BIO 302 - Exam 2 - Screening for Cancer PowerPoint Flashcards
Cancer patient management is guided by the following principles:
(1) The earlier the cancer is discovered and effectively treated, the better the outcome for most cancers.
(2) The right therapy and management are dependent on the right diagnosis and assessment.
(3) All cancer therapies have undesirable effects: the goal is to have desirable effects outweigh undesirable effects.
Screening for cancer involves:
(1) Testing people without symptoms
(2) Testing defined populations (not everyone)
(3) Usually restricted to individuals at risk for cancer
Risk is defined by what 5 things:
For most cancers there are no effective screening tests!
Age (in everyone)
Family history
Personal history
Genotype
Exposures
Why Screen for Cancer?
(1) Cancer is a common disease
Pre-clinical phases of cancer can be long, therefore, there’s time for proactive search for early stage disease.
(2) Cancer in late stage (after symptoms develop) can be lethal and treatment of advanced cancers is NOT very effective overall - It’s dangerous to wait.
(3) Effective screening to find and treat cancers or pre-cancers at early stages of development can save lives for some cancer types (proven for cervical and colon cancer).
What are the problems?
False positive tests lead to over-diagnosis, over-treatment and needless burden for patient and healthcare system
False negative tests lead to under-diagnosis and missed opportunity for life-saving early treatment
Performance of Screening Tests:
Disease Present:
True Positive and False Negative
No Disease:
False Positive and True Negative
What is Test Sensitivity?
Sensitivity = 100% if…
Sensitivity is 80% if the test is positive in 80% of patients with the disease but 20% of those with the disease would go undetected as ______ ______.
Sensitivity does not take ______ ______ into account.
Test sensitivity: A test’s ability to correctly identify those WITH the disease.
Sensitivity = 100% if ALL patients with disease test positive*
*Tests are never perfect – so this NEVER happens
Sensitivity is 80% if the test is positive in 80% of patients with the disease but 20% of those with the disease would go undetected as FALSE NEGATIVES
Sensitivity does not take FALSE POSITIVES into account, so some people may be falsely diagnosed even if the sensitivity is 100%
What is Test Specificity?
Specificity = 100% if…
Specificity is 80% if the test is negative in 80% of patients without the disease but 20% of those without the disease would be misdiagnosed as ______ ______.
Specificity does not take ______ ______ into account.
Test specificity: A test’s ability to correctly identify those WITHOUT the disease.
Specificity = 100% if all those WITHOUT disease test negative*
*Tests are never perfect - so this NEVER happens
Specificity is 80% if the test is negative in 80% of patients without the disease but 20% of those without the disease would be misdiagnosed as FALSE POSITIVES
Specificity does not take FALSE NEGATIVES into account, so some people with disease may be falsely assured that they don’t have the disease even if the specificity is 100%
What is the diagnostic threshold (DT)?
When everyone in a population is tested, those with and without disease will have a spectrum (bell curve) of results due to human variation; the curves usually overlap.
In the overlapping range, people with or without disease may have the same test rest; the more the curves overlap, the less the discriminatory power of the test.
The DT will always miss some true positives and includes some false negatives.
moving the diagnostic threshold (DT) changes the proportion of false results (slide 11)
What is the Positive predictive value (PPV)?
Equation?
As ______ ______ go up, the predictive value of the test declines.
Positive predictive value (PPV): the probability that those with a positive test actually have the disease.
PPV = _______ True Positives__________ x 100
True Positives + False Positives
false positives
What is the Negative predictive value (NPV)?
Equation?
As ______ ______ go up, the predictive value of the test declines.
Negative predictive value (NPV): the probability that those with a negative test don’t have the disease.
NPV = ________True Negatives_________ x 100
True Negatives + False Negatives
false negatives
The ______ the disease, the more likely ______ ______ are to be.
A test that is 100% ______ and 100% ______ would be needed.
rarer / false positives
sensitive / specific
3 common diseases but poor test performance.
Mammography - Breast Cancer - 50-60% False Positives
Fecal occult blood - Colon - 90-98% False Positives
Prostate specific antigen (PSA) - Prostate - 75% False Positives.
US Preventive Services Task Force (USPSTF) evaluation and recommendations
What separates the different grades?
Slide 19