Nomograms are a trending term in evidence-based medicine, and COVID-19 research is no exception. In this context, a nomogram is usually a web-based tool, a graphic interface, or an on-line calculator in which patient data on several variables is entered as input, and a single summary statistic is calculated as output, such as the likelihood of successful response to treatment. Many medical researchers and data scientists have put forward nomograms derived from multivariate clinical progression models, to assist in decisions about COVID-19 triage.
Is this enthusiasm for reducing complex clinical decisions to the use of multivariate calculators a leap forward in personalized medicine, enabled by modern computing? There is a sketchy “black box” side to all this, to say nothing of the risk of incorporating statistical design errors or untenable inferential claims into a nomogram being rolled out for immediate, untested use in the middle of pandemic. So let’s treat the history of the “number needed to treat” as a “teachable moment” in the history of nomograms in medicine. What have we learned so far?
Author(s): Savanna Reid
Publication Date: 26 February 2021
Publication Site: Towards Data Science