Parents indicate that safety is their top concern about human papillomavirus (HPV) vaccination. A data-mining method not requiring prespecification of health outcome(s) or postexposure period(s) of potentially increased risk can be used to identify possible associations between an exposure and any of thousands of medically attended health outcomes; this method was applied to data on the 9-valent HPV vaccine (HPV9) to detect potential safety problems. Data on 9- to 26-year-olds who had received HPV9 vaccine between November 4, 2016, and August 5, 2018, inclusive, were extracted from the MarketScan database and analyzed for statistically significant clustering of incident diagnoses within the hierarchy of diagnoses coded using the International Classification of Diseases and temporally within the 1 year after vaccination, using the self-controlled tree-temporal scan statistic and TreeScan software. Only 56 days of postvaccination enrollment was required; subsequent follow-up was censored at disenrollment. Multiple testing was adjusted for. The analysis included 493,089 doses of HPV9. Almost all signals resulted from temporal confounding, not unexpected with a 1-year follow-up period. The only plausible signals were for nonspecific adverse events (e.g., injection-site reactions, headache) on days 1-2 after vaccination, with attributable risks as low as 1 per 100,000 vaccinees. Considering the broad scope of the evaluation and the high statistical power, the findings of no specific serious adverse events should provide reassurance about this vaccine's safety.
Keywords: data-mining; papillomavirus vaccines; vaccination.
© The Author(s) 2021. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.