Guillain-Barré Syndrome After High-Dose Influenza Vaccine Administration in the United States, 2018-2019 Season

BACKGROUND

The Vaccine Safety Datalink (VSD) identified a statistical signal for an increased risk of Guillain-Barré syndrome (GBS) in days 1-42 after 2018-2019 high-dose influenza vaccine (IIV3-HD) administration. We evaluated the signal using Medicare.

METHODS

We conducted early- and end-of-season claims-based self-controlled risk interval analyses among Medicare beneficiaries ages ≥65 years, using days 8-21 and 1-42 postvaccination as risk windows and days 43-84 as control window. The VSD conducted chart-confirmed analyses.

RESULTS

Among 7 453 690 IIV3-HD vaccinations, we did not detect a statistically significant increased GBS risk for either the 8- to 21-day (odds ratio [OR], 1.85; 95% confidence interval [CI], 0.99-3.44) or 1- to 42-day (OR, 1.31; 95% CI, 0.78-2.18) risk windows. The findings from the end-of-season analyses were fully consistent with the early-season analyses for both the 8- to 21-day (OR, 1.64; 95% CI, 0.92-2.91) and 1- to 42-day (OR, 1.12; 95% CI, 0.70-1.79) risk windows. The VSD's chart-confirmed analysis, involving 646 996 IIV3-HD vaccinations, with 1 case each in the risk and control windows, yielded a relative risk of 1.00 (95% CI, 0.06-15.99).

CONCLUSIONS

The Medicare analyses did not exclude an association between IIV3-HD and GBS, but it determined that, if such a risk existed, it was similar in magnitude to prior seasons. Chart-confirmed VSD results did not confirm an increased risk of GBS.

Quantifying the impact of time-varying baseline risk adjustment in the self-controlled risk interval design

PURPOSE

The self-controlled risk interval design is commonly used to assess the association between an acute exposure and an adverse event of interest, implicitly adjusting for fixed, non-time-varying covariates. Explicit adjustment needs to be made for time-varying covariates, for example, age in young children. It can be performed via either a fixed or random adjustment. The random-adjustment approach can provide valid point and interval estimates but requires access to individual-level data for an unexposed baseline sample. The fixed-adjustment approach does not have this requirement and will provide a valid point estimate but may underestimate the variance. We conducted a comprehensive simulation study to evaluate their performance.

METHODS

We designed the simulation study using empirical data from the Food and Drug Administration-sponsored Mini-Sentinel Post-licensure Rapid Immunization Safety Monitoring Rotavirus Vaccines and Intussusception study in children 5-36.9 weeks of age. The time-varying confounder is age. We considered a variety of design parameters including sample size, relative risk, time-varying baseline risks, and risk interval length.

RESULTS

The random-adjustment approach has very good performance in almost all considered settings. The fixed-adjustment approach can be used as a good alternative when the number of events used to estimate the time-varying baseline risks is at least the number of events used to estimate the relative risk, which is almost always the case.

CONCLUSIONS

We successfully identified settings in which the fixed-adjustment approach can be used as a good alternative and provided guidelines on the selection and implementation of appropriate analyses for the self-controlled risk interval design.