Faculty of Health and Medical Sciences
Pharmacy student driven collection of adverse drug
events and off-label use in the community pharmacy
Ole. J. Bjerrum
Professor emeritus
Department of Drug Design and Pharmacology
and
Copenhagen Center for Regulatory Sciences
CORS, November 2016
Dias 1
Research problems for student in community pharmacies
• Pharmacovigilance is dependent on collection of AE’s
• Pharmacists are not very active in this regard
• The dispensing situation offer a unique opportunity for active
questioning about AE’s
Will such questioning this give rise to reliable data?
• Off-label prescription may pose a safety problem, even though the
physicians are specifically instructed to report ADR’s
• Measuring the magnitude of off-label use is difficult
Can analysis of the prescription data (label text) from local pharmacy
servers gives information on off-label use?
Both questions were addressed by pharmacy students having their
internship at community pharmacies
Dias 2
Community pharmacies and ADR reporting
The pharmacists
• have the qualifications and the right location for AE and ADR
reporting
• are aware of newly introduced drugs
• have no conflict of interest in the reporting
• are however, not educated to spot/diagnose AE’s
Empowerment of the pharmacist combined with a detection and
reporting of AE’s on-line will results in
- more qualified assessment,
- faster and better reporting
The study design for collection of ADR’s
Location:
Community pharmacies spread over Denmark
Questionnaire:
Simple scheme
Interviews
Pharma students trained and supervised by a post doc.
Reporting
On-line via computer to central database
Ethical issues
Not foreseen
Scheme for reporting suspected ADR’s of selected medicines
Date:
Sex:
Age:
Consent:
Reporter:
1. When was the first time that you experienced inconveniences in relation to intake of medicines? (patients
estimate)
2. Ask the patient to specify the experience of the inconvenience(s):
2.1 Objectively (e.g. direct tangible observations):
2.2 Subjectively (e.g. experiences, emotions, feelings):
3. Self adjustment of dose:
Have you in connection with the inconvenience(s) tried to lower your dose
medication
□
or stopped with the
□
In that case did the inconvenience(s) change: No □
Decreased
□
Gone
□
If you after decreased or stopped medication have started medication again, did the inconveniences return:
Yes
□
No
□
Drug:
Strength:
Indication:
Treatment started:
Dose:
Other medicine:
Training needs for pharmacists
Difficulties were observed re:
– interpretation of the patient input
– development of the right questioning technique regarding
how to substantiate/categorize the complaints
– qualification of patients vague description of complaints
E.g. “Digestion problems”
Appetite related, Nausea, Vomiting, Dyspepsia, Heart burn
“Toilet problems”
Constipation, Diarrhoea, Urination, Pain related
“Localisation of stomach pain
Epigastria, Abdomen, Lower abdomen, Stomach, Bowel,
Pilot study. Student collected data for Ibuprofen from nine
community pharmacies in provincial towns April-June 2009
•
•
•
•
•
Participants
89 F 39 M Total 128
Users reporting ADR’s
22 F 11 M Total 33
Mean age 55 years
Reported ADR’s
Total 45
Duration of Ibuprofen use:
< 1 month:
21%;
1<months <12: 11%
>12 months:
37%
• Approximately 5 minutes were spent per user when
questioning the experienced ADR
• Compliance 95 %
28/11/2016
Christensen et al., Pharmacoepidemiology Drug Safety 2011, 20, 39
7
Registered ADR symptoms related to ibuprofen users
Symptoms
This study
No. of reports
This study
(%), N=128
Emanuelli*
(%), N= 3000
___________________________________________________________________________________________________________________________________
Gastric pain
Heart burn
Nausea
Diarrhoea
Constipation
Asthenia
Vomiting
Vertigo
Somnolence
Face oedema
Muscle Spasm
Other
23
5
3
3
2
2
1
1
1
1
1
2
18
4
2
2
2
2
1
1
1
1
1
2
3
2
1
0.4
0.1
0.4
0.4
0.4
0.1
0.4
*Emanuelli and Vari: Advances in Inflammation Research 1984, vol 6, p.17
28/11/2016
8
Characteristics of student collected data on Liraglutide users
in 19 pharmacies in Denmark April – July 2010
•
•
•
•
•
Participants
21 F 44 M Total 62
Users reporting ADR’s
17 F 21M Total 38
Mean age 57 years
Reported ADR’s
Total 84
Duration of Liraglutide use:
< 4 weeks: 34%; 4< weeks < 8: 11%; > 8 weeks: 34%
• Concomitant anti-diabetic medicines were registered
• Approximately 5 minutes were spend per user questioning
experienced ADR
NB Liraglutide (Victosa) was marketed in DK January 2010
28/11/2016
Christensen and Bjerrum, J.Patient Safety 2013, 9, 219 -23
9
Major reported ADR symptoms by users of Liraglutide (1.2 – 1.8
mg/day) with concomitant anti-diabetic treatment (MET, GLI, SU)
Symptoms
•
This study
No. of reports
This study
(%), N=62
LEAD 1-3
(%), N= 5000
___________________________________________________________________________________________________________________________________
Nausea
Appetite
Diarrhoea
Fatigue
Abdominal pain
Constipation
Vomiting
Abdominal distension
Dizziness
Heart burn
Flushing
Other
28/11/2016
25
10
9
5
5
4
3
3
3
3
2
9
40
16
15
8
8
6
5
5
5
5
3
15
28-29
1-10
12-18
1-10
1-10
5-11
6-12
-
Marre, Diabet.Med. 2009; Nauch Diabetes Care 2009; Garber Lancet 2009
10
Pharmacist conducted ADR monitoring of new medicines
Flow of report forms
Pharmacist
at community
pharmacies
Electronic report
only in case the
observed ADR
need medical
attention
General
Practitioner
Electronic report form for all
customers questioned
Additional ADR report
after patient consultation
Medicines
Agency
This system does not demand for any changes in
current procedures of the general practitioner
Conclusion on Pharmacy prescription event monitoring.
•
•
•
•
Pharmacy students deliver feasible and useful data
Information on concomitant medication is on-line
On-line connection to GP’s and DMA database possible
Limited time consumption (5 min) makes it affordable
for Industry to finance such type of pharmacovigilance
“Pharmacy prescription event monitoring” opens up for
the possibility setting up a nationwide system for
systematic monitoring ofAE’s of new medicinal products
on the Danish Market
28/11/2016
L
E
2
12
Off-label prescriptions. Difficulties and challenges
• Off-label use of medicines poses a safety problem
• The prevalence of off-label prescribing is difficult to quantify ( is it 20%?)
• Reliable data are cumbersome to obtain: needs F2F questionnaire
• Label text for the patient represents an unexploited source
• Pharmacy servers contain the last two years prescription data
After a pilot study an exploratory study on off-label use was conducted for
melatonin, quetiapine and levothyroxine
Prescriptions by students in community pharmacies in the spring 2016
Off-label use. Definition.
• “This relates to situations where the medicinal
product is intentionally used for a medical purpose not
in accordance with the authorized product information”
EMA
• It may concern
• Indication area
• Dosing
• Route of administration
• Intended patient population
L:\4. sal\Ojb\Science\Combination
therapy\Adressing the GAP from
E2E
Aim of the off-label study.
By means of
- structured Query Language (SQL) to design a
programming code for CITO software to be used for
collection of prescription data from Danish pharmacy
servers.
- this method through an exploratory study to obtain,
information about off-label use for melatonin, quetiapine
and levothyroxine.
L:\4. sal\Ojb\Science\Combination
therapy\Adressing the GAP from
E2E
Indication/ATC code for melatonin quetiapine, levothyroxine
Drug
Authorized indication
ATC code
Melatonin
Short-term treatment of primary insomnia and poor N05CH01
sleep quality in patients with age over 55 year
Quetiapine
Treatment of schizophrenia
N05AH04
Treatment of bipolar disorder:
 For moderate to severe manic episodes in bipolar
disorder
 For major depressive episodes in bipolar disorder
 Recommended dosage 100-900 mg
Levothyroxine 



Myxedema regardless of etiology
Toxic goiter and Hashimoto goiter
Thyroid cancer
Substitution treatment of hypothyroidism
H03AA01
Data collection in community pharmacies
Programs used for collection of prescriptions data on own server:
CITO Data A/S, Apoteksdata I/S and NNIT-PharmaNet.
Seven pharmacies with CITO software participated from the regions
of Fyn (2) and Sjælland (5). Data was collected in May 2016 with the
help of pharmacy internship students.
CITO software
All data collected with the
permission from Datatilsynet.
Slide 17
SQL code
(requested from CITO IT A/S)
On-line collection of prescriptions
for the last two years
Workflow for data extraction by the students
Read the guidelines and instructions
Change the SQL code (date, ATC code,
prescriptions code)
Use the SQL code in CITO
Transport the data to excel
Delete the personal information (e.g.
CPR code, name/surname)
Slide 18
Example of data presentation in Excell of melatonin
prescriptions from Odense pharmacy
Patient's
age
(years)
Physian's
code
(encrypted)
Date (when
Product's code Trade name of the
prescriptions was
medicines
served)
ATC
code
Indication Prescription label
code
(indication and API)
2
00B89
17-01-2015 14:08
176616
Circadin
N05CH
01
5
005RG
08-12-2015 12:30
176616
Circadin
N05CH
01
5
00THY
18-10-2015 17:48
176616
Circadin
N05CH 166
01
5
00B89
10-03-2015 18:01
176616
Circadin
N05CH
01
DØGNRYTME
-----------------------------INDHOLD:MELATONIN
MOD SØVNBESVÆR
-----------------------------INDHOLD:MELATONIN
MOD SØVNLØSHED
-----------------------------INDHOLD:MELATONIN
DØGNRYTME
-----------------------------INDHOLD:MELATONIN
By computer assisted manual analysis only a few hours is
needed for off-labels analysis per pharmacy
Slide 19
Prescriptions of magistral melatonin and Circadin® in seven
community pharmacies around DK in a two-year period
Pharmacy
location
Total no. of
prescriptions
Prescriptions
for >55 years
old patients
Prescriptions
for <55 years
old patients
Off-label
percentage
Day of
collection
Christianshavn*
284
108
176
62%
02.06.2016
Hørsholm
677
330
347
51%
25.05.2016
Hundige/Ishøj
359
101
258
72%
20.05.2016
Nørrebro
475
124
351
74%
20.05.2016
Odense
457
137
320
70%
21.05.2016
Værløse
318
136
182
57%
21.06.2016
Vejen/Egtved
155
49
106
68%
17.05.2016
All
2725
985
1740
-
-
All [%]
100
100%
36
36%
-
-
64
64%
Daily dose of 173 quetiapine prescriptions dispensed in
Værløse pharmacy in a two-year period
Daily
dosage
No. of quetiapine Percentage of total quetiapine
prescriptions
prescriptions
12.5mg
3
2%
25mg
49
27%
50mg
53
30%
75mg
6
4%
100mg
25
15%
125 - 900mg
2
20%
78% off-label
Authorized indication is for dosages > 100 mg
Slide 21
Physicians consideration when filling out the label
space on the prescription
DMA’s instructions: “A prescription should include information on the indication, dosage
and any relevant usage mode.” “The instructions on the prescription must be easily
understood”
Physicians choice
Use of diagnosis or code within the authorized indication
Description of expected symptoms:
To help the user to differentiate between the medicines prescribed
Avoiding a “grim” diagnose on the container
Off-label use is present when:
The intended off-label indication is stated (yes)
When neutral /non-pathological wording appears (avoiding prefixes like hypo-, hyper- in
diagnose or symptoms text) (may be)
When unusual disease symptoms appears (may be)
Use of generalized drug categories or purely descriptive medical terms (may be)
Slide 22
Classification of labels of individual quetiapine prescriptions
Authorized indication
English
Danish
Medically approved indication (likely)
No. of
English
Danish
prescriptions
No. of
Off-label indication (most likely)
English
Danish
prescriptions
No. of
prescription
s
Mental
Mod
disorder
sindslidelse
Depression
Mod
848
Stabilizing
Stabiliserrende
30
Anxiety
Mod angst
162
743
Against
Mod
18
Sedative
Beroligende
132
hallucinations
hallucinationer
14
Sleep dis-
Mod
115
turbances
søvnbesvær
Unrest
Mod uro
20
Against
Mod
22
udadreagerende
Thought
tankemylder
adfærd
swarming
depression
(delusions)
CNS
Nervemedicin
327
Bad thoughts
medicines
tanker
Treatment for Behandling af
bipolar
Mod grimme
211
bipolær lidelse
Depression and
Mod depression
insomnia
og søvnbesvær
By aggression
Ved
9
disorder
Treatment for Behandling af
schizophrenia
Psychosis
69
skizofreni
Psykose
33
Against psychotic
Mod
reactions (mania
affektreaktioner
and depression)
Slide 23
1
1
Posttraumatic
stress
disorder
Mod ptsd
10
Classification of quetiapine prescriptions from 7 pharmacies
Authorized
Pharmacy
indications,
location
(%)
Christianshavn*
Hørsholm
Hundige/
Ishøj
Nørrebro
Odense
Værløse
Vejen/Egtv
ed
Total
Medically
Off-label
Without
approved
indications
Total no. of
indications,
indications (most likely),
prescriptions
(%)
(likely), (%)
(%)
71
19
8
3
265
62
14
14
10
525
71
11
15
2
185
72
65
33
19
9
16
7
25
47
2
2
5
419
1066
187
58
25
13
4
277
64 %
14%
18%
4%
2922
Slide 24
Levothyroxine indications found on the labels collected in 7
community pharmacies for two-year period
Authorized indication
English
Danish
For reduced
metabolism
Mod
nedsat
stofskifte
Mod
struma
For goiter
For
Mod
hypothyroidi hypothyresm
oidisme
For
Mod
myxedema myxødem
For canal
thyroid
cancer
All
Mod
thyreoidea
kræft
-
No. of
prescrip
tions
6560
137
7
Medically approved indication
(likely)
English
Danish
No. of
prescripti
ons
Low T3
Lav T3
1
For
metabolic
disease
For
thyroid
gland
Mod
stofskiftelidelse
Mod
skoldbrusk
kirtel
English
Danish
For
metabolism
For
stofskiftet
1
Hormone
supplements
Hormon
tilskud
6
1
Thyroid
hormone
Skjoldbruskkirtelhormon
5
Unknown
indication
pattern
Metabolism
supplement
Ukendt ind.
mønster
2
Stofskifte
tilskud
3
Hormonal
treatment
All
Hormonbehandling
-
3
6
1
6711
89%
Slide 25
All
-
Off-label indication (most likely)
3
0.1%
No. of
prescrip
tions
780
798
11%
Dose related distribution of authorized indications
for quetiapine
Daily dose (mg)
500-900
300-500
100-300
< 100
Correct use (%)
100
87
86
26
Re. schizophrenia, bipolar disorder and depression:
The higher the dose - the more correct use
L:\4. sal\Ojb\Science\Combination
therapy\Adressing the GAP from
E2E
Discussion of methods
• The Danish National Prescriptions Registry (DNPR)
and CITO provide similar information
• DNPR search needs application, approval and fee
• Analysis can be done on-line by employees at any
time without special permission
• CITO cover only about 20% of all community
pharmacies in Denmark
Conclusion and Outlook
• Community pharmacies represent a source for pharmacovigilance research
and on-line prescription analysis
• Pharmacy students on internship are well suited for AE collection, allowing
participation of sufficient number of patients and pharmacies for
Nationwide extrapolation
• Through Pharmacy Prescription Event Monitoring Danish pharmacies could
be a “Laboratory” for systematic collection of early pharmacovigilance data
• On-line data collection from local pharmacy servers using Structured Query
Language (SQL) code in the CITO software proved compared to The Danish
National Prescriptions Registry to be easy and fast
• Reliable off-label data as age and dose can easily be obtained whereas
the interpretation of the prescriptions label text is uncertain
L:\4. sal\Ojb\Science\Combination
therapy\Adressing the GAP from E2E
Dias 28
Acknowledgements
Thanks is due to
Cand. pharm. Søren T. Christensen for organising the ADR collection as
postdoc sponsored by Pharmaceutical Faculty, Univ. Copenhagen.
Master student , stud. pharm. sci. Monika Andrulyte for organising the
the collection and data handling of the off-label data
Pharmacist Asger Mortensen, Værløse, who draw the attention to the
data richness of the local servers.
Stud. pharm. Andreas E. Kern-Jespersen and Nada J. Arief conducted
the off-label pilot study.
Associate professor Lotte Stig Nørgaard for establishing contact to the
many pharmacy internL:\4.
students.
sal\Ojb\Science\Combination
therapy\Adressing the GAP from E2E
Dias 29
28/11/2016
L:\4. sal\Ojb\Science\Combination
therapy\Adressing the GAP from
E2E
30