Module 6 - Lab Test Significance

Question 1

pathology tests

Answer 1

typically do not measure, but identify cells or tissue structures that may be associated with disease

Question 2

tests with numeric measurements

Answer 2

can have a range of values that are considered normal. The normal range can be statically determined and defined (reference range)

Question 3

Frequency Chart Showing Normal Distribution
-slide 3 of module 6

Question 4

the Gaussian (or normal) distribution of data

Answer 4

-with a normal distribution, only about 5% of all results are more that 2 standard deviations (SD) above or below the mean of the population
-if a result is within 2 SD range then it is usually considered normal and if it is outside then it is abnormal
-referred to as a reference range (RR)

Question 5

analytic variation: (test result reproducibility)

Answer 5

-how much does the measurement vary between replicate tests of the same sample
-samples that are unexpectedly outside RR may be retested

Question 6

biological variation: (usually within RR)

Answer 6

-how much does a test vary between two samples taken at different times from 1 person?
-ex. Blood pressure measured during times of stress vs at rest

Question 7

Contingency Table (get from note)

Answer 7

True positive (TP): test indicated abnormal and those poop have disease
True negative (TN): test indicated normal and those people have no disease
False positive (FP): test indicates abnormal but person has no disease
False negative (FN): test indicates normal but person has disease

Question 8

Sensitivity

Answer 8

-a sensitive test is one that detects all of the people with a disease (affected)
-sensitivity = TP/all with disease (tp + fn) x 100
-a 100% sensitivity test has no false negatives and all true positives
-example:
-a test for infection with 50 disease patients, 48 TP and 2 FN
48/48+2 x 100 = 96%

Question 9

Specificity

Answer 9

-a specific test is one that detects all of the people without a disease (healthy)
-specificity = TNx100/all without disease (TN+FP)
-a 100% specific test has no false positives, detects all people without a disease
-example:
- attest for disease free clients with a 25TN and 10FP
-specificity = 25/10+25 x 100 = 74%

-where to set the positive/negative cutoff or diagnostic cutoff can depend on risks involved with false positive versus false negative

Question 10

Positive Predictive Value of a Test: PPV

Answer 10

-what is the likelihood that the test, if reported positive, means the disease is present
-PPV = TP/TP+FP x 100

Question 11

go through doc to practice calculations

Question 12

Sensitivity - more urgent disease (cancer/HIV)
Specificity - less urgent (UTIs)