 100 (%) Proportion of true negatives among all those with negatives results

Note that ……………………….. Positive and negative predictive values are calculated using both those with disease, and those without disease Therefore, both positive and negative predictive values are affected by prevalence of the target condition

CHEST X-RAY No Pneumonia Pneumonia + PV = a/ (a+b) a b c d Pneumonia RESPI RATORY - PV = d/ (c+d) No Pneumonia Sensitivity a / (a+c) Specificity d / (b+d)

FOTO RONTGEN No Pneumonia Pneumonia RESPIRASI a b c d Pneumonia No Pneumonia Accuracy = (a+d) / N Prevalence = (a+c) / N

FOTO RONTGEN No Pneumonia Pneumonia a b c d Pneumonia RESPIRASI No Pneumonia a/a + c LR + = ---------- b/b + d c/a + c LR - = ---------- d/b + d

Likelihood ratio positive: Probability of having the test result positive among those who have disease Likelihood ratio negative: Probability of having the test result negative among those who don’t have disease

Diagnostic test for anemia using ferritin

Test-Treatment Threshold Post-test probability

LIKELIHOOD RATIO • Probability of having a test result (positive or negative) in a person with disease compared to the test result (positive or negative) of person with disease free What does this mean? LR (+) = 12,3 LR (-) = 0,39

Primary questions for Diagnostic Test • Is this evidence about the accuracy of a • diagnostic test valid? 2. Does this (valid) evidence demonstrate an important ability of this test to accurately distinguish patients who do and don’t have a specific disorder? 3. Can I apply this valid, important diagnostic test to a specific patient?

Is this evidence about a diagnostic test valid? 1. Was there an independent, blind comparison with a reference (“gold”) standard of diagnosis? 2. Was the diagnostic test evaluated in an appropriate spectrum of patients (like those in whom we would use it in practice)? 3. Was the reference standard applied regardless of the diagnostic test result? 4. Was the test (or cluster of tests) validated in a second, independent group of patients?

1. Was there an independent, blind comparison with a reference (“gold”) standard of diagnosis? diagnostic test in question “gold” standard • history or • physical examination, • a blood test • autopsy or • biopsy BLINDING

DIAGNOSTIC & SCREENING