Quantifying structural selection bias in observational cohort data: a ponderation analysis of age - specific...

A recent nationwide cohort study reported an unadjusted Hazard Ratio (HR) of 2.714 for Vitiligo incidence following COVID-19 vaccination, indicating a major safety concern. This finding was based on cohorts with an ≈ 11-year age difference, immediately raising critical concerns regarding extreme structural selection and detection bias.

We hypothesize that this extreme association is an artifact of a fatal methodological flaw, challenging the study's internal validity and subsequent external validity. We aim to quantitatively separate the HR attributable to the structural age imbalance (HR Structural) from the residual HR (HR Residual), which quantifies the uncorrected methodological failure and residual confounding. We further perform a plausible recalculation of risk to demonstrate the complete collapse of the risk signal upon correcting the methodological failure in the baseline cohort.

We performed a direct age-standardization analysis analysis using the age distribution of the scrutinized study's cohorts (Vaccinated, mean age = 56.32 years vs. Non-Vaccinated, mean age = 45.51 years) and applied established national age-specific Vitiligo incidence rates (IR) from external epidemiology.

The HR Structural was calculated to be 1.2104. The remaining HR Residual of 2.2423 quantifies the uncorrected methodological failure. The NV cohort's observed incidence rate (0.67/10,000) was found to be nearly 70% lower than the expected rate (2.2146/10,000), providing quantifiable evidence of profound non-comparability. The subsequent recalculation of risk, correcting for this baseline failure, reduces the observed HR of = 2.714 to an HR Corrected of 1.0025, thus completely annulling the signal of risk due to vaccination.

The HR = 2.714 of the scrutinized study is an unstable statistical artifact. The overwhelming majority of the observed association is a consequence of a fatal design flaw. The HR Corrected of almost 1 confirms that correcting the methodological error eliminates the risk signal, demonstrating a severe lack of internal and external validity of the original study.