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Testing for adverse drug reactions using prescription event monitoring.

Testing for adverse drug reactions using prescription event monitoring.
Testing for adverse drug reactions using prescription event monitoring.
The Drug Safety Research Unit's current methods of investigating adverse drug reactions using prescription event monitoring are discussed. The statistical properties of estimators of rates of occurrence of events in post-marketing surveillance using prescription event monitoring are considered, and a simple model is proposed based on an exponential distribution of time to first occurrence of the event. It is shown that current methodology closely relates to the use of maximum likelihood estimation under this assumption and the distributions of the estimators are shown to be approximately normal, which allows simple confidence intervals and tests to be developed. Two recent applications are considered and corresponding simulations are presented to verify the approximate properties of the test statistics, based on ratios of rates over time and between drugs. Sources of bias in the rates and rate ratios are considered, including under-reporting in later months. A rule-of-thumb, developed from many years experience, is shown to be generally conservative, except when these under-reporting biases are large.
0277-6715
987-1002
Andrew, J.E.
34453494-b146-4bf3-9391-4d84214a1f83
Prescott, P.
cf0adfdd-989b-4f15-9e60-ef85eed817b2
Smith, T.M.F.
63739590-4e81-43b2-b45f-d20d98542a00
Inman, W.H.W.
1a5d91a2-3dd5-4ee6-bd31-3b54b3ad4b05
Kubota, K.
a3f45ee0-2569-4377-8196-f007c36d0e6d
Andrew, J.E.
34453494-b146-4bf3-9391-4d84214a1f83
Prescott, P.
cf0adfdd-989b-4f15-9e60-ef85eed817b2
Smith, T.M.F.
63739590-4e81-43b2-b45f-d20d98542a00
Inman, W.H.W.
1a5d91a2-3dd5-4ee6-bd31-3b54b3ad4b05
Kubota, K.
a3f45ee0-2569-4377-8196-f007c36d0e6d

Andrew, J.E., Prescott, P., Smith, T.M.F., Inman, W.H.W. and Kubota, K. (1996) Testing for adverse drug reactions using prescription event monitoring. Statistics in Medicine, 15 (10), 987-1002. (doi:10.1002/(SICI)1097-0258(19960530)15:10<987::AID-SIM210>3.0.CO;2-G).

Record type: Article

Abstract

The Drug Safety Research Unit's current methods of investigating adverse drug reactions using prescription event monitoring are discussed. The statistical properties of estimators of rates of occurrence of events in post-marketing surveillance using prescription event monitoring are considered, and a simple model is proposed based on an exponential distribution of time to first occurrence of the event. It is shown that current methodology closely relates to the use of maximum likelihood estimation under this assumption and the distributions of the estimators are shown to be approximately normal, which allows simple confidence intervals and tests to be developed. Two recent applications are considered and corresponding simulations are presented to verify the approximate properties of the test statistics, based on ratios of rates over time and between drugs. Sources of bias in the rates and rate ratios are considered, including under-reporting in later months. A rule-of-thumb, developed from many years experience, is shown to be generally conservative, except when these under-reporting biases are large.

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Published date: 1996
Organisations: Statistics

Identifiers

Local EPrints ID: 29972
URI: https://eprints.soton.ac.uk/id/eprint/29972
ISSN: 0277-6715
PURE UUID: 69aa8f81-71aa-49a9-a30b-d4c56719c518

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Date deposited: 04 May 2007
Last modified: 15 Jul 2019 19:08

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