Sensitivity (SnNOut)
TP / (TP + FN); High sensitivity test has low false negatives; when negative, reliably rules OUT disease (ideal for screening).
Specificity (SpPIn)
TN / (TN + FP); High specificity test has low false positives; when positive, reliably rules IN disease (ideal for confirmatory).
Prevalence Effects
As disease prevalence increases: PPV increases and NPV decreases. Sensitivity and Specificity remain UNCHANGED by prevalence.
NNT = 1 / ARR
Number Needed to Treat equals 1 divided by Absolute Risk Reduction (ARR = Control Event Rate - Experimental Event Rate); always round UP.
The 2x2 Contingency Table & Diagnostic Metrics
Every diagnostic test question on COMLEX and USMLE builds upon the standard 2x2 table:
| Test Result | Disease Status (Gold Standard) | Marginal Totals | |
|---|---|---|---|
| Disease Present (+) | Disease Absent (−) | ||
| Test Positive (+) | True Positive (TP) | False Positive (FP) | TP + FP (All positive tests) |
| Test Negative (−) | False Negative (FN) | True Negative (TN) | FN + TN (All negative tests) |
| Column Totals | TP + FN (All with disease) | FP + TN (All without disease) | Total Population (N) |
Sensitivity & Specificity (Inherent to Test)
- Sensitivity: TP / (TP + FN) = True Positive Rate
- Specificity: TN / (TN + FP) = True Negative Rate
- False Positive Rate (α): 1 − Specificity = FP / (FP + TN)
- False Negative Rate (β): 1 − Sensitivity = FN / (TP + FN)
Predictive Values (Depend on Prevalence)
- Positive Predictive Value (PPV): TP / (TP + FP)
- Negative Predictive Value (NPV): TN / (FN + TN)
- High prevalence → Higher PPV, Lower NPV
- Low prevalence → Lower PPV, Higher NPV
Measures of Association: Odds Ratio vs. Relative Risk
| Metric | Study Design | Formula | Interpretation |
|---|---|---|---|
| Odds Ratio (OR) | Case-Control Study (retrospective) | (a × d) / (b × c) | Odds of exposure in diseased vs. non-diseased; approximates RR when disease is rare ('rare disease assumption') |
| Relative Risk (RR) | Cohort Study (prospective or retrospective) | [a / (a + b)] / [c / (c + d)] | Risk of developing disease in exposed vs. unexposed cohort |
| Absolute Risk Reduction (ARR) | Randomized Controlled Trial (RCT) | Control Rate − Treatment Rate | Actual absolute percentage difference in risk between groups |
| Number Needed to Treat (NNT) | Randomized Controlled Trial (RCT) | 1 / ARR | Number of patients needed to receive treatment to prevent 1 adverse event; round UP to nearest integer |
OMM Board Correlate: Evidence-Based Medicine in Osteopathic Research
- Sham OMT vs. Placebo Controls: In clinical OMM trials, blinding is notoriously challenging. A sham intervention (light non-therapeutic touch) is used to control for the Hawthorne effect and provider contact time.
- Inter-Examiner Reliability: Somatic dysfunction diagnostic tests (e.g., standing flexion test, TART palpation) exhibit moderate inter-examiner reliability (kappa statistic κ 0.40 - 0.70).
- Type II Error in Small Trials: Many early OMT trials were underpowered (β error) due to small sample sizes, failing to detect statistically significant differences despite clinically meaningful effect sizes.
Board Traps & Common Distractors
- Never confuse statistical significance (p < 0.05) with clinical significance; in huge sample size studies, an intervention may lower systolic BP by 0.5 mmHg with p < 0.001, but the clinical benefit to the patient is negligible.
- If a 95% confidence interval for an Odds Ratio (OR) or Relative Risk (RR) includes 1.0 (e.g., 0.92 to 2.45), the result is NOT statistically significant (p >= 0.05). If a CI for a mean difference includes 0, it is not statistically significant.
- Lead-time bias creates the illusion of improved survival caused by early detection by screening, while the actual course of the disease and time of death remain completely unaltered.