Investigations of Heterogeneity in Diagnostic Test Accuracy Meta-Analysis: A Methodological Review

2026-03-11

AI Summary

This study addresses the lack of standardized practices in exploring heterogeneity within diagnostic test accuracy (DTA) meta-analyses and the unclear adherence to methodological guidelines. We systematically reviewed 100 DTA meta-analyses published in 2024, identified via MEDLINE, applying rigorous screening and evaluating the use of statistical models such as the bivariate and HSROC approaches. Our findings indicate that 61% of studies conducted heterogeneity investigations—57% employed subgroup analyses and 43% used meta-regression—yet only 44% fully pre-specified their analytical plans in protocols. Moreover, model selection was frequently unsupported by justification. This work provides the first systematic evidence of critical deficiencies in current practice, offering empirical support and concrete directions for enhancing methodological transparency and reducing false-positive findings in DTA meta-analyses.

Technology Category

• Search and Optimization: Metareasoning and Metaheuristics
• Data Mining & Knowledge Management: Anomaly/Outlier Detection
• Machine Learning: Calibration & Uncertainty Quantification

Application Category

• Web Mining and Content Analysis: Robustness and generalizability of Web mining methods
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Security and Privacy: Data transparency and provenance

Abstract

Background: Subgroup analyses and meta-regression are commonly used to investigate heterogeneity in diagnostic test accuracy (DTA) meta-analyses (MA), but adherence to methodological guidance is unclear. This methodological review summarizes investigations of heterogeneity (IoH) in DTA-MAs, examining their frequency, characteristics, and alignment with recommendations. Methods: We included DTA-MAs published in 2024 reporting at least one pair of summary sensitivity and specificity. Non-DTA reviews, narrative syntheses, studies reporting only alternative measures, and overviews of systematic reviews were excluded. MEDLINE (via Ovid) was searched for English-language publications, with the final search in January 2025. Results: From 403 records, the most recent 100 DTA-MAs were included, each contributing one index test. IoH were reported in 61 analyses. The number of primary studies was positively associated with conducting an investigation (OR 1.66; p = 0.008). Subgroup analyses were used in 35/61 (57%), while 26/61 (43%) applied meta-regression alone or with subgroup analyses. Subgroup analyses examined fewer variables than meta-regression (p < 0.001). Among 44/61 (72%) analyses with sufficient detail to identify a statistical model, the bivariate model was used in 28/44 (64%), univariate random-effects models in 14/44 (32%), and the HSROC model in 5/44 (11%). Formal tests for subgroup differences were reported in 37/61 (61%). Protocols were available for 43/61 (70%) analyses, of which 19/43 (44%) fully prespecified IoH. Discussion: IoH were common and more likely when more primary studies were available, although individual subgroups were often supported by limited data. Reporting of statistical models and model choice was frequently unclear. Greater prespecification of IoH in protocols may reduce spurious findings and improve transparency in diagnostic research.

Problem

• heterogeneity
• diagnostic test accuracy
• meta-analysis
• subgroup analysis
• meta-regression

Innovation

• heterogeneity investigation
• diagnostic test accuracy meta-analysis
• subgroup analysis
• meta-regression
• bivariate model