Remschmidt Cornelius, Wichmann Ole, Harder Thomas
Immunization Unit, Robert Koch Institute, Seestrasse 10, 13353, Berlin, Germany.
BMC Infect Dis. 2015 Oct 17;15:429. doi: 10.1186/s12879-015-1154-y.
Evidence on influenza vaccine effectiveness (VE) is commonly derived from observational studies. However, these studies are prone to confounding by indication and healthy vaccinee bias. We aimed to systematically investigate these two forms of confounding/bias.
Systematic review of observational studies reporting influenza VE and indicators for bias and confounding. We assessed risk of confounding by indication and healthy vaccinee bias for each study and calculated ratios of odds ratios (crude/adjusted) to quantify the effect of confounder adjustment. VE-estimates during and outside influenza seasons were compared to assess residual confounding by healthy vaccinee effects.
We identified 23 studies reporting on 11 outcomes. Of these, 19 (83 %) showed high risk of bias: Fourteen due to confounding by indication, two for healthy vaccinee bias, and three studies showed both forms of confounding/bias. Adjustment for confounders increased VE on average by 12 % (95 % CI: 7-17 %; all-cause mortality), 9 % (95 % CI: 4-14 %; all-cause hospitalization) and 7 % (95 % CI: 4-10 %; influenza-like illness). Despite adjustment, nine studies showed residual confounding as indicated by significant off-season VE-estimates. These were observed for five outcomes, but more frequently for all-cause mortality as compared to other outcomes (p = 0.03) and in studies which indicated healthy vaccinee bias at baseline (p = 0.01).
Both confounding by indication and healthy vaccinee bias are likely to operate simultaneously in observational studies on influenza VE. Although adjustment can correct for confounding by indication to some extent, the resulting estimates are still prone to healthy vaccinee bias, at least as long as unspecific outcomes like all-cause mortality are used. Therefore, cohort studies using administrative data bases with unspecific outcomes should no longer be used to measure the effects of influenza vaccination.
关于流感疫苗效力(VE)的证据通常来自观察性研究。然而,这些研究容易受到指征性混杂和健康接种者偏倚的影响。我们旨在系统地调查这两种形式的混杂/偏倚。
对报告流感VE以及偏倚和混杂指标的观察性研究进行系统综述。我们评估了每项研究中指征性混杂和健康接种者偏倚的风险,并计算比值比(粗/调整后)的比值以量化混杂因素调整的效果。比较流感季节期间和之外的VE估计值,以评估健康接种者效应导致的残余混杂。
我们确定了23项报告11项结果的研究。其中,19项(83%)显示出高偏倚风险:14项由于指征性混杂,2项由于健康接种者偏倚,3项研究显示出两种形式的混杂/偏倚。对混杂因素进行调整后,VE平均增加了12%(95%置信区间:7-17%;全因死亡率)、9%(95%置信区间:4-14%;全因住院)和7%(95%置信区间:4-10%;流感样疾病)。尽管进行了调整,但有9项研究显示出残余混杂,表现为非流感季节显著的VE估计值。在5项结果中观察到了这种情况,但与其他结果相比,全因死亡率更为常见(p = 0.03),并且在基线时显示出健康接种者偏倚的研究中也更为常见(p = 0.01)。
在关于流感VE的观察性研究中,指征性混杂和健康接种者偏倚可能同时存在。尽管调整可以在一定程度上纠正指征性混杂,但由此产生的估计值仍然容易受到健康接种者偏倚的影响,至少在使用全因死亡率等非特异性结果时如此。因此,不应再使用基于行政数据库且有非特异性结果的队列研究来衡量流感疫苗接种的效果。