The lay abstract featured today (for Quantifying overdiagnosis for multicancer detection tests: A novel method by Stuart G. Baker) is from Statistics in Medicine with the full Open Access article now available to read here.

How to cite

Baker, S.G. (2024), Quantifying Overdiagnosis for Multicancer Detection Tests: A Novel Method. Statistics in Medicine. https://doi.org/10.1002/sim.10285

Lay Abstract

There is rapidly growing interest in multicancer detection (MCD) tests, which use blood specimens to detect preclinical cancers.  Some MCD tests are already in clinical practice. However, there has been no rigorous evaluation of their benefits and harms. An important potential harm is overdiagnosis, which is the detection of preclinical cancer on screening that would not have developed into symptomatic cancer in the absence of screening. Because overdiagnosis can lead to unnecessary and harmful treatments, its quantification is important.  However, quantifying overdiagnosis is challenging because it is not observed. It is even more challenging with  MCD tests because short-term results are needed because the technology is rapidly changing.  This article proposes a novel method to quantify overdiagnosis from short-term observational MCD testing data that would arise in clinical practice. The method requires at least two yearly MCD tests given to persons having a wide range of ages and applies only to cancers for which there is no conventional screening. Because of the statistical challenges, the result is not a single estimate but a sensitivity analysis over one parameter.  As illustrated with lung cancer screening data and synthetic data, the method can distinguish small from moderate overdiagnosis, which would yield useful information for decision-making.