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Naranjo algorithm

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Naranjo algorithm

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The Naranjo algorithm, Naranjo Scale, or Naranjo Nomogram is a questionnaire designed by Naranjo et al. for determining the likelihood of whether an ADR (adverse drug reaction) is actually due to the drug rather than the result of other factors. Probability is assigned via a score termed definite, probable, possible or doubtful. Values obtained from this algorithm are often used in peer reviews to verify the validity of author's conclusions regarding adverse drug reactions. It is also called the Naranjo Scale or Naranjo Score.

It is often compared to the WHO-UMC system for standardized causality assessment for suspected adverse drug reactions (ADRs).

Empirical approaches to identifying ADRs have fallen short because of the complexity of the set of variables involved in their detection. Computer decision programs have helped in this analysis. Electronic medical record systems can be programmed to fire alerts when a potential adverse drug event is about to occur or has already occurred.[3,4] Automated adverse drug event monitors can search for keywords or phrases throughout the patient's medical record to identify drug therapies, laboratory results, or problem lists that may indicate that a patient has already been treated for an ADR. This detection method uncovers significantly more adverse events, including medication errors, than relying on empirical methods or incident reports.[1,2]

Empirical methods to assess the likelihood that an ADR has taken place have been lacking. More formal, logical analysis can help differentiate between events that are attributable to a drug from those associated with underlying diseases or other factors, underlying the complexity of detection.[5]

Several investigators, among them researchers at the FDA, have developed such logical evaluation methods, or algorithms, for evaluating the probability of an ADR.[2, 20-24] Almost all of these methods employ critical causation variables identified by Sir Austin Bradford Hill in 1965.[6] The most widely accepted of these instruments is the Naranjo algorithm[22] (Table). This method has been tested for internal validity with between-rater reliability testing, and its probability scale has consensual, content, and concurrent validity as well as ease of use in clinical settings and controlled studies.

Questionnaire

1. Are there previous conclusive reports on this reaction?

2. Did the adverse events appear after the suspected drug was given?

3. Did the adverse reaction improve when the drug was discontinued or a specific antagonist was given?

4. Did the adverse reaction appear when the drug was readministered?

5. Are there alternative causes that could have caused the reaction?

6. Did the reaction reappear when a placebo was given?

7. Was the drug detected in any body fluid in toxic concentrations?

8. Was the reaction more severe when the dose was increased, or less severe when the dose was decreased?

9. Did the patient have a similar reaction to the same or similar drugs in any previous exposure?

10. Was the adverse event confirmed by any objective evidence?

Scoring

≥ 9 = definite ADR
5-8 = probable ADR
1-4 = possible ADR
0 = doubtful ADR

Naranjo, C A; Busto, U; Sellers, E M; Sandor, P; Ruiz, I; Roberts, E A; Janecek, E; Domecq, C; Greenblatt, D J (1981). "A method for estimating the probability of adverse drug reactions". Clinical Pharmacology and Therapeutics. 30 (2): 239–245. doi:10.1038/clpt.1981.154. ISSN 0009-9236. PMID 7249508. S2CID 29728085.

A*l-Tajir GK, Kelly WN. Epidemiology, comparative methods of detection, and preventability of adverse drug events. Ann Pharmacother. 2005;39:1169-1174. Abstract

Brown S, Black K, Mrochek S, et al. RADARX: recognizing, assessing, and documenting adverse Rx events. Proc AMIA Symp. 2000:101-105.
Classen DC, Pestotnik SL, Evans RS, et al. Description of a computerized adverse drug event monitor using a hospital information system. Hosp Pharm. 1992;27:774-783. Abstract
Gandi TK, Bates DW. Computer adverse drug event detection and alerts. In: Making Healthcare Safer: A Critical Analysis of Patient Safety Practices. Rockville, Md: Agency for Healthcare Research and Quality; 2001.
Jones JK. Adverse drug reactions in the community health setting: approaches to recognizing, counseling, and reporting. Fam Community Health. 1982;5:1982.
Hill AB. The environment and disease association or causation. Proc R Soc Med. 1965;58:295-300. Abstract
Naranjo CA, Busto U, Sellers EM, et al. A method for estimating the probability of adverse drug reactions. Clin Pharmacol Ther. 1981;30:239-245. Abstract