Use of prescription databases in studies of adverse drug effects

Transkript

1 Use of prescription databases in studies of adverse drug effects Jesper Hallas Prof. Dr.med Dept. Of Clinical Pharmacology, Syddansk Universitet, Odense Denmark

2 Indvendinger Vanskeligt at uddrage noget fra kasuistikker For mange usikkerhedsmomenter Teknologien - som den udføres - er forfejlet Teknologien - som den udføres - er misforstået Historisk set af diskutabel værdi Bedre alternativer?

3 Bivirkningsproblem? sildenafil - AMI 65-årig mand tager sildenafil og får AMI en halv time efter Har ikke forsøgt samleje i den halve time Ingen forhistorie for kardiovasculær sygdom, hypertension, eller diabetes. Aldrig ryger Første gang pt. tog sildenafil Feenstra et al. Lancet 1998; 352:

4 Facit? Mittleman et al. Am J Cardiol 2005;96: )

5 Efedrin og CV events Patient 10 Patient 10 was an apparently healthy 39-year-old man who experienced numbness of the right arm and leg on March 17, 1998, 90 minutes after drinking Ultimate Orange, which according to the label contained 415 mg of ma huang (ephedra alkaloids) per serving as well as guarana (a source of caffeine), and 5 minutes after running 3 miles (4.8 km) (Table 4). He also regularly took multivitamins and amino acid supplements, but no other medications. On presentation at a nearby hospital, his blood pressure was 140/78 mm Hg and his pulse was 60 beats per minute. Haller et al. NEJM 2000 A computed tomographic scan of the head revealed a left-sided intrathalamic hemorrhage. Cerebral angiography showed no evidence of vascular anomalies. The patient had gradual clinical improvement, and his symptoms resolved except for persistent sensory loss on the right side of his face. Chemical analysis of the Ultimate Orange product confirmed the presence of ephedrine, as well as of pseudoephedrine, norephedrine, and norpseudoephedrine.

6 Facit?

7 Spontan indberetning, begrænsninger Stor margin for selektiv rapportering Afhængig af de enkelte klinikeres mistanker Rapporterne er ofte af ringe kvalitet Kan ikke afkræfte mistanker Følsom over for publicity Er sjældent konklusiv i sig selv

8 Hvor stor en del indberettes? 0.6% af reaktioner som forårsager indlæggelse (Hallas 1992) Ca 20% af alvorlige knoglemarvsreaktioner (Kaisu 1987) 1/4000 af alvorlige reaktioner i primærsektoren (Haramburu 1997) 1/25000 af mindre alvorlige reaktioner i primærsektoren (Haramburu 1997) Under-reporting varies between 0% and 100% Patrick Waller

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12 Imputability analyser, coxibs -> thromboser VIOXX AMI < 1 sept 2004 > 1 sept 2004 Stroke < 1 sept 2004 > 1 sept 2004 Total 4 18 Total 1 14 Unlikely 4 5 Unlikely 0 3 CELEBRA AMI < 1 sept 2004 > 1 sept 2004 Stroke < 1 sept 2004 > 1 sept 2004 Total 3 6 Total 0 3 Unlikely 3 1 Unlikely 0 0 SWEDIS, Biverkningsregistret oktober 2006, Läkemedelsverket

13 Formålet er vidtgående misforstået Jeg indberettede ikke, fordi jeg var usikker på om det var en bivirkning

14 Historisk betydning 1358 December 16, 1961 LETTERS TO THE EDITOR THE LANCET

15 Historisk betydning?

16 Historisk betydning?

17 Evidence hierarchy Level 1a 1b 2a 2b Therapy/Prevention, Aetiology/Harm Meta-analyses of RCTs Individual RCT Meta-analyses of cohort studies Individual cohort study (including low quality RCT; e.g., <80% follow-up) 2c 3a 3b Ecological studies Meta-analyses of case-control studies Individual Case-Control Study 4 Case-series (and poor quality cohort and case-control studies) 5 Expert opinion without explicit critical appraisal, or based on physiology, bench research or "first principles" From: Oxford Centre for Evidence-based Medicine (May 2001)

18 Classical epidemiological designs COHORT STUDY A group of drug users and non-users are compared with respect to the outcome of interest CASE-CONTROL STUDY Patients with the outcome of interest are compared with subjects without the outcome with respect to their prior drug use.

19 Hypothetical course, illustrated by register data Ibuprofen 400 mg Ibuprofen 400 mg 100 tablets 100 tablets Upper GI bleeding March 11. March 28. April 10.

20 Pharmacoepidemiologic databases worldwide Database Population, million From Saskatchewan (Ca) COMPASS (USA) Kaiser Permamente (USA) Puget Sound (USA) Jämtland, Tierp (S) GPRD (UK) MEMO (Scotl) Odense Northern Jutland Denmark 5, Norway 4, Sweden Iceland Finland Pharmo, NL

21 Pharmacoepidemiologic databases in Denmark

22 Odense Universitets Pharmacoepidemiologic Database (OPED), data Prescription module: - CPR-number - dispensed product - quantity - pharmacy - provider Demographic module: - All Funen County residents - Complete migration history - Birth / death / migration

23 OPED, status >60 mio person identifiable prescription records Status as a public research register, maintained by the Clinical Pharmacology unit, Syddansk Universitet. Data can be transferred to third parties upon approval from Datatilsynet

24 Prescription Database of Northern Jutland (PDNJ) Has covered the county of Northern Jutland since 1989 Extended to cover Regions of Mid-and Northern Jutland Covers the same variables as OPED Status as a private research register, maintained by Århus Universitet, Dept. Of Clinical Epidemiology

25 Danish Medicines Agency Prescription register Established by law 1993 Operational from 1994 Covers all 288 Danish retail pharmacies and all hospital pharmacies, alltogether 5,4 mio persons Individual-level data, using a one-one encryption of CPR-numbers. Covers reimbursed and non-reimbursed prescription drugs Established for administrative purposes, not research (!!) Provide a detailed individual-level drug utilization statistic

26 Lægemiddelstyrelsens statistik

27 Danish Medicines Agency and Danmarks Statistik A complete copy of the DKMA prescription register since 1995! A complete copy of the Danish Patient Registry since 1977 Linkage enabled by mutual encrypted CPR-number Access through secure connection Individual-level data are not given to researchers Tables and analyses are transferred by to the researchers Forskerserviceenhed Contact:

28 Key health registries in Denmark Registry holder Ministry of internal affairs National Health Board Counties Others Registry Central Person Registry The Danish Conscription Registry Danish Patient Registry Cause of Death Registry Birth Registry Abortion Registry Danish Congenital Malformation Registry Provider Registry Registry of GP services Danish amputation Registry Registry of Psychiatric Demography Multiple Sclerosis Registry Danish Cancer Registry Danish Registry of Heritable Eye Diseases Danish Accident Registry Occupational Registry of Danish Statistical Insitute Registry for Education Statistics Danish Registry of Föhlings Disease Danish Twin Registry Danish Cytogenetic Registry

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31 Confounding Lack of comparability. Bias generated by the lack of comparability between users and non-users of drugs Operational definition: 1. Independent determinant of the outcome 2. Associated with the exposure (positive or negative association)

32 Confounder Control IN DESIGN Randomisation Cross-over Restriction Matching in cohorte studies Matching in case-control studies IN ANALYSIS Standardisation Stratification Multivariate modelling Propensity scores Instrumental variables Cross-over Symmetry analysis

33 Registry based drug effect studies, limitations Treatments are not randomised Quality of diagnosis data. Not possible to validate data i Statistics Denmark! Lack of relevant confounder data (smoking, alcohol, BMI, OTC-drugs etc) (Did the patient take the drug?)

34 Other problems Undue delay from signals to rigorous studies Shortage of trained pharmacoepidemiologists Underdeveloped net-work of registry holders (Misunderstood) issues of confidentiality