1. Define the term screening for disease. Describe screening for diseases in terms of definition, types, uses, criteria for selection for disease and selection for screening tests. 2. Levels of prevention. Explain with example 3. Sensitivity and specificity of a screening test 4. Difference between screening test and diagnostic test
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1. Screening for Disease
Definition
Screening is defined as "the search for unrecognized disease or defect by means of rapidly applied tests, examinations or other procedures in apparently healthy individuals." (Park's Textbook of Preventive and Social Medicine)
The Commission on Chronic Illness (USA, 1951) defined it as: "the presumptive identification of unrecognized disease or defect by the application of tests, examinations, or other procedures which can be applied rapidly."
The key word is presumptive - a screening test is NOT a diagnostic test. Those with positive findings must be referred for further diagnostic work-up and treatment.
Types of Screening
a. Mass Screening
Screening of a whole population or a large sub-group, irrespective of individual risk (e.g., tuberculosis chest X-ray for all adults). Mass screening enjoyed past enthusiasm but has been questioned for cost-effectiveness - it has not always shown a reduction in mortality or morbidity.
b. High-Risk (Selective) Screening
Screening is applied selectively to groups at highest risk, as defined by epidemiological research. This maximizes yield per person screened.
- Example: Screening for cervical cancer in lower socio-economic groups, or screening family members of a diabetic patient.
- Extended to screening for risk factors (e.g., serum cholesterol for coronary heart disease, elevated blood pressure for stroke) before disease even occurs.
c. Multiphasic Screening
Application of two or more screening tests in combination to a large number of people at one time. May include a health questionnaire, clinical examination, blood/urine tests, lung function tests, audiometry, and visual acuity checks. While popular, randomized controlled studies in the UK and USA have not shown clear benefit in reducing mortality/morbidity, and it increases cost.
Uses of Screening
Four main uses have been described:
a. Disease detection (Prescriptive screening)
Presumptive identification of unrecognized disease, initiated for the individual's own benefit. Examples: neonatal screening (PKU, hypothyroidism), screening for bacteriuria in pregnancy, cervical cancer, breast cancer, diabetes mellitus.
b. Control of disease (Prospective screening)
People are examined for the benefit of others. Example: screening immigrants for tuberculosis and syphilis to protect the home population; streptococcal screening to prevent rheumatic fever.
c. Research purposes
To understand the natural history of diseases whose course is not fully known (e.g., cancer, hypertension). Initial screening gives prevalence estimates; repeat screening gives incidence figures.
d. Educational opportunities
Screening programmes raise public awareness and educate health professionals (e.g., diabetes screening campaigns).
Criteria for Selection of Disease (for Screening)
Before initiating a screening programme, the disease must satisfy these criteria (Wilson & Jungner principles, as described in Park's):
- The condition should be an important health problem (prevalence should be high)
- There should be a recognizable latent or early asymptomatic stage
- The natural history of the condition (from latent to declared disease) should be adequately understood
- There should be a test capable of detecting the disease before symptoms appear
- Facilities for follow-up and diagnosis must be available
- There should be an effective treatment for the disease
- There should be an agreed-on policy on whom to treat (e.g., borderline diabetes, lower blood pressure ranges)
- There should be good evidence that early detection and treatment reduces morbidity and mortality
- The expected benefits (lives saved) of early detection must exceed the risks and costs
Criteria for Selection of the Screening Test
Once the disease qualifies, the test itself must satisfy:
1. Acceptability
High cooperation rates require that the test must be acceptable - not painful, discomforting, or embarrassing. Rectal or vaginal examinations are less acceptable in mass campaigns.
2. Repeatability (Reliability/Precision)
The test must give consistent results when repeated on the same individual under the same conditions. Repeatability is affected by:
- Observer variation - Intra-observer (same observer, same test, different results) and inter-observer (different observers, same material, different results). Example: 14,867 chest X-ray films read by 8 radiologists - only 91% had unanimous agreement.
- Biological (subject) variation - Physiological variables like blood pressure and blood sugar fluctuate naturally, including regression to the mean.
- Technical errors - Defective instruments, faulty reagents, erroneous calibration.
3. Validity (Accuracy)
The ability of a test to correctly identify those with and without disease. Validity has two components: sensitivity and specificity (see Section 3 below).
Other criteria:
- Simple and rapid to administer
- Safe (no harm to the subject)
- Inexpensive (affordable for mass application)
- High yield (the amount of previously unrecognized disease diagnosed and brought to treatment)
2. Levels of Prevention
Prevention is broadly defined in terms of four levels, related to the natural history of disease. (Park's Textbook of Preventive and Social Medicine)
1. Primordial Prevention
Definition: Prevention of the emergence or development of risk factors in populations where they have not yet appeared.
This is primary prevention in its purest sense. It targets the pre-risk-factor stage of disease.
Key intervention: Individual and mass education to discourage adoption of harmful lifestyles.
Example: Many adult diseases (obesity, hypertension) have early origins in childhood when lifestyles form. Primordial prevention means discouraging children from smoking, unhealthy eating, and physical inactivity - before these risk factors have even established themselves. Health education programmes in schools are a classic example.
2. Primary Prevention
Definition: "Action taken prior to the onset of disease, which removes the possibility that a disease will ever occur." It intervenes in the pre-pathogenesis phase.
Approaches:
- Health promotion (general well-being) and specific protection (targeted measures)
- Population (mass) strategy: Directed at the whole population to produce a small but widespread risk reduction. Example: reducing average blood pressure or serum cholesterol in a population to cut cardiovascular disease incidence.
- High-risk strategy: Targeted at individuals at special risk identified through clinical screening.
Examples:
- Vaccination against polio, measles (specific protection)
- Sanitation, clean water supply (environmental measures)
- Dietary counselling to prevent coronary heart disease
- Use of folic acid in pregnancy to prevent neural tube defects
3. Secondary Prevention
Definition: "Action which halts the progress of a disease at its incipient stage and prevents complications." It operates in the early pathogenesis phase (latent/early symptomatic stage).
Specific interventions:
- Early diagnosis - screening tests, case-finding programmes
- Adequate treatment - to arrest disease process and restore health before irreversible pathological changes occur
Examples:
- Pap smear screening for early cervical cancer
- Blood pressure measurement to detect early hypertension
- Screening for diabetes (fasting blood glucose)
- Mammography to detect early breast cancer
- Treatment of latent tuberculosis to prevent active disease
Secondary prevention is largely the domain of clinical medicine and government health programmes. Its drawback is that the patient has already suffered mental anguish and physical changes.
4. Tertiary Prevention
Definition: "All measures available to reduce or limit impairments and disabilities, minimize suffering caused by existing departures from good health and to promote the patient's adjustment to irremediable conditions." It operates in the late pathogenesis phase.
Specific interventions:
- Treatment even in late stages to prevent sequelae and limit disability
- Rehabilitation - psychosocial, vocational, and medical rehabilitation
Examples:
- Physiotherapy after stroke to restore function
- Cardiac rehabilitation after myocardial infarction
- Limb prosthetics and vocational rehabilitation after amputation
- Insulin therapy in long-standing diabetes to prevent progression of complications
- Colostomy care and self-management education for bowel cancer patients post-surgery
Summary Table - Levels of Prevention
| Level | Stage of Disease | Key Intervention | Example |
|---|---|---|---|
| Primordial | Pre-risk factor | Education, lifestyle change | Anti-smoking campaigns for children |
| Primary | Pre-pathogenesis | Vaccination, sanitation | Polio vaccine, clean water |
| Secondary | Early pathogenesis | Screening, early treatment | Pap smear, BP measurement |
| Tertiary | Late pathogenesis | Rehabilitation, limiting disability | Physiotherapy post-stroke |
3. Sensitivity and Specificity of a Screening Test
The 2x2 Table
To understand sensitivity and specificity, test results are compared against a gold standard diagnosis:
| Disease Present | Disease Absent | Total | |
|---|---|---|---|
| Test Positive | a (True Positive - TP) | b (False Positive - FP) | a + b |
| Test Negative | c (False Negative - FN) | d (True Negative - TN) | c + d |
| Total | a + c | b + d | a + b + c + d |
Sensitivity
Definition: Sensitivity is the ability of a test to detect disease - the proportion of truly diseased persons who test positive.
Formula: Sensitivity = a / (a + c) × 100
- "a" = true positives (diseased + test positive)
- "c" = false negatives (diseased but test negative)
Interpretation: A test with 90% sensitivity correctly identifies 90 out of 100 diseased individuals. 10 are missed (false negatives).
Sensitivity = True Positive Rate
1 - Sensitivity = False Negative Rate
Clinical use: A highly sensitive test is used when it is important not to miss the disease (e.g., HIV screening of blood donors, where a missed case has serious consequences). A sensitive test is good for ruling OUT disease - a negative result from a highly sensitive test almost certainly means the person is disease-free.
Specificity
Definition: Specificity is the ability of a test to detect the absence of disease - the proportion of truly non-diseased persons who test negative.
Formula: Specificity = d / (b + d) × 100
- "d" = true negatives (no disease + test negative)
- "b" = false positives (no disease but test positive)
Interpretation: A test with 90% specificity correctly identifies 90 out of 100 non-diseased individuals as negative. 10 non-diseased people are incorrectly labeled positive.
Specificity = True Negative Rate
1 - Specificity = False Positive Rate
Clinical use: A highly specific test is used to confirm (rule in) a diagnosis - a positive result from a highly specific test is almost certainly a true positive. Important when a false positive would cause harm (e.g., unnecessary chemotherapy).
The Sensitivity-Specificity Trade-off
As the cutoff point of a test is moved:
- Increasing sensitivity (lowering the cutoff) → decreases specificity → more false positives
- Increasing specificity (raising the cutoff) → decreases sensitivity → more false negatives
The ROC curve (Receiver Operating Characteristic) graphically shows this trade-off. The ideal cutoff maximizes both, but in practice, the choice depends on the clinical consequences of each type of error.
Predictive Values (Related Concepts)
- Positive Predictive Value (PPV) = a / (a + b) × 100 - Probability that a positive test truly indicates disease
- Negative Predictive Value (NPV) = d / (c + d) × 100 - Probability that a negative test truly excludes disease
Unlike sensitivity and specificity, predictive values depend on the prevalence of disease in the population tested. As prevalence decreases, PPV falls (more false positives for every true positive), which is why mass population screening for rare diseases can generate many false positives.
Worked Example (from Henry's Clinical Diagnosis, cardiac marker study):
- 200 AMI patients + 200 healthy subjects tested:
- TP = 196, FN = 4, TN = 180, FP = 20
- Sensitivity = 196/200 × 100 = 98%
- Specificity = 180/200 × 100 = 90%
- PPV = 196/216 × 100 = 91%
- NPV = 180/184 × 100 = 98%
4. Difference Between Screening Test and Diagnostic Test
The following comparison is based directly on Park's Textbook of Preventive and Social Medicine:
| Feature | Screening Test | Diagnostic Test |
|---|---|---|
| Population | Done on apparently healthy individuals | Done on those with symptoms/signs or indications of disease |
| Application | Applied to groups/populations | Applied to individual patients |
| Finality | Results are preliminary; not final | Diagnosis is the sum of all clinical evidence; modified with new findings |
| Basis | Based on one criterion or cut-off point | Based on evaluation of multiple symptoms, signs, and laboratory findings |
| Accuracy | Less accurate | More accurate |
| Cost | Less expensive | More expensive |
| Treatment | NOT a basis for treatment | Used as a basis for treatment decisions |
| Initiative | Initiated by the investigator or public health agency | Initiated by a patient with a complaint |
Important caveat: These distinctions are not absolute. Some tests are used both for screening and diagnosis (e.g., blood glucose for anaemia assessment, glucose tolerance test). Screening and diagnosis are complementary, not competing, and different criteria apply to each.
Key principle: A positive screening test always requires follow-up with a diagnostic test before any treatment decision is made. For example, a positive Pap smear (screening) requires colposcopy and biopsy (diagnostic) before cervical cancer treatment is initiated.
Sources: Park's Textbook of Preventive and Social Medicine; Henry's Clinical Diagnosis and Management by Laboratory Methods; Creasy & Resnik's Maternal-Fetal Medicine.
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