South Asian Cardiovascular Research Methodology Workshop Basic Epidemiology

South Asian Cardiovascular Research Methodology Workshop Basic Epidemiology Screening and its Useful Tools Thomas Songer, Ph. D

Screening • The early detection of – disease – precursors of disease – susceptibility to disease in individuals who do not show any signs of disease Goel

Purpose of Screening • Aims to reduce morbidity and mortality from disease among persons being screened • Is the application of a relatively simple, inexpensive test, examinations or other procedures to people who are asymptomatic, for the purpose of classifying them with respect to their likelihood of having a particular disease • a means of identifying persons at increased risk for the presence of disease, who warrant further evaluation

Diagnosis = Screening • Screening tests can also often be used as diagnostic tests • Diagnosis involves confirmation of presence or absence of disease in someone suspected of or at risk for disease • Screening is generally in done among individuals who are not suspected of having disease

Natural History of Disease Detectable subclinical disease Susceptible Host Subclinical Disease Point of Exposure Clinical Disease Diagnosis sought Onset of symptoms Screening Stage of Recovery, Disability, or Death

Screening Process Population (or target group) Screening Test Negative Test Positive Unaffected Affected Re-screen Intervene Clinical Exam

Examples of Screening Tests • • • Questions Clinical Examinations Laboratory Tests Genetic Tests X-rays Goel

Validity of Screening Tests Key Measures • • Sensitivity Specificity Positive Predictive Value Negative Predictive Value Paneth

Terminology Validity is analogous to accuracy The validity of a screening test is how well the given screening test reflects another test of known greater accuracy Validity assumes that there is a gold standard to which a test can be compared Paneth

Screening Test Disease Present Absent Positive a b a+b Negative c d c+d b+d N a+c

Screening Test Disease Present Absent Positive True positives False positives Negative False negatives True negatives

Sensitivity Screening Test • Proportion of individuals who have the disease who test positive (a. k. a. true positive rate) • tells us how well a “+” test picks up disease Disease yes no + - a c b d a+c b+d a+b c+d N Sensitivity = a a + c

Specificity Screening Test • Proportion of individuals who don’t have the disease who test negative (a. k. a. true negative rate) • tell us how well a “-” test detects no disease Disease yes no + - a c b d a+c b+d a+b c+d N Specificity = d b + d

Screening Principles • Sensitivity – the ability of a test to correctly identify those who have a disease • a test with high sensitivity will have few false negatives • Specificity – the ability of a test to correctly identify those who do not have the disease • a test that has high specificity will have few false positives

Predictive Value • Measures whether or not an individual actually has the disease, given the results of a screening test • Affected by – specificity – prevalence of preclinical disease – Sensitivity • Prevalence = a + c a + b + c + d

Screening Test Disease Present Absent Positive a b a+b Negative c d c+d b+d N a+c

Positive Predictive Value Screening Test • Proportion of individuals who test positive who actually have the disease Disease yes no + - a c b d a+c b+d a+b c+d N P. P. V. = a a + b

Negative Predictive Value Screening Test • Proportion of individuals who test negative who don’t have the disease Disease yes no + - a c b d a+c b+d a+b c+d N N. P. V. = d c + d

A test is used in 50 people with disease and 50 people without. These are the results. Screening Test Disease Present Absent Positive 48 3 51 Negative 2 47 49 50 50 100 Paneth

Screening Test Disease Present Absent Positive 48 3 51 Negative 2 47 49 50 50 100 Sensitivity = 48/50 Specificity = 47/50 Positive Predictive Value = 48/51 Negative Predictive Value = 47/49 Paneth

So… you understand the accuracy of a screening test … What is the next step? Put screening to use in the population

Considerations in Screening Severity Prevalence Understand Natural History Diagnosis & Treatment Cost Efficacy Safety

Criteria for a Successful Screening Program • Disease – present in population screened – high morbidity or mortality; must be an important public health problem – early detection and intervention must improve outcome

Criteria for a Successful Screening Program • Disease – The natural history of the disease should be understood, such that the detectable sub-clinical disease stage is known and identifiable

Criteria for a Successful Screening Program • Screening Test – should be relatively sensitive and specific – should be simple and inexpensive – should be very safe – must be acceptable to subjects and providers

Criteria for a Successful Screening Program • Have an Exit Strategy – Facilities for diagnosis and appropriate treatments should be available for individuals who screen positive – It is unethical to offer screening when no services are available for subsequent treatment

Screening Strategies High-Risk Strategy • Cost-effective • Intervention appropriate to the individual • Fails to deal with the root causes of disease • Subjects motivated • Small chance of reducing disease incidence Population Approach • Potential to alter the root causes of disease • Large chance of reducing disease incidence • Small benefit to the individual • Poor subject motivation • Problematic risk-benefit ratio

NCI Guidelines for Screening Mammography “There is a general consensus among experts that routine screening every 1 -2 years with mammography and clinical breast exam can reduce breast cancer mortality by about onethird for women ages 50 and over. ” “Experts do not agree on the role of routine screening mammography for women ages 40 to 49. To date, RCTs have not shown a statistically significant reduction in mortality in this age. ”

Screening is not always free of risk

In population screening…. False positives tend to swamp true positives in populations, because most diseases we test for are rare Paneth

Risks of Screening • True Positives – “labeling effect” (classified as diseased from the time of the test forward) • False Positives – anxiety – fear of future tests – monetary expense

Risks of Screening • False Negatives – delayed intervention – disregard of early signs or symptoms which may lead to delayed diagnosis

Sources of Bias in the Evaluation of Screening Programs • Lead time bias • Length bias • Volunteer bias

Lead time bias • Lead time: interval between the diagnosis of a disease at screening and the usual time of diagnosis (by symptoms) Lead Time Diagnosis by screening Diagnosis via symptoms

Bias in Screening: Lead-Time Bias • Consider a condition where the natural history allows for an earlier diagnosis, however, survival does not improve despite identifying it earlier • A screening program here will… – over-represent earlier diagnosed cases – survival will appear to increase • but in reality, it is increased by exactly the amount of time their diagnosis was advanced by the screening program – Thus there is no benefit to screening from a survival standpoint.

Lead time bias • Assumes survival is time between screen and death • Does not take into account lead time between diagnosis at screening and usual diagnosis. Survival = 14 years Diagnosis by screening in 1994 Death in 2008

Lead time bias Survival = 14 years True Survival = 10 years Lead Time 4 years Diagnosis by screening in 1994 Usual time of diagnosis via symptoms in 1998 Death in 2008

Bias in Screening: Length Bias • Most chronic diseases, especially cancers, do not progress at the same rate in everyone. • Any group of diseased people will include some in whom the disease developed slowly and some in whom it developed rapidly. • Screening will preferentially pick up slowly developing disease (longer opportunity to be screened) which usually has a better prognosis Paneth

O P Y D Biological onset of disease Disease detectable via screening Symptoms Begin Death Length bias Screening O P O O P Y O Y P D Y D P Y O O D P Y D D Time

Volunteer bias • Type of bias where those who choose to participate are likely to be different from those who don’t • Volunteers tend to have: – Better health – Lower mortality – Likely to adhere to prescribed medical regimens