“…The main kinds of bias that accrue in retrospective and observational surgical research do not offset one another, they're additive. Selection bias (treatment groups with baseline differences in elements that may affect the outcomes in question), transfer bias (follow-up that is insufficiently long or complete to discern all relevant harms of treatment), and assessment bias (using nonvalidated endpoints when evaluating outcomes) befoul retrospective studies more than randomized trials, and they all tend to make the novel treatment appear better than it actually is [7]. If one pools a population of studies that tends to suffer from those limitations in a meta-analysis, the meta-analysis will tend to amplify those biases and overestimate the benefits of treatment.…”