AbstractThe modern era of medical research, characterized by the availability of big data and sophisticated statistical methodologies, is paradoxically vulnerable to fundamental structural flaws in experimental cohort construction, despite adherence to rigorous reporting guidelines. Errors often arise from a failure to apply simple base-rate checks, violating core statistical principles derived from the work of pioneers, and leading to contradictory results. This methodological challenge was recently amplified in large-scale COVID-19 vaccine safety surveillance, where a failure to ensure a non-asymmetric distribution of high- risk elderly or vulnerable individuals across compared subgroups (Vaccinated vs. Non-Vaccinated) leads to a systemic and reproducible failure in cohort construction. This generates predictable and spurious Hazard Ratios (HRs). This scenario is powerfully anticipated by historical failures that remind us of the importance of primary checks. For example, the Beta-Agonist Paradox showed to the world that structural bias (Confounding by Indication) could mistake a marker of severity for a causal risk, teaching us once again that external validity is lost when the core cohort structure is compromised. We address this specific issue within two exemplar studies that have alarmed the international scientific community by associating COVID-19 vaccination with increased risks of diseases, including cancer and autoimmune disorders. These studies share a single data source and, critically, this fundamentally flawed methodology. Our analysis aims to reconstruct the cohort data and quantify the exact effect of a demographic asymmetry on reportedly increased risks of cancer and a common autoimmune disease (vitiligo). The applied methodology involves the deconstruction and re-analysis of reported HRs through weighted incidence analysis to produce corrected and plausible risk estimates, thus re-establishing methodological integrity and providing clinicians and the public with reliable information free from unwarranted alarm.
Roccetti, Marco (Mon,) studied this question.