Disease Screening: Understanding Tests and Validity

Disease Screening: Understanding Tests and Validity

What is Screening?

Screening is a method of secondary prevention that uses simple tests (physical, laboratory, etc.) to detect diseases before they manifest symptoms or signs. The goal of screening is to reduce morbidity and mortality through early detection and intervention.

Types of Screening Programs:

• Mass Screening: Targets the entire population (e.g., mammograms for women aged 45-70).
• Multiple/Multiphasic Screening: Uses a variety of tests at the same time (e.g., during hospital admission).
• Targeted Screening: Focuses on groups with specific risk factors (e.g., occupational exposure).
• Case-Finding/Opportunistic Screening: Occurs when a patient consults a doctor for another reason (e.g., blood pressure check).

Criteria for Implementing a Screening Program:

Disease-Related Criteria:

• Seriousness of the disease (medical and social impact).
• High prevalence of the pre-clinical stage.
• Understanding the natural history of the disease.
• Availability of effective treatment options.

Diagnostic Test-Related Criteria:

• High sensitivity and specificity.
• Simple, cheap, rapid, safe, acceptable (non-invasive), reliable, and effective tests.

Diagnostic Facilities-Related Criteria:

• Adequate, effective, acceptable, and safe facilities for diagnosis and treatment.

Ethical Considerations:

Screening programs must consider the potential for false positive and false negative results. Participation in screening should always be voluntary.

Costs and Effectiveness:

Screening entire populations can be expensive. Selective screening of at-risk groups can improve cost-effectiveness.

Examples of Commonly Screened Diseases:

• Hypertension
• Diabetes
• Tuberculosis
• Lung cancer
• Breast cancer
• Cervical cancer
• Phenylketonuria

Validity of Diagnostic Tests

Diagnostic tests aim to make a definitive diagnosis or narrow down the differential diagnosis. However, no test is perfect.

Key Parameters of Test Validity:

Sensitivity:

The ability to correctly identify people with the disease (true positive rate).

Specificity:

The ability to correctly identify people without the disease (true negative rate).

Positive Predictive Value (PPV):

The probability that a person with a positive test result actually has the disease.

Negative Predictive Value (NPV):

The probability that a person with a negative test result truly does not have the disease.

Understanding Test Performance:

Diagnostic sensitivity and specificity are crucial attributes of laboratory tests. While we often categorize patients as healthy or ill, there is often some overlap, leading to misclassifications.

Ideal Test Scenarios:

• A 100% sensitive test would have no false negatives, correctly identifying all individuals with the disease.
• A 100% specific test would have no false positives, correctly identifying all individuals without the disease.

By understanding these concepts, healthcare professionals can make informed decisions about screening programs and diagnostic tests, ultimately improving patient care and public health outcomes.