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Pharmacovigilance Glossary

Causality

Imagine you eat at a new seafood restaurant and wake up violently ill. Was it bad oysters, or was it just the stomach bug your toddler brought home from daycare? Causality is the structured detective work used to figure out if the suspect actually caused the crime, or if it was just bad timing.

What does it mean in plain English?

In pharmacovigilance, causality is the formal scientific assessment of the relationship between a medicine and a side effect. Whenever a patient experiences an unexpected health issue after taking a drug, safety scientists cannot simply assume the drug is to blame. They have to measure the likelihood of the connection.

To do this, assessors use structured scoring systems (like the WHO-UMC criteria or the Naranjo algorithm). It is rarely a simple "yes" or "no." Instead, the result is graded on a scale: Certain, Probable, Possible, Unlikely, or Unassessable. If enough reports are scored as "Probable" or "Possible," it triggers regulators to take action.

How the investigation works

Scroll down to see the 4 core questions an assessor asks to solve a case.

  • Step 1: The Timeline (Time-to-Onset)

    Did the symptom start after the patient took the pill, and does the timeframe make biological sense? (A rash appearing 20 minutes after an injection makes sense; a broken leg does not).

  • Step 2: The Pause (Dechallenge)

    If the patient stopped taking the suspected medicine, or the dose was reduced, did the adverse event go away or improve?

  • Step 3: The Return (Rechallenge)

    If the patient started taking the medicine again, did the symptom immediately come back? (Note: Doctors rarely do this on purpose if the side effect is dangerous, so this data is often missing!)

  • Step 4: Alternative Suspects (Confounders)

    Is there another obvious reason for the symptom? Assessors check for pre-existing illnesses, concurrent medications, or lifestyle factors that could be the real culprit.

Common Misconceptions

Myth

"The patient had a heart attack an hour after taking the new pill! The pill obviously caused it. Why are we wasting time debating this?"

Truth

Just because Event B happened after Event A, does not mean Event A caused Event B. Coincidences happen every single day. Causality prevents us from banning safe drugs over random chance.