farmacoepi course leiden 0210 part 2
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TRANSCRIPT
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PharmacoepidemiologyStudy designInformation bias & selection bias
Rob Heerdink
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Dr Rob Heerdink
Pharmacoepidemiology & Pharmacotherapy
Utrecht Institute for Pharmaceutical Sciences
Universiteit UtrechtThe Netherlands
www.pharm.uu.nl/epithera
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Drug development
discovery
Discovery & screening
Proof of Concept
first administration to man
registration& launch
approx. 10-12 years
10,000
Pre-clinicaldevelopment
15-30
Fase I/IIa
10-15Fase IIb/III
15
preclinicalclinical (I-III)
phase IV
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Relevant questions in practice following registration• effect on hard endpoints
• long term (side)effects
• value compared to other drugs
• effect in populations that were not studied
• children
• elderly
• pregnant
• multiple pathology / drug use
• who benefits and who does not
• less frequently seen adverse effects
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DOMAIN
Determinant(s) Endpoint(s)time
• yes / no comparison
• experimental or observational
• retrospective or prospective
Study design
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Research designs
Follow-up (cohort)Prospective
Experimental (clinical trial)Observational
Retrospective
Case controlCase series
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Hierarchy of designs
1. Meta-analysis of clinical trials2. Clinical trial3. Prospective follow-up (observational)4. Retrospective follow-up5. Case control6. Case series
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Study design
Past Present FutureRetrospective Cohort Prospective Cohort
Case-Control (retrospective)
Cross-sectional
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Clinical trials– Randomisation
• Aim is to create groups with similar prognosis
– Control group: comparison with placebo or active treatment
• Aim is to evaluate the pharmacological effect of the new compound (exclusion of placebo effect, natural course, measurement error)
– Blinded (single, double, triple)• Aim is to prevent subjectivity (in patients, researcher,
statistician) in the scoring of the prognostic factors and outcome and to prevent differential changes in behaviour (changes that might change prognosis) of the groups to be compared.
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Source population
Randomisation
Index group Control group
Follow-up Follow-up
Outcome Outcome
In- and exclusion criteria
Method, blinding
Prognostically comparable
TreatmentDouble blind
Loss-to-follow-up
Blinded measurement of outcome
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Pharmacoepidemiological designs•Descriptive methods (Signal detection, hypothesis generating).
Identifying previously unrecognised safety issues – Case reports, – Case series, – Cross-sectional study
•Analytical methods (quantifying + risk factors, hypothesis testing). Investigating possible hazards (hypothesis-testing in order to substantiate a causal association)
– Observational • Cohort studies, • Case-control studies, • Case-crossover studies
– Intervention • Experimental Clinical trial
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Evaluation of therapy: golden standardRandomised Controlled Clinical Trial (RCT)
Randomise: why?
Controlgroup: why?
Blinding: why?
Goal:Only difference between treated and untreated group is the treatment
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Experiments are often impossible
Ethical (e.g. smoking, birth defects)
Practical (e.g. rare adverse effects)
Non-experimental (observational) research
For example:
Do animals bite more often during full moon?
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Do animals bite more during a full moon?
Bhattacharjee C et al. BMJ 2000;321:1559-61
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Observational studies
Past Present FutureRetrospective Cohort Prospective Cohort
Case-Control (retrospective)
Cross-sectional
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Case Report / Case series
Describes characteristic association in one / somepatient(s) between determinant en outcome
examples:
• serious liverdamage following use of XTC
• birth defects after use of Thalidomide (Softenon)
• etcetera, etcetera, etcetera
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The Lancet, 1961
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LETTER TO THE EDITOR
THALIDOMIDE AND CONGENITAL ABNORMALITIES
Sir, Congenital disorders are present in
approximately 1.5% of babies. In recent months
I have observed that the incidence of multiple
severe abnormalities in babies delivered of
women who were given the drug thalidomide
('Distaval') during pregnancy,as an anti-emetic
or as a sedative, to be almost 20%.
Have any of your readers seen similar
abnormalities in babies delivered of women
who have taken this drug during pregnancy?
McBride WG. The Lancet, December 16, 1961: page 1358
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Dwarsdoorsnede onderzoek
beschrijft een karakteristieke relatie tussen determinant en uitkomst op 1 moment in de tijd
Causaliteit?
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Voorbeeld dwardoorsnede onderzoek
Polymorphisms of the LEP- and LEPR gene and obesity in
patients using antipsychotic medication
Gregoor et al J Clin Psychopharmacol (2009)
Onderzoeksvraag: zijn polymorfismen in de LEPR
geassocieerd met hoger BMI in antipsychotica
gebruikers?
Studie opzet: dwarsdoorsnede onderzoek
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Voorbeeld: LEPR onderzoek
Populatie: 200 antipsychotica gebruikers
Determinanten: LEPR Q223R en LEP promoter 2548G/A SNP polymorfismen
Uitkomst: BMI
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N BMI>30
Males
QQ 30 6 (20%)
QR 73 16 (21%)
RR 31 8 (26%)
Females
QQ 17 12 (71%) **
QR 39 15 (39%)
QR 10 4 (40%)
** p<0.05
Voorbeeld: LEPR onderzoek
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Observational Cohort
Group of individuals with common inclusion criteria is followed over time until an endpoint occurs.
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Cohort study / Follow-up study
Study population
Exposed
Non-exposed
Disease +
Disease +
Disease -
Disease -
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Voorbeeld cohort onderzoek
• Zijn patiënten die van specialité naar generiek antihypertensivum switchen minder therapietrouw?
• Blootstelling: switch• Uitkomst: therapitrouw
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Switchers: 13,6% therapie-ontrouw
Niet switchers: 18,7% therapie-ontrouw
Van Wijk et al 2006
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A cohort studyRR (myocardial
infarction)*
Untreated normotensive and hypertensive men 1.0 (reference)Treated hypertensive men DBP90 mmHg 3.8 (1.3-11.0)Treated hypertensive men DBP>90 mmHg 1.1 (0.5-2.6)
* adjusted for previous MI, CVA, IHD, IC, diabetes, SBP, duration of antihypertensive therapy, hypercholesterolemia, hypertriglyceridaemia, creatinin, obesity, use of cardiac glycosides, smoking.
Conclusion: In men treated for hypertension, DBP should not be reduced to lower than 90 mmHg
Merlo J, et al. BMJ 1996;313:457-61.
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Another cohort study
RR (stroke)
Untreated “Candidates”* for treatment 1.0 (reference)
Treated Crude RR 0.49 (0.32-0.76)Adjusted RR* 0.61 (0.39-0.97)
** Adjusted for age, sex, diabetes, total cholesterol, BMI, smoking, history of CVD
* Candidates for treatment defined according to Dutch guidelines on treatment of hypertension taking into account multifactorial risk of cardiovascular disease
Klungel et al. Epidemiology 2001;12:339-344.
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Frequency measures cohort study
(P1 personyears)
(P0 personyears)
A1
A0
Exposure
No Exposure
Disease
Disease
No disease
Time
Time
No disease (B1)
(B0)
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Frequency measures
• Incidence– Cumulative incidence (CI)– Incidence rate (IR)
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Risk disease + | exposure + = A1 / N1 = CI1
Risk disease + | exposure - = A0 / N0 = CI0
Frequency measures cohort study
Disease No disease Total
Exposure + A1 B1 N1
- A0 B0 N0
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Force of morbidity | exposure + = A1 / P1 = IC1
Force of morbidity | exposure - = A0 / P0 = IC0
Frequency measures cohort study
Disease Personyears
Exposure + A1 P1
- A0 P0
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Risk difference RD CI1 – CI0 IC1 - IC0
Relative Risk RR CI1 / CI0 IC1 / IC0
Attributable Risk AR (CI1 - CI0) / CI1 (IC1-IC0) / IC1
Relative Risk Reduction RRR 1 – RR
Number needed to treat NNT 1 / RD
Effect measures cohort study
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Pill and Deep Venous Thrombosis
Risk no pill = 3.9 per 100 000 pyRisk pill gen. 2 = 10.3 per 100 000 pyRisk pill gen. 3 = 21.3 per 100 000 pyRR2/3 = 2.07
RV2/3 = 11.0 per 100 000 py
AR2/3 = 52%
‘NNH’2/3 = 9091 per yearLancet 1995; 346: 1582 - 1588
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Analysis cohort study
• Survival analysis– Kaplan Meier (CI)– Cox regression (I)
• Proportional hazards model:• ln (Inc) =h0(t) + b1xX1 + b2xX2 + … + b1xXi
• Interpretation: eb1=HRx1 (adjusted for X2 .. Xi)
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Kaplan Meier
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Prospective vs. retrospective Cohort Studies
• Prospective Cohort Studies– Time consuming, expensive– More valid information on exposure– Measurements on potential confounders
• Retrospective Cohort Studies– Quick, cheap– Appropriate to examine outcome with long latency periods– Admission to exposure data– Difficult to obtain information of exposure– Risk of confounding
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Selection of the Exposed Population
• Sample of the general population:– Geographically area, special age groups, birth cohorts
(Framingham Study)
• A group that is easy to identify:– Nurses health study
• Special population (often occupational epidemiology):– Rare and special exposure– Permits the evaluation of rare outcomes
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Selection of the Comparison Population• Internal Control Group
– Exposed and non-exposed in the same Study population (Framingham study, Nurses health study)
• Minimise the differences between exposed and non-exposed
• External Control Group– Chosen in another group, another cohort (Occupational
epidemiology: Asbestosis vs. cotton workers)
• The General Population
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Follow up study versus RCT
• Similarities– Use of same measures of frequency and association
(RR, RD, AR, RRR, NNT, NNH)– Use of same analytical techniques (“survival”
analysis: Kaplan Meier curves and Cox proportional hazard)
• Differences– Follow-up vs. RCT: no randomisation and no blinding
(outcome measurement sometimes blinded)
Follow-up studies more vulnerable to bias
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Cohort study / Follow-up study
Study population
Exposed
Non-exposed
Disease +
Disease +
Disease -
Disease -
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Case-control study
Study Population
Cases
Controls
Exposed
Non-exposed
Exposed
Non-exposed
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Example case-control study
• What is the risk on breast cancer with the use of SSRI antidepressants?
• Cases: women with breastcancer• Controles: women with no breastcancer• Exposure: SSRIs
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Coogan et al. Am J Epidemiol 2005
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Meaning of odds and odds ratio ?
• Term from English gambling “4 to 1”
• Odds means chance of succes (Ps) / chance of no success (Pns)
• Pns = 1-Ps
• Odds = Ps / 1-Ps
• Ps = 1/5 =0,2 => odds = 0,2 / 0,8 = 0.25 (4 to 1)
• In epidemiology ‘Exposure odds’ of interest
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Case Control
Exposure + a b
- c d
a+c b+d
Exposure odds among cases = a/c
Exposure odds among controls = b/d
Exposure Odds ratio (OR) = (a/c) / (b/d)
= (a*d) / (b*c) RR
Calculation OR
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Rofecoxib and risk of MI
Nested Case Control design:• 9218 MI cases of whom 93 used of rofecoxib < 3 months ago• 86349 controls, of whom 634 used of rofecoxib < 3 months ago
MI control
Rofecoxib + 93 634
- 9125 85715
OR (MI)= 93x85715 / 634x9125 = 1.38BMJ 2005;330:1366
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Selection of cases
• Establish strict diagnostic criteria for the outcome: Examples:– Type 1 diabetes in children: severe
symptoms, very high BG, marked glycosuria, and ketonuria.
– Type 2 diabetes: few if any symptoms, Slightly elevated BG, diagnosis “complicated”.
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Selection of cases
• Population-based cases: include all subjects or a random sample of all subjects with the disease at a single point or during a given period of time in the defined population:– Disease registers
• Hospital-based cases:All patients in a hospital department at a given time
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Selection of Controls
Principles of Control Selection:• Study base:
– Controls can be used to characterise the distribution of exposure
• Comparable-accuracy– Equal reliability in the information obtained from cases and
controls no systematic misclassification
• Overcome confounding– Elimination of confounding through control selection
matching or stratified sampling
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Selection of Controls
• General population controls:– registries, households, telephone sampling– costly and time consuming– recall bias– eventually high non-response rate
• Hospitalised controls:– Patients at the same hospital as the cases– Easy to identify– Less recall bias– Higher response rate
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Ascertainment of outcome and exposure status
• External sources:– Death certificates, disease registries,
Hospital and physicians records etc.
• Internal sources: – Questionnaires and interviews, information
from a surrogate (spouses or mother of children), biological sampling( e.g. antibody)
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Data CollectionExternal Data
SourcesInternal Data
Sources
Exposure Hospital records, employers
Questionnaires, physical examinations, and/or blood tests, other diagnostic tests
Event Disease registries, death certificates, physician and hospital records
Questionnaires, physical examinations, and/or blood tests, other diagnostic tests
Confounder Hospital records registries
Questionnaires, physical examinations
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Strengths in Cohort vs. Case-control?
Cohort study• Rare exposure• Examine multiple effects
of a single exposure• Minimizes bias in the in
exposure determination• Direct measurements of
incidence of the disease
Case-control study• Quick, inexpensive• Well-suited to the evaluation
of diseases with long latency period
• Rare diseases• Examine multiple etiologic
factors for a single disease
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Limitations in Cohort vs. Case-control?
Cohort study• Not rare diseases• Prospective: Expensive
and time consuming• Retrospective: in
adequate records• Validity can be affected
by losses to follow-up
Case-control study• Not rare exposure• Incidence rates cannot be
estimated unless the study is population based
• Selection Bias and recall bias
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Validiteit +
Precisie -
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Validiteit -
Precisie +
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Validiteit +
Precisie +
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Validiteit -
Precisie -
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faculteit Farmaceutische Wetenschappen
Precisie en validiteit (vertekende resultaten)
• Toevallige fouten: ‘random error’ (precisie)
steekproef
• Systematische fouten: ‘systematic error’ (validiteit)
bias en confounding
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Power and precision
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Sample size in case-control study of OC use and MI among women
Assuming proportion of current OC use of 10%;
•Power: 1- (type II error) = 80%
•Precision: (type I error) = 5%
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Sample size requirement in RCT
baseline risk number required side effect in each groupin control group
50% 1425% 7710% 2665% 5821% (liver dysfunction) 3,1040.1% (hepatitis) 31,4830.01% (cholestatic jaundice) 315,268
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The likelihood of observing an adverse drug reaction in 2,000 patients
Threshold for ADRProbability
1 / 500 0.98
(Lymphoma From Azathioprine)
1 / 1,00 0.86(Eye Damage From Practolol)
1 / 10,000 0.18(Anaphylaxis From Penicillin)
1 / 50,000 0.04 (Aplastic Anemia From Chloramphenicol)
Lembit Rägo, WHO Upsala
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Validiteit van onderzoek
• Komen de bevindingen uit het onderzoek overeen met de werkelijkheid?
• Externe en interne validiteit
Externe validiteit: representativiteit en non-response Interne validiteit: selectie bias, informatiebias en
confounding bias
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Soorten van selectie- en informatiebias
• Channeling bias• Referal bias• Diagnostic bias
• Observer bias• Recall bias• Response bias
selectie informatie
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Information bias (follow-up)
• Question: do patients who are treated for Hodgkin’s disease have a higher chance of a second tumor ?
– Compared incidence of cancer in a group of treated Hodgkin patiënts with incidence of cancer in general population (matching on age and gender)
Information bias (if RR = 1 probably no bias; if RR>1 cave bias)
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Selection bias (cohort)• Observational cohort study
RR (myocardial infarction)*
Untreated normotensive and hypertensive men 1.0 (reference)Treated hypertensive men DBP90 mmHg 3.8 (1.3-11.0)Treated hypertensive men DBP>90 mmHg 1.1 (0.5-2.6)
* adjusted for previous MI, CVA, IHD, IC, diabetes, SBP, duration of antihypertensive therapy, hypercholesterolemia, hypertriglyceridaemia, creatinin, obesity, use of cardiac glycosides, smoking.
Conclusion: In men treated for hypertension, DBP should not be reduced to lower than 90 mmHg
Merlo J, et al. BMJ 1996;313:457-61.
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Selection bias (cohort)
• Observational cohort study in the NetherlandsRR (stroke)
Untreated “Candidates”* for treatment 1.0 (reference)
Treated Crude RR 0.49 (0.32-0.76)Adjusted RR* 0.61 (0.39-0.97)
** Adjusted for age, sex, diabetes, total cholesterol, BMI, smoking, history of CVD
* Candidates for treatment defined according to Dutch guidelines on treatment of hypertension taking into account multifactorial risk of cardiovascular disease
Klungel et al. Epidemiology 2001;12:339-344.
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Case control
Time
Time
Exposure
No exposure
Exposure
No exposure
Case
(disease)
Control
(no disease)
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Selection of controls
Smoking and leukemia cases: patients with leukemia controls: patients in hospital for other disease
Patients hospitalized for CVD as control ?
Patients with history of CVD, not hospitalized for CVD
Smoking => CVD
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Information bias (case-control)
Drugs and congenital malformation
Cases : children with congenital malformation
Controls: children without malformation
Exposure: use of drugs
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Selection bias (case-control) I
Oral contraceptives and DVT
It was published (prospective follow up) in the 60’s after introduction of OAC that OAC increase the risk for DVT 3 times
New study planned: case control design Cases? Controls?
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Selection bias (case-control) II
Women with pain in leg Physician asks about use of the pil If use of pil, refer to hospital, otherwise not.
RR DVT OC use
Solution ?
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Methoden om voor vertekende resulaten te corrigeren
• Restrictie / StratificatieMantel Haenszel
• Matchen1:1 of proportioneel
• Mathematische modellenverschillende regressietechnieken (bij patiënt controle logische regressie; bij follow-up Cox of Poisson regressie)
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Risk assessment
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Registration of a drug is only the beginning of safety research
email: [email protected]: @robheerdinkwww.slideshare.net/robheerdink