Ascertainment of acute liver injury in two European primary care databases

Abstract

Purpose

The purpose of this study was to ascertain acute liver injury (ALI) in primary care databases using different computer algorithms. The aim of this investigation was to study and compare the incidence of ALI in different primary care databases and using different definitions of ALI.

Methods

The Clinical Practice Research Datalink (CPRD) in UK and the Spanish “Base de datos para la Investigación Farmacoepidemiológica en Atención Primaria” (BIFAP) were used. Both are primary care databases from which we selected individuals of all ages registered between January 2004 and December 2009. We developed two case definitions of idiopathic ALI using computer algorithms: (i) restrictive definition (definite cases) and (ii) broad definition (definite and probable cases). Patients presenting prior liver conditions were excluded. Manual review of potential cases was performed to confirm diagnosis, in a sample in CPRD (21 %) and all potential cases in BIFAP. Incidence rates of ALI by age, sex and calendar year were calculated.

Results

In BIFAP, all cases considered definite after manual review had been detected with the computer algorithm as potential cases, and none came from the non-cases group. The restrictive definition of ALI had a low sensitivity but a very high specificity (95 % in BIFAP) and showed higher rates of agreement between computer search and manual review compared to the broad definition. Higher incidence rates of definite ALI in 2008 were observed in BIFAP (3.01 (95 % confidence interval (CI) 2.13–4.25) per 100,000 person-years than CPRD (1.35 (95 % CI 1.03–1.78)).

Conclusions

This study shows that it is feasible to identify ALI cases if restrictive selection criteria are used and the possibility to review additional information to rule out differential diagnoses. Our results confirm that idiopathic ALI is a very rare disease in the general population. Finally, the construction of a standard definition with predefined criteria facilitates the timely comparison across databases.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2

References

  1. 1.

    Trifiro G et al (2009) Data mining on electronic health record databases for signal detection in pharmacovigilance: which events to monitor? Pharmacoepidemiol Drug Saf 18:1176–1184

    PubMed  Article  Google Scholar 

  2. 2.

    Lexchin J (2005) Drug withdrawals from the Canadian market for safety reasons, 1963-2004. CMAJ 172:765–767

    PubMed Central  PubMed  Article  Google Scholar 

  3. 3.

    Ibanez L, Perez E, Vidal X, Laporte JR (2002) Prospective surveillance of acute serious liver disease unrelated to infectious, obstructive, or metabolic diseases: epidemiological and clinical features, and exposure to drugs. J Hepatol 37:592–600

    PubMed  Article  Google Scholar 

  4. 4.

    de Abajo FJ, Montero D, Madurga M, Garcia Rodriguez LA (2004) Acute and clinically relevant drug-induced liver injury: a population based case-control study. Br J Clin Pharmacol 58:71–80

    PubMed Central  PubMed  Article  Google Scholar 

  5. 5.

    El-Serag HB, Everhart JE (2002) Diabetes increases the risk of acute hepatic failure. Gastroenterology 122:1822–1828

    PubMed  Article  Google Scholar 

  6. 6.

    Huerta C, Zhao SZ, Garcia Rodriguez LA (2002) Risk of acute liver injury in patients with diabetes. Pharmacotherapy 22:1091–1096

    PubMed  Article  Google Scholar 

  7. 7.

    Garcia Rodriguez LA, Stricker BH, Zimmerman HJ (1996) Risk of acute liver injury associated with the combination of amoxicillin and clavulanic acid. Arch Intern Med 156:1327–1332

    CAS  PubMed  Article  Google Scholar 

  8. 8.

    Garcia Rodriguez LA, Duque A, Castellsague J, Perez-Gutthann S, Stricker BH (1999) A cohort study on the risk of acute liver injury among users of ketoconazole and other antifungal drugs. Br J Clin Pharmacol 48:847–852

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  9. 9.

    Bjornsson ES, Bergmann OM, Bjornsson HK, Kvaran RB, Olafsson S (2013) Incidence, presentation, and outcomes in patients with drug-induced liver injury in the general population of Iceland. Gastroenterology 144:1419–1425

    PubMed  Article  Google Scholar 

  10. 10.

    Platt R et al (2012) The U.S. Food and Drug Administration’s Mini-Sentinel program: status and direction. Pharmacoepidemiol Drug Saf 21(Suppl 1):1–8

    PubMed  Google Scholar 

  11. 11.

    Carnahan RM, Moores KG (2012) Mini-Sentinel’s systematic reviews of validated methods for identifying health outcomes using administrative and claims data: methods and lessons learned. Pharmacoepidemiol Drug Saf 21(Suppl 1):82–89

    PubMed  Article  Google Scholar 

  12. 12.

    Stang PE et al (2010) Advancing the science for active surveillance: rationale and design for the Observational Medical Outcomes Partnership. Ann Intern Med 153:600–606

    PubMed  Article  Google Scholar 

  13. 13.

    Lo Re V 3rd (2013) Validity of diagnostic codes to identify cases of severe acute liver injury in the U.S. Food and Drug Administration’s Mini-Sentinel Distributed Database. Pharmacoepidemiol Drug Saf 22:861–872

    PubMed  Article  Google Scholar 

  14. 14.

    Katz AJ, Ryan PB, Racoosin JA, Stang PE (2013) Assessment of case definitions for identifying acute liver injury in large observational databases. Drug Saf 36:651

    CAS  PubMed  Article  Google Scholar 

  15. 15.

    Garcia Rodriguez LA, Perez Gutthann S (1998) Use of the UK General Practice Research Database for pharmacoepidemiology. Br J Clin Pharmacol 45:419–425

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  16. 16.

    Garcia Rodriguez LA, Perez-Gutthann S, Jick S (2000) In: Storm BL (ed) Pharmacoepidemiology, 3rd edn. Wiley, Ltd, Chichester, pp 375–385

    Google Scholar 

  17. 17.

    Garcia Rodriguez LA, Ruigomez A (2010) Case validation in research using large databases. Br J Gen Pract 60:160–161

    PubMed Central  PubMed  Article  Google Scholar 

  18. 18.

    Abbing-Karahagopian V, Kurz X, de Vries F, van Staa TP, Alvarez Y, Hesse U, Hasford J, Dijk Lv, de Abajo FJ, Weil JG, Grimaldi-Bensouda L, Egberts AC, Reynolds RF, Klungel OH.(2014)Bridging differences in outcomes of pharmacoepidemiological studies: design and first results of the PROTECT project. Curr Clin Pharmacol. 9(2):130--8

  19. 19.

    de Abajo FJ et al (2013) Upper gastrointestinal bleeding associated with NSAIDs, other drugs and interactions: a nested case-control study in a new general practice database. Eur J Clin Pharmacol 69:691–701

    CAS  PubMed  Article  Google Scholar 

  20. 20.

    Chacon Garcia A, Ruigomez A, Garcia Rodriguez LA (2010) Incidence rate of community acquired pneumonia in a population cohort registered in BIFAP. Aten Primaria 42:543–549

    PubMed  Article  Google Scholar 

  21. 21.

    Connolly JP, McGavock H, Wilson-Davis K (1997) Research methodology: coding perceived morbidity in general practice—an evaluation of the Read Classification and the International Classification of Primary Care (ICPC). Pharmacoepidemiol Drug Saf 6:325–330

    CAS  PubMed  Article  Google Scholar 

  22. 22.

    Benichou C (1990) Criteria of drug-induced liver disorders. Report of an international consensus meeting. J Hepatol 11:272–276

    CAS  PubMed  Article  Google Scholar 

  23. 23.

    Garcia Rodriguez LA, Ruigomez A, Jick H (1997) A review of epidemiologic research on drug-induced acute liver injury using the general practice research data base in the United Kingdom. Pharmacotherapy 17:721–728

    CAS  PubMed  Google Scholar 

  24. 24.

    Aithal GP et al (2011) Case definition and phenotype standardization in drug-induced liver injury. Clin Pharmacol Ther 89:806–815

    CAS  PubMed  Article  Google Scholar 

  25. 25.

    Garcia Rodriguez LA, Williams R, Derby LE, Dean AD, Jick H (1994) Acute liver injury associated with nonsteroidal anti-inflammatory drugs and the role of risk factors. Arch Intern Med 154:311–316

    CAS  PubMed  Article  Google Scholar 

  26. 26.

    Garcia Rodriguez LA, Perez Gutthann S, Walker AM, Lueck L (1992) The role of non-steroidal anti-inflammatory drugs in acute liver injury. BMJ 305:865–868

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  27. 27.

    Sgro C et al (2002) Incidence of drug-induced hepatic injuries: a French population-based study. Hepatology 36:451–455

    PubMed  Article  Google Scholar 

  28. 28.

    Graham DJ, Drinkard CR, Shatin D (2003) Incidence of idiopathic acute liver failure and hospitalized liver injury in patients treated with troglitazone. Am J Gastroenterol 98:175–179

    CAS  PubMed  Article  Google Scholar 

  29. 29.

    de Lusignan S et al (2001) A survey to identify the clinical coding and classification systems currently in use across Europe. Stud Health Technol Inform 84:86–89

    PubMed  Google Scholar 

  30. 30.

    Ruigomez A, Martin-Merino E, Rodriguez LA (2010) Validation of ischemic cerebrovascular diagnoses in the health improvement network (THIN). Pharmacoepidemiol Drug Saf 19:579–585

    PubMed  Article  Google Scholar 

  31. 31.

    Goldberg DS, Lewis JD, Halpern SD, Weiner MG, Lo Re V 3rd (2013) Validation of a coding algorithm to identify patients with hepatocellular carcinoma in an administrative database. Pharmacoepidemiol Drug Saf 22:103–107

    PubMed Central  PubMed  Article  Google Scholar 

  32. 32.

    Salvador Rosa A, Moreno Perez JC, Sonego D, Garcia Rodriguez LA, de Abajo Iglesias FJ (2002) The BIFAP project: database for pharmaco-epidemiological research in primary care. Aten Primaria 30:655–661

    CAS  PubMed  Article  Google Scholar 

Download references

Acknowledgments

We thank Dr Lucia Cea-Soriano for reviewing previous version of the manuscript. The research leading to these results was conducted as part of the Pharmacoepidemiological Research on Outcomes of Therapeutics by a European ConsorTium (PROTECT; www.imi-protect.eu) which is a public-private partnership coordinated by the European Medicines Agency. Authors would like to thank the excellent collaboration of physicians in the participating countries, whose contribution in recording their professional practice with high-quality standards makes possible the availability of databases used in this research.

Funding

The PROTECT project has received support from the Innovative Medicines Initiative Joint Undertaking (www.imi.europa.eu) under Grant Agreement no. 115004, resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in-kind contribution. In the context of the IMI Joint Undertaking (IMI JU), the Department of Pharmacoepidemiology, Utrecht University, received a direct financial contribution from Pfizer. The views expressed are those of the authors only.

Authorship statement

Guarantor of article: Ana Ruigómez

Specific author contributions

Ruigomez A, Garcia Rodriguez LA designed the research study and wrote the protocol.

Ruigomez A, Brauer R and Requena G performed the computer research and analyzed the data.

Ruigomez A, Garcia Rodriguez LA, Brauer R and Bate A drafted the manuscript.

Huerta C, Francisco de Abajo, Requena G and Gil M collected and managed the data in BIFAP and reviewed the manuscript.

Brauer R, Downey G and Feudjo Tepie M collected and managed the data in CPRD.

de Groot M, Schlienger R, Reynolds R and Klungel O reviewed the protocol and manuscript.

All authors contributed to the study design discussions, revising the manuscript, and given the approval of final versions.

Author information

Affiliations

Authors

Corresponding author

Correspondence to A. Ruigómez.

Additional information

This work has not been published or presented in any way before.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Online resource 1

(PDF 59 kb)

Online resource 2

(PDF 93 kb)

Online resource 3

(PDF 64 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Ruigómez, A., Brauer, R., Rodríguez, L.A.G. et al. Ascertainment of acute liver injury in two European primary care databases. Eur J Clin Pharmacol 70, 1227–1235 (2014). https://doi.org/10.1007/s00228-014-1721-y

Download citation

Keywords

  • Primary care databases
  • Incidence
  • Acute liver injury
  • Computer algorithms
  • Diagnosis definition
  • BIFAP
  • CPRD