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Community Medicine (PSM)Biostatisticshigh-yield

Sensitivity, specificity and predictive values

Deriving sensitivity, specificity, PPV and NPV from one 2x2 table, why predictive values chase prevalence, and when to pick a sensitive versus a specific test.

5 min read · updated 2026-08-24

One 2x2 table gives every value

Disease presentDisease absent
Test positiveTrue positive (a)False positive (b)
Test negativeFalse negative (c)True negative (d)

Read down the columns for sensitivity and specificity; read across the rows for predictive values. That one instruction stops most mistakes.

  • Sensitivity = a / (a + c) — of the diseased, how many test positive (detects disease)
  • Specificity = d / (b + d) — of the healthy, how many test negative (excludes disease)
  • PPV = a / (a + b) — of positives, how many are truly diseased
  • NPV = d / (c + d) — of negatives, how many are truly healthy

Prevalence is the hidden variable

Sensitivity and specificity are intrinsic to the test — they do not move with prevalence. PPV and NPV do. As prevalence rises, PPV rises and NPV falls; in a low-prevalence population even an excellent test throws mostly false positives, so its PPV collapses. This is why mass screening of rare disease generates so much needless follow-up.

SettingPrevalencePPVNPV
Screening general populationLowLowHigh
Symptomatic clinic / high-riskHighHighLower

Choosing a sensitive vs a specific test — SnNout / SpPin

Want to...ChooseMnemonic
Rule out disease (screening, dangerous-to-miss)High sensitivitySnNout — a Snsitive test, when Negative, rules out
Rule in disease (confirm before risky treatment)High specificitySpPin — a Specific test, when Positive, rules in

Use a sensitive test first (screening, e.g. ELISA for HIV) to catch every case, then a specific test (confirmation, e.g. Western blot) to weed out false positives. A highly sensitive test has few false negatives; a highly specific test has few false positives.

Anchor: Sensitivity/specificity belong to the test; PPV/NPV belong to the population. Screen with a sensitive test to rule out, confirm with a specific test to rule in.

Sources

  • Park's Textbook of Preventive and Social Medicine, 27e
  • Gordis Epidemiology, 6e