The Reporting of a Disproportionality Analysis for Drug Safety Signal Detection Using Individual Case Safety Reports in PharmacoVigilance (READUS-PV): Development and Statement.

Journal

Drug safety

ISSN: 1179-1942

Titre abrégé: Drug Saf

Pays: New Zealand

ID NLM: 9002928

Informations de publication

Date de publication:
07 May 2024

Historique:

accepted: 07 03 2024

medline: 7 5 2024

pubmed: 7 5 2024

entrez: 7 5 2024

Statut: aheadofprint

Résumé

Disproportionality analyses using reports of suspected adverse drug reactions are the most commonly used quantitative methods for detecting safety signals in pharmacovigilance. However, their methods and results are generally poorly reported in published articles and existing guidelines do not capture the specific features of disproportionality analyses. We here describe the development of a guideline (REporting of A Disproportionality analysis for drUg Safety signal detection using individual case safety reports in PharmacoVigilance [READUS-PV]) for reporting the results of disproportionality analyses in articles and abstracts. We established a group of 34 international experts from universities, the pharmaceutical industry, and regulatory agencies, with expertise in pharmacovigilance, disproportionality analyses, and assessment of safety signals. We followed a three-step process to develop the checklist: (1) an open-text survey to generate a first list of items; (2) an online Delphi method to select and rephrase the most important items; (3) a final online consensus meeting. Among the panel members, 33 experts responded to round 1 and 30 to round 2 of the Delphi and 25 participated to the consensus meeting. Overall, 60 recommendations for the main body of the manuscript and 13 recommendations for the abstracts were retained by participants after the Delphi method. After merging of some items together and the online consensus meeting, the READUS-PV guidelines comprise a checklist of 32 recommendations, in 14 items, for the reporting of disproportionality analyses in the main body text and four items, comprising 12 recommendations, for abstracts. The READUS-PV guidelines will support authors, editors, peer-reviewers, and users of disproportionality analyses using individual case safety report databases. Adopting these guidelines will lead to more transparent, comprehensive, and accurate reporting and interpretation of disproportionality analyses, facilitating the integration with other sources of evidence.

Sections du résumé

BACKGROUND AND AIM OBJECTIVE

METHODS METHODS

We established a group of 34 international experts from universities, the pharmaceutical industry, and regulatory agencies, with expertise in pharmacovigilance, disproportionality analyses, and assessment of safety signals. We followed a three-step process to develop the checklist: (1) an open-text survey to generate a first list of items; (2) an online Delphi method to select and rephrase the most important items; (3) a final online consensus meeting.

RESULTS RESULTS

Among the panel members, 33 experts responded to round 1 and 30 to round 2 of the Delphi and 25 participated to the consensus meeting. Overall, 60 recommendations for the main body of the manuscript and 13 recommendations for the abstracts were retained by participants after the Delphi method. After merging of some items together and the online consensus meeting, the READUS-PV guidelines comprise a checklist of 32 recommendations, in 14 items, for the reporting of disproportionality analyses in the main body text and four items, comprising 12 recommendations, for abstracts.

CONCLUSIONS CONCLUSIONS

The READUS-PV guidelines will support authors, editors, peer-reviewers, and users of disproportionality analyses using individual case safety report databases. Adopting these guidelines will lead to more transparent, comprehensive, and accurate reporting and interpretation of disproportionality analyses, facilitating the integration with other sources of evidence.

Identifiants

DOI: 10.1007/s40264-024-01421-9 PMID: 38713346

pubmed: 38713346

doi: 10.1007/s40264-024-01421-9

pii: 10.1007/s40264-024-01421-9

doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

Informations de copyright

Références

CIOMS-Cumulative-PV-Glossary-v1.0.pdf [Internet]. [cited 2023 Jul 11]. Available from https://cioms.ch/wp-content/uploads/2021/03/CIOMS-Cumulative-PV-Glossary-v1.0.pdf . Accessed 6 Mar 2024.

Croteau D, Pinnow E, Wu E, Muñoz M, Bulatao I, Dal Pan G. Sources of evidence triggering and supporting safety-related labeling changes: a 10-year longitudinal assessment of 22 new molecular entities approved in 2008 by the US Food and Drug Administration. Drug Saf. 2022;45:169–80.

doi: 10.1007/s40264-021-01142-3 pubmed: 35113347

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;27:789–96.

doi: 10.1002/pds.4446 pubmed: 29797381 pmcid: 6055643

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;179:1590–2.

doi: 10.1001/jamainternmed.2019.3066 pubmed: 31479104

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 Med. 2016;14:1–11.

Pham M, Cheng F, Ramachandran K. A Comparison study of algorithms to detect drug-adverse event associations: frequentist, Bayesian, and machine-learning approaches. Drug Saf. 2019;42:743–50.

doi: 10.1007/s40264-018-00792-0 pubmed: 30762164

Faillie J-L. Case–non-case studies: principle, methods, bias and interpretation. Therapie. 2019;74:225–32.

doi: 10.1016/j.therap.2019.01.006 pubmed: 30773344

Raschi E, Moretti U, Salvo F, Pariente A, Antonazzo IC, Ponti FD, et al. Evolving roles of spontaneous reporting systems to assess and monitor drug safety. Pharmacovigilance [Internet]. 2018 [cited 2020 Dec 1]; Available from https://www.intechopen.com/books/pharmacovigilance/evolving-roles-of-spontaneous-reporting-systems-to-assess-and-monitor-drug-safety . Accessed 6 Mar 2024.

Hauben M, Aronson JK. Defining ‘signal’ and its subtypes in pharmacovigilance based on a systematic review of previous definitions. Drug Saf. 2009;32:99–110.

doi: 10.2165/00002018-200932020-00003 pubmed: 19236117

Khouri C, Fusaroli M, Salvo F, Raschi E. Interpretation of pharmacovigilance disproportionality analyses. Clin Pharmacol Ther. 2023;114:745–6.

doi: 10.1002/cpt.2951 pubmed: 37248829

Bate A, Evans SJW. Quantitative signal detection using spontaneous ADR reporting. Pharmacoepidemiol Drug Saf. 2009;18:427–36.

doi: 10.1002/pds.1742 pubmed: 19358225

Council for International Organizations of Medical Sciences, editor. Practical aspects of signal detection in pharmacovigilance: report of CIOMS Working Group VIII. Geneva: CIOMS; 2010.

Fusaroli M, Salvo F, Bernardeau C, Idris M, Dolladille C, Pariente A, et al. Mapping strategies to assess and increase the validity of published disproportionality signals: a meta-research study. Drug Saf. 2023;46:857–66. https://doi.org/10.1007/s40264-023-01329-w .

doi: 10.1007/s40264-023-01329-w pubmed: 37421568 pmcid: 10442263

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;11:1045–51.

doi: 10.1080/17512433.2018.1526676 pubmed: 30269618

Harpaz R, DuMouchel W, Shah NH, Madigan D, Ryan P, Friedman C. Novel data mining methodologies for adverse drug event discovery and analysis. Clin Pharmacol Ther. 2012;91:1010–21.

doi: 10.1038/clpt.2012.50 pubmed: 22549283

Dhodapkar MM, Shi X, Ramachandran R, Chen EM, Wallach JD, Ross JS. Characterization and corroboration of safety signals identified from the US Food and Drug Administration Adverse Event Reporting System, 2008–19: cross sectional study. BMJ. 2022;379: e071752.

doi: 10.1136/bmj-2022-071752 pubmed: 36198428 pmcid: 9533298

Khouri C, Revol B, Lepelley M, Mouffak A, Bernardeau C, Salvo F, et al. A meta-epidemiological study found lack of transparency and poor reporting of disproportionality analyses for signal detection in pharmacovigilance databases. J Clin Epidemiol. 2021;139:191–8.

doi: 10.1016/j.jclinepi.2021.07.014 pubmed: 34329725

Khouri C, Fusaroli M, Salvo F, Raschi E. Transparency and robustness of safety signals. BMJ. 2022;379: o2588.

doi: 10.1136/bmj.o2588 pubmed: 36328354

Mouffak A, Lepelley M, Revol B, Bernardeau C, Salvo F, Pariente A, et al. High prevalence of spin was found in pharmacovigilance studies using disproportionality analyses to detect safety signals: a meta-epidemiological study. J Clin Epidemiol. 2021;138:73–9.

doi: 10.1016/j.jclinepi.2021.06.022 pubmed: 34186195

Glasziou P, Altman DG, Bossuyt P, Boutron I, Clarke M, Julious S, et al. Reducing waste from incomplete or unusable reports of biomedical research. Lancet Lond Engl. 2014;383:267–76.

doi: 10.1016/S0140-6736(13)62228-X

Boutron I, Ravaud P. Misrepresentation and distortion of research in biomedical literature. Proc Natl Acad Sci. 2018;115:2613–9.

doi: 10.1073/pnas.1710755115 pubmed: 29531025 pmcid: 5856510

Chalmers I, Glasziou P. Avoidable waste in the production and reporting of research evidence. Lancet Lond Engl. 2009;374:86–9.

doi: 10.1016/S0140-6736(09)60329-9

Schulz KF, Altman DG, Moher D, CONSORT Group. CONSORT 2010 statement: updated guidelines for reporting parallel group randomized trials. Ann Intern Med. 2010;152:726–32.

doi: 10.7326/0003-4819-152-11-201006010-00232 pubmed: 20335313

Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372: n71.

doi: 10.1136/bmj.n71 pubmed: 33782057 pmcid: 8005924

Langan SM, Schmidt SA, Wing K, Ehrenstein V, Nicholls SG, Filion KB, et al. The reporting of studies conducted using observational routinely collected health data statement for pharmacoepidemiology (RECORD-PE). BMJ. 2018;363: k3532.

doi: 10.1136/bmj.k3532 pubmed: 30429167 pmcid: 6234471

von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP, et al. The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol. 2008;61:344–9.

doi: 10.1016/j.jclinepi.2007.11.008

European Medicines Agency. Good pharmacovigilance practices [Internet]. Eur. Med. Agency. 2018 [cited 2021 Dec 6]. Available from https://www.ema.europa.eu/en/human-regulatory/post-authorisation/pharmacovigilance/good-pharmacovigilance-practices . Accessed 6 Mar 2024.

Wisniewski AFZ, Bate A, Bousquet C, Brueckner A, Candore G, Juhlin K, et al. Good signal detection practices: evidence from IMI PROTECT. Drug Saf. 2016;39:469–90.

doi: 10.1007/s40264-016-0405-1 pubmed: 26951233 pmcid: 4871909

Best Practices in Drug and Biological Product Postmarket Safety Surveillance for FDA Staff. Available from https://www.fda.gov/media/130216/download?attachment . Accessed 6 Mar 2024.

Fusaroli M, Salvo F, Begaud B, AlShammari TM, Bate A, Battini V, et al. The reporting of a disproportionality analysis for drug Safety signal detection using individual case safety reports in pharmacovigilance (READUS-PV): explanation and elaboration. Drug Saf. https://doi.org/10.1007/s40264-024-01423-7 .

Bégaud B, Judith KJ. Assessing causality from case reports. In: Strom BL, Kimmel SE, Hennessy S, editors. Textbook of pharmacoepidemiology. 3rd ed. New York: Wiley; 2021. p. 246–56.

doi: 10.1002/9781119701101.ch14

Moher D, Schulz KF, Simera I, Altman DG. Guidance for developers of health research reporting guidelines. PLOS Med. 2010;7:e1000217.

doi: 10.1371/journal.pmed.1000217 pubmed: 20169112 pmcid: 2821895

Nicholls SG, Langan SM, Benchimol EI, Moher D. Reporting transparency: making the ethical mandate explicit. BMC Med. 2016;14:44.

doi: 10.1186/s12916-016-0587-5 pubmed: 26979591 pmcid: 4793699

ICMJE | Recommendations | Browse [Internet]. [cited 2023 Jul 19]. Available from https://www.icmje.org/recommendations/browse/ . Accessed 6 Mar 2024.

Turner L, Shamseer L, Altman DG, Schulz KF, Moher D. Does use of the CONSORT Statement impact the completeness of reporting of randomised controlled trials published in medical journals? A Cochrane review. Syst Rev. 2012;1:60.

doi: 10.1186/2046-4053-1-60 pubmed: 23194585 pmcid: 3564748

Plint AC, Moher D, Morrison A, Schulz K, Altman DG, Hill C, et al. Does the CONSORT checklist improve the quality of reports of randomised controlled trials? A systematic review. Med J Aust. 2006;185:263–7.

doi: 10.5694/j.1326-5377.2006.tb00557.x pubmed: 16948622

Stevens A, Shamseer L, Weinstein E, Yazdi F, Turner L, Thielman J, et al. Relation of completeness of reporting of health research to journals’ endorsement of reporting guidelines: systematic review. BMJ. 2014;348: g3804.

doi: 10.1136/bmj.g3804 pubmed: 24965222 pmcid: 4070413

Blanco D, Altman D, Moher D, Boutron I, Kirkham JJ, Cobo E. Scoping review on interventions to improve adherence to reporting guidelines in health research. BMJ Open. 2019;9:e026589.

doi: 10.1136/bmjopen-2018-026589 pubmed: 31076472 pmcid: 6527996

van Eekeren R, Rolfes L, Koster AS, Magro L, Parthasarathi G, Al Ramimmy H, et al. What future healthcare professionals need to know about pharmacovigilance: introduction of the WHO PV core curriculum for university teaching with focus on clinical aspects. Drug Saf. 2018;41:1003–11.

doi: 10.1007/s40264-018-0681-z pubmed: 29949100 pmcid: 6182454

Pandis N, Shamseer L, Kokich VG, Fleming PS, Moher D. Active implementation strategy of CONSORT adherence by a dental specialty journal improved randomized clinical trial reporting. J Clin Epidemiol. 2014;67:1044–8.

doi: 10.1016/j.jclinepi.2014.04.001 pubmed: 24837296

Heus P, Damen JAAG, Pajouheshnia R, Scholten RJPM, Reitsma JB, Collins GS, et al. Uniformity in measuring adherence to reporting guidelines: the example of TRIPOD for assessing completeness of reporting of prediction model studies. BMJ Open. 2019;9: e025611.

doi: 10.1136/bmjopen-2018-025611 pubmed: 31023756 pmcid: 6501951

Dal Santo T, Rice DB, Amiri LSN, Tasleem A, Li K, Boruff JT, et al. Methods and results of studies on reporting guideline adherence are poorly reported: a meta-research study. J Clin Epidemiol. 2023;159:225–34.

doi: 10.1016/j.jclinepi.2023.05.017