Variability of drug exposure, exposure measurement

Transcription

1 Variability of drug exposure, exposure measurement A key element in the study of occurrence of disease given drug use (drug exposure-outcomes association) Hubert G. Leufkens

2 Declaration of interests Professor of Pharmacoepidemiology, Utrecht Institute of, 0.4 FTE. Chairman of the Dutch Medicines Evaluation Board (MEB), since mid Co-opted member of CHMP PhVWP, ; since 2009 co-opted member of CHMP. Director WHO-Utrecht Collaborating Centre on Pharmaceutical Policy Analysis, since This talk reflects my personal views; I am being inspired and challenged on a daily basis by many colleagues from these environments.

3 Napoleon's March on Moscow: exposure and outcomes Minard M, 1885

4 Two decades of progress in drug safety assessment-management: three phases 1. Beyond counting crude numbers of spontaneous ADR reports 3. Proactive risk management plans, landscaping drug use context, molecular correlates 2. Exposure correlates (channeling, compliance, duration of use, confounding by indication)

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6 Investors are reacting promptly to rumours of safety publications Gale EAM. Diabetologia 2009; 52:

7 Lancet 2011 March 12; 377:

8 Four recent EU market suspensions October 2008, rimonabant (Acomplia) for the treatment of overweight and obese patients, suspended because of psychiatric disorders. February 2009, efalizumab (Raptiva) for the treatment of psoriasis, suspended because of safety concerns, including progressive multifocal leukoencephalopathy (PML). January 2010, sibutramine (Reductil) for the treatment of overweight and obese patients, suspended because of cardiovascular harm. September 2010, rosiglitazone (Avandia) for the treatment of diabetes II, suspended because of cardiovascular harm.

9 Relevant features for managing B/R Rimonabant and CNS events MABs and risk of infections, PML Sibutramine and CV events Rosiglitazone and CV events Known effect, B/R initially positive Rare, difficult to see, but very severe Known effect, B/R uncertain at start Known effect, B/R uncertain at start Patterns of use, too short duration of use Outcome masked by indication SCOUT study driver B/R assessment Meta-analyses driver of debate Complex outcome measurement Ascertainment and traceability exposure How to define a group that may benefit How to define a group that may benefit Risk minimization insufficient Risk minimization insufficient Risk minimization insufficient Risk minimization insufficient Confounding by underlying disease Differential weighing of B/R per indication RR of 1.2 enough to suspend What about pioglitazone?

10 a b s o l u t e r i s k Shift to complex signal-noise issues in drug safety Drug exposure Examples of high baseline risk/low RR: - Antidiabetics and cardiovascular risk. - Obesity drugs and psychiatric events. - MABs and PML. - Antidepressants and suicide risk. low baseline risk/high RR high baseline risk/low RR Time

11 Drug safety = Molecule + Context Drug specific characteristics (e.g. both type A and B adverse reactions) Patient related (e.g. disease, severity of the condition, susceptible genotype) Usage/prescribing related (e.g. interactions, noncompliance with drug labeling, usage errors) Cave: Complex safety assessments when the possible drug induced problem is very close to the indication of the drug (e.g. diet drugs and cardiovascular ADRs, eczema drugs and lymphomas, psychotropics and suicide risk).

12 Three types of associations in studying occurrence of disease given drug use Real causal associations (e.g. NSAIDs and GI bleeding, glafenine and anaphylaxis) Effect modification (e.g. use SSRIs and bleeding risk, corticosteroids and fluorquinolone induced tendon disorders) Drugs enabling new dangerous behavior or circumstances (e.g. bromocriptine and breast cancer, sildenafil and MI)

13 Important data sources in pharmacoepidemiology Medical charts Case reports, spontaneous reporting systems Hospital data Pharmacy records Patient interview/questionnaire data Medical claims/insurance data Health statistics Dedicated pharmacoepidemiologic record linkage databases (GPRD, HMOs, MEMO, OPED, PHARMO and the like)

14 Exposure assessment is not a yes/no question Examples: Drug induced nephrotoxity ICS and fracture risk

15 Leufkens HG, Egberts AC. Pharmacovigilance: from signal to action. In: Broe ME de, Porter GA, eds. Clincal Nephrotoxins. 3 rd Ed, 2008: 90.

16 Inhaled steroids and bone density van Staa TP, Leufkens H, Cooper C. N Engl J Med 2002; 346: van Staa TP, Leufkens H, Cooper C. Am J Respir Crit Care Med 2003;168: 128.

17 Inhaled steroid induced fracture risk and dose beclomethasone equivalents Low dose < 300 µg/day Medium dose µg /day High dose >700 µg /day (N=46,797) (N=43,070) (N=28,815) Non-vertebral 1.11 ( ) 1.16 ( ) 1.28 ( ) Forearm 1.06 ( ) 1.19 ( ) 1.15 ( ) Hip 0.95 ( ) 1.06 ( ) 1.77 ( ) Vertebral 1.31 ( ) 1.39 ( ) 2.50 ( ) Staa TP van, Leufkens HGM et al, J Bone Miner Res 2001;16:

18 Complex drug exposure issues (who is using what, when, how long, at what dosages) Exposure Outcome Example Pregnancy exposure (in different phases) Strong increase of use over time Drug exposure as part diagnostic procedure Congenital abnormalities Stroke, other CV effects Nephrogenic Systemic Fibrosis (NSF) Lamotrigine, ACEinhibitors, SSRIs Methylphenidate Gadolinium products in MR radiology Long-term use Several Biphosponates, biologicals, statins Acute, single dose, in crisis situation Several Pandemic influenza vaccines Contaminated product Several Ethylmesylate in Nelfinavir (Viracept)

19 Measures of drug exposure Incidence of use: start of therapy at a certain moment in the time window of observation Prevalence of use: exposed at a certain moment (or period) in the time window of observation (for chronic therapy the DDD/1000 p/day is a good surrogate estimate of the prevalence when the PDD/DDD equals 1) Person-time of use: accumulated units of time (days, years) with ascertained exposure Exposure profile variable drug exposure patterns drive to case-control studies

20 Reliability of drug exposure data Evaluate the sequence of: Cave: Self medication, OTC Drug prescribing/ dispensing by nurses, other health professionals Biologicals, vaccins, etc. through special programs prescribing dispensing actual use Primary drug defaulting Patient noncompliance

21 Drug exposure patterns and time windows Start of therapy End of prescription Discontinuation of therapy Continuation of therapy Switch of therapy Time window

22 The effect of choice of time window on outcome* Time window Rate (CI 95% ) (per 10 3 person-days) Legend duration 0.7 ( ) 7 day 0.6 ( ) 30 day 0.6 ( ) 60 day 0.5 ( ) 90 day 0.4 ( ) * start of anti-ulcer therapy as marker for GI complaints Staa TP van, Abenhaim L, Leufkens H. A study of the effects of exposure misclassification due to the time-window design in pharmacoepidemiologic studies. J Clin Epidemiol 1994; 47:183-9.

23 Drug exposure scenarios in a case-control fashion current exposure past exposure future exposure? case control past exposure? Time

24 Use of beta2 agonists and risk of MI in patients with hypertension Vries F de, et al. Br J Clin Pharmacol 2008; 65:

25 Drug exposure scenarios in a cohort fashion case concomitant drug use Time

26 Duration of antihypertensive drug use and risk of dementia Haag MD et al. Neurology 2009; 72:

27 Confounding, bias and effect modification

28 Stricker BHCh, Psaty BM. Br Med J 2004; 329: 44-7.

29 Comparing like with like

30 Comparing like with like García Rodríguez LA et al. Use of multiple international healthcare databases for the detection UIPSof Utrecht rare drug-associated Institute for outcomes: a pharmacoepidemiological programme comparing rosuvastatin with other marketed statins. Pharmacoepi Drug Saf 2010; 19:

31 The juice is in new users Risk of antipsychotic induced hip/femure fracture over time Pouwels S et al. Osteoporos Int 2009; 20:

32 Immortal time bias in cohort studies Suissa S. Am J Repir Crit Care Med 2003; 168;

33 Other sources of time bias Gardarsdottir H. Duration of antidepressant drug treatment and its influence on risk of relapse/recurrence: Immortal and neglected time bias. Am J Epidemiol 170; 3:

34 Prescribing cascade Rochon PA, Gurwitz JH. Optimising drug therapy. Br Med J 1997; 315:

35 Two important measures in risk management Absolute risk: the probability of a certain event given a certain exposure: a/a+b or c/c+d Relative risk: the ratio between two absolute risks: a/a+b divided by c/c+d, in case control studies measured as the odds ratio (ad/cb) Event No event Exposed a b Non-exposed c d

36 Pharmaceutical risk management: targeting patients most at risk Absolute risk Overall relative risk Certain risk groups (effect modifiers) Risk increased by Cardiovascular events in rofecoxib high Severely ill, elderly Dose, longterm use, off label use EPS risk in patients using antipsychotics SRRI induced hyponatremia Mostly low 3 Slow metabolizers (CYP 2D6) Low 4 Elderly and users of diuretics Genotype Patient profile, disease severity

37 First reports of cardiovascular risk of rofecoxib In October 2000 presented by Lareb (Netherlands Pharmacovigilance Centre) during a WHO Annual Meeting in Tunis (Edwards IR Drug Saf 2005; 28: 651-8). First publication in March 2001 in Dutch Therapeutic Bulletin (GEBU). Until December 2001 a total of 83 reports. 5 cases of (cardiovascular) mortality, aged 63-87, high prevalence of cardiovascular risk factors, 3/5 used maximum dose of 25 mg/day.

38 Cardiovascular effects in patients using 60 mg/day etoricoxib vs 150 mg/day diclofenac Multinational Etoricoxib and Diclofenac Arthritis Long-term (MEDAL) study. Lancet 2006; 368:

39 Risk of EPS side effects in poor metabolisers of antipsychotics Antipsychotics metabolised by CYP2D6 OR (95% CI) yes 3.98 ( ) no 1.24 ( ) Schillevoort I et al. Pharmacogenetics 2002 Apr; 12(3):

40 Hyponatraemia and SSRIs Data source Case definition No. cases Relative risk PHARMO Clinical laboratory data Hospitalisation for ICD mmol/l Only one of out of three lab test based cases could be found when hospitalisation (ICD ) was applied. Movig KL et al. Br J Clin Pharmacol 2002; 53: Movig KL et al. Eur J Clin Pharmacol 2002; 58:143-8.

41 Movig KL et al. Br J Clin Pharmacol 2002; 53(4):

42 The concept of drug class has many dimensions For the purpose of taxonomy, e.g. grouping in PDR, BNF or WHO ATC code. Important in drug discovery and development, e.g. from lead compound to ideal drug. Regulatory, e.g. consistency in indication, class labeling, etc. Classes mean markets, competition within classes. Formulary and prescribing decision making, therapeutic substitution, basis for reference price.

43 Is this a drug class? Strom BL et al. N Engl J Med 2003; 349:

44 Is this a drug class? (cont d) Nature Reviews Drug Discovery 2003; 2:

45 Is this a drug class? (cont d) ETCP unbound/ic50 based on 54 drugs; some examples: Amiodarone <0.01 Fluoxetine <0.01 Olanzapine 0.02 Sertindole 0.11 Cisapride 2.45 Quinidine De Bruin ML et al. Anti-HERG activity and the risk of drug-induced arrhythmias and sudden death. Eur Heart J 2005 ; 26:

46 We struggle with class effects, showing differential risks within classes Fenoterol/beta-agonists and increased risk of asthma death. Short-acting nifedipine/ccbs and increased MI risk. Cerivastatin/statins and increased risk of rhabdomyolysis. COX-2 inhibitors and CV risk. Glitazones and CV risk. Gadolinium contrast agents and NSF.

47 Molecular dimensions in pharmacoepidemiology Related to drug exposure, e.g. drug related SAR characteristics, ADME (absorption, distribution, metabolism excretion), gene-drug interactions affecting pharmacokinetics Related to the pathway/mechanism of the drug effect, e.g. effect modifiers, intermediate biomarkers, gene-drug interactions affecting pharmacodynamics, e.g. drug-drug target interactions Related to the outcome, e.g. molecular features as outcome measure (i.e. ALT for liver toxicity, CK for rhabdomyolysis, proteinuria for renal problems, etc.), gene-drug interactions affecting clinical response

48 Schulte PA, Perera FP. Molecular Epidemiology, 1993: 6.

49 Ingelman-Sundberg M. New Eng J Med 2008; 358: (editorial) Mahal et al. New Eng J Med 2008; 358: (original study)

50 Pharmacogenetics: case of abacavir Clinical trials had shown that severe hypersensitivity reaction (HSR) to abacavir (HIV reverse-transcriptase inhibitor) was seen in 4-5% of patients. In two case-control studies hypersensitivity was linked to genetic variant HLA B5701 (data that time showed that 55% of patients with the reaction were carriers of this SNP; 1% of patients without were carriers). Regulators were reluctant to include HLA B5701 testing in the label based on these case-control studies; practice guidelines filled this gap. PREDICT-1 Study 2008 convinced regulators. Hethering S et al. Lancet 2002: 359: Mallai S et al Lancet 2002; 359: Mallai S et al. PREDICT-1 Study Team. HLA-B*5701 screening for hypersensitivity to abacavir. N Engl J Med 2008; 358:

51 Susceptible genotype responsible for troglitazone-associated hepatic failure Genotype Null/Null Wild/wild,wild/ Odds ratio GSTT1- GSTM1 N (%) null,null/wild N (%) Controls 13 (15) 72 (85) 1.00 Cases 10 (40) 15 (60) 3.7 ( ) GSTT1-GSTM1=combined gluthatione S-transferase Watanabe I et al. Clin Pharmacol Ther 2003; 73;

52 2003