Objective: To test data mining methods used in pharmacovigilance in order to identify potential emerging disease-nuisance associations in the national occupational disease surveillance and prevention network (RNV3P) database. Methods: Proportional reporting ratios (PRR) used in pharmacovigilance were applied to detect disproportional reporting of disease-nuisance associations which are not compensated by the national social security system. Results: The 24,785 reports of the RNV3P were grouped into 1344 different disease-nuisance associations reported more than twice, of which 422 did not give entitlement to compensation by the social security system. Among these associations, 162 were potentially emergent and generated a signal, of which 8 associations involve cancer. Conclusion: This work is the first stage of an exploratory investigation submitting the questions raised to experts and involving participants in the network in reflection on the hypotheses generated.
- data mining
- occupational diseases (MeSH)
- occupational network or database
- pharmacovigilance methods
- signal detection
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