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Practical use of Pharmacoepidemiology in clinical drug development

Presenter: Dr David Neasham

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Contents• Background, contributing areas & reasons to perform

pharmacoepidemiology studies• Study design• Database studies• Two practical examples:

– YASMIN (ethinylestradiol with drospirenone)– CRESTOR (rosuvastatin)

• Summary • Discussion / Q & A

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Background

• Pharmacoepidemiology– Application of epidemiological techniques

to the content area of clinical pharmacology

• Population level• Study of adverse drug effects• Many areas of contribution

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Contributions

• Better quantification of incidence of known adverse and beneficial effects – Higher precision– In patients excluded in pre-marketing

studies – e.g., children, elderly, pregnant women

– Interaction by other drugs or illnesses– Relative to other drugs used for same

indication

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Reasons• Regulatory

– e.g., obtain earlier approval for marketing

• Clinical– e.g., hypothesis testing or generating

• Marketing– e.g., assist in repositioning of drug

• Legal– e.g. In anticipation of product liability litigation

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Study design

www.diahome.org© Imperial College LondonSlide 7

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Study design

• Case-cohort design– Selecting all cases in cohort – i.e. all

subjects with adverse event– Randomly selecting a sample of pre-

determined size of subjects from the cohort– Reduced version of cohort, with all cases

added

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Study design

• Large Simple trial (LST)– Large randomized trials made simple by

reducing data collection to minimum needed to test specific hypotheses

– Randomization of treatment assignment– Controls of confounding by known or

unknown risk factors– Sufficient statistical power small risks of

common events + large risks of rare events

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Study design• Efficiency of LSTs could be enhanced using

health delivery systems databases• Relevant outcomes (e.g., hospitalizations for

gastrointestinal bleeding) could be captured electronically which would eliminate need to contact patients for follow-up

• Still necessary to identify eligible subjects, obtain consent and randomize treatment

• Could be a very effective hybrid method

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A typical scenario: identifying risks

INCIDENCE OF COMMONLY

OCCURRING EVENT FROM CLINICAL

TRIALS

BackgroundEpidemiology

Risk management strategy Risk management strategy

INCIDENCE OF EVENTIN GENERAL POPULATION

IDENTIFICATION OFRISK FACTORS

POTENTIAL SIGNALS OF RARE EVENTS

SpontaneousReports

ObservationalStudies

Other Activities

1/1,000

1/500

1/100

1/10,000

1/5,000

1/1,000

1/100,000

1/50,000

1/10,000

HYPOTHESIS TESTING1/1,000,000

1/500,000

1/100,000,

Clinical trial Data

Insufficiently powered

Evidence base

Self-report bias

Best study design….

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Safety challenges in pre-approval phase • Challenges of safety signal identification

during pre-approval phase:– pre-approval studies cannot usually be

statistically powered to identify readily low frequency safety events of concern

– samples often narrowly defined – therefore may not be truly representative of final treatment population

– short time frames: mid to long-term effects cannot be thoroughly evaluated

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Post-marketing pharmacovigilance

• Limitations of post-marketing spontaneous reporting systems:– patterns of spontaneous reporting vary by country,

increase during early post-launch period and are affected by publicity → spontaneous reporting rates biased

– limited population level denominator information– for common events (e.g., MI) difficult to separate

actual signals from background noise

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Approval

ClinicalClinical

Product life-cycleProduct life-cycle FIM Ph I Ph II Ph III Ph IV

Toxicology (e.g. genotoxicity assays)

In silico analysis/ structural alerts

Margin of safety & no observed adverse effect level defined

Ph I & II: dose ranging, efficacy & toxicity

Phase III: demonstration of efficacy and safety signal monitoring

Ph IV: spontaneous reporting systems

Exposure in humans

(Potential Denom

inator)Exposure in hum

ans(Potential D

enominator)

Product life-cycle and safety studies

PreclinicalPreclinical Postmarketing pharmacovigilance

Postmarketing pharmacovigilance

Sufficiently powered

Easy study replication

Large database studies

No self-reporting bias

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Example 1

• The YASMIN (ethinylestradiol with drospirenone) study

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Case Study - Yasmin and the Safety of DRSP

• Background– Yasmin is an OC that contains drospirenone (DRSP)

– DRSP has antimineralocorticoid activity and can raise serum potassium

• Phase IV commitment– To obtain safety data related to:

• Complications related to hyperkalemia (elevated serum potassium)

• Physician prescribing and patient monitoring

• Breakthrough pregnancy and birth outcomes

– In 25,000 users of Yasmin and 50,000 users of other OCs

• Wider business implications– Sponsor planned to introduce DRSP into menopausal therapy

– Needed strong basis for later safety claims

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INGENIX Research Database

Women (10-59 yrs)n = 959,482

Propensity score matching of 12 initiator cohorts

(n = 22,429)

New dispensing of Yasmin (n = 31,149)

New dispensing of other OCs (n = 360,505)

≥6 months continuous enrollment (n = 22,887)

≥6 months continuous enrollment (n = 227,596)

Propensity score matching of 12 initiator cohorts

(n = 44,858)1:2 Ratio

Cohort Formation

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• Create matched cohorts of Yasmin and other OC users• Collect comorbidities, demographics, healthcare utilization, exposure to oral contraceptives

• Identify women with hepatic, renal or adrenal insufficiency

• Identify potassium-sparing meds

New OC or New type of OC

OCRx

6 Months Before Dispensing

Prospective Data Collection

• Identify clinical outcomes based on claims data (prescription, diagnoses, procedures and service)

• Hospitalizations for new conditions, clinical events potentially related to hyperkalemia, electrolyte abnormality,inappropriate prescribing, potassium monitoring, pregnancy/fetal malformations

Data Collection

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Yasmin Launch

Q3

Time

Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

2001 2002 2003 2004

Yasmin

ControlP

Follow-Up

Follow-Up

Yasmin

ControlP

Follow-Up

Follow-Up

Yasmin

ControlP

Follow-Up

Follow-Up

Yasmin

ControlP

Follow-Up

Follow-Up

Yasmin

ControlP

Follow-Up

Follow-Up

Yasmin

ControlP

Follow-Up

Follow-Up

Yasmin

ControlP

Follow-Up

Follow-Up

Yasmin

ControlP

Follow-Up

Follow-Up

Yasmin

ControlP

Follow-Up

Follow-Up

Yasmin

ControlP

Follow-Up

Follow-Up

Yasmin

ControlP

Follow

Follow

Yasmin

ControlP

2005

Q1 Q2 Q3 Q4

Claims-Based Outcomes

Chart-Based Outcomes

Apr. Report

Oct. Report

Apr. Report

Oct. Report

Apr. Report

Oct. Report

Apr. Report

Final Report

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Claims Based Abstraction

Medical Chart Abstraction

Screen Claims Data

Medical

Review

Blinded Chart Reviews to Confirm Outcomes

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Some outcomes may be continuations of pre-existing conditions* No rate ratio calculated as no case in Yasmin Cohort** Composite hyperkalemia outcome comprised of chart-confirmed cases of arrhythmia, syncope, electrolyte disturbance, hyperkalemia, and myocardial infarction.

Syncope

Arrhythmia

Hyperkalemia

Other Electrolyte Disturbance

Dialysis*

Myocardial Infarction*

Hospitalization with Hyper/Hypokalemia*

Death

Composite Hyperkalemia**

0

0

0

0

Incidence Rate Ratio –Yasmin versus Other OC (95% CI)

5.01.0 2.0 4.03.00.50.25 0.330.2

0.1

Rate Ratios

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• Does Yasmin lead to more VTE than other OCs?

– NO. We added a new outcome which we could evaluate both retrospectively and prospectively for the full cohort.

• Why do physicians prescribe to women with apparent contraindications of renal, hepatic, or adrenal disease?

– MAY IGNORE NOMINAL CONTRAINDICATION FOR MILD DISEASE. We directly interviewed physicians with apparently contraindicated prescribing patterns.

• Why do physicians not perform potassium monitoring as recommended in the label?

– DISAGREE WITH LABEL. We surveyed physicians with patients who by label should have been monitored, but were not.

Flexible Data Collection Facilitates Risk Management

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Example 2

• The CRESTOR (rosuvastatin) studies

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Brief background

Rosuvastatin

• Hepato-selective and relatively hydrophilic hydroxy-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitor (statin)

• Approved by FDA on 12 August, 2003

• Management of dyslipidemia

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Potential safety issues

• Added concerns from withdrawal of cerivastatin in 2001 due to excess cases of fatal rhabdomyolysis

• Comorbidities and concomitant medications may increase risk of myotoxicity, depending on properties of given statin

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Evolution of Lipid Management ATP Guidelines*

ATP I (1988) ATP II (1993) ATP III (2001)

Diet; low-dose,non-statin monotherapy

High-dose statin, combination therapy

Low- to moderate-dose statin monotherapy

Increasing aggressiveness of cholesterol-lowering therapy

* The National Cholesterol Education Program Adult Treatment Panel (ATP)

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The CRESTOR study program

An international collaborative pharmacoepidemiology safety program involving many groups…• AstraZeneca R&D• Centro Español de Investigación

Farmacoepidemiológica (CEIFE), Spain• PHARMO Institute, Netherlands• i3 Drug Safety, US• Drug Safety Research Unit (DSRU), UK

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Pharmacoepidemiology program design

• Program consisted of nine studies grouped into three components:– Patient characteristics studies (x 4

databases)– Safety evaluation studies (x 4 databases)– Prescription-event monitoring study (DSRU)

• All studies performed according to GPP guidelines and reviewed and approved by ethics committees

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Pharmacoepidemiology program overview

Table: Study parameters

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Numbers and incidence rates of study outcomes

Results from McAfee et al. (2006) (Ingenix)

Safety evaluation studies

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Pooled person-time and outcomes

Outcome Person-years N Person-years N

Myopathy 260,844 9 196,911 9

Rhabdomyolysis 260,889 9 196,929 7

Renal dysfunction 260,772 95 196,870 57

Hepatic dysfunction 260,852 22 196,914 14

Intent-to-treat Current use

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Summary

• Contributing areas and reasons to perform pharmacoepidemiology studies

• Study design• Database studies • Two practical examples:

– YASMIN (ethinylestradiol with drospirenone)– CRESTOR (rosuvastatin)

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Dr David NeashamDavid.Neasham@i3drugsafety.com+44 (0)1628 408442

Questions & answers

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Practical use of Pharmacoepidemiology in clinical drug development