While multivariable adjustment is a powerful tool, it is not always sufficient. For instance, if there are unmeasured confounders that are not accounted for, the results may still be biased. Moreover, multivariable adjustment cannot account for reverse causation, where the outcome influences the exposure rather than the other way around. In such cases, other techniques like instrumental variable analysis or randomized controlled trials may be necessary.
