Literature DB >> 34170370

Research on Beers Criteria and STOPP/START Criteria based on the FDA FAERS database.

Qianqian Shao1, Yulong Xu1, Meng Li1, Xishi Chu1, Wei Liu2.   

Abstract

PURPOSE: Inappropriate medication criteria for the elderly have played an important role in ensuring the safety of medications for the elderly. Too few drugs included in the criteria cannot guarantee the safety of medication for the elderly. Too many drugs included in the criteria will result in less selective medication for the elderly. This paper uses real-world data to evaluate the relationship between antihypertensive drugs and falls, so as to provide references for experts and scholars to revise the criteria of potentially inappropriate medications for the elderly and clinical safe medication.
METHOD: We use the US Food and Drug Administration Adverse Event Reporting System (FDA FAERS) to evaluate the association between specific antihypertensive drugs in six categories (alpha-1 receptor blockers (α-1 blockers), calcium channel blockers (CCBs), angiotensin-converting enzyme inhibitors (ACEIs), angiotensin II receptor blockers (ARBs), beta-receptor blockers (β-blockers), and diuretics) and falls by data mining algorithms, including the reporting odds ratio (ROR), the proportional reporting ratio (PRR), Medicines and Healthcare Products Regulatory Agency (MHRA), and the empirical Bayes geometric mean (EBGM) and compared with the relevant drugs included in the Beers Criteria and STOPP/START Criteria. RESULT: There are a total of 5,157,172 co-occurrences found in 973,447 reports aged 65 years or older from 2016 to 2019 in the FDA FAERS database, and the number of co-occurrences of falls is 5917 for the six categories of 51 antihypertensive drugs. Four kinds of mining methods overlap detection of 12 kinds of positive signal drugs, none of which are not included in the Beers Criteria and 7 drugs are included in the STOPP/START Criteria; 1-3 kinds of mining methods overlap detection of positive signal drugs, a total of 12 kinds, and one drug is included in the Beers Criteria and 5 drugs are included in the STOPP/START Criteria; 22 drugs have fall adverse events, but no positive signal is detected, and 13 drugs are included in STOPP/START Criteria; and 5 drugs have no fall adverse events and 3 drugs are included in the STOPP/START Criteria.
CONCLUSION: The FAERS database was used to confirm the potential connection between some antihypertensive drugs and fall adverse events through data mining algorithms. The Beers Criteria did not clearly indicate the antihypertensive drugs that caused falls, and the antihypertensive drugs included in the STOPP/START Criteria were too extensive and did not include β-blockers and diuretics. It is recommended that experts and scholars use real-world data (such as FAERS, EudraVigilance, WHO VigiBase, and so on) to further explore the relationship between specific antihypertensive drugs and falls in the elderly, so as to revise and improve the criteria for inappropriate medications for the elderly.
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Entities:  

Keywords:  Antihypertensive drugs; Beers Criteria; FAERS; Fall; STOPP/START Criteria

Mesh:

Substances:

Year:  2021        PMID: 34170370     DOI: 10.1007/s00228-021-03175-0

Source DB:  PubMed          Journal:  Eur J Clin Pharmacol        ISSN: 0031-6970            Impact factor:   2.953


  28 in total

1.  Risk of falls associated with antihypertensive medication: self-controlled case series.

Authors:  Jonathan Gribbin; Richard Hubbard; John Gladman; Chris Smith; Sarah Lewis
Journal:  Pharmacoepidemiol Drug Saf       Date:  2011-07-11       Impact factor: 2.890

2.  Antihypertensive medications and serious fall injuries in a nationally representative sample of older adults.

Authors:  Mary E Tinetti; Ling Han; David S H Lee; Gail J McAvay; Peter Peduzzi; Cary P Gross; Bingqing Zhou; Haiqun Lin
Journal:  JAMA Intern Med       Date:  2014-04       Impact factor: 21.873

3.  Essential medicines for universal health coverage.

Authors:  Tetsuya Tanimoto; Kenji Tsuda; Tomohiro Kurokawa; Jinichi Mori; Hiroaki Shimmura
Journal:  Lancet       Date:  2017-05-11       Impact factor: 79.321

4.  Medication use and fall-risk assessment for falls in an acute care hospital.

Authors:  Ming-Huang Chiu; Hsin-Dai Lee; Hei-Fen Hwang; Shih-Chieh Wang; Mau-Roung Lin
Journal:  Geriatr Gerontol Int       Date:  2014-09-26       Impact factor: 2.730

5.  Prevalence of potentially inappropriate medication use in elderly patients: comparison between general medical and geriatric wards.

Authors:  Sabin S Egger; Andrea Bachmann; Nathalie Hubmann; Raymond G Schlienger; Stephan Krähenbühl
Journal:  Drugs Aging       Date:  2006       Impact factor: 3.923

6.  Fall-risk-increasing adverse reactions-is there value in easily accessible drug information? A case-control study.

Authors:  Susanne Schiek; Katja Hildebrandt; Olaf Zube; Thilo Bertsche
Journal:  Eur J Clin Pharmacol       Date:  2019-02-13       Impact factor: 2.953

7.  Greater daily defined dose of antihypertensive medication increases the risk of falls in older people--a population-based study.

Authors:  Michele L Callisaya; James E Sharman; Jacqueline Close; Stephen R Lord; Velandai K Srikanth
Journal:  J Am Geriatr Soc       Date:  2014-06-16       Impact factor: 5.562

8.  Diuretic initiation and the acute risk of hip fracture.

Authors:  S D Berry; Y Zhu; H Choi; D P Kiel; Y Zhang
Journal:  Osteoporos Int       Date:  2012-07-13       Impact factor: 4.507

Review 9.  Data mining of the public version of the FDA Adverse Event Reporting System.

Authors:  Toshiyuki Sakaeda; Akiko Tamon; Kaori Kadoyama; Yasushi Okuno
Journal:  Int J Med Sci       Date:  2013-04-25       Impact factor: 3.738

10.  Investigating Overlap in Signals from EVDAS, FAERS, and VigiBase®.

Authors:  Ulrich Vogel; John van Stekelenborg; Brian Dreyfus; Anju Garg; Marian Habib; Romana Hosain; Antoni Wisniewski
Journal:  Drug Saf       Date:  2020-04       Impact factor: 5.606

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