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C AUSALITY A SSESSMENT OF R EPORTED A DVERSE D RUG R EACTIONS

Ana Filipa Macedo Faculty of Health Sciences Portugal. C AUSALITY A SSESSMENT OF R EPORTED A DVERSE D RUG R EACTIONS. No drug which is pharmacologically effective is entirely without hazard. Efficacy. Quality. Safety. Safety is a relative concept. H ISTORICAL P ERSPECTIVE.

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C AUSALITY A SSESSMENT OF R EPORTED A DVERSE D RUG R EACTIONS

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  1. Ana Filipa Macedo Faculty of Health Sciences Portugal CAUSALITYASSESSMENTOFREPORTEDADVERSEDRUGREACTIONS

  2. No drug which is pharmacologically effective is entirely without hazard Efficacy Quality Safety Safety is a relative concept

  3. HISTORICAL PERSPECTIVE 2000 b.C. – HAMMURABI CODE: “The Doctor who causes death should loose his hands” 500 b.C. – HIPÓCRATES: “Primum non nocere” 200 – GALENO: “Drugs have a main action and a secondary action”

  4. PERSPECTIVA HISTÓRICA … 1937 – Sulfanilamide in Dietilenoglicol /Renal Impairment 1961 – Thalidomide / Phocomelia - 10 000 Victims 1971 – Dietilstilbestrol / Vaginal Carcinoma in the daughters, 10 to 20 years after exposition

  5. INTERNATIONAL PHARMACOVIGILANCE SYSTEMS PREMARKETING INVESTIGATION Long Latency ADR Chronic ADR Rare ADR Interactions Risk Groups Limitations PHARMACOVIGILANCE POSTMARKETING INVESTIGATION

  6. ADVERSE DRUG REACTION “a response to a drug which is noxious and unintended, and which occurs at dose normally used in humans for the prophylaxis, diagnosis or therapy of disease, or for a modification of physiological function.” W.H.O 1972

  7. EPIDEMIOLOGY OFADVERSE DRUG REACTIONS 4th to 6th cause of death in U.S.A. ,1994 5% of Hospital Admissions 11% of Hospital Patients Doubles costs, length of stay and mortality risk 50% are potentially preventable Less than 1% are reported Adverse Effects Medication Error (Preventable) Preventable ADRs ADRs not Preventable Quality Problems

  8. PHARMACOVIGILANCE Identification of a Problem Problem Characterization Communication SAFETY MONITORING Decision Benefit – Risk Evaluation Risk Management

  9. “Drug Safety is a field where can be smoke without fire”Waller, P. Drug Exposition Reported Adverse Effect IMPUTATION Dynamic Process

  10. DIFFICULT... Complex Nature of Adverse Events Individual Clinical Variability Retrospective Spontaneous Report

  11. GLOBAL INTROSPECTION“Clinical Judgement of Experts” • Subjective • Problems of reproducibility • Not calibrated

  12. DECISIONAL ALGORITHMS “Systematic Strategies of Decision in Uncertainty Conditions” • Explicit • Reproducible • Simple • Possible Automation • Improve Reporting

  13. 21. MV-V Maria 22. WHO 23. R-RUCAM 24. Ru-Ruskin 25. St-Stephens 26. Sk-Stricker 27. T-Taiwan 28. V-Venulet 29. W-Weber 30. Wi - Wiholm 1. AD-ADRIAN 2. Aust-Australian 3. By-Bayesiano 4. B-Blanc 5. Ca-Castle 6. Co-Cornelli 7. CPMP- Syst. ABO 8. D-Dangoumau 9. Em-Emanueli 10. Ev-Evreux 11. HM-Hoskins & Maninno 12. HS-Hsu-Stoll 13. I-Irey 14. Ja-Jain 15. Jo-Jones 16. KL-Karch & Lasagna 17. Ki-Kitaguchi 18. Kr-Kramer 19. La-Lagier 20. Lu-Loupi DECISIONAL ALGORITHMS

  14. CRITERIA • Challenge • Dechallenge • Rechallenge • Bibliographic Description • Etiologic Alternatives

  15. Naranjo et al (1981)

  16. LIMITATIONS • Fixed Scoring • Arbitrary Scoring • Disagreement between algorithms None universally accepted as gold standard

  17. 11.Kr-Kramer 12.N -Naranjo 13. St-Stephens 14. V-Venulet 15. W-Weber 1. Aust-Australian 2. B-Blanc 3. Co-Cornelli 4. D-Dangoumau 5. Em-Emanueli 6. HS-Hsu-Stoll 7. I-Irey 8. Jo-Jones 9. KL-Karch & Lasagna 10. Ki-Kitaguchi CAUSALITY ASSESSMENT GLOBAL INTROSPECTION SELECTED ALGORITHMS

  18. RESULTS • Agreement between algorithms and GI was 43% in average • 100% agreement was not found for any algorithm • None of the adverse events was equally imputed by all the algorithms • Sensitivity 93% and Specificity 7% in average

  19. CONCLUSIONS A reference method was not identified Decisional algorithms are not definite alternatives in the individual causality assessment of adverse drug reactions.

  20. Signal DECISIONAL ALGORITHMSAND QUANTITATIVE METHODS OFSIGNAL DETECTION Bayesian Confidence Propagation Neural Network (BCPNN)

  21. REFERENCES [1] MACEDO, A.F. [et al.] -Causality assessment of adverse drug reactions: comparison of the results obtained from published decisional algorithms and from the evaluations of an expert panel, according to different levels of imputability. J Clin Pharm Ther.2003. 28: 137-143. [2] STAHL, M. [et al.] – Introducing triage logic as a new strategy for the detection of signals in the WHO Drug Monitoring Database. Pharmacoepidemiol Drug Safe. 2004; 13: 355-363.

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