Spontaneous reporting systems for suspected adverse drug reactions (ADRs) remain a cornerstone of pharmacovigilance. In The Netherlands 'the Netherlands Pharmacovigilance Foundation Lareb' maintains such a system. A primary aim in pharmacovigilance is the timely detection of either new ADRs or a change of the frequency of ADRs that are already known to be associated with the drugs involved, i.e. signal detection. Adequate signal detection solely based on the human intellect (case by case analysis or qualitative signal detection) is becoming time consuming given the increasingly large number of data, as well as less effective, especially in more complex associations such as drug-drug interactions, syndromes and when various covariates are involved. In quantitative signal detection measures that express the extent in which combinations of drug(s) and clinical event(s) are disproportionately present in the database of reported suspected ADRs are used to reveal associations of interest. Although the rationale and the methodology of the various quantitative approaches differ, they all share the characteristic that they express to what extent the number of observed cases differs from the number of expected cases. In this paper three Dutch examples are described in which a measure of disproportionality is used in quantitative signal detection in pharmacovigilance: (i) the association between antidepressant drugs and the occurrence of non-puerpural lactation as an example of an association between a single drug and a single event; (ii) the onset or worsening of congestive heart failure associated with the combined use of nonsteroidal anti-inflammatory drugs and diuretics as an example of an association between two drugs and a single event (drug-drug interaction); and the (iii) (co)-occurrence of fever, urticaria and arthralgia and the use of terbinafine as an example of an association between a single drug and multiple events (syndrome). We conclude that the use of quantitative measures in addition to qualitative analysis is a step forward in signal detection in pharmacovigilance. More research is necessary into the performance of these approaches, especially its predictive value, its robustness as well as into further extensions of the methodology.

AimsIn spontaneous adverse drug reaction reporting systems, there is a growing need for methods facilitating the automated detection of signals concerning possible adverse drug reactions. In addition, special attention is needed for the detection of adverse drug reactions resulting from possible drug-drug interactions. We describe a method for detecting possible drug-drug interactions using logistic regression analysis to calculate ADR reporting odds ratios. Methods To illustrate this method, we analysed the adverse drug reaction 'delayed withdrawal bleeding' resulting from a possible interaction between itraconazole and oral contraceptives in reports received by the Netherlands Pharmacovigilance Foundation LAREB between 1991 and 1998. Results In total 5,503 reports were included in the study. The odds ratio, adjusted for year of reporting, age and source of the reports, for a delayed withdrawal bleeding in women who used both drugs concomitantly compared with women who used neither oral contraceptives, nor itraconazole, was 85 (95% CI: 32-230). Conclusions Since spontaneous reporting systems can only generate signals concerning possible relationships, this association needs to be analysed by other methods in more detail in order to determine the real strength of the relationship. This approach might be a promising tool for the development of procedures for automated detection of possible drug-drug interactions in spontaneous reporting systems.

The primary aim of spontaneous reporting systems (SRSs) is the timely detection of unknown adverse drug reactions (ADRs), or signal detection. Generally this is carried out by a systematic manual review of every report sent to an SRS. Statistical analysis of the data sets of an SRS, or quantitative signal detection, can provide additional information concerning a possible relationship between a drug and an ADR. We describe the role of quantitative signal detection and the way it is applied at the Netherlands Pharmacovigilance Centre Lareb. Results of the statistical analysis are implemented in the traditional case-by-case analysis. In addition, for data-mining purposes, a list of associations of ADRs and suspected drugs that are disproportionally present in the database is periodically generated. Finally, quantitative signal generation can be used to study more complex relationships, such as drug-drug interactions and syndromes. The results of quantitative signal detection should be considered as an additional source of information, complementary to the traditional analysis. Techniques for the detection of drug interactions and syndromes offer a new challenge for pharmacovigilance in the near future.

Objective. Fluoroquinolone antibiotics have been associated with tendinitis and tendon rupture. In this paper we report on the followup of 42 spontaneous reports of fluoroquinolone-associated tendon disorders. Methods. This study is based on cases of fluoroquinolone-associated tendon disorders reported to the Netherlands Pharmacovigilance Foundation Lareb and the Drug Safety Unit of the Inspectorate for Health Care between January 1, 1988, and January 1, 1998. By means of a mailed questionnaire, we collected information on the site of injury, onset of symptoms, treatment, and course of the tendon disorder as well as information on possible risk factors and concomitant medication.Results. Of 50 mailed questionnaires, 42 (84%) were returned. The data concerned 32 patients (76%) with tendinitis and 10 patients (24%) with a tendon rupture. Sixteen cases (38%) were attributed to ofloxacin, 13 (31%) to ciprofloxacin, 8 (19%) to norfloxacin, and 5 (12%) to pefloxacin. There was a male predominance, and the median age of the patients was 68 years. Most of the reports concerned the Achilles tendon, and 24 patients (57%) had bilateral tendinitis. The latency period between the start of treatment and the appearance of the first symptoms ranged from 1 to 510 days with a median of 6 days. Most patients recovered within 2 months after cessation of therapy, but 26% had not yet recovered at followup. Conclusion. These reports suggest that fluoroquinolone-associated tendon disorders are more common in patients over 60 years of age. Ofloxacin was implicated most frequently relative to the number of filled prescriptions in the Netherlands.

Aims Detection of new adverse drug reactions (ADR) after marketing is often based on a manual review of reports sent to a Spontaneous Reporting System (SRS). Among the many potential signals that are identi®ed, only a limited number are important enough to require further attention. The goal of this study is to gain insight into factors contributing to the selection and dissemination of possible signals originating from the SRS maintained by the Netherlands Pharmacovigilance Foundation. Methods In a case control design, all signals (n=42) disseminated to the Medicines Evaluation Board from the second quarter of 1997 until the third quarter of 2000, which could be expressed as a combination of a single ATC code and a single WHO preferred term, were included. For each case, four controls were matched in time. Logistic regression analysis was used to investigate the in¯uence of various factors, such as the fact whether the ADR or drug is new, the strength of the association, the seriousness of the reaction and the documentation of the reports. Results Multivariate analysis showed that the presence of a`serious report' (Odds Ratio 3.8, 95% CI 1.3, 11.0), a WHO`critical term' (OR 4.7, 95% CI 1.8, 13), the ADR being unlabelled (OR 6.1, 95% CI 2.3, 16) and the presence of a disproportionate association (OR 3.5, 95% CI 1.4,8) were all independently associated with signal selection. The number of reports and the time after marketing of the drug had no in¯uence. Conclusions This study showed that selection of signals is based on both qualitative and quantitative aspects. Knowledge of these factors may improve the ef®ciency of the underlying signal selection process.