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Determinants of robustness to unmeasured confounding in real-world data: an E-value based meta-regression through the lens of acupuncture studies
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DOI：10.1016/j.imr.2026.101383.png)
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Abstract
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This study evaluated the robustness of real-world data (RWD)–based observational studies of acupuncture to unmeasured confounding using the E-value as a quantitative index. We examined how data source, exposure specification, and methodological characteristics influence robustness across published literature.
Keywords:
Real-world data
E-value
Unmeasured confounding
Nonpharmacological interventions
Acupuncture
Observational study
Causal inference
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