Advances in Methodologies of Negative Controls: A Scoping Review.

Negative control is considered an important tool to mitigate biases in observational studies. The aim of this scoping review was to summarize current methodologies of negative controls (both negative control exposure [NCE] and negative control outcome [NCO]). We searched PubMed, Web of Science, EMBASE and Cochrane Library (up to March 9, 2023) for articles on methodologies of negative controls. Two reviewers independently and in duplicate selected eligible studies and collected relevant data. We reported total numbers and percentages and summarized methodologies narratively. A total of 37 relevant methodological articles were included in our review. These publications covered NCE (n=11, 29.8%), NCO (n=13, 35.1%) or both (n=13, 35.1%), with most focused on bias detection (n=14, 37.8%), bias correction (n=16, 43.3%) and P-value or confidence interval (CI) calibration (n=5, 13.5%). For the two remaining articles (5.4%), one discussed bias detection and P-value or CI calibration and the other covered all the three functions. For bias detection, the existence of an association between the NCE (NCO) and outcome (exposure) variables of interest simply indicates that results may suffer from confounding bias, selection bias and/or information bias. For bias correction, however, the algorithms of negative control methods need more stringent assumptions such as rank preservation, monotonicity and linearity. Negative controls can be leveraged for bias detection, P-value or CI calibration, and bias correction, among which bias correction using negative controls has been the most studied methodologically. The currently known methods need some stringent assumptions to detect or remove bias. More methodological research is needed to optimize the use of negative controls.

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Copyright © 2023. Published by Elsevier Inc.