Prescription patterns of antiepileptic drugs in young women

development of a tool to distinguish between epilepsy and psychiatric disorders

Ilaria Naldi, Carlo Piccinni, Barbara Mostacci, Jessica Renzini, Gabriele Accetta, Francesca Bisulli, Maria Tappatà, Antonella Piazza, Paola Pagano, Stefano Bianchi, Roberto D'Alessandro, Paolo Tinuper, Elisabetta Poluzzi

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Background: Antiepileptic drugs (AEDs) are also prescribed for therapeutic indications other than epilepsy (EPI), namely, psychiatric disorders (PSY). Our aim was to develop an algorithm able to distinguish between EPI and PSY among childbearing age women based on differences in AED exposure in these patient groups. Methods: Two groups of women (18–45 years) with EPI or PSY treated with AEDs in the first semester of 2010 or 2011 were extracted from paper or electronic medical charts of specialized centers. Through the prescription database of Bologna Local Health Authority (Italy), AEDs, treatment schedule and co-treatments were collected for each patient. A prescription-based hierarchical classification system was developed. The algorithm obtained was subsequently validated on internal and external data. Results: Eighty-one EPI and 94 PSY subjects were recruited. AED monotherapy was the most common choice in both groups (69% EPI vs 79% PSY). Some AEDs were used only in EPI, others exclusively in PSY. Co-treatments with antipsychotics (6% vs 67%), lithium (0% vs 9%), and antidepressants (7% vs 70%) were fewer in EPI than in PSY. The hierarchical classification system identified antipsychotics, SSRIs (Selective Serotonin Reuptake Inhibitors), and number of AEDs as variables to discriminate EPI and PSY, with an overall error rate estimate of 9.7% (95%CI: 5.3% to 14.1%). Conclusion: Among the differences between EPI and PSY, prescription data alone allowed an algorithm to be developed to diagnose each childbearing age woman receiving AEDs. This approach will be useful to stratify patients for risk estimates of AED-treated patients based on administrative databases.

Original languageEnglish
Pages (from-to)763-769
Number of pages7
JournalPharmacoepidemiology and Drug Safety
Volume25
Issue number7
DOIs
Publication statusPublished - Jul 1 2016

Fingerprint

Anticonvulsants
Prescriptions
Psychiatry
Epilepsy
Antipsychotic Agents
Medical Electronics
Databases
Serotonin Uptake Inhibitors
Therapeutics
Lithium
Italy
Antidepressive Agents
Appointments and Schedules
Health

Keywords

  • antiepileptic drugs
  • childbearing age
  • epilepsy
  • pharmacoepidemiology
  • prescription patterns
  • psychiatric disorders
  • women

ASJC Scopus subject areas

  • Pharmacology (medical)
  • Epidemiology

Cite this

Prescription patterns of antiepileptic drugs in young women : development of a tool to distinguish between epilepsy and psychiatric disorders. / Naldi, Ilaria; Piccinni, Carlo; Mostacci, Barbara; Renzini, Jessica; Accetta, Gabriele; Bisulli, Francesca; Tappatà, Maria; Piazza, Antonella; Pagano, Paola; Bianchi, Stefano; D'Alessandro, Roberto; Tinuper, Paolo; Poluzzi, Elisabetta.

In: Pharmacoepidemiology and Drug Safety, Vol. 25, No. 7, 01.07.2016, p. 763-769.

Research output: Contribution to journalArticle

Naldi, I, Piccinni, C, Mostacci, B, Renzini, J, Accetta, G, Bisulli, F, Tappatà, M, Piazza, A, Pagano, P, Bianchi, S, D'Alessandro, R, Tinuper, P & Poluzzi, E 2016, 'Prescription patterns of antiepileptic drugs in young women: development of a tool to distinguish between epilepsy and psychiatric disorders', Pharmacoepidemiology and Drug Safety, vol. 25, no. 7, pp. 763-769. https://doi.org/10.1002/pds.3984
Naldi, Ilaria ; Piccinni, Carlo ; Mostacci, Barbara ; Renzini, Jessica ; Accetta, Gabriele ; Bisulli, Francesca ; Tappatà, Maria ; Piazza, Antonella ; Pagano, Paola ; Bianchi, Stefano ; D'Alessandro, Roberto ; Tinuper, Paolo ; Poluzzi, Elisabetta. / Prescription patterns of antiepileptic drugs in young women : development of a tool to distinguish between epilepsy and psychiatric disorders. In: Pharmacoepidemiology and Drug Safety. 2016 ; Vol. 25, No. 7. pp. 763-769.
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abstract = "Background: Antiepileptic drugs (AEDs) are also prescribed for therapeutic indications other than epilepsy (EPI), namely, psychiatric disorders (PSY). Our aim was to develop an algorithm able to distinguish between EPI and PSY among childbearing age women based on differences in AED exposure in these patient groups. Methods: Two groups of women (18–45 years) with EPI or PSY treated with AEDs in the first semester of 2010 or 2011 were extracted from paper or electronic medical charts of specialized centers. Through the prescription database of Bologna Local Health Authority (Italy), AEDs, treatment schedule and co-treatments were collected for each patient. A prescription-based hierarchical classification system was developed. The algorithm obtained was subsequently validated on internal and external data. Results: Eighty-one EPI and 94 PSY subjects were recruited. AED monotherapy was the most common choice in both groups (69{\%} EPI vs 79{\%} PSY). Some AEDs were used only in EPI, others exclusively in PSY. Co-treatments with antipsychotics (6{\%} vs 67{\%}), lithium (0{\%} vs 9{\%}), and antidepressants (7{\%} vs 70{\%}) were fewer in EPI than in PSY. The hierarchical classification system identified antipsychotics, SSRIs (Selective Serotonin Reuptake Inhibitors), and number of AEDs as variables to discriminate EPI and PSY, with an overall error rate estimate of 9.7{\%} (95{\%}CI: 5.3{\%} to 14.1{\%}). Conclusion: Among the differences between EPI and PSY, prescription data alone allowed an algorithm to be developed to diagnose each childbearing age woman receiving AEDs. This approach will be useful to stratify patients for risk estimates of AED-treated patients based on administrative databases.",
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AU - Renzini, Jessica

AU - Accetta, Gabriele

AU - Bisulli, Francesca

AU - Tappatà, Maria

AU - Piazza, Antonella

AU - Pagano, Paola

AU - Bianchi, Stefano

AU - D'Alessandro, Roberto

AU - Tinuper, Paolo

AU - Poluzzi, Elisabetta

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