Literature DB >> 20486730

Validation of statistical signal detection procedures in eudravigilance post-authorization data: a retrospective evaluation of the potential for earlier signalling.

Yolanda Alvarez1, Ana Hidalgo, Francois Maignen, Jim Slattery.   

Abstract

BACKGROUND: Screening large databases of spontaneous case reports of possible adverse drug reactions (ADRs) is an established method of identifying hitherto unknown adverse effects of medicinal products; however, there is a lack of consensus concerning the value of formal statistical screening procedures in guiding such a process. This study was performed to clarify the nature of any added benefits and additional effort required when established pharmacovigilance techniques are supplemented with statistical screening.
OBJECTIVE: To evaluate whether statistical signal detection in spontaneous reporting data can lead to earlier detection of drug safety problems and to assess the additional regulatory work entailed.
METHODS: Using the EudraVigilance post-authorization module (EVPM), a screening procedure based on the proportional reporting ratio (PRR) was applied retrospectively to examine if regulatory investigations concerning ADRs in a predefined set of products could have been initiated earlier than occurred in practice. During the same time period, between September 2003 and March 2007, the number of PRR-based signals of disproportionate reporting (SDR) that arose in the same set of products was calculated and evaluated to determine the number requiring investigation. The outcome is expressed as the ratio of the number of SDRs requiring investigation compared with the number of signals pre-empted by the statistical screening approach. In those cases where the signal was discovered earlier, the delay was calculated between identification by the PRR method and by the method that originally identified the signal.
RESULTS: In 191 chemically different products, 532 adverse reactions were added to the summary of product characteristics during the study period. Of these, 405 were designated as important medical events (IMEs) based on a comprehensive predefined list. Of the IMEs, 217 (53.6%) were identified earlier by the statistical screening technique, 79 (19.6%) were detected after the date at which they were raised by standard pharmacovigilance methods and 109 (26.9%) were not signalled during the study period. 1561 SDRs requiring further evaluation were detected during the study period, giving a ratio of 7.2 assessments for each signal pre-empted. The mean delay between the discovery of signals using the statistical methods in the EVPM and established methods in the 217 cases detected earlier was 2.45 years. A review resulted in clear explanation for why the statistical method had not pre-empted detection in all but 77 of 188 cases.
CONCLUSIONS: The form of statistical signal detection tested in this study can provide significant early warning in a large proportion of drug safety problems; however, it cannot detect all safety issues more quickly than other pharmacovigilance processes and hence it should be used in addition to, rather than as an alternative to, established methods.

Mesh:

Year:  2010        PMID: 20486730     DOI: 10.2165/11534410-000000000-00000

Source DB:  PubMed          Journal:  Drug Saf        ISSN: 0114-5916            Impact factor:   5.606


  3 in total

1.  Use of proportional reporting ratios (PRRs) for signal generation from spontaneous adverse drug reaction reports.

Authors:  S J Evans; P C Waller; S Davis
Journal:  Pharmacoepidemiol Drug Saf       Date:  2001 Oct-Nov       Impact factor: 2.890

2.  A comparison of measures of disproportionality for signal detection in spontaneous reporting systems for adverse drug reactions.

Authors:  Eugène P van Puijenbroek; Andrew Bate; Hubert G M Leufkens; Marie Lindquist; Roland Orre; Antoine C G Egberts
Journal:  Pharmacoepidemiol Drug Saf       Date:  2002 Jan-Feb       Impact factor: 2.890

Review 3.  Perspectives on the use of data mining in pharmaco-vigilance.

Authors:  June Almenoff; Joseph M Tonning; A Lawrence Gould; Ana Szarfman; Manfred Hauben; Rita Ouellet-Hellstrom; Robert Ball; Ken Hornbuckle; Louisa Walsh; Chuen Yee; Susan T Sacks; Nancy Yuen; Vaishali Patadia; Michael Blum; Mike Johnston; Charles Gerrits; Harry Seifert; Karol Lacroix
Journal:  Drug Saf       Date:  2005       Impact factor: 5.606

  3 in total
  39 in total

1.  Implementation of an automated signal detection method in the French pharmacovigilance database: a feasibility study.

Authors:  Véronique Pizzoglio; Ismaïl Ahmed; Pascal Auriche; Pascale Tuber-Bitter; Françoise Haramburu; Carmen Kreft-Jaïs; Ghada Miremont-Salamé
Journal:  Eur J Clin Pharmacol       Date:  2011-12-06       Impact factor: 2.953

2.  A cohort study exploring determinants of safety-related regulatory actions for biopharmaceuticals.

Authors:  Hans C Ebbers; Aukje K Mantel-Teeuwisse; Ellen H M Moors; Fakhredin A Sayed Tabatabaei; Huub Schellekens; Hubert G M Leufkens
Journal:  Drug Saf       Date:  2012-05-01       Impact factor: 5.606

3.  Unleashing the mini-sentinel.

Authors:  Asher Mullard
Journal:  Nat Rev Drug Discov       Date:  2012-03-30       Impact factor: 84.694

4.  A decade of data mining and still counting.

Authors:  Manfred Hauben; G Niklas Norén
Journal:  Drug Saf       Date:  2010-07-01       Impact factor: 5.606

5.  Performance of Stratified and Subgrouped Disproportionality Analyses in Spontaneous Databases.

Authors:  Suzie Seabroke; Gianmario Candore; Kristina Juhlin; Naashika Quarcoo; Antoni Wisniewski; Ramin Arani; Jeffery Painter; Philip Tregunno; G Niklas Norén; Jim Slattery
Journal:  Drug Saf       Date:  2016-04       Impact factor: 5.606

6.  Early detection of pharmacovigilance signals with automated methods based on false discovery rates: a comparative study.

Authors:  Ismaïl Ahmed; Frantz Thiessard; Ghada Miremont-Salamé; Françoise Haramburu; Carmen Kreft-Jais; Bernard Bégaud; Pascale Tubert-Bitter
Journal:  Drug Saf       Date:  2012-06-01       Impact factor: 5.606

7.  Choosing thresholds for statistical signal detection with the proportional reporting ratio.

Authors:  Jim Slattery; Yolanda Alvarez; Ana Hidalgo
Journal:  Drug Saf       Date:  2013-08       Impact factor: 5.606

8.  Ongoing challenges in pharmacovigilance.

Authors:  Gerald J Dal Pan
Journal:  Drug Saf       Date:  2014-01       Impact factor: 5.606

9.  EUROmediCAT signal detection: a systematic method for identifying potential teratogenic medication.

Authors:  Johannes M Luteijn; Joan K Morris; Ester Garne; Joanne Given; Lolkje de Jong-van den Berg; Marie-Claude Addor; Marian Bakker; Ingeborg Barisic; Miriam Gatt; Kari Klungsoyr; Anna Latos-Bielenska; Nathalie Lelong; Vera Nelen; Amanda Neville; Mary O'Mahony; Anna Pierini; David Tucker; Hermien de Walle; Awi Wiesel; Maria Loane; Helen Dolk
Journal:  Br J Clin Pharmacol       Date:  2016-08-04       Impact factor: 4.335

10.  Comparison of statistical signal detection methods within and across spontaneous reporting databases.

Authors:  Gianmario Candore; Kristina Juhlin; Katrin Manlik; Bharat Thakrar; Naashika Quarcoo; Suzie Seabroke; Antoni Wisniewski; Jim Slattery
Journal:  Drug Saf       Date:  2015-06       Impact factor: 5.606

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.