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Abstract

This paper focuses on the development of a lag adjusted statistical model used in the testing procedure for detecting changes in the frequency of adverse drug event rates. The impact of a significant lag time between adverse drug event occurrence and report dates is studied. The approach in this paper to analyzing adverse drug event data of this nature is to propose a statistical model that uses a lag density function. Actual adverse drug event data for the prescription medication Seldane, along with simulated data, are used to test and compare the lag adjusted procedure to an existing procedure. Methods to adjust for a lag effect are reviewed and analyzed. Questions concerning the analysis and interpretation of adverse drug event data in light of the presence of a lag effect are posed.

Keywords

Adverse drug reaction Postmarketing surveillance Change in frequency Lag adjusted procedure Statistical sensitivity

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References

Faich

Special Report, Adverse-Drug-Reaction Monitoring. New Eng J Med. 1986;14(24):1589–1592.

Waller

Measuring the Frequency of Adverse Drug Reactions. Clin Pharma Thera. 1993;9:249–252.

Hammerstrom

Anello

Tsong

A Comparison Of Methods Of Alerting Adverse Drug Events From Spontaneous Reports. DRAFT. Rockville, MD: Office of Epidemiology and Biostatistics, Center for Drug Evaluation and Research, FDA; 1993.

Norwood

Sampson

A Statistical Methodology for Postmarketing Surveillance of Adverse Drug Reaction Reports. Stat Med. 1988;7:1023–1030.

Tsong

False Alarm Rates of Statistical Methods Used in Determining Increased Frequency of Reports on Adverse Drug Reaction. J Biopharma Stat. 1992;2(1):9–30.

Pearson

Kennedy

Adverse Drug Reactions and the Food and Drug Administration. J Pharma Pract. 1989;2(4):209–213.

Sullivan

A Pharmaceutical Manufacturer's Perspective on Reporting Adverse Drug Experiences. Am J Hosp Pharma. 1990;47(6):1342–1345.

Waller

Postmarketing Surveillance: The Viewpoint of a Newcomer to Pharmacopeidemiology. Drug Inf J. 1991;25:181–186.

Johnson

Tanner

Barash

The Evaluation of Postmarketing Adverse Drug Experience Reports at FDA: Part I. Drug Inf J. 1993;27:1159–1165.

10.

Herman

Opening Remarks. Drug Inf J. 1991;25:163.

11.

Fletcher

Griffin

International Monitoring for Adverse Drug Reactions of Long Latency. Adver Drug React Toxicol Rev. 1991;10(4):209–230.

12.

Federal Register. 50, No. 36, February 22, 1985.

13.

Lehmann

Testing Statistical Hypotheses. 2nd Edition. New York: Wiley and Sons; 1986.

14.

Rossi

Bosco

Faich

Tanner

Temple

The Importance of Adverse Reaction Reporting by Physicians-Suprofen and the Fland Pain Syndrome. JAMA. 1988;259(8):1203–1204.

15.

Finey

Statistical Logic in the Monitoring of Reactions to Therapeutic Drugs. Meth Infor Med. 1971;10(4):237–245.

16.

Tubert

Begaud

Pere

Haramburu

Lellouch

Power and Weakness of Spontaneous Reporting: A Probabilistic Approach. J Clin Epidemiol. 1992;45(3):283–286.

17.

Guess

Behavior of the Exposure Odds Ratio In a Case-Control Study when the Hazard Function is not Constant Over Time. J Clin Epidemiol. 1989;42:1179–1184.

18.

Griffin

Webber

JCP

Voluntary Systems of Adverse Reaction Reporting Parts I, II, III. Adver Drug React Acute Poison Rev. 1985;4,5,8:183–215.

19.

Kheifets

Cluster Analysis: A Perspective. Stat Med. 1993;12:1755–1756.

A Lag Adjusted Model for Postmarketing Surveillance of Adverse Drug Event Reports

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