Inclusion of unexposed subjects improves the precision and power of self-controlled case series method

Xiangmei Ma, K. F. Lam, Yin Bun Cheung

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    Abstract

    The self-controlled case series is an important method in the studies of the safety of biopharmaceutical products. It uses the conditional Poisson model to make comparison within persons. In models without adjustment for age (or other time-varying covariates), cases who are never exposed to the product do not contribute any information to the estimation. We provide analytic proof and simulation results that the inclusion of unexposed cases in the conditional Poisson model with age adjustment reduces the asymptotic variance of the estimator of the exposure effect and increases power. We re-analysed a vaccine safety dataset to illustrate.

    Original languageEnglish
    JournalJOURNAL OF BIOPHARMACEUTICAL STATISTICS
    Volume32
    Issue number2
    Early online dateNov 2021
    DOIs
    Publication statusPublished - 2022
    Publication typeA1 Journal article-refereed

    Keywords

    • Asymptotic variance
    • conditional Poisson model
    • drug safety
    • self-controlled case series
    • vaccine safety

    Publication forum classification

    • Publication forum level 1

    ASJC Scopus subject areas

    • Statistics and Probability
    • Pharmacology
    • Pharmacology (medical)

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