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Implementation of an automated signal detection method in the French pharmacovigilance database: a feasibility study

  • Pharmacoepidemiology and Prescription
  • Published:
European Journal of Clinical Pharmacology Aims and scope Submit manuscript

Abstract

Purpose

In France, early detection of adverse effects does not currently involve any automatic signal detection method. The present objective was to assess the feasibility and measure the potential benefit of the incorporation of an automatic signal detection tool (GPSpH0) in the French pharmacovigilance system.

Methods

GPSpH0 was first applied to the data collected from 1 January 2000 to 31 December 2008 and then to the data collected from 1 January 2000 to 31 March 2009. A total of 1,414 original signals were detected. They were shared out for further expertise among 32 centres, i.e. the 31 Regional Pharmacovigilance Centres and the French medicine agency (AFSSAPS) pharmacovigilance department.

Results

The participating centres (n = 28) analysed 1,292 signals in May 2009. Overall, 277 signals whether known or unknown were thus considered worth following up. Half of the other 893 categorised signals were “well-known” (35.7%) and non-interpretable/non-pertinent signals (36.6%); 4% were not categorised because of a lack of time. Analysis of the signals was time-consuming, but the working time estimated by the participants was highly variable (median time: 6 h; minimum: 2 h maximum: 26 h).

Conclusions

The results of this study are in favour of the integration of an automated signal detection tool to complement the current pharmacovigilance activities. The Anatomic Therapeutic Chemical for drug classification poses difficulties in many situations; the international proprietary name might be more efficient. The variability observed in the time needed for analysis suggests that a standardised methodology should be employed. Overall, the findings of this prospective study will contribute to refining the signal management procedure to be implemented in the future.

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Acknowledgements

We thank all the Regional Pharmacovigilance Centres who participated in this study

Funding

None.

Conflicts of interest

None.

Author information

Authors and Affiliations

  1. AFSSAPS, 93285, Saint-Denis, Paris, France

    Véronique Pizzoglio & Pascal Auriche

  2. INSERM, CESP Centre for Research in Epidemiology and Population Health, U1018, Biostatistics, 94807, Villejuif, Paris, France

    Ismaïl Ahmed & Pascale Tuber-Bitter

  3. Université Paris-Sud, UMRS 1018, 94807, Villejuif, Paris, France

    Ismaïl Ahmed & Pascale Tuber-Bitter

  4. Université de Bordeaux, 33000, Bordeaux, France

    Françoise Haramburu & Ghada Miremont-Salamé

  5. INSERM, U657, 33000, Bordeaux, France

    Françoise Haramburu & Ghada Miremont-Salamé

  6. CHU, Service de Pharmacologie, Centre Régional de Pharmacovigilance, 33000, Bordeaux, France

    Françoise Haramburu & Ghada Miremont-Salamé

  7. Université Paris Descartes, Hôpital Européen Georges Pompidou, AP-HP, 75015, Paris, France

    Carmen Kreft-Jaïs

  8. Biostatistique (équipe 1), Centre de recherche en Epidémiologie et Santé des Populations (CESP), INSERM – Université Paris Sud UMRS 1018, 16, avenue Paul Vaillant Couturier, 94807, Villejuif, Paris, France

    Ismaïl Ahmed

Authors
  1. Véronique Pizzoglio
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  2. Ismaïl Ahmed
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  3. Pascal Auriche
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  4. Pascale Tuber-Bitter
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  5. Françoise Haramburu
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  6. Carmen Kreft-Jaïs
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  7. Ghada Miremont-Salamé
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French Network of Pharmacovigilance Centres

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Correspondence to Ismaïl Ahmed.

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Pizzoglio, V., Ahmed, I., Auriche, P. et al. Implementation of an automated signal detection method in the French pharmacovigilance database: a feasibility study. Eur J Clin Pharmacol 68, 793–799 (2012). https://doi.org/10.1007/s00228-011-1178-1

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  • DOI: https://doi.org/10.1007/s00228-011-1178-1

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