Human papillomavirus vaccine-associated premature ovarian insufficiency and related adverse events: data mining of Vaccine Adverse Event Reporting System

Abstract

We detected disproportionate reports of premature ovarian insufficiency (POI) and related events, including amenorrhea, menstruation irregular, FSH increased, and premature menopause, following human papillomavirus (HPV) vaccine from FDA Vaccine Adverse Event Reporting System (VAERS). The signal was detected by the methods of Bayesian Confidence Propagation Neural Network (BCPNN) and Multi-item Gamma Poisson Shrinker (MGPS). When both methods detected a positive result, a signal was generated. Besides, time-scan map is drawn based on the IC value and 95%CI of BCPNN, if the IC curve showed a steady upward trend and the 95%CI narrowed, the signal was stable and strong association.The results showed that there were not POI reports of HPV vaccine, but VAERS received a total of 2, 389, 27 POI related events for HPV2, HPV4, HPV9 respectively from the year of marketed to 2018. No signal was detected for HPV2. HPV4-POI ralated events were all detected as signals by two methods. There was only one signal of menstruation irregular for HPV9. Time scan of HPV4-POI ralated events showed those signals were stability and strong association, but not for HPV9. Our results only represent statistical association between HPV vaccine and POI related events, causal relationship needs further investigation.

Figure 1

Flow diagram of case inclusion in this study.

Figure 2

Time scans of IC for HPV4-associated POI raleted events from the year 2006 to 2018: (a) HPV4-amenorrhea association, (b) HPV4-menstruation irregular association, (c) HPV4-FSH increased association, (d) HPV4-premature menopause association.

Figure 3

Time scans of IC for HPV9-associated POI related events from the year 2015 to 2018: (a) HPV9-amenorrhea association, (b) HPV9-menstruation irregular association, (c) HPV9-FSH increased association, (d) HPV9-premature menopause association.