🦠Epidemiology Unit 6 – Screening and Diagnostic Tests

Key Concepts and Definitions

• Screening tests identify apparently healthy individuals who may have a disease or condition
• Diagnostic tests confirm or establish a diagnosis in individuals suspected of having a specific disease or condition based on signs, symptoms, or screening test results
• Prevalence refers to the proportion of a population that has a disease or condition at a given point in time
• Incidence measures the occurrence of new cases of a disease or condition in a population over a specified period
• Gold standard is the best available method for establishing the presence or absence of a disease or condition
• False positive occurs when a test result indicates the presence of a disease or condition in an individual who does not actually have it
• False negative happens when a test result fails to detect a disease or condition in an individual who actually has it

Types of Screening and Diagnostic Tests

• Mass screening involves testing a large population, regardless of individual risk factors or symptoms (population-based screening)
  • Examples include mammography for breast cancer and colonoscopy for colorectal cancer
• Targeted screening focuses on high-risk populations based on factors such as age, gender, family history, or exposure to risk factors
  • Examples include screening for sickle cell disease in African American newborns and screening for Down syndrome in pregnant women over 35 years old
• Diagnostic tests can be invasive (biopsy) or non-invasive (imaging tests)
• Laboratory tests analyze bodily fluids or tissues to detect abnormalities (blood tests, urine tests)
• Imaging tests visualize internal structures and organs (X-rays, CT scans, MRI)
• Genetic tests identify genetic variations associated with certain diseases or conditions (BRCA1/BRCA2 testing for hereditary breast and ovarian cancer)

Test Performance Characteristics

• Validity refers to the accuracy of a test in measuring what it is intended to measure
  • Includes sensitivity and specificity
• Reliability is the consistency or reproducibility of test results when repeated under similar conditions
• Sensitivity measures the ability of a test to correctly identify individuals with a disease or condition (true positive rate)
  • Calculated as: $\text{Sensitivity} = \frac{\text{True Positives}}{\text{True Positives + False Negatives}}$
• Specificity measures the ability of a test to correctly identify individuals without a disease or condition (true negative rate)
  • Calculated as: $\text{Specificity} = \frac{\text{True Negatives}}{\text{True Negatives + False Positives}}$
• Positive predictive value (PPV) is the probability that an individual with a positive test result actually has the disease or condition
• Negative predictive value (NPV) is the probability that an individual with a negative test result does not have the disease or condition

Sensitivity and Specificity

• High sensitivity tests have a low false negative rate and are useful for ruling out a disease or condition when the test result is negative (SnNout: high Sensitivity, Negative test, rules out disease)
• High specificity tests have a low false positive rate and are useful for confirming a disease or condition when the test result is positive (SpPin: high Specificity, Positive test, rules in disease)
• Sensitivity and specificity are intrinsic properties of a test and do not change with disease prevalence
• Receiver Operating Characteristic (ROC) curve is a graphical representation of the trade-off between sensitivity and specificity at different test cut-off values
  • Area under the ROC curve (AUC) measures the overall accuracy of a test, with a perfect test having an AUC of 1.0
• Balancing sensitivity and specificity depends on the purpose of the test and the consequences of false positive and false negative results

Predictive Values and Likelihood Ratios

• Positive predictive value (PPV) and negative predictive value (NPV) are influenced by disease prevalence in the population being tested
  • Higher prevalence increases PPV and decreases NPV
  • Lower prevalence decreases PPV and increases NPV
• Likelihood ratios express how much a test result changes the pre-test probability of a disease or condition
• Positive likelihood ratio (LR+) is the ratio of the probability of a positive test result in individuals with the disease to the probability of a positive test result in individuals without the disease
  • Calculated as: $\text{LR+} = \frac{\text{Sensitivity}}{1 - \text{Specificity}}$
• Negative likelihood ratio (LR-) is the ratio of the probability of a negative test result in individuals with the disease to the probability of a negative test result in individuals without the disease
  • Calculated as: $\text{LR-} = \frac{1 - \text{Sensitivity}}{\text{Specificity}}$
• Pre-test probability can be estimated using prevalence data or clinical judgment
• Post-test probability can be calculated using likelihood ratios and pre-test probability (Fagan's nomogram)

Designing and Evaluating Screening Programs

• Define the target population and the disease or condition to be screened
• Select an appropriate screening test based on validity, reliability, cost, and acceptability
• Establish a screening interval based on the natural history of the disease and the performance of the test
• Ensure adequate follow-up and diagnostic testing for individuals with positive screening results
• Evaluate the effectiveness of the screening program using measures such as:
  • Participation rate
  • Detection rate
  • False positive rate
  • Positive predictive value
  • Reduction in disease-specific morbidity and mortality
• Consider the potential harms of screening, including overdiagnosis, overtreatment, and psychological distress
• Conduct cost-effectiveness analyses to assess the balance between the benefits and costs of the screening program

Ethical Considerations in Screening

• Respect for autonomy involves informed consent and the right of individuals to make their own decisions about participating in screening
• Beneficence requires that the benefits of screening outweigh the potential harms
• Non-maleficence means minimizing the risks and harms associated with screening, such as false positive results and unnecessary interventions
• Justice ensures that screening programs are accessible and equitable, regardless of socioeconomic status or other factors
• Confidentiality and privacy of screening results and personal health information must be protected
• Screening programs should provide adequate education and support for participants, including information about the limitations and potential consequences of screening

Real-World Applications and Case Studies

• Newborn screening for metabolic disorders (phenylketonuria, congenital hypothyroidism) has dramatically reduced the incidence of intellectual disability and other complications
• Mammography screening for breast cancer in women aged 50-74 years has been shown to reduce breast cancer mortality by 20-40%
• Prostate-specific antigen (PSA) screening for prostate cancer remains controversial due to concerns about overdiagnosis and overtreatment
  • Shared decision-making between patients and healthcare providers is recommended
• Prenatal screening for chromosomal abnormalities (Down syndrome) using a combination of maternal age, serum markers, and ultrasound has improved detection rates and reduced the need for invasive diagnostic tests (amniocentesis, chorionic villus sampling)
• Screening for colorectal cancer using fecal occult blood testing, sigmoidoscopy, or colonoscopy has been shown to reduce colorectal cancer incidence and mortality
  • Different screening modalities have varying levels of sensitivity, specificity, and acceptability