Biotech Primer Institute

Statistical Features of Diagnostics

10 STUDENTS ENROLLED

Course Availability: Unlimited views for 72 hours from time of purchase
Course Running Time:
 47 min | Assessment: 20 min
Course Material: Downloadable PDF of all presented slides
Preview Now: Specificity & Sensitivity

Statistical Features Of Diagnostics explores the basic measurement concepts used in the development and evaluation of a diagnostic. These included variability and distribution, standard curve, accuracy, and sensitivity and specificity. Using these measurements participants learned how false negative/false positive are determined and how those results are compared to a “Gold Standard” to determine the likelihood of receiving diagnostic approval for marketing. Running time: 47 minutes/Assessment: 20 minutes

Measures: Determining Unknowns
At the end of this section you should be able to:
1. Identify the gold standard
2. Appreciate how testing a new diagnostics against a gold standard is crucial when seeking FDA approval
2. Produce, use, and interpret a standard curve

Measures: Variability & Distributions
At the end of this section you should be able to:
1. Interpret measurements and graphic distributions
2. Determine if a patient falls into normal or abnormal distribution for disease as determined by diagnostic tests

Examples of Test Distributions
At the end of this section you should be able to:
1. Analyze various bi-model distributions diagnostic tests to determine if patients fall within the normal or abnormal range for disease
2. Identify an ideal distribution for diagnostic tests

Measurement Considerations
At the end of this section you should be able to:
1. Recognize all measurements have sample and instrument variability
2. Choose the correct measurements to determine disease state of a patient

Accuracy of a Measurement
At the end of this section you should be able to:
1. Define accuracy, precision, and bias
2. Determine if a diagnostic is accurate or not

Specificity & Sensitivity
At the end of this section you should be able to:
1. Differentiate between sensitivity and specificity
2. Calculate and interpret sensitivity and specificity

Positives & Negatives
At the end of this section you should be able to:
1. Define false positive and false negative
2. Calculate and interpret percentages of false positives and false negative

Risks of Diagnostics
At the end of this section you should be able to:
1. Calculate and interpret positive predictive value
2. Understand how to use a ROC curve and interpret the strength of the diagnostic

Examples of Diagnostics: Mammogram & PSA Testing
At the end of this section you should be able to:
1. Explain the risks associated with screening for low prevalence diseases

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