Diagnostic Measurements Primer
*This microcourse includes optional CPE Credits and is powered by Biotech Primer, a trusted leader in life science training that simplifies complex topics for non-scientists.
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Optional CPE Credit: 1.0
Overview:
Diagnostic Measurements Primer unravels the importance of direct and indirect measurements and their vital role in obtaining regulatory approval. This class begins with the art of constructing and reading a standard curve to determine unknown analyte concentrations. The agenda extends to testing accuracy, focusing on the ins and outs of specificity, sensitivity, false positives/false negatives, and true positives/true negatives. These concepts are reinforced with a graphics exercise on distributions, exploring the varied factors contributing to data variability and bi-modal distribution. This class ends with two real-world case studies critiquing data from mammography for breast cancer and PSA diagnostics for prostate cancer.
- Section 1: Introduction to Measurements: Introduces the concept of measurements and discusses the process of producing, using and interpreting a standard curve when attempting to determine the results of a diagnostic test.
- Section 2: Variability of Measurements: Explains how a diagnostic’s variability measurements determine if a patient falls into a normal or abnormal distribution for a disease.
- Section 3: Examples of Test Distributions: Discover the relationship between blood pressure, cholesterol, and atherosclerotic disease, exploring the concept of bi-modal distribution and the ideal distribution of these health indicators.
- Section 4: Testing Accuracy: Gain insights into measurement considerations, accuracy, false positives, false negatives, specificity, sensitivity, and predictive values, illustrated with examples such as mammography for breast cancer and PSA diagnostics for prostate cancer.
By the end of the course, participants will be able to:
- Produce and interpret a standard curve to analyze a diagnostic’s results.
- Recognize types of data distributions and how each is used to determine if a patient’s condition falls in the normal or abnormal range.
- Explain how precision, bias, specificity, and sensitivity measurements determine the accuracy of a diagnostic.
- Discuss how false positive and false negative percentages and their comparison to the reference product determine regulatory approval for a novel diagnostic.
- Choose the correct measurement to determine a patient’s disease state.
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