Fig 7. Directness of outcome measures, risk of bias and generalizability.

Studies evaluating outcomes that provide very direct evidence for impacting patient outcomes may be–on average–more prone to confounding and selection bias and may lead to results that are less easily generalizable. The risk of confounding is likely increased because the number of covariates that have an influence on downstream outcomes (for which balance between compared cohorts needs to be ensured) increases. The risk of selection bias increases because the required length of follow-up increases as one assesses further downstream outcomes. Generalizability of specific estimates may become increasingly questionable because the role of contextual factors that vary from setting to setting also have increasing influence on the further downstream outcomes. In contrast, studies providing only very indirect evidence may have lower risk of bias but require much stronger assumptions if we try to extrapolate from their findings to make statements about downstream patient outcomes. In general it is therefore important to take both risk of bias and applicability into account to come to an overall conclusion about the likely impact of diagnostic tests on patient outcomes.