Signals of adverse drug reactions communicated by pharmacovigilance stakeholders: protocol for a scoping review of the global literature

doi:10.21203/rs.3.rs-26922/v2

Download PDF

Protocol

Signals of adverse drug reactions communicated by pharmacovigilance stakeholders: protocol for a scoping review of the global literature

https://doi.org/10.21203/rs.3.rs-26922/v2

This work is licensed under a CC BY 4.0 License

Journal Publication

published 13 Aug, 2020

Read the published version in Systematic Reviews →

You are reading this latest preprint version

Background: Signals of adverse drug reactions (ADRs) form the basis of some regulatory risk-minimization actions in pharmacovigilance. Reviews of limited scope have highlighted that such signals are mostly supported by reports of ADRs or multiple types of evidence. . The time that elapses between a report of a suspected ADR and the communication of a signal has not been systematically characterized. Neither have the features of reports of suspected ADRs that authors used to support putative causal relationships, although difficulties with establishing causal relationships between medicinal products and adverse events have been highlighted. The objectives of this study will be to describe the evidence underpinning signals in pharmacovigilance, the features of reports of ADRs supporting signals, and the time that it takes to communicate a signal.

Methods: . We shall retrieve records from PubMed, EMBASE, Web of Science, PsycINFO (from inception onwards), without language/design restrictions and apply backward citation screening . We shall hand-search the websites of 35 regulatory agencies/authorities, restricted publications from the Uppsala Monitoring Centre, and drug bulletins. Signals will be requested from the competent stakeholder, if absent from websites. We shall use VigiBase, the World Health Organization’s Global Individual Case Safety Report database, to determine the dates on which ADRs were reported . We shall manage records using EndNote (v. 8.2); one reviewer will screen titles/abstracts and full texts, a second will cross-validate the findings, and a third will arbitrate disagreements. Data will be charted via the Systematic Reviews Data Repository, following the same procedures as for data retrieval. Evidence will be categorized according to the Oxford Centre for Evidence-Based Medicine Levels of Evidence. Features of reports of ADRs will be coded. Tables will display frequencies of types of evidence and features of reports of ADRs. We shall use plots or pictograms (if appropriate) to represent the time from the first report of a suspected ADR to a signal.

Discussion: We expect the findings from this review will allow better understanding of global patterns of similarities or differences in terms of supporting evidence and timing of communications, and identify relevant research questions for future systematic reviews.

Scoping review registration: osf.io/jtv38

Clinical Pharmacology

Signal

adverse event

adverse drug reaction

ADR

scoping review

protocol

signal detection

pharmacovigilance

A systematic review of definitions, later adopted by the Council for International Organizations of Medical Sciences, defined signal as “information that arises from one or multiple sources (including observations and experiments), which suggests a new potentially causal association, or a new aspect of a known association, between an intervention and an event or set of related events, either adverse or beneficial, which would command regulatory, societal or clinical attention, and is judged to be of sufficient likelihood to justify verificatory and, when necessary, remedial actions” [1, 2].

Based on this definition, a signal can be supported by diverse levels of evidence, ranging from one or more reports of suspected adverse drug reactions (ADRs) to observational studies and randomized clinical trials [3–5]. On the other hand, signals of disproportionate reporting, a subtype of signal [1], can be highlighted solely by statistical associations resulting from ratios of observed versus expected numbers of reports (i.e. disproportionality) [6]. Different stakeholders can detect signals – including regulatory agencies, academia, independent research organizations, or patients and their health carers – and avail themselves of several channels to disseminate them, such as peer-reviewed articles, abstracts, drug bulletins, websites, and restricted publications. Minutes of meetings of committees can also document discussions relating to signals [7].

Comparative assessments of signals discussed at the Pharmacovigilance Risk Assessment Committee have suggested that reports of ADRs often supported signals, but that support from multiple sources of evidence increased the likelihood of a regulatory action (e.g. changes to Summaries of Product Characteristics) [8, 9]. Similar investigations carried out in the USA have highlighted the same finding [10]. Regulatory actions, however, appear to be inconsistent across international settings; discrepancies in communications of the same risks of drug-induced harms in healthcare systems have been recorded, and it has been suggested that they may be better understood by characterizing the strength of the underpinning evidence [11, 12].

An important component of detection of signals of ADRs is clinical judgment of the data. The Bradford-Hill viewpoints or guidelines [13] and other structured methods of causality assessment [14] have typically guided clinical judgments in pharmacovigilance, but their intrinsic subjectivity has yielded low interrater agreement across independent assessors [15]. Though some methods have higher interrater agreement than others, there appears to be no consensus on which ought to be the gold standard [16]; consequently, regulators’ clinical judgments on features of reports of ADRs have occasionally been criticized by healthcare workers or their professional associations [17–20]. It has been reported that the difficulties in assessing causality result in delays in the withdrawal of medicinal products from the market when fatal adverse events are attributed to their use [21]. Furthermore, the time intervals before signals of ADRs and follow-up with regulatory actions are determined by availability of information about the ADRs at medicinal product launch; in fact, these intervals were shorter when ADRs were present in a sample of the Food and Drug Administration’s ‘drug label’ at launch (e.g. severe liver injury with telithromycin or suicidal behaviour with varenicline), but longer when ADRs were absent [22]. Other accounts report that it may take 2–12 years for drug-induced harms to be communicated to healthcare workers after marketing authorization of a medicinal product [23–26]. These studies have computed the difference between dates of communication of signals and launch dates to measure the time-to-signal, while databases of reports of ADRs, such as VigiBase, the World Health Organization’s (WHO’s) global individual case safety reports database, could estimate this interval and account for unpublished records.

Ultimately, signals are spread across a gamut of channels of dissemination and may be supported by one or more levels of evidence, or solely by statistical associations. Investigations supporting evidence and delays in the time-to-signal have been limited to specific countries, time intervals, medicinal products or adverse effects. The types of subjective judgments that are applied to features of reports of ADRs to detect signals also remain scarcely characterized. Given these premises, systematic investigations are warranted.

The questions this review will address are: 1) What levels of evidence support signals of adverse drug reactions communicated by drug regulatory authorities or other pharmacovigilance stakeholders? 2) What are the similarities and differences between the levels of evidence supporting signals from different stakeholders? 3) Have the levels of evidence changed over time? 4) What is the interval between a signal and the first report of the corresponding suspected adverse drug reaction? 5) Has this interval shortened or increased over the years? 6) In the case of signals supported by reports of adverse drug reactions, what elements of the reports have led authors to signal suspected drug-related harms?

The aims of this scoping review are: (a) to provide an evidence synthesis for decision-making at a regulatory level; (b) to collate signals currently in different platforms; (c) to produce an overview of the types and levels of evidence of studies supporting signals; (d) to highlight any differences or similarities in assessment of the evidence used to support signals, with a particular focus on reports of ADRs; (e) to better understand the delays before signals are detected and to clarify whether they have changed over time.

Pharmacovigilance, as defined by the European Union directive 2001/83/EC [27]; regulation 2004/726/EC [28]; Good Vigilance Practices – Module IX [7]; International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use efficacy guidelines E2A to E2F [29], will serve as references to contextualize pharmacovigilance in a global landscape.

Searches

We shall search MEDLINE (via PubMed, 1946 - present), EMBASE (1974 - present), PsycINFO (1806 - present), Web of Science (indexes SCI-EXPANDED, CPCI-S, 1945 - present) for signals published by organizations involved in pharmacovigilance and/or independent research groups (e.g. regional pharmacovigilance centres or academia), and pharmaceutical companies. We shall use Web of Science to perform backward and forward citation screenings; if we are unable to use Web of Science, we shall use Google Scholar.

We shall search the English language websites of regulatory authorities or organizations involved in the WHO Programme for International Drug Monitoring through the websites’ search engines, to identify communicated signals and among minutes of meetings, expanding the list of countries compiled by Onakpoya et al. [21] where possible. If signals are not publicly available in a country, we shall forward requests to the competent authority. If the evidence used to support available signals is not publicly available, we shall issue freedom of information requests (where regulated) for Assessment Reports or equivalent documents.

We shall hand-search the Uppsala Monitoring Centre’s SIGNAL Document, the WHO Pharmaceuticals Newsletter, the Full List of WHO Medical Product Alerts, the WHO Drug Information, Australian Prescriber, Prescrire International, and other drug bulletins available in English via the International Society of Drug Bulletins’ index for relevant records.

We shall query Google Scholar in incognito browser tabs. We shall evaluate the results as long as two consecutive pages of results yield at least one useful article.

We shall also search OpenGrey and GreyNet International.

We shall use VigiBase [30], to obtain additional information on the year in which suspected ADRs were first reported.

The data lock point for the retrieval of all records is 6 August 2019.
Additional file 1 – Search strategy details the complete search strategy for electronic databases (adapted to PubMed) and for grey literature.

Inclusion Criteria

Peer-reviewed papers and government or agency reports and working papers concerning one or more medicinal products for human use [31] and one or more adverse events, effects, or reactions [32] that are statistically associated by disproportionality analysis [33-35], or

(a) with the primary aim of detecting, assessing, or reviewing one or more signals, as defined by [1];

(b) that explicitly mention the successful detection of a signal or whose results constitute a signal;

Documents in languages other than English will be included if the review team can translate them into English. Requests for translations will be issued to the publishing stakeholder if the review team cannot translate.

Exclusion Criteria

(a) Abstracts or papers for which the full text is unavailable.

(b) Documents that claim that the evidence does not support a signal or that no signal was detected.

(c) Signals that are communicated in the same or similar form or substance more than once by the same stakeholder (only the first signal in chronological order will be considered, if no new information appears in subsequent reports).

(d) Non-English documents and websites for which a translation is unavailable.

Primary Outcome(s)

Evidence level assessment and comparison of evidence sources used to support signals.

Secondary Outcome(s)

Elements of reports of suspected ADRs that authors used to support putative causal relationships between drugs and adverse reactions in signals.

Data retrieval

All retrieved records will be imported into EndNote™ X8.2. We shall deduplicate records manually, based on list of authors, titles, abstracts, journal, paging.

Two reviewers will independently search the titles and abstracts to determine eligibility. Any disagreements will be resolved through discussion. If a consensus cannot be reached, a third reviewer will arbitrate.

Data extraction, selection, and coding

We shall extract data from eligible studies and documents with the aid of forms provided online by the Systematic Review Data Repository and adapted to scoping reviews. Studies will be screened by title and abstract, and then by full text, against the inclusion and exclusion criteria. Data to be extracted are: publication year, type of evidence used to support signals, definition of signal used in a study or signal communication, year of the case report of the suspected ADR that was first transmitted to VigiBase and that relates to the same medicinal product and ADR in a considered signal, country of origin/communication of a signal, stakeholder, design, eligibility criteria, population involved, setting, brandname of the medicinal product (where available), corresponding active pharmaceutical ingredient(s), formulation, considered ADR(s), and possible confounding factors. Medicinal products will be coded to substance level, using the WHO Drug Dictionaries (latest version available at the start of the review), and adverse events at the Low-Level Term level of the hierarchy in the Medical Dictionary for Regulatory Activities® (MedDRA) (latest version available at the start of the review), where possible (e.g. signals of increased mortality or serious adverse events cannot be coded to MedDRA).

One reviewer will independently extract and code the data, and a second will independently cross validate the findings. Any disagreements will be resolved through consensus. If no consensus is reached a third reviewer will arbitrate.

Stakeholder(s)

We consider “stakeholders” to be healthcare practitioners and patients, national and international regulatory agencies or authorities, national and regional pharmacovigilance centres, non-governmental organizations, research institutions, and academia.

Calculation of the time-to-signal

The date on which an ADR occurred, as stated in reports of ADRs entered in VigiBase will be used to calculate the time-to-signal, by accounting for the date on which the signal relating to the same combination of medicinal product and adverse effect was communicated. If the date of occurrence of the ADR is unavailable, we shall use the first date in which the report was entered in VigiBase instead.

Strategy for data synthesis and dissemination of results

We shall summarize findings narratively by level of evidence (documented using the Oxford Centre for Evidence-Based Medicine levels of evidence); stakeholder; signal subtypes (e.g. signals of disproportionate reporting).

Descriptive statistics, where appropriate, will accompany summaries of findings, and be applied to quantify the proportions of elements in spontaneous case reports associated with signals.

We shall also present the time-to-signal, and changes in evidence sources over time and across stakeholders, in timeline plots and pictures (if appropriate).

We shall report this scoping review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for Scoping Reviews [36].

To the best of the authors’ knowledge, this would be the first study to systematically chart the evidence in support of signals and draw international comparisons of its levels using a standardized framework. The time from the first report of an ADR to the communication of a related signal will also be quantified and compared across different healthcare settings, accounting for unpublished reports of ADRs available in VigiBase – the largest database of this kind.

The accepted pharmacovigilance definition of “signal” is nowadays used in a broader context than its early formulation from the mid-60s. That merely alluded to rates of reporting of adverse effects across different groups of patients that would exceed a predefined threshold and, in turn, “be made a signal to the computer to invoke a secondary program” to produce a desired output [37] (our emphasis). Since its inception, the definition has been applied inconsistently or ambiguously [38]; moreover, there are no guidelines for reporting signals in publications, which complicates the retrieval of relevant publications. As such, the assistance of a medical librarian became indispensable in the design and adaptation to selected databases in search strategies, which were iteratively developed in line with published literature on search strategies for adverse effects [39, 40] to increase the relevance of the records retrieved. It is, however, beyond the scope of this review to evaluate the trade-off of specificity and sensitivity of the search strategy. The retrieval of data from electronic databases has revealed over 8600 unique publications, including abstracts and publications, without language restrictions. This number is likely to increase when the grey literature has been fully retrieved. Without prespecified constraints on adverse effects, medicinal products, or study designs, the retrieved dataset is bound to display heterogeneity of methods and endpoints. At early stages of this review we anticipated a large number of records, with varying methods and endpoints; so, we opted for a narrative-driven data synthesis (charting).

A challenge in this study has been to identify appropriate inclusion criteria; in principle, the presence or absence of a signal could be judged for each retrieved study – notwithstanding their numbers. However, in light of the breadth of levels of evidence that support signals, such judgments would have to be extended to the whole of the published and unpublished scientific literature, to preserve logical consistency. Given the added subjectivity introduced in this process, we saw fit to ground eligibility criteria on the explicit mention of successful detection of a signal or on the use of methods unequivocally applied in signal detection (disproportionality analysis). Similarly, the decision to contact regulatory agencies to retrieve unavailable signals reflects the position that there are different channels of communications (such as direct healthcare communications or notices posted on agency websites) for signals [8] and that inaccurate expressions have been used to refer to them [38]. Previous characterizations of the evidence underpinning “initial safety signals” [41] have focussed, for example, solely on Drug Safety Communications published by the US Food and Drug Administration [42]. These postings concern “important drug safety issue(s)” with “potential to alter the benefit–risk analysis for a drug in such a way as to affect decisions about prescribing or taking the drug” [43]. The agency’s website, however, also lists “potential signals of serious risks” [44], that is concerns “about an excess of adverse events compared to what would be expected to be associated with a product's use” [45]. This indicates that resorting to a pre-established set of webpages may result in omission of relevant records and may misrepresent the activities of those regulatory agencies who refer to “signal” using different expressions.

ADR(s): Adverse drug reaction(s)
MedDRA: Medical Dictionary for Regulatory Activities®
WHO: World Health Organization

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data and materials

The data extraction form with the extracted data will be made public via osf.io. The full URL will be made available once the scoping review is published. Data used to calculate the time-to-signal will also be made available, since it will be included in the extraction form; the dates of onset of an ADR, or dates of reporting to VigiBase, will be available on request to the corresponding author.

Competing interests

JKA has written papers on adverse drug reactions in peer-reviewed journals and has received royalties from textbooks that he has edited or co-edited; he has often acted as an expert witness in cases involving adverse drug reactions, including opioids, most often in Coroners’ courts. DS has authored signals published on drug bulletins, as abstracts or posters and received funding for doctoral studies from Uppsala Monitoring Centre. Part of the material expected to be reviewed has been published in peer-reviewed journals, drug bulletins and abstracts or posters by other researchers presently or formerly belonging to this foundation. IJO has no competing interests

Funding

This protocol is part of Daniele Sartori’s DPhil in Evidence-Based Medicine, at the University of Oxford (Nuffield Departments of Primary Care and of Continuing Education), United Kingdom. The DPhil is fully funded by Uppsala Monitoring Centre. Uppsala Monitoring Centre has suggested some aspects, such as capturing the motivations, that justify putative causal associations between medicinal products and adverse events. Uppsala Monitoring Centre manages part of the data that will be used to conduct this study, namely VigiBase, and the archives of the Signal Document. The Conflict of Interest section reiterates Daniele Sartori’s involvement in analysing this part of the data and writing of the resulting manuscripts.

Authors' contributions

DS designed the study, with input from IJO and JKA.
NR substantially aided DS in the design of the search strategy and its adaptation to multiple databases

This manuscript was written by DS, IJO, and JKA

Acknowledgements

We thank Nia Roberts, outreach librarian at the Bodleian Library of Oxford, for substantial contributions to the design of the search strategy and its adaptation to the electronic databases.

Authors' information

DS is a research pharmacist at Uppsala Monitoring Centre and reading for a DPhil in Evidence-Based Health Care at the University of Oxford, Nuffield Departments of Primary Care and Continuing Education, Oxford, UK.

JKA is a physician and clinical pharmacologist working the Centre for Evidence Based Medicine in the Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.

IJO is an MD, with an MSc and DPhil in Evidence-Based Health Care from the University of Oxford, Oxford, UK.

Hauben M, Aronson JK. Defining 'signal' and its subtypes in pharmacovigilance based on a systematic review of previous definitions. Drug Saf. 2009;32(2):99-110.
Council for International Organizations of Medical Sciences. Practical Aspects of Signal Detection in Pharmacovigilance: Report of CIOMS Working Group VIII. June Raine, editor. Geneva: World Health Organization; 2010.
Bombardier C, Laine L, Reicin A, Shapiro D, Burgos-Vargas R, Davis B, et al. Comparison of upper gastrointestinal toxicity of rofecoxib and naproxen in patients with rheumatoid arthritis. VIGOR Study Group. N Engl J Med. 2000;343(21):1520-8.
European Medicines Agency. Summary Assessment Report of the PhVWP: Domperidone - Risk of cardiac disorders [Internet]. 2011. Accessed: 26 Mar 2020. Available: https://www.ema.europa.eu/en/documents/report/monthly-report-pharmacovigilance-working-party-phvwp-october-2011-plenary-meeting_en.pdf.
van Noord C, Dieleman JP, van Herpen G, Verhamme K, Sturkenboom CJM. Domperidone and Ventricular Arrhythmia or Sudden Cardiac Death. Drug Saf. 2010;33(11):1003-14.
Bate A, Lindquist M, Edwards IR, Olsson S, Orre R, Lansner A, et al. A Bayesian neural network method for adverse drug reaction signal generation. Eur J Clin Pharmacol. 1998;54(4):315-21.
European Medicines Agency. Guideline on good pharmacovigilance practices (GVP) Module IX – Signal management [Guideline]. 2017. Rev 1. Accessed: 26 Mar 2020. Available: https://www.ema.europa.eu/en/documents/scientific-guideline/guideline-good-pharmacovigilance-practices-gvp-module-ix-signal-management-rev-1_en.pdf.
Farcaş A, Măhălean A, Bulik NB, Leucuta D, Mogoșan C. New safety signals assessed by the Pharmacovigilance Risk Assessment Committee at EU level in 2014–2017. Expert Rev Clin Pharmacol. 2018;11(10):1045-51.
Insani WN, Pacurariu AC, Mantel-Teeuwisse AK, Gross-Martirosyan L. Characteristics of drugs safety signals that predict safety related product information update. Pharmacoepidemiol Drug Saf. 2018;27(7):789-96.
Lester J, Neyarapally GA, Lipowski E, Graham CF, Hall M, Dal Pan G. Evaluation of FDA safety-related drug label changes in 2010. Pharmacoepidemiol Drug Saf. 2013;22(3):302-5.
Perry LT, Bhasale A, Fabbri A, Lexchin J, Puil L, Joarder M, et al. Comparative Analysis of Medicines Safety Advisories Released by Australia, Canada, the United States, and the United Kingdom. JAMA Intern Med. 2019;179(7):982-4.
Zeitoun J-D, Lefèvre JH, Downing N, Bergeron H, Ross JS. Inconsistencies among European Union Pharmaceutical Regulator Safety Communications: A Cross-Country Comparison. PLOS ONE. 2014;9(10):e109100.
Hill AB. THE ENVIRONMENT AND DISEASE: ASSOCIATION OR CAUSATION? Proc R Soc Med. 1965;58(5):295-300.
Naranjo CA, Busto U, Sellers EM, Sandor P, Ruiz I, Roberts EA, et al. A method for estimating the probability of adverse drug reactions. Clin Pharmacol Ther. 1981;30(2):239-45.
Kramer MS. Assessing Causality of Adverse Drug Reactions: Global Introspection and Its Limitations. Drug Inf J. 1986;20(4):433-7.
Agbabiaka TB, Savovic J, Ernst E. Methods for causality assessment of adverse drug reactions: a systematic review. Drug Saf. 2008;31(1):21-37.
Gan Tong J, M.D., White Paul F, Ph.D., M.D., Scuderi Philip E, M.D., Watcha Mehernoor F, M.D., Kovac A, M.D. FDA “Black Box” Warning Regarding Use of Droperidol for Postoperative Nausea and Vomiting: Is It Justified? Anesthesiology. 2002;97(1):287.
Handelsman Y, Henry RR, Bloomgarden ZT, Dagogo-Jack S, DeFronzo RA, Einhorn D, et al. AMERICAN ASSOCIATION OF CLINICAL ENDOCRINOLOGISTS AND AMERICAN COLLEGE OF ENDOCRINOLOGY POSITION STATEMENT ON THE ASSOCIATION OF SGLT-2 INHIBITORS AND DIABETIC KETOACIDOSIS. Endocr Pract. 2016;22(6):753-62.
Meyer-Massetti C, Cheng CM, Sharpe BA, Meier CR, Guglielmo BJ. The FDA extended warning for intravenous haloperidol and torsades de pointes: how should institutions respond? J Hosp Med. 2010;5(4):E8-16.
Schumock GT, Lee TA, Joo MJ, Valuck RJ, Stayner LT, Gibbons RD. Association between Leukotriene-Modifying Agents and Suicide. Drug Saf. 2011;34(7):533-44.
Onakpoya IJ, Heneghan CJ, Aronson JK. Post-marketing withdrawal of 462 medicinal products because of adverse drug reactions: a systematic review of the world literature. BMC medicine. 2016;14:10.
Hashiguchi M, Imai S, Uehara K, Maruyama J, Shimizu M, Mochizuki M. Factors Affecting the Timing of Signal Detection of Adverse Drug Reactions. PLOS ONE. 2015;10(12):e0144263.
Giezen TJ, Mantel-Teeuwisse AK, Straus SM, Schellekens H, Leufkens HG, Egberts AC. Safety-related regulatory actions for biologicals approved in the United States and the European Union. JAMA. 2008;300(16):1887-96.
Ishiguro C, Misu T, Iwasa E, Izawa T. Analysis of safety-related regulatory actions by Japan's pharmaceutical regulatory agency. Pharmacoepidemiol Drug Saf. 2017;26(11):1314-20.
Powers A, Cook GE. Potential safety signals and their significance. Arch Intern Med. 2012;172(1):72-3.
Sriphiromya P, Theeraroungchaisri A. An analysis of legal warnings after drug approval in Thailand. Regul Toxicol Pharmacol. 2015;71(1):108-13.
European Commission. Directive 2001/83/EC of the european parliament and of the council of 6 November 2001 on the Community code relating to medicinal products for human use. Eur-Lex. 2001. Accessed: 26 Mar 2020. Available: https://ec.europa.eu/health//sites/health/files/files/eudralex/vol-1/dir_2001_83_consol_2012/dir_2001_83_cons_2012_en.pdf.
European Commission. Regulation (EC) no 726/2004 of the European Parliament and of the Council for International Organizations of Medical Sciences of 31 March 2004, laying down Community procedures for the authorisation and supervision of medicinal products for human and veterinary use and establishing a European Medicines Agency. Eur-Lex. 2004. Accessed: 26 Mar 2020. Available: https://ec.europa.eu/health/sites/health/files/files/eudralex/vol-1/reg_2004_726/reg_2004_726_en.pdf.
International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use. Efficacy Guidelines. 2020. Accessed. Available: https://www.ich.org/page/efficacy-guidelines.
Lindquist M. VigiBase, the WHO Global ICSR Database System: Basic Facts. Drug Inf J. 2008;42(5):409-19.
European Commission. On the approximation of provisions laid down by law, regulation or administrative action relating to proprietary medicinal products. Official Journal of the European Communities. 1965. Accessed: 26 Mar 2020. Available: https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:31965L0065&from=EN.
Edwards IR, Aronson JK. Adverse drug reactions: definitions, diagnosis, and management. Lancet. 2000;356(9237):1255-9.
Arnaud M, Begaud B, Thurin N, Moore N, Pariente A, Salvo F. Methods for safety signal detection in healthcare databases: a literature review. Expert Opin Drug Saf. 2017;16(6):721-32.
Caster O, Juhlin K, Watson S, Norén GN. Improved Statistical Signal Detection in Pharmacovigilance by Combining Multiple Strength-of-Evidence Aspects in vigiRank. Drug Saf. 2014;37(8):617-28.
van Puijenbroek EP, Bate A, Leufkens HG, Lindquist M, Orre R, Egberts AC. A comparison of measures of disproportionality for signal detection in spontaneous reporting systems for adverse drug reactions. Pharmacoepidemiol Drug Saf. 2002;11(1):3-10.
Tricco AC, Lillie E, Zarin W, O'Brien KK, Colquhoun H, Levac D, et al. PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Ann Intern Med. 2018;169(7):467-73.
Finney DJ. THE DESIGN AND LOGIC OF A MONITOR OF DRUG USE. J Chronic Dis. 1965;18:77-98.
Hauben M, Reich L. Communication of findings in pharmacovigilance: use of the term “signal” and the need for precision in its use. Eur J Clin Pharmacol. 2005;61(5):479-80.
Golder S, Loke YK. The performance of adverse effects search filters in MEDLINE and EMBASE. Health Info Libr J. 2012;29(2):141-51.
Golder S, McIntosh HM, Duffy S, Glanville J. Developing efficient search strategies to identify reports of adverse effects in MEDLINE and EMBASE. Health Info Libr J. 2006;23(1):3-12.
Tau N, Shochat T, Gafter-Gvili A, Tibau A, Amir E, Shepshelovich D. Association Between Data Sources and US Food and Drug Administration Drug Safety Communications. JAMA Intern Med. 2019.
United States Food and Drug Administration. Drug Safety Communications [Internet]. 2020. Accessed: 26/03/2020. Available: https://www.fda.gov/drugs/drug-safety-and-availability/drug-safety-communications.
U.S. Food and Drug Administration. Guidance Drug Safety Information – FDA’s Communication to the Public [Internet]. 2015. Accessed: 26 Mar 2020. Available: https://www.fda.gov/media/83097/download.
U.S. Food and Drug Administration. Potential Signals of Serious Risks/New Safety Information Identified from the FDA Adverse Event Reporting System (FAERS) [Internet]. 2020. Accessed: 26 Mar 2020. Available: https://www.fda.gov/drugs/questions-and-answers-fdas-adverse-event-reporting-system-faers/potential-signals-serious-risksnew-safety-information-identified-fda-adverse-event-reporting-system.
U.S. Food and Drug Administration. Guidance for Industry - Good Pharmacovigilance Practices and Pharmacoepidemiologic Assessment [Internet]. 2005. Accessed: 26 Mar 2020. Available: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/good-pharmacovigilance-practices-and-pharmacoepidemiologic-assessment.

Download PDF

Journal Publication

published 13 Aug, 2020

Read the published version in Systematic Reviews →

Editorial decision: Accept
23 Jul, 2020
Editor assigned by journal
20 Jul, 2020
Submission checks completed at journal
19 Jul, 2020
Editor invited by journal
19 Jul, 2020

You are reading this latest preprint version

Signals of adverse drug reactions communicated by pharmacovigilance stakeholders: protocol for a scoping review of the global literature

Status:

Journal Publication

Version 2

Abstract

Background

Methods/design

Discussion

Abbreviations

Declarations

References

Supplementary Files

Status:

Journal Publication

Version 2