Intro to Epidemiology Unit 9 Review: Screening and Diagnostic Tests

Key Concepts and Definitions

• Screening tests identify individuals who may have a specific disease or condition among an apparently healthy population
• Diagnostic tests confirm or rule out the presence of a disease or condition in individuals with signs or symptoms
• Prevalence refers to the proportion of individuals in a population who have a specific disease or condition at a given point in time
• Gold standard is the best available method for determining the presence or absence of a disease or condition
• False positive occurs when a test result indicates the presence of a disease or condition when it is actually absent
• False negative happens when a test result indicates the absence of a disease or condition when it is actually present
• Cut-off value is the threshold used to distinguish between a positive and negative test result

Types of Screening and Diagnostic Tests

• Mass screening involves testing a large population, regardless of individual risk factors (population-based screening)
• Targeted screening focuses on testing high-risk groups or individuals with specific risk factors
• Opportunistic screening occurs when tests are offered to individuals during routine healthcare visits or encounters
• Confirmatory tests are used to verify the results of an initial screening test
• Imaging tests use various techniques (X-rays, CT scans, MRI) to visualize internal structures and detect abnormalities
• Genetic tests analyze an individual's DNA to identify genetic variations associated with certain diseases or conditions
• Biochemical tests measure the levels of specific substances in bodily fluids (blood, urine) to detect abnormalities

Test Characteristics and Performance

• Validity refers to the extent to which a test accurately measures what it is intended to measure
• Reliability is the consistency of test results when repeated under similar conditions
• Accuracy represents the overall proportion of correct test results (true positives and true negatives) among all test results
• Precision refers to the reproducibility of test results when repeated multiple times
• Bias occurs when there are systematic errors in the design, conduct, or interpretation of a test that lead to inaccurate results
  • Selection bias happens when the study population is not representative of the target population
  • Measurement bias arises from errors in the measurement or classification of test results
• Confounding factors are variables that are associated with both the disease and the test result, potentially distorting the relationship between them

Sensitivity and Specificity

• Sensitivity is the ability of a test to correctly identify individuals who have the disease or condition (true positive rate)
  • Calculated as: $\text{Sensitivity} = \frac{\text{True Positives}}{\text{True Positives + False Negatives}}$
• Specificity is the ability of a test to correctly identify individuals who do not have the disease or condition (true negative rate)
  • Calculated as: $\text{Specificity} = \frac{\text{True Negatives}}{\text{True Negatives + False Positives}}$
• Trade-off exists between sensitivity and specificity, as increasing one often decreases the other
• Receiver Operating Characteristic (ROC) curve is a graphical representation of the relationship between sensitivity and specificity at different cut-off values
• Area Under the Curve (AUC) is a measure of the overall performance of a test, with higher values indicating better discriminatory power

Predictive Values and Likelihood Ratios

• Positive Predictive Value (PPV) is the probability that an individual with a positive test result actually has the disease or condition
  • Calculated as: $\text{PPV} = \frac{\text{True Positives}}{\text{True Positives + False Positives}}$
• Negative Predictive Value (NPV) is the probability that an individual with a negative test result does not have the disease or condition
  • Calculated as: $\text{NPV} = \frac{\text{True Negatives}}{\text{True Negatives + False Negatives}}$
• Likelihood Ratio (LR) expresses how much a test result changes the odds of having the disease or condition
  • Positive LR (LR+) indicates how much the odds of having the disease increase with a positive test result
  • Negative LR (LR-) indicates how much the odds of having the disease decrease with a negative test result
• Pre-test probability is the estimated probability of an individual having the disease or condition before the test is performed
• Post-test probability is the updated probability of an individual having the disease or condition after the test result is known

Screening Program Evaluation

• Effectiveness assesses the extent to which a screening program achieves its intended health outcomes in real-world settings
• Cost-effectiveness analysis compares the costs and health outcomes of a screening program to determine its value for money
• Participation rate is the proportion of the target population that undergoes screening, which affects the program's impact
• Interval cancers are cases of the disease or condition that are diagnosed between scheduled screening rounds
• Overdiagnosis occurs when a screening program detects cases that would not have caused symptoms or harm during an individual's lifetime
• Lead time is the period between the detection of a disease through screening and when it would have been diagnosed based on symptoms
• Length time bias refers to the tendency of screening to detect slower-growing, less aggressive cases, leading to an overestimation of survival benefits

Ethical Considerations

• Informed consent ensures that individuals understand the purpose, benefits, risks, and limitations of screening before deciding to participate
• Autonomy respects an individual's right to make decisions about their own health and healthcare
• Beneficence requires that the benefits of screening outweigh the risks and harms for both individuals and society
• Non-maleficence obligates healthcare providers to avoid causing harm to individuals through screening
• Justice demands that screening programs are accessible and equitable for all members of the target population
• Confidentiality protects an individual's privacy and the security of their personal health information
• Stigmatization can occur when individuals are labeled or discriminated against based on their screening results

Real-World Applications and Case Studies

• Mammography screening for breast cancer in women aged 50-74 years has been shown to reduce breast cancer mortality
• Prostate-Specific Antigen (PSA) testing for prostate cancer screening remains controversial due to concerns about overdiagnosis and overtreatment
• Newborn screening programs use blood tests to identify infants with rare but serious genetic, metabolic, or endocrine disorders (phenylketonuria, congenital hypothyroidism)
• Prenatal screening tests (ultrasound, maternal serum markers) can detect fetal abnormalities (Down syndrome, neural tube defects) and inform pregnancy management decisions
• HIV screening in high-risk populations (men who have sex with men, injection drug users) facilitates early diagnosis and treatment, reducing transmission
• Colorectal cancer screening using fecal occult blood tests, sigmoidoscopy, or colonoscopy has been shown to reduce colorectal cancer incidence and mortality
• Cervical cancer screening with Pap smears and HPV testing has dramatically reduced cervical cancer incidence and mortality in countries with organized screening programs