A Biostatistical Reappraisal Unveiling the Mechanism Behind Apparent Cancer Risk Signals in a COVID-19 Vaccinated Cohort

Abstract

Background: A recent large-scale COVID-19 vaccine cohort study has reported statistical associations suggesting increased cancer risk. Our initial application of fundamental demographic and incidence metrics to that specific cohort study suggested instead a pronounced external validity discrepancy: the study’s overall cancer incidence showed a 26% deficit compared to the coherent national rate (South Korea), implying  a methodological artifact.

Objectives: To determine if the observed external validity discrepancy in the cohort's overall incidence is attributable to an asymmetry in the demographic composition of the exposure groups, and to quantify the resulting impact on the reported statistical association between COVID-19 vaccination and cancer incidence.

Methods: We performed a core check of external validity utilizing fundamental demographic and incidence metrics for the country of interest, specifically comparing Age-Stratified Demographic Composition and Crude Incidence Rates (CRs) of the cohort against established national standards.

Results: The non-vaccinated subgroup aged >= 65 showed a pronounced, asymmetric undercount of approx. 45% in expected cancer cases relative to the national age-specific rate. This asymmetric underrepresentation of high-risk elderly participants is the specific mechanism that explains the 26% overall incidence suppression, mathematically generating the appearance of excess risk in the vaccinated group.

Discussion: The reported association of the scrutinized study is likely to be a statistical artifact due to marked asymmetric selection bias in cohort enrollment, fully demonstrable through fundamental demographic and cancer incidence metrics. Balanced cohorts would predictably show no statistically significant difference in cancer incidence between groups.