Naranjo scale

The Naranjo algorithm is a questionnaire developed by Naranjo et al. to determine the probability of whether an adverse drug reaction (ADR) is actually due to the drug or to other factors. The probability is indicated by an assessment as definite, probable, possible or doubtful. The scores obtained using this algorithm are often used in peer reviews to check the validity of the author's conclusions regarding ADRs.

Questions and evaluation (typical):

1. are there any previous, well-documented reports of this response? Yes +1 / No 0 / Unknown 0

2. did the reaction occur after administration of the drug? Yes +2 / No -1 / Unknown 0

3. did it improve after discontinuation (dechallenge)? Yes +1 / No 0 / Unknown 0

4. did it return after re-exposure (rechallenge)? Yes +2 / No -1 / Unknown 0

5. are there alternative causes that explain the reaction? Yes -1 / No +2 / Unknown 0

6. did the reaction occur again after placebo? Yes -1 / No +1 / Unknown 0

7. were drug levels measured to be toxic? Yes +1 / No 0 / Unknown 0

8. did the reaction become stronger/weaker when the dose was changed? Yes +1 / No 0 / Unknown 0

9. did the patient have a similar reaction to similar substances? Yes +1 / No 0 / Unknown 0

10. has the adverse reaction been confirmed by objective evidence (e.g. laboratory, biopsy)? Yes +1 / No 0 / Unknown 0

Interpretation of the sum

- ≥ 9: Definite (very likely)

- 5-8: Probable

- 1-4: Possible

- ≤ 0: Doubtful

Empirical approaches to identifying ADRs have failed due to the complexity of the variables involved in their detection. Computer programs for decision making have helped in this analysis. Electronic medical records can be programmed to provide alerts when a potential adverse drug event is imminent or has already occurred. Automated adverse drug event monitors can search the patient's medical record for key words or phrases to identify drug therapies, lab 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 solely on empirical methods or incident reports.

For a long time, empirical methods for assessing the likelihood of an ADR occurring were lacking. A more formal, logical analysis can help distinguish between events attributable to a drug and those related to underlying conditions or other factors. The widely accepted tool for this is the Naranjo algorithm. This method has been tested for internal validity with inter-rater reliability tests. Its probability scale has consensus, content and concurrent validity, as well as ease of use in clinical settings and controlled studies.

Questionnaire

1. Are there already conclusive reports on this reaction? Yes (+1) No (0) Don't know or not done (0)
2. Did the adverse events occur after administration of the suspected drug? yes (+2) no (-1) don't know or not done (0)
3. Did the adverse reaction improve when the drug was discontinued or a specific antagonist was administered? Yes (+1) No (0) Don't know or not performed (0)
4. Did the adverse reaction occur when the drug was re-administered? Yes (+2) No (-1) Don't know or not performed (0)
5. Are there alternative causes that could have triggered the reaction? Yes (-1) No (+2) Don't know (0)
6. Did the reaction occur again when a placebo was administered? Yes (-1) No (+1) Don't know or not performed (0)
7. Was the drug detected in toxic concentrations in body fluid? Yes (+1) No (0) Don't know or not known (0)
8. Was the reaction stronger when the dose was increased or weaker when the dose was decreased? Yes (+1) No (0) Don't know or not performed (0)
9. Has the patient had a similar reaction to the same or similar drugs in a previous exposure? Yes (+1) No (0) Don't know or not performed (0)
10. Has the adverse event been confirmed by objective evidence? Yes (+1) No (0) Don't know or not performed (0)

Evaluation (scoring)

• ≥ 9 = Drug reaction definite
• 5-8 = Drug rejection probable
• 1-4 = Drug treatment possible
• 0 = Drug administration doubtful