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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.

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Apresentação em tema: "C AUSALITY A SSESSMENT OF R EPORTED A DVERSE D RUG R EACTIONS Ana Filipa Macedo Faculty of Health Sciences Portugal."— Transcrição da apresentação:

1 C AUSALITY A SSESSMENT OF R EPORTED A DVERSE D RUG R EACTIONS Ana Filipa Macedo Faculty of Health Sciences Portugal

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

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

4 P ERSPECTIVA H ISTÓRICA … 1937 – Sulfanilamide in Dietilenoglicol / Renal Impairment 1961 – Thalidomide / Phocomelia Victims 1971 – Dietilstilbestrol / Vaginal Carcinoma in the daughters, 10 to 20 years after exposition

5 I NTERNATIONAL P HARMACOVIGILANCE S YSTEMS PREMARKETING INVESTIGATION Long Latency ADR Chronic ADR Rare ADR Interactions Risk Groups Limitations POSTMARKETING INVESTIGATION PHARMACOVIGILANCE

6 A DVERSE D RUG R EACTION “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 E PIDEMIOLOGY OF A DVERSE D RUG R EACTIONS 4 th to 6 th 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 Medication Error (Preventable) Preventable ADRs ADRs not Preventable Quality Problems Adverse Effects

8 SAFETY MONITORING Identification of a Problem Problem Characterization Benefit – Risk Evaluation Risk Management Communication Decision P HARMACOVIGILANCE

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

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

11 G LOBAL I NTROSPECTION “ Clinical Judgement of Experts” Subjective Problems of reproducibility Not calibrated

12 D ECISIONAL A LGORITHMS “Systematic Strategies of Decision in Uncertainty Conditions” Explicit Reproducible Simple Possible Automation Improve Reporting

13 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 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 D ECISIONAL A LGORITHMS

14 1.Challenge 2.Dechallenge 3.Rechallenge 4.Bibliographic Description Etiologic Alternatives C RITERIA

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16 SIMNÃONÃO SEI PONTOS 1. Existem outras notificações conclusivas sobre esta reacção? O acontecimento adverso manifestou-se depois da administração do fármaco suspeito? A reacção adversa melhorou com suspensão do fármaco ou administração de um antagonista específico? A reacção adversa reapareceu com readministração do fármaco? Existem causas alternativas (diferentes do fármaco) capazes de provocar a reacção por si mesmas? A reacção adversa reapareceu com administração dum placebo? Foi detectado fármaco no sangue (ou outros fluidos) em concentrações tóxicas? A reacção foi mais severa com aumento da dose e menos com a diminuição? O doente apresentou uma reacção semelhante ao fármaco ou outros semelhantes em qualquer exposição anterior? O acontecimento adverso foi confirmado por qualquer tipo de evidência objectiva? +100 PONTUAÇÃO TOTAL Naranjo et al (1981)

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19 L IMITATIONS Fixed Scoring Arbitrary Scoring Disagreement between algorithms None universally accepted as gold standard

20 C AUSALITY A SSESSMENT G LOBAL I NTROSPECTION S ELECTED A LGORITHMS 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 11. Kr-Kramer 12. N -Naranjo 13. St-Stephens 14. V-Venulet 15. W-Weber

21 R ESULTS  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

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

23 D ECISIONAL A LGORITHMS AND Q UANTITATIVE M ETHODS OF S IGNAL D ETECTION Bayesian Confidence Propagation Neural Network (BCPNN) Signal

24 R EFERENCES [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 : [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:


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