A Method for Estimating the Probability of Adverse Drug Reactions¶
Naranjo, C. A., Busto, U., Sellers, E. M., Sandor, P., Ruiz, I., Roberts, E. A., Janecek, E., et al. (1981). A Method for Estimating the Probability of Adverse Drug Reactions. Clinical Pharmacology and Therapeutics, 30(2), 239-245.
Cited by¶
2 citations across 2 artifacts.
Each citation links to the sentence it supports in the citing article.
Domain-specific¶
- Adverse Drug Reaction
- Clinical pharmacology — forecasting Type A reactions straight from a drug's receptor-binding profile (β-blocker bradycardia, NSAID gastric bleeding, anticholinergic confusion) and reasoning about reactive-metabolite or immune mechanisms behind Type B. Pharmacovigilance and regulatory science — the surveillance backbone: spontaneous-reporting systems (FAERS, EudraVigilance, WHO/Uppsala VigiBase) and signal-detection methods (sequence-symmetry, self-controlled case series) aimed at the Type B tail that trials are structurally blind to. Hospital medication-safety programs — ADR monitoring within pharmaceutical care, with computerized decision support flagging high-risk interactions and contraindications at the point of care. Drug development — pre-approval studies powered for common (Type A) reactions, and post-approval Phase 4 studies and risk-management plans aimed at the uncommon (Type B) ones. Pharmacoepidemiology — case-control and cohort analyses estimating ADR incidence and identifying susceptibility factors (pharmacogenomic, organ-function, age-related) across populations. Causality assessment practice — structured Naranjo and WHO-UMC scoring of individual case reports
This sourcePaper introducing the weighted ADR probability scale, motivated by the between-raters variability of unaided clinical judgement about whether a drug caused an event.
Supported in partVerified against the publisher's abstract
“assigning a weighted score (ADR probability scale) to each of the components that must be considered in establishing causal associations”
- Clinical pharmacology — forecasting Type A reactions straight from a drug's receptor-binding profile (β-blocker bradycardia, NSAID gastric bleeding, anticholinergic confusion) and reasoning about reactive-metabolite or immune mechanisms behind Type B. Pharmacovigilance and regulatory science — the surveillance backbone: spontaneous-reporting systems (FAERS, EudraVigilance, WHO/Uppsala VigiBase) and signal-detection methods (sequence-symmetry, self-controlled case series) aimed at the Type B tail that trials are structurally blind to. Hospital medication-safety programs — ADR monitoring within pharmaceutical care, with computerized decision support flagging high-risk interactions and contraindications at the point of care. Drug development — pre-approval studies powered for common (Type A) reactions, and post-approval Phase 4 studies and risk-management plans aimed at the uncommon (Type B) ones. Pharmacoepidemiology — case-control and cohort analyses estimating ADR incidence and identifying susceptibility factors (pharmacogenomic, organ-function, age-related) across populations. Causality assessment practice — structured Naranjo and WHO-UMC scoring of individual case reports
Mechanisms¶
- Washout and Rechallenge
- Its strength is turning a belief — "the inhibitor is working," or "the inhibitor caused this" — into evidence, cleanly separating the inhibitor's effect from natural drift and, as a bonus, exposing resistance when a rechallenge fails to reproduce the effect.
This sourceUses improvement after withdrawal and recurrence after readministration as evidence in adverse-drug-reaction causality assessment.
- Its strength is turning a belief — "the inhibitor is working," or "the inhibitor caused this" — into evidence, cleanly separating the inhibitor's effect from natural drift and, as a bonus, exposing resistance when a rechallenge fails to reproduce the effect.
Verification¶
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