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10 Spontaneous Reporting Systems
245
The reasons for its unique value are likely
linked with:
1. Spontaneous reports describe the real-life
clinical practice and cover all real-life scenarios, including off-label use, all ages, all
comorbidities, and all interactions. There are
no prescribed limits, e.g. no inclusion or
exclusion criteria, limitations of data collection tools, regulatory constraints, etc.
2. Unique insights of experienced physicians
who regularly consider adverse reactions
among the options in their differential diagnosis work, as well as theviews of patients
with a very personal experience.
3. It benets from global coverage, including
all countries and healthcare systems.
The most likely types of reactions revealed by
spontaneous reports would be relatively dramatic
ones, with clear (and usually short) time to onset,
with a few alternative explanations, low background incidence/prevalence, and are not confounded by indication (e.g. not explainable by
symptoms of the treated disease).
Examples of the most likely types of ADRs
discovered by spontaneous reporting systems
include aplastic anaemia, agranulocytosis, acute
liver failure, rhabdomyolysis, certain arrhythmias such as torsade de pointes, and serious skin
reactions such as Stevens-Johnson syndrome.
Causal relationship of these ADRs can often be
established by well-documented case series.
10 Weaknesses of Spontaneous
Reporting Systems
Limitations of spontaneous reports are signicant
and need to be addressed at all levels of the
reporting systems. They primarily relate to low
data quality, an uncertain denominator, and
underreporting.
10.1 Low Quality ofData
The challenges linked with the quality of ICSRs
have been discussed above. Usually, just a tiny
proportion of the reports are well documented. In
signal detection, while aggregating data, even
poorly written ICSRs may sometimes play a signicant supportive role in signal detection, validation, and evaluation. Raising suspicion based
on incomplete reports and communicating it to
the healthcare community may stimulate further
reporting and complement missing information.
Safety communication of incomplete information with uncertainty is an art of itself and needs
to take into account local context to prevent raising unwanted alarm with unintended consequences. Data of low quality usually cannot lead
to a denitive conclusion of the signal assessment, and other pharmacovigilance studies may
be required.
10.2 Uncertain Denominator
While there are estimates available to the pharmaceutical industry and regulatory agencies concerning the exposure of a population to an
individual medicinal product, these are still rough
estimates. We may have exact numbers of dened
daily dose (DDD) released on the market.
However, we do not know how much has been
dispensed, who has been treated, and whether the
patients took the drug as prescribed. The phenomenon of non-adherence of patients to a prescribed therapeutic regime is a well-known and
recognised factor in clinical practice. Therefore,
a frequency of an ADR cannot be based on ADR
reporting only.
Another limitation of spontaneous reporting
systems is that temporal trends in the number of
reported ICSRs for a drug–event combination
may not reect actual exposure to the medicinal
product. Multiple factors can affect the number
of ICSRs received. First, the number of reports
linked with a particular medicine is thought to
peak in the second year after approval and
decline, even though the drug may be widely
used. This phenomenon, known as the Weber
effect, was initially described concerning nonsteroidal anti-inammatory medicines [21].
A more recent analysis of reporting patterns
for the angiotensin-II receptor blocker class of
medicines revealed no discernible trend when
246
J. Petracek and M. Fialova
examining the number of reports over time [22].
Specically, this analysis did not conrm that the
number of reports increased towards the end of
the second year and declined after that. Instead, it
indicated that additional factors such as the
approval of further indications and modications
of the rms’ reporting requirements affected the
total number of reports received. However, when
the number of reports in a year was adjusted for
the number of prescriptions in that period, it was
found that the adjusted number of reports was
highest in the rst years after approval and
declined thereafter.
However, the frequency of ICSRs per estimated unit of drug utilisation may not be constant
over time. An analysis of FAERS data for 62
drugs did not conrm a reporting pattern over
time as described by Weber [23].
10.3 Underreporting
Understandably, not all cases of AEsor ADRs in
clinical practice would be reported. The likelihood of them being reported depends primarily
on two factors—reporting culture of the country
and the nature of the drug–event pair. Generally,
the proportion of reported cases is between 1 and
10% of the total prevalence [24].
As discussed throughout this chapter, underreporting is linked with the culture and legal
environment of a particular country. Both can be
improved by suitable policies, educational
activities, and leadership by example. There are
several studies in this respect published for
countries and clinical areas. For evaluating a
true drug–event pair incidence in a particular
population, a correction for underreporting may
need to be used, e.g. multiplication by a factor
of 10 [25–27].
11 The Future ofSpontaneous
Reporting Systems
Spontaneous reporting systems have proven their
high usefulness as part of pharmacovigilance;
therefore, many efforts are ongoing to improve
their performance further. They include the use of
better technology, improvements of regulatory
frameworks, and potentially, partial integration
with other systems to decrease the barriers of
reporting, improve the quality of data, decrease
underreporting, and streamline all associated
processes, such as case intake, processing, and
reporting.
11.1 Integration of Spontaneous
Reporting Systems into
Healthcare Systems
Harmonisation of formats and seamless integration of the spontaneous reporting tools to systems
used at the point of care has the potential tosignicantly address many weaknesses observed
today. The HL7 platform (www.hl7.org) has
already integrated ICSR reports, and further harmonisation of data models is ongoing.In the UK,
Yellow Card reporting has been integrated into
primary care healthcare record and prescribing
systems.
11.2 Use ofArticial Intelligence
Tools
Case intake, processing, and reporting are being
automated to a large extent. In addition, articial intelligence (AI) approaches are used for
the analysis of data and even for the prediction
of specic ADRs during the product development [28].
Integrating data science in clinical practice
may include pharmacovigilance approaches,
including spontaneous reporting systems into
healthcare communication pathways and clinical
decision support systems. It may result in signicant democratisation of the system and decentralised decision-making in speeding up the learning
cycle to benet patient safety.
11.3 Electronic Healthcare Records
The widespread availability of electronic healthcare data may, at rst, seem to undermine the
importance of spontaneous reporting. However,
10 Spontaneous Reporting Systems
247
motivation for creating most existing healthcare
records introduces signicant biases that spontaneous reports usually do not have. It makes electronic healthcare records complementary to
spontaneous reporting systems. In fact, they may
enrich each other.
Spontaneous reports with automatically
attached data from electronic healthcare records,
including laboratory, radiologic, and other diagnostic test results, can signicantly improve the
quality of data available in spontaneous reporting
systems [29].
With new advanced medicinal products, monitoring post-marketing benets and risks is
increasingly necessary. Spontaneous reporting
systems will continue to be the cornerstone of
this effort because of their unique advantages. As
social media, active surveillance, and the use of
large healthcare databases begin to play a role in
drug safety surveillance, demonstrate their utility, and realise their potential, they could become
valuable adjuncts to existing pharmacovigilance
reporting systems worldwide.
12 Summary andConclusions
Early systems of spontaneous reporting were
developed in the second half of twentieth century. Now, these systems are worldwide systems for processing millions of ICSRs per
yearin highly advanced databases. Despite the
signicant underreporting bias, the amount and
quality of information collected are sufcient
to inform a large number of regulatory actions
to minimise harms associated with medicinal
products.
Spontaneous reports still represent an irreplaceable source of information for pharmacovigilance, not least because of the inherent
implicit potential suspicion of causation in the
mind of the reporter. They have been signicantly strengthened by the new technology of
mobile phone apps, social media, and AI applications in healthcare. Essential rules of implied
causality and acceptance of patient reports,
paired with the emphasis on the quality of reports
and their validation at source, have further
improved the usefulness of the collected infor-
mation for signal detection, assessment, and
regulatory decision-making.
Data integration of spontaneous reports with
other types of reports and available data in healthcare systems is ongoing on a large scale. Data
science techniques are being further developed to
improve the quality of data and its interpretation.
This may lead to even quicker risk minimisation,
including the prediction of ADRs to new medicinal products.
13 Case Studies
Two cases which illustrate the importance,
advantages, disadvantages, limitations, and interpretation of spontaneous report data are described
below.
13.1 Case Study 1: Dabigatran
Dabigatran is an oral direct thrombin inhibitor
approved in the US in October 2010 to reduce the
risk of stroke and systemic embolism in patients
with nonvalvular atrial brillation. It was the rst
oral anticoagulant approved for this indication
since warfarin had been approved for a similar
indication.
In the clinical trial that supported dabigatran’s
approval, 6076 patients were randomised to dabigatran 150mg twice daily, and 6022 were randomised to warfarin treatment. The rates of
major bleeding were 3.3 per 100 person-years in
dabigatran- treated patients and 3.6 per 100
person- years in warfarin-treated patients (hazard
ratio 0.93, 95% condence interval (CI) 0.81–
1.07). The corresponding rates for lifethreatening bleeds were 1.5 per 100 person-years
and 1.9 per 100 person-years in the dabigatran
and warfarin groups, respectively (hazard ratio
0.80, 95% condence interval 0.66–0.98).
Gastrointestinal bleeding was more common in
dabigatran-treated than in warfarin-treated
patients (1.6% vs 1.1%, hazard ratio 1.5, 95%
condence interval 1.2–1.9) [30].
In the rst 14 months after dabigatran’s
approval, the US FDA received 2347 case reports
of bleeding with dabigatran (348 with a fatal out-
248
J. Petracek and M. Fialova
come), compared to 647 case reports of bleeding
with warfarin (46 with a fatal outcome) [30].
This disparity in report numbers between the
two agents suggested that dabigatran might be
responsible for more bleeding in clinical practice.
This nding was contrary to the preapproval
observations. These numbers also raised the possibility of increased mortality with dabigatran
relative to warfarin. A population-based analysis
using administrative claims data found that the
bleeding rates associated with dabigatran use
were no higher than those associated with warfarin use [31].
A subsequent study using data from the US
Medicare system found that, in clinical practice
settings, dabigatran was associated with a lower
risk of ischaemic stroke, intracranial haemorrhage and death, and a higher risk of major gastrointestinal bleeding relative to warfarin. These
ndings were consistent with the preapproval
clinical trial data [32].
This example illustrates some important limitations concerning using aggregate spontaneous
report data to estimate population-based risk or
relative risk of an AE between two drugs. A comparison of raw numbers of AE reports generally
cannot be used to estimate the relative frequency
of the AE in a population between two drugs.
Population- based rates of an AE generally cannot
be estimated from spontaneous reporting data
because of underreporting and lack of a reliable
measure of population exposure.
Notably, there often is a differential extent of
reporting of AEs across a product’s marketed life
(Weber effect, see above). Thus, even though a
newly approved drug may not be widely used,
more spontaneous AE reports may be received
for the newer drug compared to an older, widely
used drug, even if there is no actual difference in
risk.
13.2 Case Study 2: Peginesatide
Peginesatide is a synthetic peptide considered
a significant breakthrough for treating anaemia in patients with dialysis-dependent
chronic kidney disease, approved by US
FDA. It was withdrawn from the market in
2012, within months of becoming commercially available, when the manufacturer
received a surprising number of case reports of
fatal anaphylaxis [33].
Subsequent analyses suggested that the root
cause of the reactions may have been a preservative present in the commercially available
multiple- use vials [34]. This excipient was not
used in the single-use formulation in clinical trials [35].
Anaphylaxis is a rare, unpredictable adverse
reaction that can occur within minutes of exposure to an agent. The risk of such reactions must
be minimised. If no effective risk minimisation
measures are available, the medicinal product
will struggle to demonstrate a positive benet–
risk balance and need to be withdrawn from the
market.
Fatal anaphylaxis is a rare occurrence with a
strong temporal relationship between a triggering
exposure and the onset of severe symptoms. It
represents an excellent example of the type of
ADR for which spontaneous reporting systems
are well suited to inform timely signal detection.
Although the decision to withdraw peginesatide
from market was relatively swift, the results of
subsequent nonclinical analyses suggesting an
unexpected root cause illustrate the importance
of a thorough investigation, including the product
quality [36].
References
1. International conference on harmonisation of technical requirements for registration of pharmaceuticals for human use. POST-APPROVAL SAFETY
DATA MANAGEMENT: DEFINITIONS AND
STANDARDS FOR EXPEDITED REPORTING
E2D. Current Step 4 version dated 12 November
2003. https://database.ich.org/sites/default/les/E2D_
Guideline.pdf.
2. Vargesson N. Thalidomide-induced teratogenesis:
history and mechanisms. Birth Defects Res C Embryo
Today. 2015;105(2):140–56. https://doi.org/10.1002/
bdrc.21096.
3. McBride WG. Thalidomide and congenital abnormalities. [Letter to the Editor]. Lancet. 1961;
2:1358.
10 Spontaneous Reporting Systems
249
4. Lenz W, Knapp K.Foetal malformations due to thalidomide. In: Problems of birth defects. Springer;
1962. p.200–6.
5. Kelsey FO. Thalidomide update: regulatory
aspects. Teratology. 1988;38(3):221–6. https://doi.
org/10.1002/tera.1420380305.
6. Fornasier G, Francescon S, Leone R, Baldo P.An historical overview over Pharmacovigilance. Int J Clin
Pharm. 2018;40(4):744–7. https://doi.org/10.1007/
s11096- 018- 0657- 1.
7. Yellow Card | Making medicines and medical devices
safer. n.d.. https://yellowcard.mhra.gov.uk/.
8. Boston Collaborative Drug Surveillance Program—
Medical Technology Assessment Directory—NCBI
Bookshelf. n.d.. https://www.ncbi.nlm.nih.gov/books/
NBK218319/.
9. Programme for International Drug Monitoring.
n.d..
prequalification/regulation- and- safety/
pharmacovigilance/health- professionals- info/pidm.
10. IVigee, iViReg. Technology. https://www.ivigee.com/
technology.ivireg.
11. Kessler DA.Introducing MEDWatch. A new approach
to reporting medication and device adverse effects
and product problems. JAMA. 1993;269(21):2765–8.
https://doi.org/10.1001/jama.269.21.2765.
12. Margraff F, Bertram D.Adverse drug reaction reporting by patients: an overview of fty countries. Drug
Saf. 2014;37(6):409–19. https://doi.org/10.1007/
s40264- 014- 0162- y.
13. Inácio P, Cavaco A, Airaksinen M.The value of patient
reporting to the pharmacovigilance system: a systematic review. Br J Clin Pharmacol. 2017;83(2):227–46.
https://doi.org/10.1111/bcp.13098.
14. Avery AJ, Anderson C, Bond CM, Fortnum H, Gifford
A, Hannaford PC, Hazell L, Krska J, Lee AJ, McLernon
DJ, Murphy E, Shakir S, Watson MC. Evaluation of
patient reporting of adverse drug reactions to the UK
'Yellow Card Scheme': literature review, descriptive
and qualitative analyses, and questionnaire surveys.
Health Technol Assess. 2011;15(20):1–234. https://
doi.org/10.3310/hta15200.
15. Rolfes L, van Hunsel F, van der Linden L, Taxis K,
van Puijenbroek E.The quality of clinical information in adverse drug reaction reports by patients and
healthcare professionals: a retrospective comparative
analysis. Drug Saf. 2017;40(7):607–14. https://doi.
org/10.1007/s40264- 017- 0530- 5.
16. Watson S, Chandler RE, Taavola H, Härmark L,
Grundmark B, Zekarias A, Star K, van Hunsel F.Safety
concerns reported by patients identied in a collaborative signal detection workshop using VigiBase:
results and reections from Lareb and Uppsala monitoring centre. Drug Saf. 2018;41(2):203–12. https://
doi.org/10.1007/s40264- 017- 0594- 2.
17. Hammond IW, Rich DS, Gibbs TG.Effect of consumer
reporting on signal detection: using disproportionality
analysis. Expert Opin Drug Saf. 2007;6(6):705–12.
https://doi.org/10.1517/14740338.6.6.705.
https://www.who.int/teams/regulation-
18. World Health Organization. Ethical criteria for medicinal drug promotion. WHO Publications Center USA
Distributor; 1988.
19. Sloane R, Osanlou O, Lewis D, Bollegala D, Maskell
S, Pirmohamed M.Social media and pharmacovigilance: a review of the opportunities and challenges.
Br J Clin Pharmacol. 2015;80(4):910–20. https://doi.
org/10.1111/bcp.12717.
20. Convertino I, Ferraro S, Blandizzi C, Tuccori M.The
usefulness of listening social media for pharmacovigilance purposes: a systematic review. Expert Opin
Drug Saf. 2018;17(11):1081–93. https://doi.org/10.10
80/14740338.2018.1531847.
21. Weber J. Epidemiology of adverse reactions to nonsteroidal anti-inammatory drugs. In: Rainsford KD,
Velo GD, editors. Side-effects of anti-inammatory
drugs, advances in inammation research. Raven
Press; 1984. p.1–7.
22. McAdams MA, Governale LA, Swartz L, Hammad
TA, Dal Pan GJ.Identifying patterns of adverse event
reporting for four members of the angiotensin II receptor blockers class of drugs: revisiting the Weber effect.
Pharmacoepidemiol Drug Saf. 2008;17(9):882–9.
https://doi.org/10.1002/pds.1633.
23. Hoffman KB, Dimbil M, Erdman CB, Tatonetti NP,
Overstreet BM. The Weber effect and the United
States Food and Drug Administration's Adverse
Event Reporting System (FAERS): analysis of
sixty-two drugs approved from 2006 to 2010. Drug
Saf. 2014;37(4):283–94. https://doi.org/10.1007/
s40264- 014- 0150- 2.
24. Hazell L, Shakir SA. Under-reporting of
adverse drug reactions: a systematic review.
Drug Saf. 2006;29(5):385–96. https://doi.
org/10.2165/00002018- 200629050- 00003.
25. McGettigan P, Golden J, Conroy RM, Arthur N,
Feely J.Reporting of adverse drug reactions by hospital doctors and the response to intervention. Br
J Clin Pharmacol. 1997;44(1):98–100. https://doi.
org/10.1046/j.1365- 2125.1997.00616.x.
26. Perlík F, Slanar O, Smíd M, Petrácek J. Attitude of
Czech physicians to adverse drug reaction reporting.
Eur J Clin Pharmacol. 2002;58(5):367–9. https://doi.
org/10.1007/s00228- 002- 0476- z.
27. Wallerstedt SM, Brunlöf G, Johansson M-L, Tukukino
C, Ny L.Reporting of adverse drug reactions may be
inuenced by feedback to the reporting doctor. Eur
J Clin Pharmacol. 2007;63(5):505–8. https://doi.
org/10.1007/s00228- 007- 0270- z.
28. Salas M, Petracek J, Yalamanchili P, Aimer O,
Kasthuril D, Dhingra S, Junaid T, Bostic T.The use of
articial intelligence in pharmacovigilance: a systematic review of the literature. Pharmaceut Med. 2022;
https://doi.org/10.1007/s40290- 022- 00441- z.
29. Harpaz R, Vilar S, Dumouchel W, Salmasian
H, Haerian K, Shah NH, Chase HS, Friedman
C. Combing signals from spontaneous reports
and electronic health records for detection of
adverse drug reactions. J Am Med Inform Assoc.
250
J. Petracek and M. Fialova
2013;20(3):413–9. https://doi.org/10.1136/
amiajnl- 2012- 000930.
30. McConeghy KW, Bress A, Qato DM, Wing C, Nutescu
EA.Evaluation of dabigatran bleeding adverse reaction reports in the FDA adverse event reporting system
during the rst year of approval. Pharmacotherapy.
2014;34(6):561–9. https://doi.org/10.1002/phar.1415.
31. Southworth MR, Reichman ME, Unger
EF. Dabigatran and postmarketing reports of bleeding. N Engl J Med. 2013;368(14):1272–4. https://doi.
org/10.1056/NEJMp1302834.
32. Graham DJ, Reichman ME, Wernecke M, Zhang R,
Southworth MR, Levenson M, Sheu TC, Mott K,
Goulding MR, Houstoun M, MaCurdy TE, Worrall
C, Kelman JA.Cardiovascular, bleeding, and mortality risks in elderly Medicare patients treated with
dabigatran or warfarin for nonvalvular atrial brillation. Circulation. 2015;131(2):157–64. https://
doi.org/10.1161/circulationaha.114.012061.
33. Bennett CL, Jacob S, Hymes J, Usvyat LA, Maddux
FW.Anaphylaxis and hypotension after administration
of peginesatide. N Engl J Med. 2014;370(21):2055–6.
https://doi.org/10.1056/NEJMc1400883.
34. Weaver JL, Boyne M, Pang E, Chimalakonda K,
Howard KE.Nonclinical evaluation of the potential
for mast cell activation by an erythropoietin ana-
log. Toxicol Appl Pharmacol. 2015;287(3):246–52.
https://doi.org/10.1016/j.taap.2015.06.009.
35. Kotarek J, Stuart C, De Paoli SH, Simak J, Lin TL,
Gao Y, Ovanesov M, Liang Y, Scott D, Brown J, Bai
Y, Metcalfe DD, Marszal E, Ragheb JA. Subvisible
particle content, formulation, and dose of an erythropoietin peptide mimetic product are associated
with severe adverse postmarketing events. J Pharm
Sci. 2016;105(3):1023–7. https://doi.org/10.1016/
s0022- 3549(15)00180- x.
36. Hermanson T, Bennett CL, Macdougall
IC. Peginesatide for the treatment of anemia due to
chronic kidney disease—an unfullled promise.
Expert Opin Drug Saf. 2016;15(10):1421–6. https://
doi.org/10.1080/14740338.2016.1218467.
Further Reading
Strom BL, Kimmel SE, Hennessy S, editors.
Pharmacoepidemiology. John Wiley & Sons Ltd.;
2021.
Stephens MD.The dawn of drug safety. Hampshire, UK:
George Mann; 2010.
Communicating Drug Safety
MarcoTuccori, IrmaConvertino, SaraFerraro,
MarcoBonaso, GiuliaValdiserra,
andEmilianoCappello
11
Abstract
Promoting safety of medications is imperative
for optimal use, and the communication of the
risk is entrusted to communicators. The communication of the risk of medicine requires
peculiar expertise that is different from communications about its benet. The identication of a risk related to a medicinal product is a
dynamic process that involves the acquisition
of information that progressively transforms
into knowledge. In the initial stages of this process, the risk is often only potential but this
uncertainty still requires caution. Uncertain
risks are frequently matter of communication,
and the magnitude of this uncertainty often
drives the risk communication itself as the
main subject. A message has to be tailored to
the attitude and concerns of the target audience
for achieving the best effects. Otherwise,
uncertainties and hesitancies could persist
M. Tuccori (*)
Unit of Pharmacology and Pharmacovigilance,
Department of Clinical and Experimental Medicine,
University of Pisa, Pisa, Italy
Unit of Adverse Drug Reactions Monitoring,
University Hospital of Pisa, Pisa, Italy
e-mail: m.tuccori@ao-pisa.toscana.it
I. Convertino · S. Ferraro · M. Bonaso · G. Valdiserra
E. Cappello
Unit of Pharmacology and Pharmacovigilance,
Department of Clinical and Experimental Medicine,
University of Pisa, Pisa, Italy
even after the conrmation of the absence of a
risk or could spread throughout media with
consequent possible inappropriate use of drugs
or therapeutic failure of medicines. In this
regard, case studies such as measles vaccination and autism and the COVID-19 infodemic
are paradigmatic examples. In risk communication about medicines, it is important to identify the subjects involved, dene their roles
(senders or receivers) and characteristics, to
build the message and its content, and choosing the appropriate media for conveying the
message. Several expertise is also required,
including rhetoric, ethics, social sciences, and
pharmacoepidemiology.
Keywords
Drug safety · Risk communication ·
Infodemic · Risk perception · Social media ·
Rhetoric
Learning Objectives
• Describe theprinciples and denitions of the
risk communication on drugs.
• Understand how to build effective risk com-
munication strategies.
• Discuss the multidisciplinary approaches
involved in risk communication on
medicines.
• Analyze the ethical and legal framework in
risk communication on medicines.
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
J. Jose et al. (eds.), Principles and Practice of Pharmacovigilance and Drug Safety,
https://doi.org/10.1007/978-3-031-51089-2_11
251
252
Key Points
• The attention to the communication of
risk on medicinal products has grown in
the recent years, when the experiences
with rofecoxib, thalidomide, and H1N1
inuenza vaccine brought regulatory
authorities and all professionals to the
awareness that preventing and managing risk needs an improvement in transparency and compliance with the
recommendations, meaning a quick and
effective risk communication.
• Constructing an effective risk communication strategy requires not only
specic expertise but also a structured
process, tailored to the condition for
ensuring its benet. This includes the
identication and characterization
(e.g., level of understanding) of subjects involved in the communication
process (senders or receivers), the designation of the message and its content,
and the determination of the media for
conveying the message in a quick way,
for stemming fake news and uncertainties from rapid expansion.
• A risk can occur whenever a patient
takes a drug. However, to distinguish
from fears, uncertainties, and fake
beliefs, it is required that after the identication of risk and the classication as
potential risk through the observations
of evidence from clinical practice or
ndings from observational studies, the
risk has to be conrmed and communicated leading to an impact on clinical
practice.
1 Introduction
The Swiss physician, alchemist, and philosopher
Paracelsus (1493–1541) considered to be the
father of modern toxicology, argued that “Omnia
venenum sunt: nec sine veneno quicquam existit.
M. Tuccori et al.
Dosis sola facit, ut venenum non t” (Everything
is poison, and nothing exists without poison.
Only the dose prevents the poison from taking
effect) [1]. The sentence in modern times was
intended as “every drug is a poison. It is just a
matter of dose.” Although he referred in a broad
sense to all substances, somehow and perhaps
unwittingly, with this admonition, Paracelsus
ventured into a sort of proto-communication of
the risk of medicinal products. From the perspective of rhetoric, the combination of the two words
“poison” and “drug” can condition the attitude of
the recipients of the message to move with caution toward substances, thus acting on their perception of risk. The sentence by Paracelsus was
probably very effective in communicating the
risk of medicine to people of the Renaissance
period, but today things are much more
complicated.
While in the time of Paracelsus, medical information traveled only on medical treatises and
was intended for the medical elite, today the
means of communication are much more universal and accessible. The safety of medicines is
now a matter of public concern. People are
increasingly interested in transparency around
medicationsafety-related matters. Clear communication of the facts relating to drug safety is
entrusted to communicators, who can make use
of various tools to best exercise their role as
mediators. The communication of the risk of
medicinal products must therefore take into
account many factors and in particular the centrality of the patient in the management of treatments [2]. In the 1980s, the doctor, the patient,
and medical information were identied as the
three essential elements of evidence-based medi-
cine and their optimal interaction is considered
the key to ensure the effectiveness of treatments
under the maximum safety conditions [3]. The
principles of evidence-based medicine can now
be extended to all communication processes of
information on medicines, involving all the
stakeholders of modern pharmacovigilance and
in particular governments, regulatory agencies,
pharmaceutical companies, healthcare professionals, and patients.
11 Communicating Drug Safety
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In this chapter, we will illustrate the general principles of risk communication on
medicinal products starting from the definitions to arrive at the construction of effective
communication strategies based on multidisciplinary approaches, passing through some
case studies from which we have learned
important lessons.
2 The Scope
ofCommunicating Risk
About Medicinal Products
The purpose of risk communication of medicinal
products is to inform and educate the stakeholders
about the potential benets and harms of using a
certain medicinal product and to facilitate the
decision-making process based on the best available evidence. Risk communication is an integral
part of quality risk management, which is a systematic process for the assessment, control, communication, and review of risks to the quality of
medicinal products [4]. Risk communication also
supports pharmacovigilancesignicantly [5].
3 Risk andRisk Perception
About Medicinal Products
The risks of a medicinal product, or its ability to
cause harm to the patient, are usually linked to
the active substance (more rarely to its excipients or contaminants). In some cases, we can
identify specic susceptibility of the patient who
takes it (e.g., genetics, concomitant diseases,
concomitant treatments). However, in many
cases, the determinants of a risk may be unknown
or undetectable, and in these cases the damage
may be unpredictable and not preventable. The
risk can also be generated by the circumstances
in which the drug is taken (e.g., misuse, errors in
therapy management). The lack of efcacy,
regardless of the cause, also falls within the concept of risk since it can cause damage that in certain situations can be particularly relevant
(life-threatening diseases, vaccines, contraceptives) [6].
Although there is a conceptual difference
between harm and risk, in the general language
the word risk is used to dene both terms. While
harm can be dened as an actual injury to someone’s goods (e.g., house, car, money) or values
(e.g., family, health, freedom), a risk refers to
the probability or potentiality or uncertainty that
something negative could happen to that goods
or values, whatever the magnitude of this probability. In this context, risk communication for
medicinal products can be dened as the not
necessarily mutual transfer of information about
the probability (risk) that a certain clinically
adverse event may occur with the intake of a
medicinal product in relation or not to an
expected benet (including any measures to be
taken to minimize this probability), between
two or more subjects, usually a communicator
(or sender) and a target audience (receiver)
(doctor and patient, regulatory authority and
population, pharmaceutical industry and regulatory authority). It is important to underline that
the communication of the risk of medicinal
products can almost never be separated from
that of the expected benet (benet–risk balance) and that the evaluation and communication of benets require specic expertise,
different from that of risks [6].
The identication of a risk related to a
medicinal product is a process developing
through various degrees of certainty, from a
risk that can be dened as “potential” up to the
conrmation of the risk itself. The hypothesis
of the existence of a risk can be generated in a
theoretical and speculative way starting from
the knowledge surrounding the biological
mechanisms with which the drug is supposed to
act. Much more often, it is generated by anecdotal reporting of events observed in clinical
practice (see, e.g., the case of thalidomide) [7].
More rarely, the signals may be generated by
clinical trials or observational studies. The latter are more useful for conrming a risk, but
intrinsic limitations of the observational studies
themselves (limited study power, statistical
assumptions, residual confounding) may produce results that must still be interpreted with
caution [8].
254
M. Tuccori et al.
Risk communication of medicinal products
more often deals with potential risks than with conrmed risks. This means that uncertainties are often
the subject of the communication and can affect the
characteristics and outcomes of the communication
itself. The uncertainties may concern diagnostic and
clinical or epidemiological aspects but very often
they are related to causality. The description of
uncertainties is an element of risk communication
that affects the communicator’s credibility and must
be handled with the utmost transparency [9].
People may have various concerns about taking
medicines. These concerns derive from the personal beliefs of individuals and are inuenced by
education, religious belief, politics, morality, and
in general by the environment in which one grows
up and by the people who associate with one
another. These aforementioned factors determine
the individual perception of risk, that is, the cognitive process involved in various daily activities and
which guides people’s behavior in the face of decisions involving potential risks [9]. The effective-
ness of a message may depend on how closely it is
tailored to the recipient’s possible concerns.
Concerns may persist for a long time even when
the risk has been denitively excluded, as in the
case of autism “fraudly” associated with measles
vaccination [10]. Even simple rumors and fake
news can fuel or limit worries and, given the popularity of modern means of communication such as
social media, the effects can be signicant and on
a large scale. The main consequences may be the
failure to use medicines effectively (resulting in
therapeutic failure) or inappropriate use, with the
possibility of developing adverse events in the face
of a non-existent benet. In this regard, the
COVID-19 pandemic has produced important
examples both before and after the advent of vaccines, from which it is essential to learn lessons for
the future (see Sect. 8) [11].
4 Essential Elements ofRisk
Communication
forMedicinal Products
Communication refers in common language to the
complex interplay of messages, tools, and processes necessary for the transfer of information
between different parties in order to achieve certain objectives. Mapping the communication
model is recommended for building effective communication (Fig.11.1). In particular, it is important to identify the subjects involved and dene
their roles (senders or receivers), the message and
its content, the media through which the message
is conveyed, and the information transfer ows.
The content of the communication refers to
the information conveyed. The information
describes facts provided or learned from something or someone (source) and is related to
knowledge or data. The information is not necessarily in verbal or written form but can also be
made in images or sounds. It can contain numerical data to favor cognitive processes of quantication useful for transforming uncertain situations
into more certain, in order to favor the decisionmaking process toward any choices. In the case
of medicinal products risk communication, the
information is intrinsically uncertain (Sect. 2),
the quality of the content and its presentation are
highly variable, and the passage of the message
can be easily confused or hindered by external
elements (rumors and fake news). Therefore, the
cognitive process can be particularly challenging
for individuals [12].
In the context of the risk communication of
medicinal products, the subjects most often
involved are patients (also understood as citizens), caregivers, regulatory authorities, the
pharmaceutical industry, academia, and organizations of these subjects. However, given today’s
accessibility to the media, political and religious
leaders, governments, journalists, teachers,
judges, lawyers, bloggers, lm makers, ction
writers, and artists can often be involved in the
debate on drug safety [6]. Depending on the situation, all these subjects can be either communicators (senders) or target audience (receivers).
The drug communication model can be developed through four main levels that can overlap
and be more or less dened: (1) the interpersonal
level: it is most important for the patient and concerns direct communication of patients with caregivers (doctor, pharmacist, and nurse); (2) the
intra-group (or intra-organization) level: patients
and caregivers can communicate within groups
that include other patients (self-help groups) or
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