• PDF / 13,191,142 Bytes
• 11 Pages / 612 x 792 pts (letter) Page_size
• 84 Downloads / 174 Views

DOWNLOAD

REPORT

Woronee Buncbuoiluo, BPbarm, PhD candidate Department of Community Pharmacy, Faculty of Pharmacy, Silpakorn University. Nakhon Pathom. Thailand; Department of Tropical Hygiene, Faculty of Tropical Medicine. Mahidol University, Bangkok. Thailand Ilene H. Zrckermon, PhornD, PhD Department of Pharmaceutical Health Services Research, University of Maryland School of Pharmacy. Baltimore. Maryland Vitboyo Kulsomboon, PhD Department of Social and Administrative Pharmacy, Faculty of Pharmaceutical Sciences. Chulalongkorn University. Bangkok. Thailand Wimon Suwonkesowong, BSc (Pbarm), MA Health Products Vigilance Center, Thai Food and Drug Administration, Nonthaburi, Thailand Protop Singhasironon, MBBS, DTMLH (Bangkok), DrPH (Epidemiology), MPH Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University. Bangkok, Thailand Joranit Koewkmgwol, PhD Department of Tropical Hygiene. Faculty of Tropical Medicine. Mahidol University. Bangkok. Thailand Key Words Adverse drug reaction; Spontaneous reporting; Signal detection; ROR; BCPNN Correspondence Address Waranee Bunchuailua, Department of Community Pharmacy, Faculty of Pharmacy, Silpakorn University. Sanamchantra Palace Campus, Muang, Nakhon Pathom 73000 (email: [email protected]).

393

Detection of Adverse Drug Reaction Signals in the Thai FDA Database: Comparison Between Reporting Odds Ratio and Bayesian Confidence Propagation Neural Network Methods The study aimed to compare performance between the reporting odds ratio (ROR) and the Bayesian confidence propagation neural network (BCPNN)methods in identifiing serious adverse drug reactions (ADRs) using the Thai FDA spontaneous database. The two methods were retrospectively applied to identifi new, serious ADRs reported with antiretroviral therapy (ART) drugs using the data set between 1990 and 2006.We plotted the ROR and the information component against time to compare the differential timing of signal detection

INTRODUCTION Advances in antiretroviral therapy (ART), especially the use of highly active antiretroviral therapy (HAART), have resulted in significant reductions in morbidity and mortality associated with HIV infection (1-3). As a combination regimen of three different classes of drugs (nucleoside analog reverse transcriptase inhibitors, NRTls; nonnucleoside reverse transcriptase inhibitors, NNRTIs; and protease inhibitors), HAART has the ability to effectively suppress HIV-1 viral replication (4,5).However, the treatment is associated with a number of adverse effects that have short-term and long-term consequences ranging from mild to severe (6). Adverse reactions were reported in up to 50% of patients treated with ART, including gastrointestinal, metabolic, neurologic, and dermatologic effects (7). Moreover, some adverse effects may result in increased morbidity and represent additional risk factors for future complications that require treatment interruptions along with therapeutic drug monitoring for management (8). Studies have indicated that adverse effects of ART are a major cause of trea

Recommend Documents

Adverse drug reaction reporting in Canada: consumer versus physician reports

186 6 735KB

Combining Social Media and FDA Adverse Event Reporting System to Detect Adverse Drug Reactions

174 10 1016KB

Reporting of Drug Benefit in FDA-Approved Prescription Drug Labeling

185 55 168KB

Improving the Reporting of Adverse Drug Reactions

178 20 124KB

Adverse Drug Reaction Update

191 27 132KB

Adverse Drug Reaction Update

169 39 109KB

Adverse Drug Reaction

167 32 35MB

Odds Ratio

153 80 35MB

Odds Ratio

169 13 37KB

Adverse Drug Reaction Risk Measures: A Comparison of Estimates from Drug Surveillance and Randomised Trials

155 9 832KB

Animal Experiments and Adverse Drug Reaction Reports

163 66 3MB

Correction to: Adverse drug reaction reporting in Canada: consumer versus physician reports

157 117 356KB