tetano
Editor, Senior Moderator
Pharmacoepidemiol Drug Saf. 2019 Jun 20. doi: 10.1002/pds.4807. [Epub ahead of print]
[h=1]A simulation study of the statistical power and signaling characteristics of an early season sequential test for influenza vaccine safety.[/h] Forshee RA[SUP]1[/SUP], Hu M[SUP]2[/SUP], Arya D[SUP]1[/SUP], Perez-Vilar S[SUP]1[/SUP], Anderson SA[SUP]1[/SUP], Lo AC[SUP]2[/SUP], Swarr M[SUP]2[/SUP], Wernecke M[SUP]2[/SUP], MaCurdy T[SUP]2,[/SUP][SUP]3[/SUP], Chu S[SUP]4[/SUP], Kelman J[SUP]4[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] [h=4]PURPOSE:[/h] The US Food and Drug Administration monitors the risk of Guillain-Barr? syndrome (GBS) following influenza vaccination using several data sources including Medicare. In the 2017 to 2018 season, we transitioned our near real-time surveillance in Medicare to more effectively detect large GBS risk increases early in the season while avoiding false positives.
[h=4]METHODS:[/h] We conducted a simulation study examining the ability of the updating sequential probability ratio test (USPRT) to detect substantially elevated GBS risk in the 8- to 21-day postvaccination versus 5? to 30? the historical rate. We varied the first testing week (weeks 5-8) and the null rate (1?-3?) and evaluated power. We estimated signal probability and the risk ratio (RR) after signaling when high-risk seasons were rare.
[h=4]RESULTS:[/h] Applying fixed alternatives, we found >80% power to detect a risk 30? the historical rate in week 5 for the 1? null and in week 6 for the 1.5? to 3? nulls. Nearly all testing schedules had >80% power for a 5? risk by week 11. To test the robustness of USPRT, we further simulated seasons where 1% were true high-risk seasons. Using a 1? null led to 10% of seasons signaling by week 11 (median RR approximately 1.4), which decreased to approximately 1% with the ≥2.5? null (median RR approximately 16.0).
[h=4]CONCLUSIONS:[/h] On the basis of the results from this simulation and subsequent consultations with experts and stakeholders, we specified USPRT to test continuously from weeks 7 to 11 using the null hypothesis that the observed GBS rate was 2.5? the historical rate. This helped improve the ability of USPRT to provide early detection of GBS risk following influenza vaccination as part of a multilayered system of surveillance.
? 2019 John Wiley & Sons, Ltd.
[h=4]KEYWORDS:[/h] Guillain-Barr? syndrome; influenza vaccines; near real-time surveillance; pharmacoepidemiology; sequential tests; vaccine safety
PMID: 31222967 DOI: 10.1002/pds.4807
[h=1]A simulation study of the statistical power and signaling characteristics of an early season sequential test for influenza vaccine safety.[/h] Forshee RA[SUP]1[/SUP], Hu M[SUP]2[/SUP], Arya D[SUP]1[/SUP], Perez-Vilar S[SUP]1[/SUP], Anderson SA[SUP]1[/SUP], Lo AC[SUP]2[/SUP], Swarr M[SUP]2[/SUP], Wernecke M[SUP]2[/SUP], MaCurdy T[SUP]2,[/SUP][SUP]3[/SUP], Chu S[SUP]4[/SUP], Kelman J[SUP]4[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] [h=4]PURPOSE:[/h] The US Food and Drug Administration monitors the risk of Guillain-Barr? syndrome (GBS) following influenza vaccination using several data sources including Medicare. In the 2017 to 2018 season, we transitioned our near real-time surveillance in Medicare to more effectively detect large GBS risk increases early in the season while avoiding false positives.
[h=4]METHODS:[/h] We conducted a simulation study examining the ability of the updating sequential probability ratio test (USPRT) to detect substantially elevated GBS risk in the 8- to 21-day postvaccination versus 5? to 30? the historical rate. We varied the first testing week (weeks 5-8) and the null rate (1?-3?) and evaluated power. We estimated signal probability and the risk ratio (RR) after signaling when high-risk seasons were rare.
[h=4]RESULTS:[/h] Applying fixed alternatives, we found >80% power to detect a risk 30? the historical rate in week 5 for the 1? null and in week 6 for the 1.5? to 3? nulls. Nearly all testing schedules had >80% power for a 5? risk by week 11. To test the robustness of USPRT, we further simulated seasons where 1% were true high-risk seasons. Using a 1? null led to 10% of seasons signaling by week 11 (median RR approximately 1.4), which decreased to approximately 1% with the ≥2.5? null (median RR approximately 16.0).
[h=4]CONCLUSIONS:[/h] On the basis of the results from this simulation and subsequent consultations with experts and stakeholders, we specified USPRT to test continuously from weeks 7 to 11 using the null hypothesis that the observed GBS rate was 2.5? the historical rate. This helped improve the ability of USPRT to provide early detection of GBS risk following influenza vaccination as part of a multilayered system of surveillance.
? 2019 John Wiley & Sons, Ltd.
[h=4]KEYWORDS:[/h] Guillain-Barr? syndrome; influenza vaccines; near real-time surveillance; pharmacoepidemiology; sequential tests; vaccine safety
PMID: 31222967 DOI: 10.1002/pds.4807