Table 3.
Risk of DM1 after HPV vaccine | Hazard ratio | 95% CI | P-value | ||
---|---|---|---|---|---|
Primary analysis | HPV vaccinated vs. unvaccinateda | 1.21 | 0.94, 1.57 | 0.15 | |
Sensitivity analyses assessed | Sensitivity analyses interpretation | ||||
Potential confounding by sex | Stratified by sexb | 1.18 | 0.91, 1.53 | 0.22 | Model was more restrictive because there had to be variation of HPV vaccination status among people who were the same sex as each DM1 case. It would have yielded different results if there was a risk of DM1 after HPV vaccine and if the risk differed by sex |
Females onlyc | 1.23 | 0.90, 1.67 | 0.20 | Most of the vaccinated study population was female. | |
Males onlyc | 1.07 | 0.64, 1.77 | 0.80 | These analyses confirmed that inclusion ofmales did not drive the primary result | |
Impact of sparse data | Stratified by sexd | 1.18 | 0.91, 1.53 | 0.22 | If sparse strata mattered to the size of the confidence intervals, computing with exact methods would have yielded different results |
Females onlyd | 1.23 | 0.90, 1.67 | 0.20 | ||
Potential confounding by age | Stratified by 6-month instead of 1-year age categoriese | 1.21 | 0.93, 1.57 | 0.15 | All sensitivity analyses were also done using age in 6- month categories and results were all similar |
Analysis used an age timeline instead of a calendar timelinef | 1.21 | 0.92, 1.59 | 0.17 | These analyses controlled very finely for the effects of age. They demonstrate that the primary results were not strongly confounded by age | |
Analysis used an age timeline instead of a calendar timeline, females onlyg | 1.27 | 0.92, 1.76 | 0.14 | ||
Influence of age groups for whom vaccine delivery differed over time | Included only people aged <26 yearsh | 1.17 | 0.92, 1.49 | 0.21 | This analysis showed that the primary analysis results were not unduly influenced by the small number of DM1 cases which occurred in people >26years of age, all of whom were female |
Influence of outliers | Analysis restricted to risk sets where at least 2% were vaccinated with HPV | 1.18 | 0.91, 1.53 | 0.22 | This analysis showed that outliers did not have undue influence on the primary results and that results were not driven by a small number of overly-influential DM1 cases |
Cox regression stratified by age in years, calendar year, years of prior membership, race and Medicaid status. HPV vaccination status and sex were independent variables in the model.
Cox regression stratified by sex, age in years, calendar year, years of prior membership, race and Medicaid status. HPV vaccination status was an independent variable in the model.
Same as b, but restricted to females/males only.
Same as b, but confidence intervals and p-value computed with exact methods.
Cox regression stratified by age in 6-month categories, calendar year, years of prior membership, race and Medicaid status. HPV vaccination status and male sex were independent variables in the model.
Same as b, except analysis used an age timeline instead of a calendar timeline. In this analysis, all individuals in each risk set were born within two weeks of each other.
Same as g, but restricted to females only.
Same as b, but restricted to those <26 years of age.