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.

翻译：对于许多疾病，临床不仅需要了解测试区分患病与非患病个体的能力，还需掌握其检测不同疾病阶段的敏感性：特别是检测最适宜治疗阶段的疾病能力。在测试准确性的系统评价中，可通过亚组分析或荟萃回归获得合并的阶段特异性估计值。然而，这要求每项研究均提供阶段特异性数据，而此类数据往往未被报告。但研究可能报告合并阶段类别（如I-II期）或跨所有阶段合并的测试敏感性，同时提供各阶段患者比例信息。本文论证了如何将报告合并阶段数据的研究与报告阶段特异性数据的研究相结合，以便在荟萃分析中纳入更多研究。我们既考虑了二分类结果测试的荟萃分析，也探讨了连续结果测试的荟萃分析——后者可估计在整个观测阈值范围内检测各阶段疾病的敏感性。通过系列模拟数据集验证了该方法，并将其应用于肝硬化患者肝细胞癌筛查测试准确性的系统评价数据。研究表明：纳入合并阶段数据的研究可获得更精确的估计值，并在某些情况下能修正因阶段特异性数据有限而产生的生物学不合理结果。