Abstract The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement has significantly improved research transparency. However, STROBE compliance does not guarantee external validity. In the era of big medical data, studies often report internally consistent associations that fail to generalize because the underlying cohorts deviate significantly from population-level baselines. This paper proposes the External Validity Consistency Condition (EVCC), a quantitative framework designed to bridge the gap between reporting transparency and data integrity. The EVCC formalizes the relative deviation 𝛿 between cohort incidence rates and national benchmarks, providing a reproducible metric to identify selection bias. To validate this framework, we use a recent high-profile cohort study on post-vaccination cancer risks as a test-bed. Our analysis shows that while the study is published as STROBE-compliant, its control group exhibits a 36% deficit in cancer incidence compared to national registry data. This violation of the EVCC suggests that the reported risks are likely artifacts of a non-representative sample. We argue that integrating quantitative checks like the EVCC into evidence-based medicine workflows is essential to prevent inferential overreach and ensure that public health policies are grounded in population-wide reality.