Novel Adverse Events of Iloperidone: A Disproportionality Analysis in US Food and Drug Administration Adverse Event Reporting System (FAERS) Database

Author(s): Viswam Subeesh*, Eswaran Maheswari, Hemendra Singh, Thomas Elsa Beulah, Ann Mary Swaroop.

Journal Name: Current Drug Safety

Volume 14 , Issue 1 , 2019

Become EABM
Become Reviewer

Graphical Abstract:


Abstract:

Background: The signal is defined as “reported information on a possible causal relationship between an adverse event and a drug, of which the relationship is unknown or incompletely documented previously”.

Objective: To detect novel adverse events of iloperidone by disproportionality analysis in FDA database of Adverse Event Reporting System (FAERS) using Data Mining Algorithms (DMAs).

Methodology: The US FAERS database consists of 1028 iloperidone associated Drug Event Combinations (DECs) which were reported from 2010 Q1 to 2016 Q3. We consider DECs for disproportionality analysis only if a minimum of ten reports are present in database for the given adverse event and which were not detected earlier (in clinical trials). Two data mining algorithms, namely, Reporting Odds Ratio (ROR) and Information Component (IC) were applied retrospectively in the aforementioned time period. A value of ROR-1.96SE>1 and IC- 2SD>0 were considered as the threshold for positive signal.

Results: The mean age of the patients of iloperidone associated events was found to be 44years [95% CI: 36-51], nevertheless age was not mentioned in twenty-one reports. The data mining algorithms exhibited positive signal for akathisia (ROR-1.96SE=43.15, IC-2SD=2.99), dyskinesia (21.24, 3.06), peripheral oedema (6.67,1.08), priapism (425.7,9.09) and sexual dysfunction (26.6-1.5) upon analysis as those were well above the pre-set threshold.

Conclusion: Iloperidone associated five potential signals were generated by data mining in the FDA AERS database. The result requires an integration of further clinical surveillance for the quantification and validation of possible risks for the adverse events reported of iloperidone.

Keywords: Pharmacovigilance, disproportionality analysis, reporting odds ratio, iloperidone, drug safety, FAERS.

[1]
Solanki RK, Singh P, Midha A, Chugh K. Schizophrenia: Impact on quality of life. ‎. Indian J Psychiatry 2008; 50(3): 181-6.
[2]
Vigo D, Thornicroft G, Atun R. Estimating the true global burden of mental illness. Lancet Psychiatry 2016; 3(2): 171-8.
[3]
Thara R. Schizophrenia - Enhancing hope with better care & research. Indian J Med Res 2014; 140(4): 469-71.
[4]
Caccia S, Pasina L, Nobili A. New atypical antipsychotics for schizophrenia: Iloperidone. Drug Des Devel Ther 2010; 4: 33-48.
[5]
Tonin FS, Wiens A, Fernandez-Llimos F, Pontarolo R. Iloperidone in the treatment of schizophrenia: An evidence-based review of its place in therapy. Core Evid 2016; 11: 49-61.
[6]
Lahon K, Shetty HM, Paramel A, Sharma G. A retrospective study of extrapyramidal syndromes with second generation antipsychotics in the psychiatric unit of a tertiary care teaching hospital. J Pharmacol Pharmacother 2012; 3(3): 266-8.
[7]
Luft B, Taylor D. A review of atypical antipsychotic drugs versus conventional medication in schizophrenia. Expert Opin Pharmacother 2006; 7(13): 1739-48.
[8]
Chadda RK, Ramshankar P, Deb KS, Sood M. Metabolic syndrome in schizophrenia: Differences between antipsychotic-naïve and treated patients. J Pharmacol Pharmacother 2013; 4(3): 176-86.
[9]
Montes AB, Rey JA. Iloperidone (Fanapt): An FDA-approved treatment option for schizophrenia. P&T 2009; 34(11): 606-13.
[10]
WHO. Safety of Medicines - A Guide to Detecting and Reporting Adverse Drug Reactions - Why Health Professionals Need to Take Action 2002. Available from: http://apps.who.int/medicinedocs/en/ d/Jh2992e/
[11]
Wilson AM, Thabane L, Holbrook A. Application of data mining techniques in pharmacovigilance. Br J Clin Pharmacol 2004; 57(2): 127-34.
[12]
Poluzzi E, Raschi E, Piccinni C, De Ponti F. Data mining techniques in pharmacovigilance: Analysis of the publicly accessible FDA adverse event reporting system (AERS). Data mining applications in engineering and medicine: InTech; 2012.
[13]
Sakaeda T, Tamon A, Kadoyama K, Okuno Y. Data mining of the public version of the FDA Adverse Event Reporting System. ‎. Int J Med Sci 2013; 10(7): 796-803.
[14]
Bate A, Lindquist M, Edwards IR, Orre R. A data mining approach for signal detection and analysis. Drug Saf 2002; 25(6): 393-7.
[15]
Crabtree BL, Montgomery J. Iloperidone for the management of adults with schizophrenia. Clin Ther 2011; 33(3): 330-45.
[16]
Sears E, Brooks S. New drugs approved in 2009. Proceedings (Baylor University Medical Center) 2010; 23(2): 175-83.
[17]
Scarff JR, Casey DA. Newer oral atypical antipsychotic agents: A review. P&T 2011; 36(12): 832-8.
[18]
Citrome L. Iloperidone: Chemistry, pharmacodynamics, pharmacokinetics and metabolism, clinical efficacy, safety and tolerability, regulatory affairs, and an opinion. Expert Opin Drug Metab Toxicol 2010; 6(12): 1551-64.
[19]
Kumar R, Sachdev PS. Akathisia and second-generation antipsychotic drugs. Curr Opin Psychiatry 2009; 22(3): 293-9.
[20]
Abbott C, Jaramillo A, Wilcox C, Hamilton D. Antipsychotic drug effects in schizophrenia: A review of longitudinal fmri investigations and neural interpretations. Curr Med Chem 2013; 20(3): 428-37.
[21]
Zeng C, Zhang M, Asico LD, Eisner GM, Jose PA. The dopaminergic system in hypertension. Clin Sci 2007; 112(12): 583-97.
[22]
Ng B, Postlethwaite A, Rollnik J. Peripheral oedema in patients taking olanzapine. ‎. Int Clin Psychopharmacol 2003; 18(1): 57-9.
[23]
Umar MU, Abdullahi AT. Self-limiting atypical antipsychotics-induced edema: Clinical cases and systematic review. ‎. Indian J Psychol Med 2016; 38(3): 182-8.
[24]
Rodriguez-Cabezas LA, Kong BY, Agarwal G. Priapism associated with iloperidone: A case report. Gen Hosp Psychiatry 2014; 36(4): 451.e5-6.
[25]
Hosseini SH, Polonowita AK. Priapism associated with olanzapine. PJBS 2009; 12(2): 198-200.
[26]
Park YW, Kim Y, Lee JH. Antipsychotic-induced sexual dysfunction and its management. World J Mens Health 2012; 30(3): 153-9.
[27]
Bégaud BB. Dictionary of pharmacoepidemiology. John Wiley & Sons, Ltd 2002; pp. 15-22.
[28]
Pariente A, Gregoire F, Fourrier-Reglat A, Haramburu F, Moore N. Impact of safety alerts on measures of disproportionality in spontaneous reporting databases: The notoriety bias. Drug Saf 2007; 30(10): 891-8.
[29]
Weber JCP. Epidemiology of adverse reactions to nonsteroidal anti-inflammatory drugs. In: Rainsford KD, Velo GD, Eds. Side-effects of anti-inflammatory drugs, advances in inflammation research. Raven Press: New York 1984; pp. 1-7.
[30]
Weber JCP. Epidemiology in the United Kingdom of adverse drug reactions from non-steroidal anti-inflammatory drugs. In: Rainsford KD, Velo GP, Eds. Side-Effects of anti-inflammatory drugs: Part one clinical and epidemiological aspects. Dordrecht: Springer Netherlands 1987; pp. 27-35.


Rights & PermissionsPrintExport Cite as

Article Details

VOLUME: 14
ISSUE: 1
Year: 2019
Page: [21 - 26]
Pages: 6
DOI: 10.2174/1574886313666181026100000
Price: $58

Article Metrics

PDF: 45
HTML: 4
EPUB: 1
PRC: 1