Drug-versus-Drug Adverse Event Rate Comparisons A Pilot Study Based on Data from the US FDA Adverse Event Reporting System

被引:17
|
作者
Hochberg, Alan M. [1 ]
Pearson, Ronald. K. [1 ]
O'Hara, Donald J. [1 ]
Reisinger, Stephanie J. [1 ]
机构
[1] ProSanos Corp, Harrisburg, PA 17101 USA
关键词
NONSTEROIDAL ANTIINFLAMMATORY DRUGS; GATIFLOXACIN; TOXICITY; SAFETY;
D O I
10.2165/00002018-200932020-00006
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background: A number of published Studies compare adverse event rates for drugs on the basis of reports in the US FDA Adverse Event Reporting System (AERS). While the AERS data have the advantage of timely availability and a large capture population, the database is subject to many significant biases, and lacks complete patient information that Would allow for correction of those biases. The accuracy of comparative AERS-based data mining has been questioned, but has not been systematically studied. Objective: To determine whether AERS could be used as a data source to accurately compare the adverse event rates for pairs of drugs, using predefined, stringent criteria to dictate whether a given pair of drugs was considered eligible for such a comparison. Methods: The Fisher's Exact test was utilized to detect differences in adverse event rates between such pairs of drugs. Concordance was determined between statistically significant AERS-based adverse event rate differences, and adverse event rate differences published in the literature from clinical trials and case-control studies. The conditions for validity included (i) data that are free of 'extreme duplication' in AERS reports; (ii) drugs used in similar patient populations; (iii) drugs used for similar indications; (iv) drugs used with the same spectrum of concomitant medications; and (v) drugs not widely disparate in time on the market. Results: For 19 drugs studied, a total of 36 evaluable adverse event rate comparisons were identified. Comparisons were classified as favouring' drug A', favouring 'drug B' or detecting no difference. Concordance for the resulting 3 x 3 table (AERS vs literature) gave a kappa statistic of 0.654, indicating moderately good agreement. In only two cases was there absolute discordance, with AERS designating one drug as having a lower rate, while the published study designated the other drug as having a lower rate, with respect to a given adverse event. Conclusions: This pilot study encourages further research regarding the use of spontaneous report databases such as AERS, under stringently defined conditions, to compare adverse event rates for drugs. While not hypothesis proving, such estimates can be used for purposes such as generating hypotheses for controlled studies, and for designing those studies.
引用
收藏
页码:137 / 146
页数:10
相关论文
共 50 条
  • [1] Drug-versus-Drug Adverse Event Rate ComparisonsA Pilot Study Based on Data from the US FDA Adverse Event Reporting System
    Alan M. Hochberg
    Ronald K. Pearson
    Donald J. O’Hara
    Stephanie J. Reisinger
    [J]. Drug Safety, 2009, 32 : 137 - 146
  • [2] Comparisons of adverse event reporting for colistin versus polymyxin B using the US Food and Drug Administration Adverse Event Reporting System (FAERS)
    Cong Bang Truong
    Durham, Spencer H.
    Qian, Jingjing
    [J]. EXPERT OPINION ON DRUG SAFETY, 2021, 20 (05) : 603 - 609
  • [3] Comparisons of data mining algorithms for adverse drug reactions: An empirical study based on the adverse event reporting system of the food and drug administration
    Chen, Y.
    Guo, J. J.
    Patel, N. C.
    Steinbuch, M.
    Lin, X. D.
    Buncher, C.
    [J]. VALUE IN HEALTH, 2008, 11 (03) : A174 - A174
  • [4] Comparison of brand versus generic antiepileptic drug adverse event reporting rates in the US Food and Drug Administration Adverse Event Reporting System (FAERS)
    Rahman, Md. Motiur
    Alatawi, Yasser
    Cheng, Ning
    Qian, Jingjing
    Plotkina, Annya V.
    Peissig, Peggy L.
    Berg, Richard L.
    Page, David
    Hansen, Richard A.
    [J]. EPILEPSY RESEARCH, 2017, 135 : 71 - 78
  • [5] Multiple sclerosis as an adverse drug reaction: clues from the FDA Adverse Event Reporting System
    Antonazzo, Ippazio Cosimo
    Raschi, Emanuel
    Forcesi, Emanuele
    Riise, Trond
    Bjornevik, Kjetil
    Baldin, Elisa
    De Ponti, Fabrizio
    Poluzzi, Elisabetta
    [J]. EXPERT OPINION ON DRUG SAFETY, 2018, 17 (09) : 869 - 874
  • [6] Adverse drug reactions in neonates: a brief analysis of the FDA adverse event reporting system
    Byskov, Pernille Kahler
    Baden, Christoffer Storm
    Andersen, Jon Traerup
    Jimenez-Solem, Espen
    Olsen, Ramus Huan
    Gade, Christina
    Lausten-Thomsen, Ulrik
    [J]. FRONTIERS IN PHARMACOLOGY, 2024, 15
  • [7] Adverse Drug Event Reporting
    Vaughan, William
    [J]. HEALTH AFFAIRS, 2012, 31 (08) : 1911 - 1911
  • [8] Standardizing Drug Adverse Event Reporting Data
    Wang, Liwei
    Jiang, Guoqian
    Li, Dingcheng
    Liu, Hongfang
    [J]. MEDINFO 2013: PROCEEDINGS OF THE 14TH WORLD CONGRESS ON MEDICAL AND HEALTH INFORMATICS, PTS 1 AND 2, 2013, 192 : 1101 - 1101
  • [9] Standardizing adverse drug event reporting data
    Liwei Wang
    Guoqian Jiang
    Dingcheng Li
    Hongfang Liu
    [J]. Journal of Biomedical Semantics, 5
  • [10] Standardizing adverse drug event reporting data
    Wang, Liwei
    Jiang, Guoqian
    Li, Dingcheng
    Liu, Hongfang
    [J]. JOURNAL OF BIOMEDICAL SEMANTICS, 2014, 5