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

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.

KEYWORDS:

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

Data availability statement

We used a publicly available dataset from https://sccs-studies.info/stata.html for the illustration (accessed 7 August 2020).

Disclaimer

Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not reflect the views of Ministry of Health/National Medical Research Council, Singapore.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed on the publisher’s website.

Additional information

Funding

This work was supported by the National Medical Research Council, Singapore (MOH-000526-00).