Meta-analysis of diagnostic test accuracy with multiple disease stages: combining stage-specific and merged-stage data

TL;DR

This paper develops methods to include studies with merged disease stage data in meta-analyses of diagnostic test accuracy, improving estimate precision and addressing data limitations.

Contribution

It introduces novel statistical approaches for meta-analyzing test accuracy when stage-specific data are incomplete or merged, applicable to both binary and continuous test results.

Findings

Incorporating merged stage data improves estimate precision.

Methods correct biologically implausible results from limited data.

Application to hepatocellular carcinoma screening data demonstrates practical utility.

Abstract

For many conditions, it is of clinical importance to know not just the ability of a test to distinguish between those with and without the disease, but also the sensitivity to detect disease at different stages: in particular, the test's ability to detect disease at a stage most amenable to treatment. In a systematic review of test accuracy, pooled stage-specific estimates can be produced using subgroup analysis or meta-regression. However, this requires stage-specific data from each study, which is often not reported. Studies may however report test sensitivity for merged stage categories (e.g. stages I-II) or merged across all stages, together with information on the proportion of patients with disease at each stage. We demonstrate how to incorporate studies reporting merged stage data alongside studies reporting stage-specific data, to allow the inclusion of more studies in the meta-analysis. We consider both meta-analysis of tests with binary results, and meta-analysis of tests with continuous results, where the sensitivity to detect disease of each stage across the whole range of observed thresholds is estimated. The methods are demonstrated using a series of simulated datasets and applied to data from a systematic review of the accuracy of tests used to screen for hepatocellular carcinoma in people with liver cirrhosis. We show that incorporating studies with merged stage data can lead to more precise estimates and, in some cases, corrects biologically implausible results that can arise when the availability of stage-specific data is limited.