Ronghui Xu1, Yunjun Luo, Christina Chambers. 1. Department of Family and Preventive Medicine, University of California, San Diego, La Jolla, CA, USA. rxu@ucsd.edu
Abstract
PURPOSE: In studying the safety of vaccine for influenza A (H1N1) given during pregnancy, spontaneous abortion (SAB) is one of the important points to consider. Because women may receive the vaccine any time during their pregnancy, evaluation of the effect of the vaccine on SAB should only take place after vaccination and in the risk window for SAB, that is, the first 20 weeks of gestation. In addition, when such studies are conducted through pregnancy registries where recruitment occurs after pregnancy recognition, the accrued subjects are left truncated in the sense that they are not followed from the start of pregnancy. METHODS: As previously reported, left truncation needs to be properly handled using survival analysis methods to avoid bias. In the context of time-dependent vaccine exposure, a time-dependent covariate Cox model can be used to simultaneously take into account the left truncation and the vaccine exposure timing. RESULTS: In this communication, we illustrate the approach using the Vaccine and Medication in Pregnancy Surveillance System data. We explain in details how the model is fitted using different software. CONCLUSIONS: We recommend survival analysis methods together with collection of necessary data to study the effects of vaccine on SAB.
PURPOSE: In studying the safety of vaccine for influenza A (H1N1) given during pregnancy, spontaneous abortion (SAB) is one of the important points to consider. Because women may receive the vaccine any time during their pregnancy, evaluation of the effect of the vaccine on SAB should only take place after vaccination and in the risk window for SAB, that is, the first 20 weeks of gestation. In addition, when such studies are conducted through pregnancy registries where recruitment occurs after pregnancy recognition, the accrued subjects are left truncated in the sense that they are not followed from the start of pregnancy. METHODS: As previously reported, left truncation needs to be properly handled using survival analysis methods to avoid bias. In the context of time-dependent vaccine exposure, a time-dependent covariate Cox model can be used to simultaneously take into account the left truncation and the vaccine exposure timing. RESULTS: In this communication, we illustrate the approach using the Vaccine and Medication in Pregnancy Surveillance System data. We explain in details how the model is fitted using different software. CONCLUSIONS: We recommend survival analysis methods together with collection of necessary data to study the effects of vaccine on SAB.
Authors: Siri E Håberg; Lill Trogstad; Nina Gunnes; Allen J Wilcox; Håkon K Gjessing; Sven Ove Samuelsen; Anders Skrondal; Inger Cappelen; Anders Engeland; Preben Aavitsland; Steinar Madsen; Ingebjørg Buajordet; Kari Furu; Per Nafstad; Stein Emil Vollset; Berit Feiring; Hanne Nøkleby; Per Magnus; Camilla Stoltenberg Journal: N Engl J Med Date: 2013-01-16 Impact factor: 91.245
Authors: Ronghui Xu; Yunjun Luo; Robert Glynn; Diana Johnson; Kenneth L Jones; Christina Chambers Journal: Int J Environ Res Public Health Date: 2014-03-12 Impact factor: 3.390
Authors: Christina D Chambers; Diana L Johnson; Ronghui Xu; Yunjun Luo; Janina Lopez-Jimenez; Margaret P Adam; Stephen R Braddock; Luther K Robinson; Keith Vaux; Kenneth Lyons Jones Journal: PLoS One Date: 2019-10-18 Impact factor: 3.240
Authors: Mollie E Wood; Angela Lupattelli; Kristin Palmsten; Gretchen Bandoli; Caroline Hurault-Delarue; Christine Damase-Michel; Christina D Chambers; Hedvig M E Nordeng; Marleen M H J van Gelder Journal: Epidemiol Rev Date: 2022-01-14 Impact factor: 6.222