Modern Sources of Controls in Case-Control Studies.

Abstract

In 1992, Wacholder and colleagues developed a theoretical framework for case-control studies to minimize bias in control selection. They described three comparability principles (study base, deconfounding, and comparable accuracy) to reduce the potential for selection bias, confounding, and information bias in case-control studies. Wacholder et al. explained how these principles apply to traditional sources of controls for case-control studies, including population controls, hospital controls, controls from a medical practice, friend or relative controls, and deceased controls. The goal of the current manuscript is to extend this seminal work on case-control studies by providing a modern perspective on sources of controls. Today, there are many more potential sources of controls for case-control studies than there were in the 1990s. This is due to technological advances in computing power, internet access, and availability of 'big data' resources. These advances have vastly expanded the quantity and diversity of data available for case-control studies. In this manuscript, we discuss control selection from electronic health records, health insurance claims databases, publicly available online data sources, and social media-based data. We focus on practical considerations for unbiased control selection, emphasizing the strengths and weaknesses of each modern source of controls for case-control studies.