Patients The Key to Real World Data?

Alan G. Wade

Real World Data Sources

29%

41%

18%

6%6%

Sources of Data

Clinical TrialsPatient DataRegistriesPrescribing DataBig Data

Reflects the average patient in a real-world setting• Demographics

– Sex– Age– Social status– Education

• Diagnosis• Co-morbidities• Co-medications• Medical system• Social impact• Work impact• Family impact• Impact on Quality of Life

What is real world data?

Pre market entry disease, burden, unmet need, treatment pathway mapping

Licensing when impact only known by patient or difficult to assess

Labelling extension Validated PRO’s

Market Access HTA; effectiveness

Post license safety, benefit:risk(registry),risk/management plan

Guideline development ???

Uses for “real world” data?

Source

Randomised Controlled TrialsPMS Studies

Physician driven

Patient registriesPrescribing data

Database – physician recorded

Focus groupsPatient organisations

Patients

Traditional data sources

Hierarchies of evidence

1. Systematic reviews of randomised controlled trials (RCTs).

2. RCTs.3. Controlled observational studies - cohort

and case control studies.4. Uncontrolled observational studies - case

reports.5. Expert opinion

?KoL

Randomised Controlled Trials

• “the gold standard” for demonstrating (or refuting) the benefits of a particular intervention.

• Important limitations

Limitations of RCT’s

Patients– Age - Effectiveness in younger or older patients– Sex– Severity - effectiveness in mild or severe– Risk factors - effectiveness in patients with risk factors for the condition (eg, smokers)– Co morbidities - Influence of other conditions– Ethnicity - effectiveness in other ethnic groups– Socioeconomic status - effectiveness in disadvantaged patients

Treatment– Dose - high dose used in RCTs?– Timing of administration Influence on adherence (compliance) to treatment regimens– Duration of therapy - effectiveness during long-term use– Co medication - adverse interactions– Comparative effectiveness - in comparison with other products used for the same indication

Setting– Quality of care – Prescription and monitoring by less specialist (expert) healthcare providers– Care pathway

Effectiveness and efficiency

Does it work in Does it work in Does it contribute to aclinical trials? real life? more efficient use of

resources? COST-EFFECTIVENESS

Efficacy Effectiveness Efficiency

To assess performance of drug in real world setting– Large numbers– Off-label prescribing– Comorbidities– Concomitant medications– Speed of reporting

Do we achieve this with formal PMS?

Post Marketing Surveillance

Hierarchies of evidence

1. Systematic reviews of randomised controlled trials (RCTs).

2. RCTs.3. Controlled observational studies - cohort

and case control studies.4. Uncontrolled observational studies - case

reports.5. Expert opinion

?KoL

6. Patient reports ?

• Small numbers• Representative?• Skill of co-ordinator/observers

Focus groups

Who in the world most influences the pharmaceutical industry?

1. Barack Obama

2. Michael Rawlins

Harveian Oration

Hierarchies of evidence should be replaced by accepting—

indeed embracing—a diversity of approaches.

The Lancet Vol 372 December 20/27, 2008

NICE

Patient and public involvement

The views of patients, carers and the public matter to NICE. We want to involve them, as well as doctors, nurses, other healthcare professionals and managers in our work.

http://www.nice.org.uk – accessed 22 06 09

EMA

The assessment of the benefit-risk balance should be based on the available tests and trials, which are designed to determine the efficacy and safety of the product under normal conditions of use (Directive 2001/83), and which are generally performed under ideal conditions.It is important to be explicit about the perspectives of different stakeholders that are taken into account in the assessment of the benefit-risk balance, in particular the perspectives of patients and treating physicians.Considerations about how the treatment is expected to perform under real conditions of use are relevant in the context of pharmacovigilance activities, for example, to take into account any available information on misuse and abuse of medicinal products which may have an impact on the evaluationof their benefits and risks (Directive 2001/83).

Patient groups - the patient?

EPF is the umbrella organisation of pan-European patient organisations active in the field of European public

health and health advocacy.

The European Patients’ Forum (EPF) currently represents 57 patient

organisations and an estimated 150 million patients across the 27 Member

States throughout Europe.

EU drugs agency working with patient groups bankrolled by big pharma

23.04.10 @ 19:17

Patient organisations

But equally, we have a right and responsibility to look at the interests of other patients who use the healthcare system. What I am critical of, however, is patient organisations that are acting on behalf of pharma companies. I am not alone in complaining about them.

The Lancet Vol 372 December 20/27, 2008

Harveian Oration

“Big Data”

No single agreed definition

but

The bottom line: whatever the disagreements over the definition, everybody agrees on one thing: big data is a big deal, and will lead to huge new opportunities in the coming years.

Big Data - definition

http://timoelliott.com/blog/2013/07/7-definitions-of-big-data-you-should-know-about.html Accessed 27 01 14

Big Data – Pharma???

22

RegistriesClaims Databases (US)

e - Medical Records

Also

Pharmacy databasesSpecific hospital databasesSpecific disease or procedure databases

What do you want from a registry?

• Large numbers• Patient level data• Immediacy of data• Longitudinal data• Representative population

• Presence of YOUR required data• Linkage of data fields of interest• Confirmation of diagnosis• Standardised measurement• Validated PRO’s

Existing registries

Strengths• Large numbers• Immediate access• Longitudinal data

• Prescribing data

Weaknesses• Inherent biases• Representative population• Diagnostic drift • Patient level data• Surrogate outcomes• Completeness of data• Family social and work history

To effectively use any registry it is important to understand how it has been developed and its strengths and weaknesses

• Some treatment effects only known to patient• Pts provide unique perspective on treatment• Provide information on QoL, work, social and

family

• Formal assessment may be more reliable than informal interview

Patient Reported Outcomes Why & How?

25

What the Patient Knows

What the Patient Shares

What the physician understands

What the Physician records

Big Data

Addressing registry weaknesses

Ask the patient – but how?

Real World Data Sources

29%

41%

18%

6%6%

Sources of Data

Clinical TrialsPatient DataRegistriesPrescribing DataBig Data

Conclusion

Collect data directly from patients

Patient Reported Outcomes

PRO’s

• “any aspect of patients health status that comes directly from patient” - FDA

• “insight into way patients perceive their health & impact treatments or adjustments to lifestyle have on their quality of life” –DH

Patient Reported Outcomes - Definition

29

FDA Guideline report Dec 09

• Pt recording versus doctor• Pt understanding of question/form• Validity of question (in that format, pt popn)• Reliability of question• Ability of question to detect change• For licensing – need set as per RCT

Patient Reported Outcomes – concerns

31

Definition of “Real Data from Real Patients”

• Collecting data from patients receiving “routine care”

BUT• Not affecting their prescribers/ healthcare

professionals behaviour

Methodology

33

PROBE Patient Reported Outcome Based

Evaluation

Process set-up

• Define question - protocol• Define patient group of interest• Determine location of group e.g. Specialist unit,

community setting, geography• Review options for accessing patient group

– Orphan indications

• Design questionnaires and reports– development and testing

• Structure customised database

• Bespoke – ask required questions• Innovative• Prospective• Hosted on Patients Direct site• Interactive• Global Coverage

Structured patient registries

35

• Is on-line collection satisfactory?• Will patients cooperate• How do you recruit?

– Methodology– Achieving a representative population

Problems

www.InternetWorldStats.com 2009

• Age?• Education?• Social class?• Carer reporting?

– Alz Dis– children

On-line reporting

Age and Social Media

Conclusion

Generally require alternative data collection routes

Nurse manned telephone

• Outlet for their feelings and views – might be a threat to their relationship if they report problems to their healthcare professional – we’re neutral

• Altruistic - Assist in developing new and better treatments

• Obtain better information and knowledge through participation• Feel valued through regular contact/ interaction• Desire to make sure the patients voice is heard

Why do people participate?

42

...the benefits and attraction to each individual will differ but we believe the main reasons are :

7. REPORT CONCLUSIONS.

The above report has shown the public’s enthusiasm towards a system that would let

consumers report adverse drug reactions through the Internet. The findings of the

survey carried out by us revealed to us this enthusiasm. The report has further shown

that health professionals have a positive opinion towards such a system, which

works

in favour of the overall mission of Patients Direct. Not only has the report articulated

the publicity campaign that Patients Direct can carry out to raise its awareness, but

also examples of different medicine inserts has been provided with reasoning behind

them that could be used by the company to make itself different from its competition.

Patients Directs corporate identity is important to begin the process of publicity. IT

has been noted that establishing a user friendly website that is easily navigable is

fundamental to setting the pace for a strong brand and image that will appeal to

Patient’s Direct customers.

Will patients cooperate?

43EDGE Survey - Market Research, 2008

• social networking sites• search engine and website optimisation • public affairs articles and traditional methods of publicity e.g.

Newsprint/TV• Healthcare professionals –Doctors, pharmacists• wholesalers, distributors• Clinical trial participants• patient groups Special focus can be given to groups of interest such as children if

appropriate and recruitment monitored to ensure sufficient numbers in each cohort.

Recruitment

...tailored to attract patients of interest with a conscious effort to reduce bias and population selection issues

Core recruitment methods include :

Recruitment Examples

• General – statins– Pharmacy/wholesale distributor– Advertising - Google

• Vaccines– Direct at vaccination

• Families and children– Appropriate web-sites

• Specialist product – home delivery– Invitation with delivery

• OTC – Strepsils– General advertising– Pharmacy– Package wrap

Inflammatory Back Pain

3rd February 2014

48

Recruitment

• Recruitment Method - Facebook only

• First Participant Recruited – 22nd Dec 2013

49

Facebook Advert Example

50

Facebook Advert Example

51

Landing Page

52

Respondents

Started Completed Incomplete Meets IBP Criteria

0

50

100

150

200

250

300 262

151

10879

53

Age Profile

Under 30

31 to 40 41 to 50 51 to 60 61 to 70 Over 700

1020304050607080

5257

77

36

15

2

54

Sex Ratio

Total Male Female0

50

100

150

200188

40

148

55

Meets IBP Criteria

Total Calin ASAS Calin and ASAS

01020304050607080

79

53

3731

56

Age Profile of Respondents with IBP

Under 30

31 to 40 41 to 50 51 to 60 61 to 70 Over 700

5

10

15

20

25

30

35

16

24

32

13

41

57

Non Completers

Total EQ5D0

20

40

60

80

100

120108

52

Influenza Family Study

Family Influenza Survey

Households completed study 946

Individuals in completer households 3695

Flu-like Illness episodes in households

540

Total “Flu-like” Illness 851

Considerations

• Data Protection/ Confidentiality• Ethics

– NRES response

• Industry Code of Practice• Safety Reporting systems – MHRA

– Automated A/E reporting– A/E cascade

• Medical considerations/standards– No interference with prescribing/treatment

Process - management

• Patient response handling and back up• Review of data as study progresses• Design of reports

– A/E reporting in agreement with sponsors

• Statistical interpretation and reporting• Publications• If appropriate, patient education or further action

e.g. Adherence schemes

Managing data – a dynamic processReal data from Real patients

61

Patient

www......./ tel

Database

“continuous” Output

Analysis and report

Retrospective Prospectivepatient

Presence of YOUR required data + +++

Representative population + ++

Large numbers +++ ++

Linkage of data fields of interest ? +++

Confirmation of diagnosis ++ ++

Standardised measurement + +++

Validated PRO’s + ++

Patient level data + +++

Unfiltered patient data - +++

Response to unexpected findings + +++

Immediacy of data +++ ++

Longitudinal data - Retro/pro ..... spective +++ +++

Sensitivity + ++

Registries

• Medical interventions are now being assessed on the basis of “real world” data

• Current collection methods are inadequate• Novel systems for collection are required• Patients are increasingly being involved in

medical decision making• Collecting “real world” data directly from patients

may be one possible method

Summary

www.patients direct.org

Patients Direct

3 Todd Campus

G20 0 XA

United Kingdom

Output Examples

Practicality

Cover all 4 areas of use

65

Mapping Treatment Pathways

Burden of Illness

Drug Safety/ PV

Real world “effectiveness”benefit QOL

Patient Satisfaction/experience/Adherence

CVA evaluation

Sleep evaluation

Wellbeing Study (depression)

Problem Periods survey

Problem Periods survey

Impact of opioid use

CVA evaluation

Family Flu survey

Statin survey

Swine vs seasonal flu vaccination

Seasonal flu vaccination 2008

EQ 5D mapping 3 level to 5 level

Etanercept survey

Satisfaction with analgesia in OA

Pulse Rate survey

Etanercept survey

Satisfaction with analgesia in OA

Project examples

66

PV - Flu Vaccination

• 102 leaflets distributed• 73 PIN numbers have been entered on the database (72%)• 40 male and 33 female aged between 21 and 99 years. • They were asked about pain and discomfort from the vaccination

67

Flu Vaccination - Day 2• 70 responses were entered for Day 2• 14 having side-effects.

02468

1012

NothingTreated it yourself

012345678

rednessdiarrhoealoss of appetiteother

68

In response to “What did you doabout these side effects?”

Reported Side Effects

HiVE - H1N1 Vaccination Evaluation

H1N1 only seasonal only both +travel/pnemococcal0

100

200

300

400

500

600

700

800

Vaccination Received

Co

un

t

HiVE - Demographics

< 5 5-29 30-49 50-69 70 +0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Age of Participants

Male – 449Female - 663

HiVE - Adherence

Baseline Week 6 Week 12 Week 260

200

400

600

800

1000

12001112

716646

570

Number of Participants

HiVE – Side effects

Baseline week 6 week 12 week 260

5

10

15

20

25

30

35

40

45

50

Any Side Effects over time

Swine only

Seasonal only

Both

%

Injection site discomfort

36.4%

Flu-like symptoms

23.5%

Injection site pain

20.1%

χ2-test p <0.001

H1N1 only

HiVE - Absenteeism

Baseline Week 6 Week 12 Week 260

1

2

3

4

5

6

Time of Work due to flu like symptoms

H1N1 only

Seasonal Only

Both

% w

ith

tim

e o

ff

HiVE – Pain/Discomfort Reports

Category Odds ratio P valueSex Male

female 2.08 0.052

Chr illness NoYes 1.32 0.052

Swine flu vaccine NoYes 4.49 <0.001

Seasonal flu vaccine NoYes 0.89 0.481

Subject participates

“Buy-in”

Enrols “Buddy”

Feedback on outcome

Engaged for next year

“Viral Transmission”

Subject + Buddies + “Virals”

The Virtuous

Cycle

• Delivery at home• Compliance with drug still low• Understand agency effectiveness, reasons for

drop outs• Understand real life prescribing vs guidelines• Evaluate and then implement ways of improving

outcomes• Measures – AEs, compliance, QOL – disease

specific and generic EQ5D

Enbrel Project

76

Enbrel - Process

77

• Patient group recruited through leaflets with hospital clinic or HaH nurse visit to train on injection

• Initially 6 month follow up at 1 month intervals

• Recently extended to 2 year follow up at 3 month intervals

• Enrolled 344 patients • Out of ~1000 leaflets distributed• 284 patients by web site• 60 patients by telephone

• 93-100% completion of questions at baseline

• 140 patients have reached month 6

Enbrel – First 6 months

78

If you are experiencing problems with the website or any of the questions please contact the following number and we will endeavour te help you: 0800 731 2647

Age of Participants

< 10 10-19 20-39 40-59 60 + missing0

20

40

60

80

100

120

140

160

180

AllRA only

Nu

mb

er e

nro

lled

Baseline Use of Methotrexate

All RA AS PsArth0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

noyesnot sure

• Examples – MS, epilepsy, gout, infectious illness, depression

• Pre programmed questionnaire – timing ??• Baseline then every month/ 2 weeks -

recall?• Simple email – yes or no• Rely on people saying when they have

“event”

Intermittent events- data gathering

82

• Capture QoL changes when worst time of cycle

• Variation within and between women

• Compare to “normal” time

Intermittent Condition – Problem Periods

83

2699 respondents

Age – good range from < 20 to > 49 (61% < 30)

Absenteeism – 3+ days/mth 6%

1-2 days/mth 16%

Results – Screening survey

84

Significant impact on ALL Quality of Life Scales

Significant change between the different times of period cycle

Results – Main Outcomes

85

Main outcomes – EQ5D

86

Day 1 Day 2 Day 3 Day 4 Day 5 Day 60

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8EQ5D Score

Mean

SF 36 utility score

87

Day 6Day 1

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

Day

SF6

D_R

2

Boxplot of SF6D_R2

• Routinely gather PRO on• All Medication related to condition• Doctor visits (Primary & Secondary care)• Nurse visits• Pharmacy visits• Telephone calls (if relevant)• Hospital In/ Out Patient visits and number of

days

Resource utilisation

88

A real world study using Patient Reported Outcomes to assess the consequences associated with the forced switching of asthma

medication/device in stable adult asthma patients

• Data to be captured from Patients themselves:

• baseline patient reported level of Asthma control/satisfaction with device

• Reasons for switch (if known) (prospectively)• Outcomes of switch: Clinical (FEV1, Control)

Health resource use (GP visits, hospitalisations) lifestyle impact (days off work) (prospective)

• The questionnaires would be administered monthly (prospectively) so that any changes are captured 89

• Unmet need• Gathering information on children/ adolescents/

parents• Adherence, satisfaction, burden of illness

Cystic Fibrosis

90

• If you need real world PRO data in Europe/US• Databases don’t collect info you need

• Patients Direct can collect the data, directly from the patient

Quick, efficient, cost effective solution

Conclusion

91

• Burden Of Illness Study – Depression Management

• Understanding Patients ability to monitor their own condition – Heart Rate survey

• Disease treatment pathway mapping – CVA Study

• Mapping new EQ5D• Are QALYs appropriate across EU ?

Market Access

92

• Socio-demographics,• PMHx, • Resources use – Client Service Receipt Inventory

• QOL - EuroQoL• Productivity – WHO Health & Productivity Questionnaire

• Depression – HAM-D, MADRS

Burden Of Illness - 300 pts depression

93

• Utility weights UK population data • and EQ5D

• → QALYs

Burden Of Illness

94

• Depression severity - cost

• Depression severity - QALYs

Burden Of Illness

95

• Medical pathway of ischaemic stroke until 1 year acute episode

• Cost of stroke management• Cost drivers• Comparison between UK, France, Germany

Disease Pathway and Management

96

• Socio-demographic• Pre hospital management – PMHx, 1st contact,

transport• Hospital management – treatments,

investigations• Post hospital management - rehabilitation

Disease Pathway and Management

97

• New 5 level questionnaire (from 3 level)

• 500 pts UK

• Different levels disability

• CV disease, Respiratory, Neurological, RA

EQ 5D Mapping

98

• FP 7 grant• Pan European – UK arm (with A Walker)• University of Lyon

• Identification of different methods in HTA• Review of different methods• Alternatives to QALY

Use of QALY across EU

99

• Involved in questionnaire mapping• Gathered data via various QoL scales• Gathered data on inputs and outputs -

costs, diseases, outcome• Individuals involved in SMC and NICE

submissions and Advisory Boards• Access and use of UK experts –

Robertson Centre

HE and OR

100

• Bespoke Innovative solutions• Professional Quality Assurance /control• History of delivering results

– On time– Value for Money

• Tailored to sponsor brief• Multiple Applications

Summary

101

Source

Randomised Controlled TrialsPMS Studies

Physician driven

Patient registriesPrescribing data

Database/physician input

Focus groupsPatient organisations

Patients

Current data sources