Clinical Chemistry I - Lab Test Evaluation

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Questions and Answers

What is the formula for calculating sensitivity?

$\frac{TP}{TP + FP}$

$\frac{FN}{TP + FN}$

$\frac{TP}{TP + FN}$ (correct)

$\frac{TN}{TN + FP}$

Which of the following best describes specificity?

The ratio of true negatives to the sum of false positives and false negatives

The proportion of false negatives

The ability to correctly identify those without the disease (correct)

The ability to correctly identify those with the disease

How is the positive predictive value (PPV) affected by the prevalence of the disease?

PPV increases with higher prevalence (correct)

PPV decreases as prevalence increases

PPV increases with higher sensitivity

PPV is independent of prevalence

In a receiver operating characteristic (ROC) plot, what is primarily represented on the x-axis?

False positive rate Signup and view all the answers

What is the primary goal of a screening test with high sensitivity?

To ensure all potential positive cases are identified Signup and view all the answers

What term describes the best current method established for determining the presence of a disorder?

Gold standard Signup and view all the answers

Which of the following statements about false positives and false negatives is true in the context of diagnostic testing?

A false positive occurs when a test incorrectly indicates a disease is present. Signup and view all the answers

What does the likelihood ratio (LR) measure in clinical testing?

The ratio of the probability of the test being positive in those with the disease to those without Signup and view all the answers

What does a specificity of 95% imply regarding false positives?

5% of patients without the disease will test positive. Signup and view all the answers

If the prevalence of a disease is 0.1 and the population examined is 1,000,000, how many individuals are expected to have the disease?

100,000 Signup and view all the answers

What is the formula for calculating Positive Predictive Value (PV+)?

TP / (TP + FP) Signup and view all the answers

What does a sensitivity of 90% indicate regarding false negatives?

10% of patients with the disease will test negative. Signup and view all the answers

How is the Likelihood Ratio (LR) defined?

The probability of a positive test result among patients with the disorder compared to those without. Signup and view all the answers

Given the following data: 100 have the disease and test positive, 5 have the disease and test negative, 7 do not have the disease and test positive, and 95 do not have the disease and test negative, what is the Positive Predictive Value (PV+)?

87.5% Signup and view all the answers

If there are 5 false negatives in a test group, what can be inferred about the sensitivity?

Not all patients with the disease test positive. Signup and view all the answers

What percentage of positive results in this scenario would be considered to have the disease if 100 are true positives and 7 are false positives?

93.75% Signup and view all the answers

Study Notes

Clinical Chemistry I - 0202304

Course instructor: Mohammad Qabajah
Email: [email protected]

Week 05&06 - Clinical Evaluation of Laboratory Tests

Objectives:
- State formulas for calculating clinical sensitivity, specificity, and predictive value of a lab test.
- Explain how prevalence affects a lab test's predictive value.
- Construct a receiver operating characteristic (ROC) plot using diagnostic test data.
- Interpret difference plots used in method comparison.

Agreement of Test Results: Accurate Diagnosis

Key concepts:
- Sensitivity and Specificity
- Predictive Values
- Prevalence
- Likelihood Ratio (LR)
- Odds Ratio (OR)

Review: Gaussian Probability Distribution

Distribution graph shown, with key percentiles marked:
- 99.7%
- 95%
- 68%
Values are shown on the horizontal axis (e.g., -3σ, -2σ, -1σ, μ, +1σ, +2σ, +3σ).

Sensitivity and Specificity

True Positive Rate:
- Sensitivity—measures the proportion of true positives correctly identified.
- Predictive models or algorithms are used to correctly identify true positive cases.
True Negative Rate:
- Specificity — measures the proportion of true negatives correctly identified.
- Predictive models or algorithms correctly identify true negative cases.

Negative and Positive

Graph depicting true negatives (disease absent) and true positives (disease present).
Shows false negatives and false positives as areas on the graph.

Source of the False

Graph similar to the previous one, but with a focus on false negatives and false positives.

Reference Method (Gold/Reference Standard)

"Best current practice" for confirming a disorder.
Screening:
- High sensitivity (high false positives, low false negatives)
- Finds all possible positives for further testing
- Ensures no one is missed
Diagnostic:
- High specificity (low false positives, high false negatives)
- Excludes individuals without the disease;
- Ensures no one with the disease is missed.
- Diagnostic testing should be done on all positive screened results.

Sensitivity and Specificity (Table)

Table outlines True Positives (TP), False Negatives (FN), False Positives (FP), and True Negatives (TN).
Shows the relationship to how the results are categorized and used for analysis.

Sensitivity and Specificity (Formulas)

Sensitivity: TP / (TP + FN)
Specificity: TN / (FP + TN)
% Sensitivity: (TP / (TP + FN)) * 100
% Specificity: (TN / (FP + TN)) * 100

Predictive Values

Positive Predictive Value (PV+): TP / (TP + FP)
Negative Predictive Value (PV−): TN / (TN + FN)

Prevalence

Frequency of a condition in a given population.
Example: 1 in 10 (0.1) in a population of 1,000,000

Example: Sensitivity, Specificity, PV+, and PV-

Example data provided, showing how to calculate Sensitivity, Specificity, positive predictive value , and negative predictive value.
Prevalence of the disease affects the positive and negative predictive values.

Likelihood Ratio (LR)

Likelihood that a symptom is related to the target disease, compared to the likelihood of the symptom in the absence of the disease.
Positive Likelihood Ratio (+LR): Sensitivity/(1-Specificity)
Negative Likelihood Ratio (-LR): (1-Sensitivity)/Specificity

Likelihood Ratio (LR) - Table

Table showing Likelihood Ratio values and their relationship to change in probability of disease (e.g., LR of 0.1 decreases probability by 45%).
Good LR tests are +LR > 10, or - LR < 0.1
Relationship between sensitivity, specificity, and likelihood ratios: a nomogram is provided using this info to show the zones of good tests (strong positive/negative findings).

Odds Ratio (OR)

Probability of a disease's presence divided by probability of absence.
The calculation of Pretest odds, Posttest odds, and Posttest probability
Example of a blood pressure test and how to analyze the likelihood results.

LR Nomogram

The graph shows different likelihood ratios and how they correlate to sensitivity vs specificity
How these measures can be used to create a quick analysis on the LR test value.

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Description

This quiz focuses on the clinical evaluation of laboratory tests, covering key concepts such as sensitivity, specificity, predictive values, and the effects of prevalence on these metrics. Additionally, it includes constructing ROC plots and interpreting difference plots for method comparison, essential for accurate diagnosis.