DIAGNOSTICS AT WORK: From the clinic to the community

Nitika Pant Pai, MD, MPH., PhD

Madhukar Pai, MD, PhD

WHY SCREENING, DIAGNOSTIC AND PROGNOSTIC TESTS MATTER

o Diagnosis is the first and important step in the pathway to correct treatment• “Companion diagnostics” are emerging as a critical theme

o Early and rapid diagnosis can reduce morbidity, improve patient outcomes, and reduce cost of care

o Tests can o identify risk factors

o predict prognosis

o monitor therapy over time

o promote healthy behaviours

o tailor therapies (i.e. personalized medicine)

IN THE PAST, DOCTORS RELIED ON THEIR CLINICAL INTUITION…

Source: The Hindu

AND SOME BASIC TESTS LIKE MICROSCOPE

Antonie van Leeuwenhoek (1632–1723), the father of microbiology, is best known for his work to improve the microscope and use it for microbiology

Source: Wikipedia

STETHOSCOPE AND X-RAYS

Rene Laënnec in Paris invented the first stethoscope in 1816.

Wilhelm Rontgen detected x-rays in 1895.

Source: Wikipedia

TODAY, WE HAVE COME A LONG WAY…

www.nature.com

THE OLD STETHOSCOPE COMES OF AGE!

http://www.thinklabs.com/

TESTS FOR TUBERCULOSIS: FROM MICROSCOPE TO RAPID MOLECULAR TESTS (<2 HOURS)

TESTS FOR HIV: FROM THE LAB TO OUR HOMES

Source: www.insideradiology.com Source: www.siemens.co.uk

ULTRASONOGRAPHY: FROM SPECIALIST TO

FAMILY DOC

YOUR MOBILE SMARTPHONE HAS EMERGED AS A POWERFUL NEW

DIAGNOSTIC TOOL!

http://www.healthcanal.com/eyes-vision/41915-eye-phone-that-could-help-prevent-blindness.html http://lgtmedical.com/global-health/pneumonia.html

Retina imaging

Vital signs, oxygen saturation

YOUR TABLET IS NOW A HEALTH TECHNOLOGY

ASSISTANTThis Slate is a book-sized machine; it wirelessly communicates with an Android tablet and includes a bag of plug-and-play sensors that measure blood pressure and levels of blood sugar and hemoglobin, conduct electrocardiography (EKG) tests, etc.

http://www.the-scientist.com/?articles.view/articleNo/33761/title/A-Dime-a-Dozen/

WEARABLE HEALTH TECHNOLOGIES:

Fitbit, iWatch, OMwear RECORD SLEEP, VITAL SIGNS

http://www.nuubo.com/ http://www.cnet.com/news/wearable-tech-most-important-race-turning-heartbeats-into-cash/

WEARABLE HEALTH TECHNOLOGIES

http://www.medtronicdiabetes.com/res/img/misc/guardian-introducing.png

Real-time glucose monitoring

WE ARE SO READY FOR THE TRICORDER!

http://blogs-images.forbes.com/markpmills/files/2012/01/tricorder-spock1.jpg

INNOVATION: HIVSmart!: INTEGRATED SMARTPHONE

APP AND INTERNET BASED HIV SELF TESTING STRATEGY

PROBLEM: HEALTH FACILITY BASED

TESTINGoBarriers:

o Stigma and Discrimination

o Social Embarrassment

o Fear of visibility

o Lack of Confidentiality

o Judgemental Attitudes

o About 50% people WORLDWIDE and 25% DOMESTICALLY don’t

know their HIV status!!

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NEEDa. Confidential, Anonymous,

personalized, b. convenient, non invasive, cost

effective

c. Easy linkages, easy conduct

d. Saves time and money

HIV SELF-TEST APP: ANDROID, iPHONE

21Copyright protected. HIVSmart! is copyright protected authored by Dr Pant Pai and trainees (Roni Deli-Houssein, Sushmita Shivkumar, Caroline Vadnais) and owned by McGill University

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SMARTER CONDUCT & LINKAGES

© Pant Pai and McGill University 2013

SO, WE HAVE NOW ENTERED THE BRAVE NEW WORLD OF

DIAGNOSTICS!o Faster, Easier, time savingso Real-timeo Personalizedo Connectivity (from your

mobile to your doctor’s laptop)

o At point of clinical care, at home, any place, anywhere!

And the world of big data 1. Data:

1. Social, medical, genetic, daily caloric intake, daily sleep, vital signs. Step count, all will be available (in real time)

2. Anonymized, compliant with confidentiality guidelines

2. Sources:

1. from electronic medical records available on your phone, to your family physician and in your health facility

2. from smart wear and Fitbits- on the internet and phones

3. from personalized genomics testing are available on the cloud

3. What for?

1. For a personalized, plan for health promotion, targeted medication intake, monitoring, and better management.

This is all exciting, but…

HOW DO WE KNOW THESE NEW TESTS ARE ACCURATE? THAT THEY ACTUALLY MAKE A DIFFERENCE??

o This is where clinical epidemiologists enter the picture.

o Diagnostic tests, just like drugs and vaccines, need adequate validation before they can be used on people.

o Just like drug trials, we do diagnostic trials.

DIAGNOSIS VS SCREENING:

THEY ARE DIFFERENT!

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o A diagnostic test is done on sick people• patient presents with symptoms• pre-test probability of disease is high (i.e. disease

prevalence is high)

o A screening test is usually done on asymptomatic, apparently healthy people• healthy people are encouraged to get screened• pre-test probability of disease is low (i.e. disease

prevalence is low)

PROCESS OF DIAGNOSIS: ALL ABOUT PROBABILITY!

Test Treatment

Threshold Threshold

0% 100%

Probability of Diagnosis

No Tests

Need to Test Treat

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THE PERFECT DIAGNOSTIC TEST

☻☺

X YDisease No

Disease 31

VARIATIONS IN DIAGNOSTIC TESTS

☺ ☻ Overlap

Range of Variation in Disease free

Range of Variation in Diseased 32

SO, CUT-POINTS MATTER A LOT!

o Many tests produce continuous numbers, and doctors tend to use cut-points to make decisions

o Cut-points are a compromise – they are not perfect

o Same test can produce different results, based on cut-points used

o Cut-points can change over time

There is no perfect test!

All we can hope to do is increase or decrease probabilities, and Bayes’ theorem helps with this process

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BAYES' THEORY

pre-test probability

post-test probability

Test

Post-test odds = Pre-test odds x Likelihood ratio

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What you thought before + New information = What you think now

pre-test probability

LOW

post-test probability

HIGH

Test

o An accurate test will help reduce uncertainty

o The pre-test probability is revised using test result to get the post-test probability

o Tests that produce the biggest changes from pretest to post-test probabilities are most useful in clinical practice [very large or very small likelihood ratios]

pre-test probability

HIGH

post-test probability

LOWTest

Bayesian approach to diagnosis

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Steps in evaluating a diagnostic test

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o Define gold standard

o Recruit consecutive patients in whom the test is indicated (in whom the disease is suspected)

o Perform gold standard and separate diseased and disease free groups

o Perform test on all and classify them as test positives or negatives

o Set up 2 x 2 table and compute:

• Sensitivity• Specificity• Predictive values• Likelihood ratios

Evaluating a diagnostic test

• Diagnostic 2 X 2 table*:

Disease + Disease -

Test + True Positive

False Positive

Test - False Negative

True Negative

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Disease present

Disease absent

Test positive

True positives

False positives

Test negative

False negative

True negatives

Sensitivity[true positive rate]

The proportion of patients with disease who test positive = P(T+|D+) = TP / (TP+FN)

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Disease present

Disease absent

Test positive

True positives

False positives

Test negative

False negative

True negatives

Specificity[true negative rate]

The proportion of patients without disease who test negative: P(T-|D-) = TN / (TN + FP).

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Disease present

Disease absent

Test positive

True positives

False positives

Test negative

False negative

True negatives

Predictive value of a positive test

Proportion of patients with positive tests who have disease = P(D+|T+) = TP / (TP+FP)

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Disease present

Disease absent

Test positive

True positives

False positives

Test negative

False negative

True negatives

Predictive value of a negative test

Proportion of patients with negative tests who do not have disease = P(D-|T-) = TN / (TN+FN)

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Imagine a hypothetical population (some with disease and others without)

Loong T BMJ 2003;327:716-719©2003 by British Medical Journal Publishing Group

If a test was positive in everyone, what would you make of this test?

Loong T BMJ 2003;327:716-719©2003 by British Medical Journal Publishing Group

What about this scenario?

Loong T BMJ 2003;327:716-719

©2003 by British Medical Journal Publishing Group

In reality, most tests will produce these sorts of results

Loong T BMJ 2003;327:716-719

©2003 by British Medical Journal Publishing Group

Example: Ultrasonography for Down Syndrome

NUCHAL FOLD & DOWN SYNDROME

Down Syndrome

Yes No

Nuchal fold Positive 21 4 25

Negative 7 188 195

28 192 220

Sensitivity = 75%Specificity = 98%

LR+ = 36LR- = 0.26

N Engl J Med 1987;317:1371

The interpretation of this test will depend a lot on the context (i.e. prior

probability)

o Scenario 1:• Mrs. B, a 20-year old woman with a previous normal pregnancy,

seen at a community hospital

o Scenario 2:• Mrs. A, a 37-year old woman with a previous affected pregnancy,

seen at a high-risk clinic in a tertiary, referral hospital

o Who has a higher pretest probability of Down syndrome?

TAKE HOME MESSAGES

o Diagnostic tests are important and can help all of us

o But, they are not perfect

o Diagnostic and screening tests are very different and should not be confused

o Doctors and patients need to understand that all tests have their inherent error (i.e. false positives and false negatives)

o Tests should always be interpreted in context

o Tests should be avoided unless there is a clear indication

THANK YOU!!!We are grateful to:

• Prof Jim Hanley• Prof Abe Fuks• Mini-Med team:

• Elise, Gloria, Ibby & Kappy

• Department of Epidemiology, Biostatistics & Occupational Health

Slide credits: Sehar Manji, Executive Assistant