Screening vs diagnostic testing

Core Concepts - Test Type Triage

• Screening Test: Applied to a large, asymptomatic population to detect potential disease. Aims for high sensitivity to minimize false negatives. Not a definitive diagnosis.

  • Example: Pap smear, Mammogram.

• Diagnostic Test: Used on symptomatic individuals or those with a positive screening result to establish a definitive diagnosis. Aims for high specificity to minimize false positives.

  • Example: Colposcopy, Biopsy.

📌 SPIN & SNOUT:

• A highly SPecific test, when Positive, rules IN the disease.
• A highly SNensitive test, when Negative, rules OUT the disease.

⭐ Screening tests are subject to biases like lead-time bias (earlier detection without improved outcome) and length-time bias (detecting more slow-growing, less aggressive cases).

Statistical Measures - The Numbers Game

• Sensitivity (Sn): True Positive Rate. Correctly identifies those with disease.

  • $Sn = \frac{TP}{TP+FN}$
  • 📌 SN-N-OUT: A sensitive test, when negative, rules out the disease. Ideal for screening.

• Specificity (Sp): True Negative Rate. Correctly identifies those without disease.

  • $Sp = \frac{TN}{TN+FP}$
  • 📌 SP-P-IN: A specific test, when positive, rules in the disease. Ideal for confirmation.

• Positive Predictive Value (PPV): Probability of disease if the test is positive.

  • $PPV = \frac{TP}{TP+FP}$
  • Directly varies with prevalence (↑ Prevalence → ↑ PPV).

• Negative Predictive Value (NPV): Probability of no disease if the test is negative.

  • $NPV = \frac{TN}{TN+FN}$
  • Inversely varies with prevalence (↓ Prevalence → ↑ NPV).

⭐ Sensitivity and Specificity are intrinsic to the test and independent of disease prevalence. PPV and NPV are heavily dependent on prevalence.

Screening Biases - Hidden Traps

• Lead-Time Bias:

  • Apparent increase in survival time due to earlier detection by screening, without changing the date of death.
  • The clock starts earlier, giving an illusion of longer survival.

• Length-Time Bias:

  • Screening is more likely to detect slow-growing, less aggressive cases with a better prognosis.
  • Aggressive, rapidly progressive cases often become symptomatic between screening intervals.

• Volunteer Bias (Self-Selection Bias):

  • People who volunteer for screening are often healthier and more health-conscious than the general population.
  • This can lead to better outcomes in the screened group, independent of the test's benefit.

• Overdiagnosis Bias:

  • Detection of a "disease" that would never have become clinically significant or caused symptoms in the patient's lifetime.

⭐ The only way to truly assess a screening program's effectiveness and mitigate lead-time bias is by demonstrating a reduction in disease-specific mortality in a randomized controlled trial (RCT).

High‑Yield Points - ⚡ Biggest Takeaways

• Screening tests are for asymptomatic populations to detect potential disease; they should have high sensitivity.
• Diagnostic tests are to confirm a diagnosis in symptomatic patients or after a positive screen; they require high specificity.
• Screening is generally cheaper and less invasive.
• Diagnostic tests are typically more expensive, invasive, and accurate.
• Pre-test probability is a key factor in choosing which test to order and interpreting its results.